python-3.6.zip added from Github

README.cosmo contains the necessary links.
This commit is contained in:
ahgamut 2021-08-08 09:38:33 +05:30 committed by Justine Tunney
parent 75fc601ff5
commit 0c4c56ff39
4219 changed files with 1965860 additions and 0 deletions

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variables:
manylinux: false
coverage: false
jobs:
- job: Prebuild
displayName: Pre-build checks
pool:
vmImage: ubuntu-16.04
steps:
- template: ./prebuild-checks.yml
- job: Docs_PR
displayName: Docs PR
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['docs.run'], 'true'))
pool:
vmImage: ubuntu-16.04
steps:
- template: ./docs-steps.yml
parameters:
upload: true
- job: macOS_CI_Tests
displayName: macOS CI Tests
dependsOn: Prebuild
#condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
# bpo-39837: macOS tests on Azure Pipelines are disabled
variables:
testRunTitle: '$(build.sourceBranchName)-macos'
testRunPlatform: macos
pool:
vmImage: macos-10.14
steps:
- template: ./macos-steps.yml
- job: Ubuntu_CI_Tests
displayName: Ubuntu CI Tests
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
pool:
vmImage: ubuntu-16.04
variables:
testRunTitle: '$(build.sourceBranchName)-linux'
testRunPlatform: linux
openssl_version: 1.1.0g
steps:
- template: ./posix-steps.yml
- job: ManyLinux1_CI_Tests
displayName: ManyLinux1 CI Tests
dependsOn: Prebuild
condition: |
and(
and(
succeeded(),
eq(variables['manylinux'], 'true')
),
eq(dependencies.Prebuild.outputs['tests.run'], 'true')
)
pool:
vmImage: ubuntu-16.04
variables:
testRunTitle: '$(build.sourceBranchName)-manylinux1'
testRunPlatform: manylinux1
imageName: 'dockcross/manylinux-x64'
steps:
- template: ./docker-steps.yml
- job: Ubuntu_Coverage_CI_Tests
displayName: Ubuntu CI Tests (coverage)
dependsOn: Prebuild
condition: |
and(
and(
succeeded(),
eq(variables['coverage'], 'true')
),
eq(dependencies.Prebuild.outputs['tests.run'], 'true')
)
pool:
vmImage: ubuntu-16.04
variables:
testRunTitle: '$(Build.SourceBranchName)-linux-coverage'
testRunPlatform: linux-coverage
openssl_version: 1.1.0g
steps:
- template: ./posix-steps.yml
parameters:
coverage: true
- job: Windows_CI_Tests
displayName: Windows CI Tests
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
pool:
vmImage: vs2017-win2016
strategy:
matrix:
win32:
arch: win32
buildOpt:
testRunTitle: '$(Build.SourceBranchName)-win32'
testRunPlatform: win32
win64:
arch: amd64
buildOpt: '-p x64'
testRunTitle: '$(Build.SourceBranchName)-win64'
testRunPlatform: win64
maxParallel: 2
steps:
- template: ./windows-steps.yml

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steps:
- checkout: self
clean: true
fetchDepth: 5
- ${{ if ne(parameters.targetBranch, '') }}:
- script: |
git fetch -q origin ${{ parameters.targetbranch }}
if ! git diff --name-only HEAD $(git merge-base HEAD FETCH_HEAD) | grep -qvE '(\.rst$|^Doc|^Misc)'
then
echo "Only docs were updated, stopping build process."
echo "##vso[task.setvariable variable=DocOnly]true"
exit
fi
displayName: Detect doc-only changes
- task: docker@0
displayName: 'Configure CPython (debug)'
inputs:
action: 'Run an image'
imageName: $(imageName)
volumes: |
$(build.sourcesDirectory):/src
$(build.binariesDirectory):/build
workDir: '/src'
containerCommand: './configure --with-pydebug'
detached: false
condition: and(succeeded(), ne(variables['DocOnly'], 'true'))
- task: docker@0
displayName: 'Build CPython'
inputs:
action: 'Run an image'
imageName: $(imageName)
volumes: |
$(build.sourcesDirectory):/src
$(build.binariesDirectory):/build
workDir: '/src'
containerCommand: 'make -s -j4'
detached: false
condition: and(succeeded(), ne(variables['DocOnly'], 'true'))
- task: docker@0
displayName: 'Display build info'
inputs:
action: 'Run an image'
imageName: $(imageName)
volumes: |
$(build.sourcesDirectory):/src
$(build.binariesDirectory):/build
workDir: '/src'
containerCommand: 'make pythoninfo'
detached: false
condition: and(succeeded(), ne(variables['DocOnly'], 'true'))
- task: docker@0
displayName: 'Tests'
inputs:
action: 'Run an image'
imageName: $(imageName)
volumes: |
$(build.sourcesDirectory):/src
$(build.binariesDirectory):/build
workDir: '/src'
containerCommand: 'make buildbottest TESTOPTS="-j4 -uall,-cpu --junit-xml=/build/test-results.xml"'
detached: false
condition: and(succeeded(), ne(variables['DocOnly'], 'true'))
- task: PublishTestResults@2
displayName: 'Publish Test Results'
inputs:
testResultsFiles: '$(build.binariesDirectory)/test-results.xml'
mergeTestResults: true
testRunTitle: $(testRunTitle)
platform: $(testRunPlatform)
condition: and(succeededOrFailed(), ne(variables['DocOnly'], 'true'))

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parameters:
latex: false
upload: false
steps:
- checkout: self
clean: true
fetchDepth: 5
- task: UsePythonVersion@0
displayName: 'Use Python 3.6 or later'
inputs:
versionSpec: '>=3.6'
- script: python -m pip install sphinx==1.8.2 blurb python-docs-theme
displayName: 'Install build dependencies'
- ${{ if ne(parameters.latex, 'true') }}:
- script: make check suspicious html PYTHON=python
workingDirectory: '$(build.sourcesDirectory)/Doc'
displayName: 'Build documentation'
- ${{ if eq(parameters.latex, 'true') }}:
- script: sudo apt-get update && sudo apt-get install -qy --force-yes texlive-full
displayName: 'Install LaTeX'
- script: make dist PYTHON=python SPHINXBUILD='python -m sphinx' BLURB='python -m blurb'
workingDirectory: '$(build.sourcesDirectory)/Doc'
displayName: 'Build documentation'
- ${{ if eq(parameters.upload, 'true') }}:
- task: PublishBuildArtifacts@1
displayName: 'Publish docs'
inputs:
PathToPublish: '$(build.sourcesDirectory)/Doc/build'
ArtifactName: docs
publishLocation: Container
- ${{ if eq(parameters.latex, 'true') }}:
- task: PublishBuildArtifacts@1
displayName: 'Publish dist'
inputs:
PathToPublish: '$(build.sourcesDirectory)/Doc/dist'
ArtifactName: docs_dist
publishLocation: Container

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steps:
- checkout: self
clean: true
fetchDepth: 5
- script: ./configure --with-pydebug --with-openssl=/usr/local/opt/openssl --prefix=/opt/python-azdev
displayName: 'Configure CPython (debug)'
- script: make -j4
displayName: 'Build CPython'
- script: make pythoninfo
displayName: 'Display build info'
- script: make buildbottest TESTOPTS="-j4 -uall,-cpu --junit-xml=$(build.binariesDirectory)/test-results.xml"
displayName: 'Tests'
continueOnError: true
timeoutInMinutes: 30
- task: PublishTestResults@2
displayName: 'Publish Test Results'
inputs:
testResultsFiles: '$(build.binariesDirectory)/test-results.xml'
mergeTestResults: true
testRunTitle: $(testRunTitle)
platform: $(testRunPlatform)
condition: succeededOrFailed()

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sudo apt-get update
sudo apt-get -yq install \
build-essential \
zlib1g-dev \
libbz2-dev \
liblzma-dev \
libncurses5-dev \
libreadline6-dev \
libsqlite3-dev \
libssl-dev \
libgdbm-dev \
tk-dev \
lzma \
lzma-dev \
liblzma-dev \
libffi-dev \
uuid-dev \
xvfb
if [ ! -z "$1" ]
then
echo ##vso[task.prependpath]$PWD/multissl/openssl/$1
echo ##vso[task.setvariable variable=OPENSSL_DIR]$PWD/multissl/openssl/$1
python3 Tools/ssl/multissltests.py --steps=library --base-directory $PWD/multissl --openssl $1 --system Linux
fi

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parameters:
coverage: false
steps:
- checkout: self
clean: true
fetchDepth: 5
- script: ./.azure-pipelines/posix-deps.sh $(openssl_version)
displayName: 'Install dependencies'
- script: ./configure --with-pydebug
displayName: 'Configure CPython (debug)'
- script: make -s -j4
displayName: 'Build CPython'
- ${{ if eq(parameters.coverage, 'true') }}:
- script: ./python -m venv venv && ./venv/bin/python -m pip install -U coverage
displayName: 'Set up virtual environment'
- script: ./venv/bin/python -m test.pythoninfo
displayName: 'Display build info'
- script: |
xvfb-run ./venv/bin/python -m coverage run --pylib -m test \
--fail-env-changed \
-uall,-cpu \
--junit-xml=$(build.binariesDirectory)/test-results.xml" \
-x test_multiprocessing_fork \
-x test_multiprocessing_forkserver \
-x test_multiprocessing_spawn \
-x test_concurrent_futures
displayName: 'Tests with coverage'
- script: ./venv/bin/python -m coverage xml
displayName: 'Generate coverage.xml'
- script: source ./venv/bin/activate && bash <(curl -s https://codecov.io/bash)
displayName: 'Publish code coverage results'
- ${{ if ne(parameters.coverage, 'true') }}:
- script: make pythoninfo
displayName: 'Display build info'
- script: xvfb-run make buildbottest TESTOPTS="-j4 -uall,-cpu --junit-xml=$(build.binariesDirectory)/test-results.xml"
displayName: 'Tests'
- script: ./python Tools/scripts/patchcheck.py --travis true
displayName: 'Run patchcheck.py'
condition: and(succeeded(), eq(variables['Build.Reason'], 'PullRequest'))
- task: PublishTestResults@2
displayName: 'Publish Test Results'
inputs:
testResultsFiles: '$(build.binariesDirectory)/test-results.xml'
mergeTestResults: true
testRunTitle: $(testRunTitle)
platform: $(testRunPlatform)
condition: succeededOrFailed()

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jobs:
- job: Prebuild
displayName: Pre-build checks
pool:
vmImage: ubuntu-16.04
steps:
- template: ./prebuild-checks.yml
- job: Docs_PR
displayName: Docs PR
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['docs.run'], 'true'))
pool:
vmImage: ubuntu-16.04
steps:
- template: ./docs-steps.yml
- job: macOS_PR_Tests
displayName: macOS PR Tests
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
#condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
# bpo-39837: macOS tests on Azure Pipelines are disabled
variables:
testRunTitle: '$(system.pullRequest.TargetBranch)-macos'
testRunPlatform: macos
pool:
vmImage: macos-10.14
steps:
- template: ./macos-steps.yml
parameters:
targetBranch: $(System.PullRequest.TargetBranch)
- job: Ubuntu_PR_Tests
displayName: Ubuntu PR Tests
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
pool:
vmImage: ubuntu-16.04
variables:
testRunTitle: '$(system.pullRequest.TargetBranch)-linux'
testRunPlatform: linux
openssl_version: 1.1.0g
steps:
- template: ./posix-steps.yml
parameters:
targetBranch: $(System.PullRequest.TargetBranch)
- job: Windows_PR_Tests
displayName: Windows PR Tests
dependsOn: Prebuild
condition: and(succeeded(), eq(dependencies.Prebuild.outputs['tests.run'], 'true'))
pool:
vmImage: vs2017-win2016
strategy:
matrix:
win32:
arch: win32
buildOpt:
testRunTitle: '$(System.PullRequest.TargetBranch)-win32'
testRunPlatform: win32
win64:
arch: amd64
buildOpt: '-p x64'
testRunTitle: '$(System.PullRequest.TargetBranch)-win64'
testRunPlatform: win64
maxParallel: 2
steps:
- template: ./windows-steps.yml
parameters:
targetBranch: $(System.PullRequest.TargetBranch)

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steps:
- checkout: self
fetchDepth: 5
- script: echo "##vso[task.setvariable variable=diffTarget]HEAD~1"
displayName: Set default diff target
- script: |
git fetch -q origin $(System.PullRequest.TargetBranch)
echo "##vso[task.setvariable variable=diffTarget]HEAD \$(git merge-base HEAD FETCH_HEAD)"
displayName: Fetch comparison tree
condition: and(succeeded(), variables['System.PullRequest.TargetBranch'])
- script: |
if ! git diff --name-only $(diffTarget) | grep -qE '(\.rst$|^Doc|^Misc)'
then
echo "No docs were updated: docs.run=false"
echo "##vso[task.setvariable variable=run;isOutput=true]false"
else
echo "Docs were updated: docs.run=true"
echo "##vso[task.setvariable variable=run;isOutput=true]true"
fi
displayName: Detect documentation changes
name: docs
- script: |
if ! git diff --name-only $(diffTarget) | grep -qvE '(\.rst$|^Doc|^Misc)'
then
echo "Only docs were updated: tests.run=false"
echo "##vso[task.setvariable variable=run;isOutput=true]false"
else
echo "Code was updated: tests.run=true"
echo "##vso[task.setvariable variable=run;isOutput=true]true"
fi
displayName: Detect source changes
name: tests

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steps:
- checkout: self
clean: true
fetchDepth: 5
- powershell: |
# Relocate build outputs outside of source directory to make cleaning faster
Write-Host '##vso[task.setvariable variable=Py_IntDir]$(Build.BinariesDirectory)\obj'
# UNDONE: Do not build to a different directory because of broken tests
Write-Host '##vso[task.setvariable variable=Py_OutDir]$(Build.SourcesDirectory)\PCbuild'
Write-Host '##vso[task.setvariable variable=EXTERNAL_DIR]$(Build.BinariesDirectory)\externals'
displayName: Update build locations
- script: PCbuild\build.bat -e $(buildOpt)
displayName: 'Build CPython'
- script: python.bat -m test.pythoninfo
displayName: 'Display build info'
- script: PCbuild\rt.bat -q -uall -u-cpu -rwW --slowest --timeout=1200 -j0 --junit-xml="$(Build.BinariesDirectory)\test-results.xml"
displayName: 'Tests'
env:
PREFIX: $(Py_OutDir)\$(arch)
- task: PublishTestResults@2
displayName: 'Publish Test Results'
inputs:
testResultsFiles: '$(Build.BinariesDirectory)\test-results.xml'
mergeTestResults: true
testRunTitle: $(testRunTitle)
platform: $(testRunPlatform)
condition: succeededOrFailed()

42
third_party/python/.bzrignore vendored Normal file
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.purify
autom4te.cache
config.log
config.cache
config.status
config.status.lineno
db_home
Makefile
buildno
python
build
Makefile.pre
platform
pybuilddir.txt
pyconfig.h
libpython*.a
libpython*.so*
python.exe
python-gdb.py
reflog.txt
tags
TAGS
.gdb_history
Doc/tools/sphinx
Doc/tools/jinja
Doc/tools/jinja2
Doc/tools/pygments
Doc/tools/docutils
Misc/python.pc
Modules/Setup
Modules/Setup.config
Modules/Setup.local
Modules/config.c
Modules/ld_so_aix
Parser/pgen
Lib/test/data/*
Lib/lib2to3/Grammar*.pickle
Lib/lib2to3/PatternGrammar*.pickle
__pycache__
.coverage
coverage/*
htmlcov/*

58
third_party/python/.gitattributes vendored Normal file
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@ -0,0 +1,58 @@
# Binary data types
*.aif binary
*.aifc binary
*.aiff binary
*.au binary
*.bmp binary
*.exe binary
*.icns binary
*.gif binary
*.ico binary
*.jpg binary
*.pck binary
*.png binary
*.psd binary
*.tar binary
*.wav binary
*.whl binary
*.zip binary
# Specific binary files
Lib/test/sndhdrdata/sndhdr.* binary
# Text files that should not be subject to eol conversion
Lib/test/cjkencodings/* -text
Lib/test/decimaltestdata/*.decTest -text
Lib/test/test_email/data/*.txt -text
Lib/test/xmltestdata/* -text
Lib/test/coding20731.py -text
# Special files in third party code
Modules/zlib/zlib.map -text
# CRLF files
*.bat text eol=crlf
*.ps1 text eol=crlf
*.sln text eol=crlf
*.vcxproj* text eol=crlf
*.props text eol=crlf
*.proj text eol=crlf
PCbuild/readme.txt text eol=crlf
PC/readme.txt text eol=crlf
# Generated files
# https://github.com/github/linguist#generated-code
Include/graminit.h linguist-generated=true
Python/graminit.h linguist-generated=true
Modules/clinic/*.h linguist-generated=true
Objects/clinic/*.h linguist-generated=true
PC/clinic/*.h linguist-generated=true
Python/clinic/*.h linguist-generated=true
Python/importlib.h linguist-generated=true
Python/importlib_external.h linguist-generated=true
Include/Python-ast.h linguist-generated=true
Python/Python-ast.c linguist-generated=true
Include/opcode.h linguist-generated=true
Python/opcode_targets.h linguist-generated=true
Objects/typeslots.inc linguist-generated=true
Modules/unicodedata_db.h linguist-generated=true

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## CPython Mirror
https://github.com/python/cpython is a cpython mirror repository. Pull requests
are not accepted on this repo and will be automatically closed.
### Submit patches at https://bugs.python.org
For additional information about contributing to CPython, see the
[developer's guide](https://docs.python.org/devguide/#contributing).

38
third_party/python/.github/appveyor.yml vendored Normal file
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@ -0,0 +1,38 @@
version: 3.6build{build}
clone_depth: 5
branches:
only:
- master
- /\d\.\d/
- buildbot-custom
cache:
- externals -> PCbuild\*
before_build:
- ps: |+
if ($env:APPVEYOR_RE_BUILD) {
echo 'Doing full build due to re-build request.'
} elseif (!$env:APPVEYOR_PULL_REQUEST_HEAD_COMMIT) {
echo 'Not a PR, doing full build.'
} else {
git fetch -q origin +refs/heads/$env:APPVEYOR_REPO_BRANCH
$mergebase = git merge-base HEAD FETCH_HEAD
$changes = git diff --name-only HEAD $mergebase | grep -vE '(\.rst$)|(^Doc)|(^Misc)'
If (!$changes) {
echo 'Only docs were updated, stopping build process.'
Exit-AppveyorBuild
} else {
echo 'Doing full build due to non-doc changes in these files:'
echo $changes
}
}
build_script:
- cmd: PCbuild\build.bat -e
- cmd: PCbuild\win32\python.exe -m test.pythoninfo
test_script:
- cmd: PCbuild\rt.bat -q -uall -u-cpu -u-largefile -rwW --slowest --timeout=1200 -j0
environment:
HOST_PYTHON: C:\Python36\python.exe
image:
- Visual Studio 2015

30
third_party/python/.github/codecov.yml vendored Normal file
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@ -0,0 +1,30 @@
codecov:
strict_yaml_branch: master
notify:
require_ci_to_pass: true
comment: off
ignore:
- "Doc/**/*"
- "Misc/**/*"
- "Mac/**/*"
- "PC/**/*"
- "PCbuild/**/*"
- "Tools/**/*"
- "Grammar/*"
coverage:
precision: 2
range: 70...90
round: down
status:
changes: off
project: off
patch: off
parsers:
gcov:
branch_detection:
conditional: true
loop: true
macro: false
method: false
javascript:
enable_partials: false

103
third_party/python/.gitignore vendored Normal file
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@ -0,0 +1,103 @@
# Two-trick pony for OSX and other case insensitive file systems:
# Ignore ./python binary on Unix but still look into ./Python/ directory.
/python
!/Python/
*.cover
*.o
*.orig
*.pyc
*.pyd
*.pyo
*.rej
*.swp
*~
*.gc??
*.profclang?
*.profraw
*.dyn
.gdb_history
Doc/build/
Doc/venv/
Doc/.venv/
Doc/env/
Doc/.env/
Include/pydtrace_probes.h
Lib/distutils/command/*.pdb
Lib/lib2to3/*.pickle
Lib/test/data/*
Makefile
Makefile.pre
Misc/python.pc
Misc/python-config.sh
Modules/Setup
Modules/Setup.config
Modules/Setup.local
Modules/config.c
Modules/ld_so_aix
Programs/_freeze_importlib
Programs/_testembed
PC/python_nt*.h
PC/pythonnt_rc*.h
PC/*/*.exe
PC/*/*.exp
PC/*/*.lib
PC/*/*.bsc
PC/*/*.dll
PC/*/*.pdb
PC/*/*.user
PC/*/*.ncb
PC/*/*.suo
PC/*/Win32-temp-*
PC/*/x64-temp-*
PC/*/amd64
PCbuild/*.user
PCbuild/*.suo
PCbuild/*.*sdf
PCbuild/*-pgi
PCbuild/*-pgo
PCbuild/*.VC.db
PCbuild/*.VC.opendb
PCbuild/.vs/
PCbuild/amd64/
PCbuild/obj/
PCbuild/win32/
.purify
Parser/pgen
__pycache__
autom4te.cache
build/
buildno
config.cache
config.log
config.status
config.status.lineno
core
db_home
.hg/
ipch/
libpython*.a
libpython*.so*
libpython*.dylib
platform
pybuilddir.txt
pyconfig.h
python-config
python-config.py
python.bat
python.exe
python-gdb.py
python.exe-gdb.py
reflog.txt
.svn/
tags
TAGS
.coverage
coverage/
externals/
htmlcov/
Tools/msi/obj
Tools/ssl/amd64
Tools/ssl/win32
.vs/
.vscode/
gmon.out

105
third_party/python/.hgignore vendored Normal file
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@ -0,0 +1,105 @@
.gdb_history
.purify
.svn/
^.idea/
^.vscode/
.DS_Store
Makefile$
Makefile.pre$
TAGS$
autom4te.cache$
^build/
^Doc/build/
^Doc/venv/
buildno$
config.cache
config.log
config.status
config.status.lineno
db_home
platform$
pyconfig.h$
python$
python.bat$
python.exe$
python-config$
python-config.py$
reflog.txt$
tags$
Misc/python.pc
Misc/python-config.sh$
Modules/Setup$
Modules/Setup.config
Modules/Setup.local
Modules/config.c
Modules/ld_so_aix$
Parser/pgen$
^lcov-report/
^core
^python-gdb.py
^python.exe-gdb.py
^pybuilddir.txt
syntax: glob
libpython*.a
libpython*.so*
libpython*.dylib
*.swp
*.o
*.pyc
*.pyo
*.pyd
*.cover
*~
*.gc??
*.profclang?
*.profraw
*.dyn
Include/pydtrace_probes.h
Lib/distutils/command/*.pdb
Lib/lib2to3/*.pickle
Lib/test/data/*
Misc/*.wpu
PC/python_nt*.h
PC/pythonnt_rc*.h
PC/*/*.exe
PC/*/*.exp
PC/*/*.lib
PC/*/*.bsc
PC/*/*.dll
PC/*/*.pdb
PC/*/*.user
PC/*/*.ncb
PC/*/*.suo
PC/*/Win32-temp-*
PC/*/x64-temp-*
PC/*/amd64
PCbuild/*.user
PCbuild/*.suo
PCbuild/*.*sdf
PCbuild/*-pgi
PCbuild/*-pgo
PCbuild/.vs
PCbuild/amd64
PCbuild/obj
PCbuild/win32
Tools/unicode/build/
Tools/unicode/MAPPINGS/
BuildLog.htm
__pycache__
Programs/_freeze_importlib
Programs/_testembed
.coverage
coverage/
externals/
htmlcov/
*.gcda
*.gcno
*.gcov
ipch/
coverage.info
Tools/msi/obj
Tools/ssl/amd64
Tools/ssl/win32
.vs/
.vscode/

135
third_party/python/.travis.yml vendored Normal file
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@ -0,0 +1,135 @@
language: c
dist: xenial
# To cache doc-building dependencies and C compiler output.
cache:
- pip
- ccache
env:
global:
# Use -O3 because we don't use debugger on Travis-CI
- CFLAGS="-O3"
branches:
only:
- master
- /^\d\.\d$/
- buildbot-custom
matrix:
fast_finish: true
allow_failures:
- env: OPTIONAL=true
include:
- os: linux
language: c
compiler: clang
# gcc also works, but to keep the # of concurrent builds down, we use one C
# compiler here and the other to run the coverage build. Clang is preferred
# in this instance for its better error messages.
env: TESTING=cpython
addons:
apt:
packages:
- xvfb
- os: linux
language: python
python: 3.6
env: TESTING=docs
before_script:
- cd Doc
# Sphinx is pinned so that new versions that introduce new warnings won't suddenly cause build failures.
# (Updating the version is fine as long as no warnings are raised by doing so.)
- python -m pip install sphinx==1.8.2 blurb
script:
- make check suspicious html SPHINXOPTS="-q -W -j4"
- os: linux
language: c
compiler: gcc
env: OPTIONAL=true
addons:
apt:
packages:
- xvfb
before_script:
- ./configure PYTHON_FOR_REGEN=python3
- make -s -j4
# Need a venv that can parse covered code.
- ./python -m venv venv
- ./venv/bin/python -m pip install -U coverage
- ./venv/bin/python -m test.pythoninfo
script:
# Skip tests that re-run the entire test suite.
- xvfb-run ./venv/bin/python -m coverage run --pylib -m test -uall,-cpu -x test_multiprocessing_fork -x test_multiprocessing_forkserver -x test_multiprocessing_spawn
after_script: # Probably should be after_success once test suite updated to run under coverage.py.
# Make the `coverage` command available to Codecov w/ a version of Python that can parse all source files.
- source ./venv/bin/activate
- bash <(curl -s https://codecov.io/bash)
before_install:
- set -e
- |
# Check short-circuit conditions
if [ "${TESTING}" != "docs" ]
then
if [ "$TRAVIS_PULL_REQUEST" = "false" ]
then
echo "Not a PR, doing full build."
else
# Pull requests are slightly complicated because $TRAVIS_COMMIT_RANGE
# may include more changes than desired if the history is convoluted.
# Instead, explicitly fetch the base branch and compare against the
# merge-base commit.
git fetch -q origin +refs/heads/$TRAVIS_BRANCH
changes=$(git diff --name-only HEAD $(git merge-base HEAD FETCH_HEAD))
echo "Files changed:"
echo "$changes"
if ! echo "$changes" | grep -qvE '(\.rst$)|(^Doc)|(^Misc)'
then
echo "Only docs were updated, stopping build process."
exit
fi
fi
fi
# Travis provides only 2 cores, so don't overdo the parallelism and waste memory.
before_script:
- ./configure --with-pydebug PYTHON_FOR_REGEN=python3
- make -j4 regen-all
- changes=`git status --porcelain`
- |
# Check for changes in regenerated files
if ! test -z "$changes"
then
echo "Generated files not up to date"
echo "$changes"
exit 1
fi
- make -j4
- make pythoninfo
script:
# Using the built Python as patchcheck.py is built around the idea of using
# a checkout-build of CPython to know things like what base branch the changes
# should be compared against.
# Only run on Linux as the check only needs to be run once.
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then ./python Tools/scripts/patchcheck.py --travis $TRAVIS_PULL_REQUEST; fi
# Check that all symbols exported by libpython start with "Py" or "_Py"
- make smelly
# `-r -w` implicitly provided through `make buildbottest`.
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then XVFB_RUN=xvfb-run; fi; $XVFB_RUN make buildbottest TESTOPTS="-j4 -uall,-cpu"
notifications:
email: false
irc:
channels:
# This is set to a secure variable to prevent forks from notifying the
# IRC channel whenever they fail a build. This can be removed when travis
# implements https://github.com/travis-ci/travis-ci/issues/1094.
# The actual value here is: irc.freenode.net#python-dev
- secure: "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"
on_success: change
on_failure: always
skip_join: true

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Python Documentation README
~~~~~~~~~~~~~~~~~~~~~~~~~~~
This directory contains the reStructuredText (reST) sources to the Python
documentation. You don't need to build them yourself, `prebuilt versions are
available <https://docs.python.org/dev/download.html>`_.
Documentation on authoring Python documentation, including information about
both style and markup, is available in the "`Documenting Python
<https://devguide.python.org/documenting/>`_" chapter of the
developers guide.
Building the docs
=================
The documentation is built with several tools which are not included in this
tree but are maintained separately and are available from
`PyPI <https://pypi.org/>`_.
* `Sphinx <https://pypi.org/project/Sphinx/>`_
* `blurb <https://pypi.org/project/blurb/>`_
The easiest way to install these tools is to create a virtual environment and
install the tools into there.
Using make
----------
To get started on UNIX, you can create a virtual environment with the command ::
make venv
That will install all the tools necessary to build the documentation. Assuming
the virtual environment was created in the ``venv`` directory (the default;
configurable with the VENVDIR variable), you can run the following command to
build the HTML output files::
make html
By default, if the virtual environment is not created, the Makefile will
look for instances of sphinxbuild and blurb installed on your process PATH
(configurable with the SPHINXBUILD and BLURB variables).
On Windows, we try to emulate the Makefile as closely as possible with a
``make.bat`` file. If you need to specify the Python interpreter to use,
set the PYTHON environment variable instead.
Available make targets are:
* "clean", which removes all build files.
* "venv", which creates a virtual environment with all necessary tools
installed.
* "html", which builds standalone HTML files for offline viewing.
* "htmlview", which re-uses the "html" builder, but then opens the main page
in your default web browser.
* "htmlhelp", which builds HTML files and a HTML Help project file usable to
convert them into a single Compiled HTML (.chm) file -- these are popular
under Microsoft Windows, but very handy on every platform.
To create the CHM file, you need to run the Microsoft HTML Help Workshop
over the generated project (.hhp) file. The make.bat script does this for
you on Windows.
* "latex", which builds LaTeX source files as input to "pdflatex" to produce
PDF documents.
* "text", which builds a plain text file for each source file.
* "epub", which builds an EPUB document, suitable to be viewed on e-book
readers.
* "linkcheck", which checks all external references to see whether they are
broken, redirected or malformed, and outputs this information to stdout as
well as a plain-text (.txt) file.
* "changes", which builds an overview over all versionadded/versionchanged/
deprecated items in the current version. This is meant as a help for the
writer of the "What's New" document.
* "coverage", which builds a coverage overview for standard library modules and
C API.
* "pydoc-topics", which builds a Python module containing a dictionary with
plain text documentation for the labels defined in
`tools/pyspecific.py` -- pydoc needs these to show topic and keyword help.
* "suspicious", which checks the parsed markup for text that looks like
malformed and thus unconverted reST.
* "check", which checks for frequent markup errors.
* "serve", which serves the build/html directory on port 8000.
* "dist", (Unix only) which creates distributable archives of HTML, text,
PDF, and EPUB builds.
Without make
------------
First, install the tool dependencies from PyPI.
Then, from the ``Doc`` directory, run ::
sphinx-build -b<builder> . build/<builder>
where ``<builder>`` is one of html, text, latex, or htmlhelp (for explanations
see the make targets above).
Deprecation header
==================
You can define the ``outdated`` variable in ``html_context`` to show a
red banner on each page redirecting to the "latest" version.
The link points to the same page on ``/3/``, sadly for the moment the
language is lost during the process.
Contributing
============
Bugs in the content should be reported to the
`Python bug tracker <https://bugs.python.org>`_.
Bugs in the toolset should be reported to the tools themselves.
You can also send a mail to the Python Documentation Team at docs@python.org,
and we will process your request as soon as possible.
If you want to help the Documentation Team, you are always welcome. Just send
a mail to docs@python.org.

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=====================
About these documents
=====================
These documents are generated from `reStructuredText`_ sources by `Sphinx`_, a
document processor specifically written for the Python documentation.
.. _reStructuredText: http://docutils.sourceforge.net/rst.html
.. _Sphinx: http://sphinx-doc.org/
.. In the online version of these documents, you can submit comments and suggest
changes directly on the documentation pages.
Development of the documentation and its toolchain is an entirely volunteer
effort, just like Python itself. If you want to contribute, please take a
look at the :ref:`reporting-bugs` page for information on how to do so. New
volunteers are always welcome!
Many thanks go to:
* Fred L. Drake, Jr., the creator of the original Python documentation toolset
and writer of much of the content;
* the `Docutils <http://docutils.sourceforge.net/>`_ project for creating
reStructuredText and the Docutils suite;
* Fredrik Lundh for his `Alternative Python Reference
<http://effbot.org/zone/pyref.htm>`_ project from which Sphinx got many good
ideas.
Contributors to the Python Documentation
----------------------------------------
Many people have contributed to the Python language, the Python standard
library, and the Python documentation. See :source:`Misc/ACKS` in the Python
source distribution for a partial list of contributors.
It is only with the input and contributions of the Python community
that Python has such wonderful documentation -- Thank You!

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.. _reporting-bugs:
*****************
Dealing with Bugs
*****************
Python is a mature programming language which has established a reputation for
stability. In order to maintain this reputation, the developers would like to
know of any deficiencies you find in Python.
It can be sometimes faster to fix bugs yourself and contribute patches to
Python as it streamlines the process and involves less people. Learn how to
:ref:`contribute <contributing-to-python>`.
Documentation bugs
==================
If you find a bug in this documentation or would like to propose an improvement,
please submit a bug report on the :ref:`tracker <using-the-tracker>`. If you
have a suggestion how to fix it, include that as well.
If you're short on time, you can also email documentation bug reports to
docs@python.org (behavioral bugs can be sent to python-list@python.org).
'docs@' is a mailing list run by volunteers; your request will be noticed,
though it may take a while to be processed.
.. seealso::
`Documentation bugs`_ on the Python issue tracker
.. _using-the-tracker:
Using the Python issue tracker
==============================
Bug reports for Python itself should be submitted via the Python Bug Tracker
(https://bugs.python.org/). The bug tracker offers a Web form which allows
pertinent information to be entered and submitted to the developers.
The first step in filing a report is to determine whether the problem has
already been reported. The advantage in doing so, aside from saving the
developers time, is that you learn what has been done to fix it; it may be that
the problem has already been fixed for the next release, or additional
information is needed (in which case you are welcome to provide it if you can!).
To do this, search the bug database using the search box on the top of the page.
If the problem you're reporting is not already in the bug tracker, go back to
the Python Bug Tracker and log in. If you don't already have a tracker account,
select the "Register" link or, if you use OpenID, one of the OpenID provider
logos in the sidebar. It is not possible to submit a bug report anonymously.
Being now logged in, you can submit a bug. Select the "Create New" link in the
sidebar to open the bug reporting form.
The submission form has a number of fields. For the "Title" field, enter a
*very* short description of the problem; less than ten words is good. In the
"Type" field, select the type of your problem; also select the "Component" and
"Versions" to which the bug relates.
In the "Comment" field, describe the problem in detail, including what you
expected to happen and what did happen. Be sure to include whether any
extension modules were involved, and what hardware and software platform you
were using (including version information as appropriate).
Each bug report will be assigned to a developer who will determine what needs to
be done to correct the problem. You will receive an update each time action is
taken on the bug.
.. seealso::
`How to Report Bugs Effectively <http://www.chiark.greenend.org.uk/~sgtatham/bugs.html>`_
Article which goes into some detail about how to create a useful bug report.
This describes what kind of information is useful and why it is useful.
`Bug Writing Guidelines <https://developer.mozilla.org/en-US/docs/Mozilla/QA/Bug_writing_guidelines>`_
Information about writing a good bug report. Some of this is specific to the
Mozilla project, but describes general good practices.
.. _contributing-to-python:
Getting started contributing to Python yourself
===============================================
Beyond just reporting bugs that you find, you are also welcome to submit
patches to fix them. You can find more information on how to get started
patching Python in the `Python Developer's Guide`_. If you have questions,
the `core-mentorship mailing list`_ is a friendly place to get answers to
any and all questions pertaining to the process of fixing issues in Python.
.. _Documentation bugs: https://bugs.python.org/issue?@filter=status&@filter=components&components=4&status=1&@columns=id,activity,title,status&@sort=-activity
.. _Python Developer's Guide: https://devguide.python.org/
.. _core-mentorship mailing list: https://mail.python.org/mailman/listinfo/core-mentorship/

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.. highlightlang:: c
.. _abstract:
**********************
Abstract Objects Layer
**********************
The functions in this chapter interact with Python objects regardless of their
type, or with wide classes of object types (e.g. all numerical types, or all
sequence types). When used on object types for which they do not apply, they
will raise a Python exception.
It is not possible to use these functions on objects that are not properly
initialized, such as a list object that has been created by :c:func:`PyList_New`,
but whose items have not been set to some non-\ ``NULL`` value yet.
.. toctree::
object.rst
number.rst
sequence.rst
mapping.rst
iter.rst
buffer.rst
objbuffer.rst

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.. highlightlang:: c
.. _allocating-objects:
Allocating Objects on the Heap
==============================
.. c:function:: PyObject* _PyObject_New(PyTypeObject *type)
.. c:function:: PyVarObject* _PyObject_NewVar(PyTypeObject *type, Py_ssize_t size)
.. c:function:: PyObject* PyObject_Init(PyObject *op, PyTypeObject *type)
Initialize a newly-allocated object *op* with its type and initial
reference. Returns the initialized object. If *type* indicates that the
object participates in the cyclic garbage detector, it is added to the
detector's set of observed objects. Other fields of the object are not
affected.
.. c:function:: PyVarObject* PyObject_InitVar(PyVarObject *op, PyTypeObject *type, Py_ssize_t size)
This does everything :c:func:`PyObject_Init` does, and also initializes the
length information for a variable-size object.
.. c:function:: TYPE* PyObject_New(TYPE, PyTypeObject *type)
Allocate a new Python object using the C structure type *TYPE* and the
Python type object *type*. Fields not defined by the Python object header
are not initialized; the object's reference count will be one. The size of
the memory allocation is determined from the :c:member:`~PyTypeObject.tp_basicsize` field of
the type object.
.. c:function:: TYPE* PyObject_NewVar(TYPE, PyTypeObject *type, Py_ssize_t size)
Allocate a new Python object using the C structure type *TYPE* and the
Python type object *type*. Fields not defined by the Python object header
are not initialized. The allocated memory allows for the *TYPE* structure
plus *size* fields of the size given by the :c:member:`~PyTypeObject.tp_itemsize` field of
*type*. This is useful for implementing objects like tuples, which are
able to determine their size at construction time. Embedding the array of
fields into the same allocation decreases the number of allocations,
improving the memory management efficiency.
.. c:function:: void PyObject_Del(PyObject *op)
Releases memory allocated to an object using :c:func:`PyObject_New` or
:c:func:`PyObject_NewVar`. This is normally called from the
:c:member:`~PyTypeObject.tp_dealloc` handler specified in the object's type. The fields of
the object should not be accessed after this call as the memory is no
longer a valid Python object.
.. c:var:: PyObject _Py_NoneStruct
Object which is visible in Python as ``None``. This should only be accessed
using the :c:macro:`Py_None` macro, which evaluates to a pointer to this
object.
.. seealso::
:c:func:`PyModule_Create`
To allocate and create extension modules.

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.. highlightlang:: c
.. _apiabiversion:
***********************
API and ABI Versioning
***********************
``PY_VERSION_HEX`` is the Python version number encoded in a single integer.
For example if the ``PY_VERSION_HEX`` is set to ``0x030401a2``, the underlying
version information can be found by treating it as a 32 bit number in
the following manner:
+-------+-------------------------+------------------------------------------------+
| Bytes | Bits (big endian order) | Meaning |
+=======+=========================+================================================+
| ``1`` | ``1-8`` | ``PY_MAJOR_VERSION`` (the ``3`` in |
| | | ``3.4.1a2``) |
+-------+-------------------------+------------------------------------------------+
| ``2`` | ``9-16`` | ``PY_MINOR_VERSION`` (the ``4`` in |
| | | ``3.4.1a2``) |
+-------+-------------------------+------------------------------------------------+
| ``3`` | ``17-24`` | ``PY_MICRO_VERSION`` (the ``1`` in |
| | | ``3.4.1a2``) |
+-------+-------------------------+------------------------------------------------+
| ``4`` | ``25-28`` | ``PY_RELEASE_LEVEL`` (``0xA`` for alpha, |
| | | ``0xB`` for beta, ``0xC`` for release |
| | | candidate and ``0xF`` for final), in this |
| | | case it is alpha. |
+-------+-------------------------+------------------------------------------------+
| | ``29-32`` | ``PY_RELEASE_SERIAL`` (the ``2`` in |
| | | ``3.4.1a2``, zero for final releases) |
+-------+-------------------------+------------------------------------------------+
Thus ``3.4.1a2`` is hexversion ``0x030401a2``.
All the given macros are defined in :source:`Include/patchlevel.h`.

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.. highlightlang:: c
.. _arg-parsing:
Parsing arguments and building values
=====================================
These functions are useful when creating your own extensions functions and
methods. Additional information and examples are available in
:ref:`extending-index`.
The first three of these functions described, :c:func:`PyArg_ParseTuple`,
:c:func:`PyArg_ParseTupleAndKeywords`, and :c:func:`PyArg_Parse`, all use *format
strings* which are used to tell the function about the expected arguments. The
format strings use the same syntax for each of these functions.
-----------------
Parsing arguments
-----------------
A format string consists of zero or more "format units." A format unit
describes one Python object; it is usually a single character or a parenthesized
sequence of format units. With a few exceptions, a format unit that is not a
parenthesized sequence normally corresponds to a single address argument to
these functions. In the following description, the quoted form is the format
unit; the entry in (round) parentheses is the Python object type that matches
the format unit; and the entry in [square] brackets is the type of the C
variable(s) whose address should be passed.
Strings and buffers
-------------------
These formats allow accessing an object as a contiguous chunk of memory.
You don't have to provide raw storage for the returned unicode or bytes
area.
In general, when a format sets a pointer to a buffer, the buffer is
managed by the corresponding Python object, and the buffer shares
the lifetime of this object. You won't have to release any memory yourself.
The only exceptions are ``es``, ``es#``, ``et`` and ``et#``.
However, when a :c:type:`Py_buffer` structure gets filled, the underlying
buffer is locked so that the caller can subsequently use the buffer even
inside a :c:type:`Py_BEGIN_ALLOW_THREADS` block without the risk of mutable data
being resized or destroyed. As a result, **you have to call**
:c:func:`PyBuffer_Release` after you have finished processing the data (or
in any early abort case).
Unless otherwise stated, buffers are not NUL-terminated.
Some formats require a read-only :term:`bytes-like object`, and set a
pointer instead of a buffer structure. They work by checking that
the object's :c:member:`PyBufferProcs.bf_releasebuffer` field is *NULL*,
which disallows mutable objects such as :class:`bytearray`.
.. note::
For all ``#`` variants of formats (``s#``, ``y#``, etc.), the type of
the length argument (int or :c:type:`Py_ssize_t`) is controlled by
defining the macro :c:macro:`PY_SSIZE_T_CLEAN` before including
:file:`Python.h`. If the macro was defined, length is a
:c:type:`Py_ssize_t` rather than an :c:type:`int`. This behavior will change
in a future Python version to only support :c:type:`Py_ssize_t` and
drop :c:type:`int` support. It is best to always define :c:macro:`PY_SSIZE_T_CLEAN`.
``s`` (:class:`str`) [const char \*]
Convert a Unicode object to a C pointer to a character string.
A pointer to an existing string is stored in the character pointer
variable whose address you pass. The C string is NUL-terminated.
The Python string must not contain embedded null code points; if it does,
a :exc:`ValueError` exception is raised. Unicode objects are converted
to C strings using ``'utf-8'`` encoding. If this conversion fails, a
:exc:`UnicodeError` is raised.
.. note::
This format does not accept :term:`bytes-like objects
<bytes-like object>`. If you want to accept
filesystem paths and convert them to C character strings, it is
preferable to use the ``O&`` format with :c:func:`PyUnicode_FSConverter`
as *converter*.
.. versionchanged:: 3.5
Previously, :exc:`TypeError` was raised when embedded null code points
were encountered in the Python string.
``s*`` (:class:`str` or :term:`bytes-like object`) [Py_buffer]
This format accepts Unicode objects as well as bytes-like objects.
It fills a :c:type:`Py_buffer` structure provided by the caller.
In this case the resulting C string may contain embedded NUL bytes.
Unicode objects are converted to C strings using ``'utf-8'`` encoding.
``s#`` (:class:`str`, read-only :term:`bytes-like object`) [const char \*, int or :c:type:`Py_ssize_t`]
Like ``s*``, except that it doesn't accept mutable objects.
The result is stored into two C variables,
the first one a pointer to a C string, the second one its length.
The string may contain embedded null bytes. Unicode objects are converted
to C strings using ``'utf-8'`` encoding.
``z`` (:class:`str` or ``None``) [const char \*]
Like ``s``, but the Python object may also be ``None``, in which case the C
pointer is set to *NULL*.
``z*`` (:class:`str`, :term:`bytes-like object` or ``None``) [Py_buffer]
Like ``s*``, but the Python object may also be ``None``, in which case the
``buf`` member of the :c:type:`Py_buffer` structure is set to *NULL*.
``z#`` (:class:`str`, read-only :term:`bytes-like object` or ``None``) [const char \*, int]
Like ``s#``, but the Python object may also be ``None``, in which case the C
pointer is set to *NULL*.
``y`` (read-only :term:`bytes-like object`) [const char \*]
This format converts a bytes-like object to a C pointer to a character
string; it does not accept Unicode objects. The bytes buffer must not
contain embedded null bytes; if it does, a :exc:`ValueError`
exception is raised.
.. versionchanged:: 3.5
Previously, :exc:`TypeError` was raised when embedded null bytes were
encountered in the bytes buffer.
``y*`` (:term:`bytes-like object`) [Py_buffer]
This variant on ``s*`` doesn't accept Unicode objects, only
bytes-like objects. **This is the recommended way to accept
binary data.**
``y#`` (read-only :term:`bytes-like object`) [const char \*, int]
This variant on ``s#`` doesn't accept Unicode objects, only bytes-like
objects.
``S`` (:class:`bytes`) [PyBytesObject \*]
Requires that the Python object is a :class:`bytes` object, without
attempting any conversion. Raises :exc:`TypeError` if the object is not
a bytes object. The C variable may also be declared as :c:type:`PyObject\*`.
``Y`` (:class:`bytearray`) [PyByteArrayObject \*]
Requires that the Python object is a :class:`bytearray` object, without
attempting any conversion. Raises :exc:`TypeError` if the object is not
a :class:`bytearray` object. The C variable may also be declared as :c:type:`PyObject\*`.
``u`` (:class:`str`) [Py_UNICODE \*]
Convert a Python Unicode object to a C pointer to a NUL-terminated buffer of
Unicode characters. You must pass the address of a :c:type:`Py_UNICODE`
pointer variable, which will be filled with the pointer to an existing
Unicode buffer. Please note that the width of a :c:type:`Py_UNICODE`
character depends on compilation options (it is either 16 or 32 bits).
The Python string must not contain embedded null code points; if it does,
a :exc:`ValueError` exception is raised.
.. versionchanged:: 3.5
Previously, :exc:`TypeError` was raised when embedded null code points
were encountered in the Python string.
.. deprecated-removed:: 3.3 4.0
Part of the old-style :c:type:`Py_UNICODE` API; please migrate to using
:c:func:`PyUnicode_AsWideCharString`.
``u#`` (:class:`str`) [Py_UNICODE \*, int]
This variant on ``u`` stores into two C variables, the first one a pointer to a
Unicode data buffer, the second one its length. This variant allows
null code points.
.. deprecated-removed:: 3.3 4.0
Part of the old-style :c:type:`Py_UNICODE` API; please migrate to using
:c:func:`PyUnicode_AsWideCharString`.
``Z`` (:class:`str` or ``None``) [Py_UNICODE \*]
Like ``u``, but the Python object may also be ``None``, in which case the
:c:type:`Py_UNICODE` pointer is set to *NULL*.
.. deprecated-removed:: 3.3 4.0
Part of the old-style :c:type:`Py_UNICODE` API; please migrate to using
:c:func:`PyUnicode_AsWideCharString`.
``Z#`` (:class:`str` or ``None``) [Py_UNICODE \*, int]
Like ``u#``, but the Python object may also be ``None``, in which case the
:c:type:`Py_UNICODE` pointer is set to *NULL*.
.. deprecated-removed:: 3.3 4.0
Part of the old-style :c:type:`Py_UNICODE` API; please migrate to using
:c:func:`PyUnicode_AsWideCharString`.
``U`` (:class:`str`) [PyObject \*]
Requires that the Python object is a Unicode object, without attempting
any conversion. Raises :exc:`TypeError` if the object is not a Unicode
object. The C variable may also be declared as :c:type:`PyObject\*`.
``w*`` (read-write :term:`bytes-like object`) [Py_buffer]
This format accepts any object which implements the read-write buffer
interface. It fills a :c:type:`Py_buffer` structure provided by the caller.
The buffer may contain embedded null bytes. The caller have to call
:c:func:`PyBuffer_Release` when it is done with the buffer.
``es`` (:class:`str`) [const char \*encoding, char \*\*buffer]
This variant on ``s`` is used for encoding Unicode into a character buffer.
It only works for encoded data without embedded NUL bytes.
This format requires two arguments. The first is only used as input, and
must be a :c:type:`const char\*` which points to the name of an encoding as a
NUL-terminated string, or *NULL*, in which case ``'utf-8'`` encoding is used.
An exception is raised if the named encoding is not known to Python. The
second argument must be a :c:type:`char\*\*`; the value of the pointer it
references will be set to a buffer with the contents of the argument text.
The text will be encoded in the encoding specified by the first argument.
:c:func:`PyArg_ParseTuple` will allocate a buffer of the needed size, copy the
encoded data into this buffer and adjust *\*buffer* to reference the newly
allocated storage. The caller is responsible for calling :c:func:`PyMem_Free` to
free the allocated buffer after use.
``et`` (:class:`str`, :class:`bytes` or :class:`bytearray`) [const char \*encoding, char \*\*buffer]
Same as ``es`` except that byte string objects are passed through without
recoding them. Instead, the implementation assumes that the byte string object uses
the encoding passed in as parameter.
``es#`` (:class:`str`) [const char \*encoding, char \*\*buffer, int \*buffer_length]
This variant on ``s#`` is used for encoding Unicode into a character buffer.
Unlike the ``es`` format, this variant allows input data which contains NUL
characters.
It requires three arguments. The first is only used as input, and must be a
:c:type:`const char\*` which points to the name of an encoding as a
NUL-terminated string, or *NULL*, in which case ``'utf-8'`` encoding is used.
An exception is raised if the named encoding is not known to Python. The
second argument must be a :c:type:`char\*\*`; the value of the pointer it
references will be set to a buffer with the contents of the argument text.
The text will be encoded in the encoding specified by the first argument.
The third argument must be a pointer to an integer; the referenced integer
will be set to the number of bytes in the output buffer.
There are two modes of operation:
If *\*buffer* points a *NULL* pointer, the function will allocate a buffer of
the needed size, copy the encoded data into this buffer and set *\*buffer* to
reference the newly allocated storage. The caller is responsible for calling
:c:func:`PyMem_Free` to free the allocated buffer after usage.
If *\*buffer* points to a non-*NULL* pointer (an already allocated buffer),
:c:func:`PyArg_ParseTuple` will use this location as the buffer and interpret the
initial value of *\*buffer_length* as the buffer size. It will then copy the
encoded data into the buffer and NUL-terminate it. If the buffer is not large
enough, a :exc:`ValueError` will be set.
In both cases, *\*buffer_length* is set to the length of the encoded data
without the trailing NUL byte.
``et#`` (:class:`str`, :class:`bytes` or :class:`bytearray`) [const char \*encoding, char \*\*buffer, int \*buffer_length]
Same as ``es#`` except that byte string objects are passed through without recoding
them. Instead, the implementation assumes that the byte string object uses the
encoding passed in as parameter.
Numbers
-------
``b`` (:class:`int`) [unsigned char]
Convert a nonnegative Python integer to an unsigned tiny int, stored in a C
:c:type:`unsigned char`.
``B`` (:class:`int`) [unsigned char]
Convert a Python integer to a tiny int without overflow checking, stored in a C
:c:type:`unsigned char`.
``h`` (:class:`int`) [short int]
Convert a Python integer to a C :c:type:`short int`.
``H`` (:class:`int`) [unsigned short int]
Convert a Python integer to a C :c:type:`unsigned short int`, without overflow
checking.
``i`` (:class:`int`) [int]
Convert a Python integer to a plain C :c:type:`int`.
``I`` (:class:`int`) [unsigned int]
Convert a Python integer to a C :c:type:`unsigned int`, without overflow
checking.
``l`` (:class:`int`) [long int]
Convert a Python integer to a C :c:type:`long int`.
``k`` (:class:`int`) [unsigned long]
Convert a Python integer to a C :c:type:`unsigned long` without
overflow checking.
``L`` (:class:`int`) [long long]
Convert a Python integer to a C :c:type:`long long`.
``K`` (:class:`int`) [unsigned long long]
Convert a Python integer to a C :c:type:`unsigned long long`
without overflow checking.
``n`` (:class:`int`) [Py_ssize_t]
Convert a Python integer to a C :c:type:`Py_ssize_t`.
``c`` (:class:`bytes` or :class:`bytearray` of length 1) [char]
Convert a Python byte, represented as a :class:`bytes` or
:class:`bytearray` object of length 1, to a C :c:type:`char`.
.. versionchanged:: 3.3
Allow :class:`bytearray` objects.
``C`` (:class:`str` of length 1) [int]
Convert a Python character, represented as a :class:`str` object of
length 1, to a C :c:type:`int`.
``f`` (:class:`float`) [float]
Convert a Python floating point number to a C :c:type:`float`.
``d`` (:class:`float`) [double]
Convert a Python floating point number to a C :c:type:`double`.
``D`` (:class:`complex`) [Py_complex]
Convert a Python complex number to a C :c:type:`Py_complex` structure.
Other objects
-------------
``O`` (object) [PyObject \*]
Store a Python object (without any conversion) in a C object pointer. The C
program thus receives the actual object that was passed. The object's reference
count is not increased. The pointer stored is not *NULL*.
``O!`` (object) [*typeobject*, PyObject \*]
Store a Python object in a C object pointer. This is similar to ``O``, but
takes two C arguments: the first is the address of a Python type object, the
second is the address of the C variable (of type :c:type:`PyObject\*`) into which
the object pointer is stored. If the Python object does not have the required
type, :exc:`TypeError` is raised.
.. _o_ampersand:
``O&`` (object) [*converter*, *anything*]
Convert a Python object to a C variable through a *converter* function. This
takes two arguments: the first is a function, the second is the address of a C
variable (of arbitrary type), converted to :c:type:`void \*`. The *converter*
function in turn is called as follows::
status = converter(object, address);
where *object* is the Python object to be converted and *address* is the
:c:type:`void\*` argument that was passed to the :c:func:`PyArg_Parse\*` function.
The returned *status* should be ``1`` for a successful conversion and ``0`` if
the conversion has failed. When the conversion fails, the *converter* function
should raise an exception and leave the content of *address* unmodified.
If the *converter* returns ``Py_CLEANUP_SUPPORTED``, it may get called a
second time if the argument parsing eventually fails, giving the converter a
chance to release any memory that it had already allocated. In this second
call, the *object* parameter will be NULL; *address* will have the same value
as in the original call.
.. versionchanged:: 3.1
``Py_CLEANUP_SUPPORTED`` was added.
``p`` (:class:`bool`) [int]
Tests the value passed in for truth (a boolean **p**\ redicate) and converts
the result to its equivalent C true/false integer value.
Sets the int to ``1`` if the expression was true and ``0`` if it was false.
This accepts any valid Python value. See :ref:`truth` for more
information about how Python tests values for truth.
.. versionadded:: 3.3
``(items)`` (:class:`tuple`) [*matching-items*]
The object must be a Python sequence whose length is the number of format units
in *items*. The C arguments must correspond to the individual format units in
*items*. Format units for sequences may be nested.
It is possible to pass "long" integers (integers whose value exceeds the
platform's :const:`LONG_MAX`) however no proper range checking is done --- the
most significant bits are silently truncated when the receiving field is too
small to receive the value (actually, the semantics are inherited from downcasts
in C --- your mileage may vary).
A few other characters have a meaning in a format string. These may not occur
inside nested parentheses. They are:
``|``
Indicates that the remaining arguments in the Python argument list are optional.
The C variables corresponding to optional arguments should be initialized to
their default value --- when an optional argument is not specified,
:c:func:`PyArg_ParseTuple` does not touch the contents of the corresponding C
variable(s).
``$``
:c:func:`PyArg_ParseTupleAndKeywords` only:
Indicates that the remaining arguments in the Python argument list are
keyword-only. Currently, all keyword-only arguments must also be optional
arguments, so ``|`` must always be specified before ``$`` in the format
string.
.. versionadded:: 3.3
``:``
The list of format units ends here; the string after the colon is used as the
function name in error messages (the "associated value" of the exception that
:c:func:`PyArg_ParseTuple` raises).
``;``
The list of format units ends here; the string after the semicolon is used as
the error message *instead* of the default error message. ``:`` and ``;``
mutually exclude each other.
Note that any Python object references which are provided to the caller are
*borrowed* references; do not decrement their reference count!
Additional arguments passed to these functions must be addresses of variables
whose type is determined by the format string; these are used to store values
from the input tuple. There are a few cases, as described in the list of format
units above, where these parameters are used as input values; they should match
what is specified for the corresponding format unit in that case.
For the conversion to succeed, the *arg* object must match the format
and the format must be exhausted. On success, the
:c:func:`PyArg_Parse\*` functions return true, otherwise they return
false and raise an appropriate exception. When the
:c:func:`PyArg_Parse\*` functions fail due to conversion failure in one
of the format units, the variables at the addresses corresponding to that
and the following format units are left untouched.
API Functions
-------------
.. c:function:: int PyArg_ParseTuple(PyObject *args, const char *format, ...)
Parse the parameters of a function that takes only positional parameters into
local variables. Returns true on success; on failure, it returns false and
raises the appropriate exception.
.. c:function:: int PyArg_VaParse(PyObject *args, const char *format, va_list vargs)
Identical to :c:func:`PyArg_ParseTuple`, except that it accepts a va_list rather
than a variable number of arguments.
.. c:function:: int PyArg_ParseTupleAndKeywords(PyObject *args, PyObject *kw, const char *format, char *keywords[], ...)
Parse the parameters of a function that takes both positional and keyword
parameters into local variables. The *keywords* argument is a
*NULL*-terminated array of keyword parameter names. Empty names denote
:ref:`positional-only parameters <positional-only_parameter>`.
Returns true on success; on failure, it returns false and raises the
appropriate exception.
.. versionchanged:: 3.6
Added support for :ref:`positional-only parameters
<positional-only_parameter>`.
.. c:function:: int PyArg_VaParseTupleAndKeywords(PyObject *args, PyObject *kw, const char *format, char *keywords[], va_list vargs)
Identical to :c:func:`PyArg_ParseTupleAndKeywords`, except that it accepts a
va_list rather than a variable number of arguments.
.. c:function:: int PyArg_ValidateKeywordArguments(PyObject *)
Ensure that the keys in the keywords argument dictionary are strings. This
is only needed if :c:func:`PyArg_ParseTupleAndKeywords` is not used, since the
latter already does this check.
.. versionadded:: 3.2
.. XXX deprecated, will be removed
.. c:function:: int PyArg_Parse(PyObject *args, const char *format, ...)
Function used to deconstruct the argument lists of "old-style" functions ---
these are functions which use the :const:`METH_OLDARGS` parameter parsing
method, which has been removed in Python 3. This is not recommended for use
in parameter parsing in new code, and most code in the standard interpreter
has been modified to no longer use this for that purpose. It does remain a
convenient way to decompose other tuples, however, and may continue to be
used for that purpose.
.. c:function:: int PyArg_UnpackTuple(PyObject *args, const char *name, Py_ssize_t min, Py_ssize_t max, ...)
A simpler form of parameter retrieval which does not use a format string to
specify the types of the arguments. Functions which use this method to retrieve
their parameters should be declared as :const:`METH_VARARGS` in function or
method tables. The tuple containing the actual parameters should be passed as
*args*; it must actually be a tuple. The length of the tuple must be at least
*min* and no more than *max*; *min* and *max* may be equal. Additional
arguments must be passed to the function, each of which should be a pointer to a
:c:type:`PyObject\*` variable; these will be filled in with the values from
*args*; they will contain borrowed references. The variables which correspond
to optional parameters not given by *args* will not be filled in; these should
be initialized by the caller. This function returns true on success and false if
*args* is not a tuple or contains the wrong number of elements; an exception
will be set if there was a failure.
This is an example of the use of this function, taken from the sources for the
:mod:`_weakref` helper module for weak references::
static PyObject *
weakref_ref(PyObject *self, PyObject *args)
{
PyObject *object;
PyObject *callback = NULL;
PyObject *result = NULL;
if (PyArg_UnpackTuple(args, "ref", 1, 2, &object, &callback)) {
result = PyWeakref_NewRef(object, callback);
}
return result;
}
The call to :c:func:`PyArg_UnpackTuple` in this example is entirely equivalent to
this call to :c:func:`PyArg_ParseTuple`::
PyArg_ParseTuple(args, "O|O:ref", &object, &callback)
---------------
Building values
---------------
.. c:function:: PyObject* Py_BuildValue(const char *format, ...)
Create a new value based on a format string similar to those accepted by the
:c:func:`PyArg_Parse\*` family of functions and a sequence of values. Returns
the value or *NULL* in the case of an error; an exception will be raised if
*NULL* is returned.
:c:func:`Py_BuildValue` does not always build a tuple. It builds a tuple only if
its format string contains two or more format units. If the format string is
empty, it returns ``None``; if it contains exactly one format unit, it returns
whatever object is described by that format unit. To force it to return a tuple
of size 0 or one, parenthesize the format string.
When memory buffers are passed as parameters to supply data to build objects, as
for the ``s`` and ``s#`` formats, the required data is copied. Buffers provided
by the caller are never referenced by the objects created by
:c:func:`Py_BuildValue`. In other words, if your code invokes :c:func:`malloc`
and passes the allocated memory to :c:func:`Py_BuildValue`, your code is
responsible for calling :c:func:`free` for that memory once
:c:func:`Py_BuildValue` returns.
In the following description, the quoted form is the format unit; the entry in
(round) parentheses is the Python object type that the format unit will return;
and the entry in [square] brackets is the type of the C value(s) to be passed.
The characters space, tab, colon and comma are ignored in format strings (but
not within format units such as ``s#``). This can be used to make long format
strings a tad more readable.
``s`` (:class:`str` or ``None``) [char \*]
Convert a null-terminated C string to a Python :class:`str` object using ``'utf-8'``
encoding. If the C string pointer is *NULL*, ``None`` is used.
``s#`` (:class:`str` or ``None``) [char \*, int]
Convert a C string and its length to a Python :class:`str` object using ``'utf-8'``
encoding. If the C string pointer is *NULL*, the length is ignored and
``None`` is returned.
``y`` (:class:`bytes`) [char \*]
This converts a C string to a Python :class:`bytes` object. If the C
string pointer is *NULL*, ``None`` is returned.
``y#`` (:class:`bytes`) [char \*, int]
This converts a C string and its lengths to a Python object. If the C
string pointer is *NULL*, ``None`` is returned.
``z`` (:class:`str` or ``None``) [char \*]
Same as ``s``.
``z#`` (:class:`str` or ``None``) [char \*, int]
Same as ``s#``.
``u`` (:class:`str`) [wchar_t \*]
Convert a null-terminated :c:type:`wchar_t` buffer of Unicode (UTF-16 or UCS-4)
data to a Python Unicode object. If the Unicode buffer pointer is *NULL*,
``None`` is returned.
``u#`` (:class:`str`) [wchar_t \*, int]
Convert a Unicode (UTF-16 or UCS-4) data buffer and its length to a Python
Unicode object. If the Unicode buffer pointer is *NULL*, the length is ignored
and ``None`` is returned.
``U`` (:class:`str` or ``None``) [char \*]
Same as ``s``.
``U#`` (:class:`str` or ``None``) [char \*, int]
Same as ``s#``.
``i`` (:class:`int`) [int]
Convert a plain C :c:type:`int` to a Python integer object.
``b`` (:class:`int`) [char]
Convert a plain C :c:type:`char` to a Python integer object.
``h`` (:class:`int`) [short int]
Convert a plain C :c:type:`short int` to a Python integer object.
``l`` (:class:`int`) [long int]
Convert a C :c:type:`long int` to a Python integer object.
``B`` (:class:`int`) [unsigned char]
Convert a C :c:type:`unsigned char` to a Python integer object.
``H`` (:class:`int`) [unsigned short int]
Convert a C :c:type:`unsigned short int` to a Python integer object.
``I`` (:class:`int`) [unsigned int]
Convert a C :c:type:`unsigned int` to a Python integer object.
``k`` (:class:`int`) [unsigned long]
Convert a C :c:type:`unsigned long` to a Python integer object.
``L`` (:class:`int`) [long long]
Convert a C :c:type:`long long` to a Python integer object.
``K`` (:class:`int`) [unsigned long long]
Convert a C :c:type:`unsigned long long` to a Python integer object.
``n`` (:class:`int`) [Py_ssize_t]
Convert a C :c:type:`Py_ssize_t` to a Python integer.
``c`` (:class:`bytes` of length 1) [char]
Convert a C :c:type:`int` representing a byte to a Python :class:`bytes` object of
length 1.
``C`` (:class:`str` of length 1) [int]
Convert a C :c:type:`int` representing a character to Python :class:`str`
object of length 1.
``d`` (:class:`float`) [double]
Convert a C :c:type:`double` to a Python floating point number.
``f`` (:class:`float`) [float]
Convert a C :c:type:`float` to a Python floating point number.
``D`` (:class:`complex`) [Py_complex \*]
Convert a C :c:type:`Py_complex` structure to a Python complex number.
``O`` (object) [PyObject \*]
Pass a Python object untouched (except for its reference count, which is
incremented by one). If the object passed in is a *NULL* pointer, it is assumed
that this was caused because the call producing the argument found an error and
set an exception. Therefore, :c:func:`Py_BuildValue` will return *NULL* but won't
raise an exception. If no exception has been raised yet, :exc:`SystemError` is
set.
``S`` (object) [PyObject \*]
Same as ``O``.
``N`` (object) [PyObject \*]
Same as ``O``, except it doesn't increment the reference count on the object.
Useful when the object is created by a call to an object constructor in the
argument list.
``O&`` (object) [*converter*, *anything*]
Convert *anything* to a Python object through a *converter* function. The
function is called with *anything* (which should be compatible with :c:type:`void
\*`) as its argument and should return a "new" Python object, or *NULL* if an
error occurred.
``(items)`` (:class:`tuple`) [*matching-items*]
Convert a sequence of C values to a Python tuple with the same number of items.
``[items]`` (:class:`list`) [*matching-items*]
Convert a sequence of C values to a Python list with the same number of items.
``{items}`` (:class:`dict`) [*matching-items*]
Convert a sequence of C values to a Python dictionary. Each pair of consecutive
C values adds one item to the dictionary, serving as key and value,
respectively.
If there is an error in the format string, the :exc:`SystemError` exception is
set and *NULL* returned.
.. c:function:: PyObject* Py_VaBuildValue(const char *format, va_list vargs)
Identical to :c:func:`Py_BuildValue`, except that it accepts a va_list
rather than a variable number of arguments.

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.. highlightlang:: c
.. _boolobjects:
Boolean Objects
---------------
Booleans in Python are implemented as a subclass of integers. There are only
two booleans, :const:`Py_False` and :const:`Py_True`. As such, the normal
creation and deletion functions don't apply to booleans. The following macros
are available, however.
.. c:function:: int PyBool_Check(PyObject *o)
Return true if *o* is of type :c:data:`PyBool_Type`.
.. c:var:: PyObject* Py_False
The Python ``False`` object. This object has no methods. It needs to be
treated just like any other object with respect to reference counts.
.. c:var:: PyObject* Py_True
The Python ``True`` object. This object has no methods. It needs to be treated
just like any other object with respect to reference counts.
.. c:macro:: Py_RETURN_FALSE
Return :const:`Py_False` from a function, properly incrementing its reference
count.
.. c:macro:: Py_RETURN_TRUE
Return :const:`Py_True` from a function, properly incrementing its reference
count.
.. c:function:: PyObject* PyBool_FromLong(long v)
Return a new reference to :const:`Py_True` or :const:`Py_False` depending on the
truth value of *v*.

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.. highlightlang:: c
.. index::
single: buffer protocol
single: buffer interface; (see buffer protocol)
single: buffer object; (see buffer protocol)
.. _bufferobjects:
Buffer Protocol
---------------
.. sectionauthor:: Greg Stein <gstein@lyra.org>
.. sectionauthor:: Benjamin Peterson
.. sectionauthor:: Stefan Krah
Certain objects available in Python wrap access to an underlying memory
array or *buffer*. Such objects include the built-in :class:`bytes` and
:class:`bytearray`, and some extension types like :class:`array.array`.
Third-party libraries may define their own types for special purposes, such
as image processing or numeric analysis.
While each of these types have their own semantics, they share the common
characteristic of being backed by a possibly large memory buffer. It is
then desirable, in some situations, to access that buffer directly and
without intermediate copying.
Python provides such a facility at the C level in the form of the :ref:`buffer
protocol <bufferobjects>`. This protocol has two sides:
.. index:: single: PyBufferProcs
- on the producer side, a type can export a "buffer interface" which allows
objects of that type to expose information about their underlying buffer.
This interface is described in the section :ref:`buffer-structs`;
- on the consumer side, several means are available to obtain a pointer to
the raw underlying data of an object (for example a method parameter).
Simple objects such as :class:`bytes` and :class:`bytearray` expose their
underlying buffer in byte-oriented form. Other forms are possible; for example,
the elements exposed by an :class:`array.array` can be multi-byte values.
An example consumer of the buffer interface is the :meth:`~io.BufferedIOBase.write`
method of file objects: any object that can export a series of bytes through
the buffer interface can be written to a file. While :meth:`write` only
needs read-only access to the internal contents of the object passed to it,
other methods such as :meth:`~io.BufferedIOBase.readinto` need write access
to the contents of their argument. The buffer interface allows objects to
selectively allow or reject exporting of read-write and read-only buffers.
There are two ways for a consumer of the buffer interface to acquire a buffer
over a target object:
* call :c:func:`PyObject_GetBuffer` with the right parameters;
* call :c:func:`PyArg_ParseTuple` (or one of its siblings) with one of the
``y*``, ``w*`` or ``s*`` :ref:`format codes <arg-parsing>`.
In both cases, :c:func:`PyBuffer_Release` must be called when the buffer
isn't needed anymore. Failure to do so could lead to various issues such as
resource leaks.
.. _buffer-structure:
Buffer structure
================
Buffer structures (or simply "buffers") are useful as a way to expose the
binary data from another object to the Python programmer. They can also be
used as a zero-copy slicing mechanism. Using their ability to reference a
block of memory, it is possible to expose any data to the Python programmer
quite easily. The memory could be a large, constant array in a C extension,
it could be a raw block of memory for manipulation before passing to an
operating system library, or it could be used to pass around structured data
in its native, in-memory format.
Contrary to most data types exposed by the Python interpreter, buffers
are not :c:type:`PyObject` pointers but rather simple C structures. This
allows them to be created and copied very simply. When a generic wrapper
around a buffer is needed, a :ref:`memoryview <memoryview-objects>` object
can be created.
For short instructions how to write an exporting object, see
:ref:`Buffer Object Structures <buffer-structs>`. For obtaining
a buffer, see :c:func:`PyObject_GetBuffer`.
.. c:type:: Py_buffer
.. c:member:: void \*buf
A pointer to the start of the logical structure described by the buffer
fields. This can be any location within the underlying physical memory
block of the exporter. For example, with negative :c:member:`~Py_buffer.strides`
the value may point to the end of the memory block.
For :term:`contiguous` arrays, the value points to the beginning of
the memory block.
.. c:member:: void \*obj
A new reference to the exporting object. The reference is owned by
the consumer and automatically decremented and set to *NULL* by
:c:func:`PyBuffer_Release`. The field is the equivalent of the return
value of any standard C-API function.
As a special case, for *temporary* buffers that are wrapped by
:c:func:`PyMemoryView_FromBuffer` or :c:func:`PyBuffer_FillInfo`
this field is *NULL*. In general, exporting objects MUST NOT
use this scheme.
.. c:member:: Py_ssize_t len
``product(shape) * itemsize``. For contiguous arrays, this is the length
of the underlying memory block. For non-contiguous arrays, it is the length
that the logical structure would have if it were copied to a contiguous
representation.
Accessing ``((char *)buf)[0] up to ((char *)buf)[len-1]`` is only valid
if the buffer has been obtained by a request that guarantees contiguity. In
most cases such a request will be :c:macro:`PyBUF_SIMPLE` or :c:macro:`PyBUF_WRITABLE`.
.. c:member:: int readonly
An indicator of whether the buffer is read-only. This field is controlled
by the :c:macro:`PyBUF_WRITABLE` flag.
.. c:member:: Py_ssize_t itemsize
Item size in bytes of a single element. Same as the value of :func:`struct.calcsize`
called on non-NULL :c:member:`~Py_buffer.format` values.
Important exception: If a consumer requests a buffer without the
:c:macro:`PyBUF_FORMAT` flag, :c:member:`~Py_buffer.format` will
be set to *NULL*, but :c:member:`~Py_buffer.itemsize` still has
the value for the original format.
If :c:member:`~Py_buffer.shape` is present, the equality
``product(shape) * itemsize == len`` still holds and the consumer
can use :c:member:`~Py_buffer.itemsize` to navigate the buffer.
If :c:member:`~Py_buffer.shape` is *NULL* as a result of a :c:macro:`PyBUF_SIMPLE`
or a :c:macro:`PyBUF_WRITABLE` request, the consumer must disregard
:c:member:`~Py_buffer.itemsize` and assume ``itemsize == 1``.
.. c:member:: const char \*format
A *NUL* terminated string in :mod:`struct` module style syntax describing
the contents of a single item. If this is *NULL*, ``"B"`` (unsigned bytes)
is assumed.
This field is controlled by the :c:macro:`PyBUF_FORMAT` flag.
.. c:member:: int ndim
The number of dimensions the memory represents as an n-dimensional array.
If it is ``0``, :c:member:`~Py_buffer.buf` points to a single item representing
a scalar. In this case, :c:member:`~Py_buffer.shape`, :c:member:`~Py_buffer.strides`
and :c:member:`~Py_buffer.suboffsets` MUST be *NULL*.
The macro :c:macro:`PyBUF_MAX_NDIM` limits the maximum number of dimensions
to 64. Exporters MUST respect this limit, consumers of multi-dimensional
buffers SHOULD be able to handle up to :c:macro:`PyBUF_MAX_NDIM` dimensions.
.. c:member:: Py_ssize_t \*shape
An array of :c:type:`Py_ssize_t` of length :c:member:`~Py_buffer.ndim`
indicating the shape of the memory as an n-dimensional array. Note that
``shape[0] * ... * shape[ndim-1] * itemsize`` MUST be equal to
:c:member:`~Py_buffer.len`.
Shape values are restricted to ``shape[n] >= 0``. The case
``shape[n] == 0`` requires special attention. See `complex arrays`_
for further information.
The shape array is read-only for the consumer.
.. c:member:: Py_ssize_t \*strides
An array of :c:type:`Py_ssize_t` of length :c:member:`~Py_buffer.ndim`
giving the number of bytes to skip to get to a new element in each
dimension.
Stride values can be any integer. For regular arrays, strides are
usually positive, but a consumer MUST be able to handle the case
``strides[n] <= 0``. See `complex arrays`_ for further information.
The strides array is read-only for the consumer.
.. c:member:: Py_ssize_t \*suboffsets
An array of :c:type:`Py_ssize_t` of length :c:member:`~Py_buffer.ndim`.
If ``suboffsets[n] >= 0``, the values stored along the nth dimension are
pointers and the suboffset value dictates how many bytes to add to each
pointer after de-referencing. A suboffset value that is negative
indicates that no de-referencing should occur (striding in a contiguous
memory block).
If all suboffsets are negative (i.e. no de-referencing is needed), then
this field must be NULL (the default value).
This type of array representation is used by the Python Imaging Library
(PIL). See `complex arrays`_ for further information how to access elements
of such an array.
The suboffsets array is read-only for the consumer.
.. c:member:: void \*internal
This is for use internally by the exporting object. For example, this
might be re-cast as an integer by the exporter and used to store flags
about whether or not the shape, strides, and suboffsets arrays must be
freed when the buffer is released. The consumer MUST NOT alter this
value.
.. _buffer-request-types:
Buffer request types
====================
Buffers are usually obtained by sending a buffer request to an exporting
object via :c:func:`PyObject_GetBuffer`. Since the complexity of the logical
structure of the memory can vary drastically, the consumer uses the *flags*
argument to specify the exact buffer type it can handle.
All :c:data:`Py_buffer` fields are unambiguously defined by the request
type.
request-independent fields
~~~~~~~~~~~~~~~~~~~~~~~~~~
The following fields are not influenced by *flags* and must always be filled in
with the correct values: :c:member:`~Py_buffer.obj`, :c:member:`~Py_buffer.buf`,
:c:member:`~Py_buffer.len`, :c:member:`~Py_buffer.itemsize`, :c:member:`~Py_buffer.ndim`.
readonly, format
~~~~~~~~~~~~~~~~
.. c:macro:: PyBUF_WRITABLE
Controls the :c:member:`~Py_buffer.readonly` field. If set, the exporter
MUST provide a writable buffer or else report failure. Otherwise, the
exporter MAY provide either a read-only or writable buffer, but the choice
MUST be consistent for all consumers.
.. c:macro:: PyBUF_FORMAT
Controls the :c:member:`~Py_buffer.format` field. If set, this field MUST
be filled in correctly. Otherwise, this field MUST be *NULL*.
:c:macro:`PyBUF_WRITABLE` can be \|'d to any of the flags in the next section.
Since :c:macro:`PyBUF_SIMPLE` is defined as 0, :c:macro:`PyBUF_WRITABLE`
can be used as a stand-alone flag to request a simple writable buffer.
:c:macro:`PyBUF_FORMAT` can be \|'d to any of the flags except :c:macro:`PyBUF_SIMPLE`.
The latter already implies format ``B`` (unsigned bytes).
shape, strides, suboffsets
~~~~~~~~~~~~~~~~~~~~~~~~~~
The flags that control the logical structure of the memory are listed
in decreasing order of complexity. Note that each flag contains all bits
of the flags below it.
.. tabularcolumns:: |p{0.35\linewidth}|l|l|l|
+-----------------------------+-------+---------+------------+
| Request | shape | strides | suboffsets |
+=============================+=======+=========+============+
| .. c:macro:: PyBUF_INDIRECT | yes | yes | if needed |
+-----------------------------+-------+---------+------------+
| .. c:macro:: PyBUF_STRIDES | yes | yes | NULL |
+-----------------------------+-------+---------+------------+
| .. c:macro:: PyBUF_ND | yes | NULL | NULL |
+-----------------------------+-------+---------+------------+
| .. c:macro:: PyBUF_SIMPLE | NULL | NULL | NULL |
+-----------------------------+-------+---------+------------+
.. index:: contiguous, C-contiguous, Fortran contiguous
contiguity requests
~~~~~~~~~~~~~~~~~~~
C or Fortran :term:`contiguity <contiguous>` can be explicitly requested,
with and without stride information. Without stride information, the buffer
must be C-contiguous.
.. tabularcolumns:: |p{0.35\linewidth}|l|l|l|l|
+-----------------------------------+-------+---------+------------+--------+
| Request | shape | strides | suboffsets | contig |
+===================================+=======+=========+============+========+
| .. c:macro:: PyBUF_C_CONTIGUOUS | yes | yes | NULL | C |
+-----------------------------------+-------+---------+------------+--------+
| .. c:macro:: PyBUF_F_CONTIGUOUS | yes | yes | NULL | F |
+-----------------------------------+-------+---------+------------+--------+
| .. c:macro:: PyBUF_ANY_CONTIGUOUS | yes | yes | NULL | C or F |
+-----------------------------------+-------+---------+------------+--------+
| .. c:macro:: PyBUF_ND | yes | NULL | NULL | C |
+-----------------------------------+-------+---------+------------+--------+
compound requests
~~~~~~~~~~~~~~~~~
All possible requests are fully defined by some combination of the flags in
the previous section. For convenience, the buffer protocol provides frequently
used combinations as single flags.
In the following table *U* stands for undefined contiguity. The consumer would
have to call :c:func:`PyBuffer_IsContiguous` to determine contiguity.
.. tabularcolumns:: |p{0.35\linewidth}|l|l|l|l|l|l|
+-------------------------------+-------+---------+------------+--------+----------+--------+
| Request | shape | strides | suboffsets | contig | readonly | format |
+===============================+=======+=========+============+========+==========+========+
| .. c:macro:: PyBUF_FULL | yes | yes | if needed | U | 0 | yes |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_FULL_RO | yes | yes | if needed | U | 1 or 0 | yes |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_RECORDS | yes | yes | NULL | U | 0 | yes |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_RECORDS_RO | yes | yes | NULL | U | 1 or 0 | yes |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_STRIDED | yes | yes | NULL | U | 0 | NULL |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_STRIDED_RO | yes | yes | NULL | U | 1 or 0 | NULL |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_CONTIG | yes | NULL | NULL | C | 0 | NULL |
+-------------------------------+-------+---------+------------+--------+----------+--------+
| .. c:macro:: PyBUF_CONTIG_RO | yes | NULL | NULL | C | 1 or 0 | NULL |
+-------------------------------+-------+---------+------------+--------+----------+--------+
Complex arrays
==============
NumPy-style: shape and strides
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The logical structure of NumPy-style arrays is defined by :c:member:`~Py_buffer.itemsize`,
:c:member:`~Py_buffer.ndim`, :c:member:`~Py_buffer.shape` and :c:member:`~Py_buffer.strides`.
If ``ndim == 0``, the memory location pointed to by :c:member:`~Py_buffer.buf` is
interpreted as a scalar of size :c:member:`~Py_buffer.itemsize`. In that case,
both :c:member:`~Py_buffer.shape` and :c:member:`~Py_buffer.strides` are *NULL*.
If :c:member:`~Py_buffer.strides` is *NULL*, the array is interpreted as
a standard n-dimensional C-array. Otherwise, the consumer must access an
n-dimensional array as follows:
``ptr = (char *)buf + indices[0] * strides[0] + ... + indices[n-1] * strides[n-1]``
``item = *((typeof(item) *)ptr);``
As noted above, :c:member:`~Py_buffer.buf` can point to any location within
the actual memory block. An exporter can check the validity of a buffer with
this function:
.. code-block:: python
def verify_structure(memlen, itemsize, ndim, shape, strides, offset):
"""Verify that the parameters represent a valid array within
the bounds of the allocated memory:
char *mem: start of the physical memory block
memlen: length of the physical memory block
offset: (char *)buf - mem
"""
if offset % itemsize:
return False
if offset < 0 or offset+itemsize > memlen:
return False
if any(v % itemsize for v in strides):
return False
if ndim <= 0:
return ndim == 0 and not shape and not strides
if 0 in shape:
return True
imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] <= 0)
imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] > 0)
return 0 <= offset+imin and offset+imax+itemsize <= memlen
PIL-style: shape, strides and suboffsets
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In addition to the regular items, PIL-style arrays can contain pointers
that must be followed in order to get to the next element in a dimension.
For example, the regular three-dimensional C-array ``char v[2][2][3]`` can
also be viewed as an array of 2 pointers to 2 two-dimensional arrays:
``char (*v[2])[2][3]``. In suboffsets representation, those two pointers
can be embedded at the start of :c:member:`~Py_buffer.buf`, pointing
to two ``char x[2][3]`` arrays that can be located anywhere in memory.
Here is a function that returns a pointer to the element in an N-D array
pointed to by an N-dimensional index when there are both non-NULL strides
and suboffsets::
void *get_item_pointer(int ndim, void *buf, Py_ssize_t *strides,
Py_ssize_t *suboffsets, Py_ssize_t *indices) {
char *pointer = (char*)buf;
int i;
for (i = 0; i < ndim; i++) {
pointer += strides[i] * indices[i];
if (suboffsets[i] >=0 ) {
pointer = *((char**)pointer) + suboffsets[i];
}
}
return (void*)pointer;
}
Buffer-related functions
========================
.. c:function:: int PyObject_CheckBuffer(PyObject *obj)
Return ``1`` if *obj* supports the buffer interface otherwise ``0``. When ``1`` is
returned, it doesn't guarantee that :c:func:`PyObject_GetBuffer` will
succeed. This function always succeeds.
.. c:function:: int PyObject_GetBuffer(PyObject *exporter, Py_buffer *view, int flags)
Send a request to *exporter* to fill in *view* as specified by *flags*.
If the exporter cannot provide a buffer of the exact type, it MUST raise
:c:data:`PyExc_BufferError`, set :c:member:`view->obj` to *NULL* and
return ``-1``.
On success, fill in *view*, set :c:member:`view->obj` to a new reference
to *exporter* and return 0. In the case of chained buffer providers
that redirect requests to a single object, :c:member:`view->obj` MAY
refer to this object instead of *exporter* (See :ref:`Buffer Object Structures <buffer-structs>`).
Successful calls to :c:func:`PyObject_GetBuffer` must be paired with calls
to :c:func:`PyBuffer_Release`, similar to :c:func:`malloc` and :c:func:`free`.
Thus, after the consumer is done with the buffer, :c:func:`PyBuffer_Release`
must be called exactly once.
.. c:function:: void PyBuffer_Release(Py_buffer *view)
Release the buffer *view* and decrement the reference count for
:c:member:`view->obj`. This function MUST be called when the buffer
is no longer being used, otherwise reference leaks may occur.
It is an error to call this function on a buffer that was not obtained via
:c:func:`PyObject_GetBuffer`.
.. c:function:: Py_ssize_t PyBuffer_SizeFromFormat(const char *)
Return the implied :c:data:`~Py_buffer.itemsize` from :c:data:`~Py_buffer.format`.
This function is not yet implemented.
.. c:function:: int PyBuffer_IsContiguous(Py_buffer *view, char order)
Return ``1`` if the memory defined by the *view* is C-style (*order* is
``'C'``) or Fortran-style (*order* is ``'F'``) :term:`contiguous` or either one
(*order* is ``'A'``). Return ``0`` otherwise. This function always succeeds.
.. c:function:: int PyBuffer_ToContiguous(void *buf, Py_buffer *src, Py_ssize_t len, char order)
Copy *len* bytes from *src* to its contiguous representation in *buf*.
*order* can be ``'C'`` or ``'F'`` (for C-style or Fortran-style ordering).
``0`` is returned on success, ``-1`` on error.
This function fails if *len* != *src->len*.
.. c:function:: void PyBuffer_FillContiguousStrides(int ndims, Py_ssize_t *shape, Py_ssize_t *strides, int itemsize, char order)
Fill the *strides* array with byte-strides of a :term:`contiguous` (C-style if
*order* is ``'C'`` or Fortran-style if *order* is ``'F'``) array of the
given shape with the given number of bytes per element.
.. c:function:: int PyBuffer_FillInfo(Py_buffer *view, PyObject *exporter, void *buf, Py_ssize_t len, int readonly, int flags)
Handle buffer requests for an exporter that wants to expose *buf* of size *len*
with writability set according to *readonly*. *buf* is interpreted as a sequence
of unsigned bytes.
The *flags* argument indicates the request type. This function always fills in
*view* as specified by flags, unless *buf* has been designated as read-only
and :c:macro:`PyBUF_WRITABLE` is set in *flags*.
On success, set :c:member:`view->obj` to a new reference to *exporter* and
return 0. Otherwise, raise :c:data:`PyExc_BufferError`, set
:c:member:`view->obj` to *NULL* and return ``-1``;
If this function is used as part of a :ref:`getbufferproc <buffer-structs>`,
*exporter* MUST be set to the exporting object and *flags* must be passed
unmodified. Otherwise, *exporter* MUST be NULL.

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.. highlightlang:: c
.. _bytearrayobjects:
Byte Array Objects
------------------
.. index:: object: bytearray
.. c:type:: PyByteArrayObject
This subtype of :c:type:`PyObject` represents a Python bytearray object.
.. c:var:: PyTypeObject PyByteArray_Type
This instance of :c:type:`PyTypeObject` represents the Python bytearray type;
it is the same object as :class:`bytearray` in the Python layer.
Type check macros
^^^^^^^^^^^^^^^^^
.. c:function:: int PyByteArray_Check(PyObject *o)
Return true if the object *o* is a bytearray object or an instance of a
subtype of the bytearray type.
.. c:function:: int PyByteArray_CheckExact(PyObject *o)
Return true if the object *o* is a bytearray object, but not an instance of a
subtype of the bytearray type.
Direct API functions
^^^^^^^^^^^^^^^^^^^^
.. c:function:: PyObject* PyByteArray_FromObject(PyObject *o)
Return a new bytearray object from any object, *o*, that implements the
:ref:`buffer protocol <bufferobjects>`.
.. XXX expand about the buffer protocol, at least somewhere
.. c:function:: PyObject* PyByteArray_FromStringAndSize(const char *string, Py_ssize_t len)
Create a new bytearray object from *string* and its length, *len*. On
failure, *NULL* is returned.
.. c:function:: PyObject* PyByteArray_Concat(PyObject *a, PyObject *b)
Concat bytearrays *a* and *b* and return a new bytearray with the result.
.. c:function:: Py_ssize_t PyByteArray_Size(PyObject *bytearray)
Return the size of *bytearray* after checking for a *NULL* pointer.
.. c:function:: char* PyByteArray_AsString(PyObject *bytearray)
Return the contents of *bytearray* as a char array after checking for a
*NULL* pointer. The returned array always has an extra
null byte appended.
.. c:function:: int PyByteArray_Resize(PyObject *bytearray, Py_ssize_t len)
Resize the internal buffer of *bytearray* to *len*.
Macros
^^^^^^
These macros trade safety for speed and they don't check pointers.
.. c:function:: char* PyByteArray_AS_STRING(PyObject *bytearray)
Macro version of :c:func:`PyByteArray_AsString`.
.. c:function:: Py_ssize_t PyByteArray_GET_SIZE(PyObject *bytearray)
Macro version of :c:func:`PyByteArray_Size`.

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.. highlightlang:: c
.. _bytesobjects:
Bytes Objects
-------------
These functions raise :exc:`TypeError` when expecting a bytes parameter and are
called with a non-bytes parameter.
.. index:: object: bytes
.. c:type:: PyBytesObject
This subtype of :c:type:`PyObject` represents a Python bytes object.
.. c:var:: PyTypeObject PyBytes_Type
This instance of :c:type:`PyTypeObject` represents the Python bytes type; it
is the same object as :class:`bytes` in the Python layer.
.. c:function:: int PyBytes_Check(PyObject *o)
Return true if the object *o* is a bytes object or an instance of a subtype
of the bytes type.
.. c:function:: int PyBytes_CheckExact(PyObject *o)
Return true if the object *o* is a bytes object, but not an instance of a
subtype of the bytes type.
.. c:function:: PyObject* PyBytes_FromString(const char *v)
Return a new bytes object with a copy of the string *v* as value on success,
and *NULL* on failure. The parameter *v* must not be *NULL*; it will not be
checked.
.. c:function:: PyObject* PyBytes_FromStringAndSize(const char *v, Py_ssize_t len)
Return a new bytes object with a copy of the string *v* as value and length
*len* on success, and *NULL* on failure. If *v* is *NULL*, the contents of
the bytes object are uninitialized.
.. c:function:: PyObject* PyBytes_FromFormat(const char *format, ...)
Take a C :c:func:`printf`\ -style *format* string and a variable number of
arguments, calculate the size of the resulting Python bytes object and return
a bytes object with the values formatted into it. The variable arguments
must be C types and must correspond exactly to the format characters in the
*format* string. The following format characters are allowed:
.. % XXX: This should be exactly the same as the table in PyErr_Format.
.. % One should just refer to the other.
.. % XXX: The descriptions for %zd and %zu are wrong, but the truth is complicated
.. % because not all compilers support the %z width modifier -- we fake it
.. % when necessary via interpolating PY_FORMAT_SIZE_T.
.. tabularcolumns:: |l|l|L|
+-------------------+---------------+--------------------------------+
| Format Characters | Type | Comment |
+===================+===============+================================+
| :attr:`%%` | *n/a* | The literal % character. |
+-------------------+---------------+--------------------------------+
| :attr:`%c` | int | A single byte, |
| | | represented as a C int. |
+-------------------+---------------+--------------------------------+
| :attr:`%d` | int | Exactly equivalent to |
| | | ``printf("%d")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%u` | unsigned int | Exactly equivalent to |
| | | ``printf("%u")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%ld` | long | Exactly equivalent to |
| | | ``printf("%ld")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%lu` | unsigned long | Exactly equivalent to |
| | | ``printf("%lu")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%zd` | Py_ssize_t | Exactly equivalent to |
| | | ``printf("%zd")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%zu` | size_t | Exactly equivalent to |
| | | ``printf("%zu")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%i` | int | Exactly equivalent to |
| | | ``printf("%i")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%x` | int | Exactly equivalent to |
| | | ``printf("%x")``. |
+-------------------+---------------+--------------------------------+
| :attr:`%s` | char\* | A null-terminated C character |
| | | array. |
+-------------------+---------------+--------------------------------+
| :attr:`%p` | void\* | The hex representation of a C |
| | | pointer. Mostly equivalent to |
| | | ``printf("%p")`` except that |
| | | it is guaranteed to start with |
| | | the literal ``0x`` regardless |
| | | of what the platform's |
| | | ``printf`` yields. |
+-------------------+---------------+--------------------------------+
An unrecognized format character causes all the rest of the format string to be
copied as-is to the result object, and any extra arguments discarded.
.. c:function:: PyObject* PyBytes_FromFormatV(const char *format, va_list vargs)
Identical to :c:func:`PyBytes_FromFormat` except that it takes exactly two
arguments.
.. c:function:: PyObject* PyBytes_FromObject(PyObject *o)
Return the bytes representation of object *o* that implements the buffer
protocol.
.. c:function:: Py_ssize_t PyBytes_Size(PyObject *o)
Return the length of the bytes in bytes object *o*.
.. c:function:: Py_ssize_t PyBytes_GET_SIZE(PyObject *o)
Macro form of :c:func:`PyBytes_Size` but without error checking.
.. c:function:: char* PyBytes_AsString(PyObject *o)
Return a pointer to the contents of *o*. The pointer
refers to the internal buffer of *o*, which consists of ``len(o) + 1``
bytes. The last byte in the buffer is always null, regardless of
whether there are any other null bytes. The data must not be
modified in any way, unless the object was just created using
``PyBytes_FromStringAndSize(NULL, size)``. It must not be deallocated. If
*o* is not a bytes object at all, :c:func:`PyBytes_AsString` returns *NULL*
and raises :exc:`TypeError`.
.. c:function:: char* PyBytes_AS_STRING(PyObject *string)
Macro form of :c:func:`PyBytes_AsString` but without error checking.
.. c:function:: int PyBytes_AsStringAndSize(PyObject *obj, char **buffer, Py_ssize_t *length)
Return the null-terminated contents of the object *obj*
through the output variables *buffer* and *length*.
If *length* is *NULL*, the bytes object
may not contain embedded null bytes;
if it does, the function returns ``-1`` and a :exc:`ValueError` is raised.
The buffer refers to an internal buffer of *obj*, which includes an
additional null byte at the end (not counted in *length*). The data
must not be modified in any way, unless the object was just created using
``PyBytes_FromStringAndSize(NULL, size)``. It must not be deallocated. If
*obj* is not a bytes object at all, :c:func:`PyBytes_AsStringAndSize`
returns ``-1`` and raises :exc:`TypeError`.
.. versionchanged:: 3.5
Previously, :exc:`TypeError` was raised when embedded null bytes were
encountered in the bytes object.
.. c:function:: void PyBytes_Concat(PyObject **bytes, PyObject *newpart)
Create a new bytes object in *\*bytes* containing the contents of *newpart*
appended to *bytes*; the caller will own the new reference. The reference to
the old value of *bytes* will be stolen. If the new object cannot be
created, the old reference to *bytes* will still be discarded and the value
of *\*bytes* will be set to *NULL*; the appropriate exception will be set.
.. c:function:: void PyBytes_ConcatAndDel(PyObject **bytes, PyObject *newpart)
Create a new bytes object in *\*bytes* containing the contents of *newpart*
appended to *bytes*. This version decrements the reference count of
*newpart*.
.. c:function:: int _PyBytes_Resize(PyObject **bytes, Py_ssize_t newsize)
A way to resize a bytes object even though it is "immutable". Only use this
to build up a brand new bytes object; don't use this if the bytes may already
be known in other parts of the code. It is an error to call this function if
the refcount on the input bytes object is not one. Pass the address of an
existing bytes object as an lvalue (it may be written into), and the new size
desired. On success, *\*bytes* holds the resized bytes object and ``0`` is
returned; the address in *\*bytes* may differ from its input value. If the
reallocation fails, the original bytes object at *\*bytes* is deallocated,
*\*bytes* is set to *NULL*, :exc:`MemoryError` is set, and ``-1`` is
returned.

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.. highlightlang:: c
.. _capsules:
Capsules
--------
.. index:: object: Capsule
Refer to :ref:`using-capsules` for more information on using these objects.
.. versionadded:: 3.1
.. c:type:: PyCapsule
This subtype of :c:type:`PyObject` represents an opaque value, useful for C
extension modules who need to pass an opaque value (as a :c:type:`void\*`
pointer) through Python code to other C code. It is often used to make a C
function pointer defined in one module available to other modules, so the
regular import mechanism can be used to access C APIs defined in dynamically
loaded modules.
.. c:type:: PyCapsule_Destructor
The type of a destructor callback for a capsule. Defined as::
typedef void (*PyCapsule_Destructor)(PyObject *);
See :c:func:`PyCapsule_New` for the semantics of PyCapsule_Destructor
callbacks.
.. c:function:: int PyCapsule_CheckExact(PyObject *p)
Return true if its argument is a :c:type:`PyCapsule`.
.. c:function:: PyObject* PyCapsule_New(void *pointer, const char *name, PyCapsule_Destructor destructor)
Create a :c:type:`PyCapsule` encapsulating the *pointer*. The *pointer*
argument may not be *NULL*.
On failure, set an exception and return *NULL*.
The *name* string may either be *NULL* or a pointer to a valid C string. If
non-*NULL*, this string must outlive the capsule. (Though it is permitted to
free it inside the *destructor*.)
If the *destructor* argument is not *NULL*, it will be called with the
capsule as its argument when it is destroyed.
If this capsule will be stored as an attribute of a module, the *name* should
be specified as ``modulename.attributename``. This will enable other modules
to import the capsule using :c:func:`PyCapsule_Import`.
.. c:function:: void* PyCapsule_GetPointer(PyObject *capsule, const char *name)
Retrieve the *pointer* stored in the capsule. On failure, set an exception
and return *NULL*.
The *name* parameter must compare exactly to the name stored in the capsule.
If the name stored in the capsule is *NULL*, the *name* passed in must also
be *NULL*. Python uses the C function :c:func:`strcmp` to compare capsule
names.
.. c:function:: PyCapsule_Destructor PyCapsule_GetDestructor(PyObject *capsule)
Return the current destructor stored in the capsule. On failure, set an
exception and return *NULL*.
It is legal for a capsule to have a *NULL* destructor. This makes a *NULL*
return code somewhat ambiguous; use :c:func:`PyCapsule_IsValid` or
:c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: void* PyCapsule_GetContext(PyObject *capsule)
Return the current context stored in the capsule. On failure, set an
exception and return *NULL*.
It is legal for a capsule to have a *NULL* context. This makes a *NULL*
return code somewhat ambiguous; use :c:func:`PyCapsule_IsValid` or
:c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: const char* PyCapsule_GetName(PyObject *capsule)
Return the current name stored in the capsule. On failure, set an exception
and return *NULL*.
It is legal for a capsule to have a *NULL* name. This makes a *NULL* return
code somewhat ambiguous; use :c:func:`PyCapsule_IsValid` or
:c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: void* PyCapsule_Import(const char *name, int no_block)
Import a pointer to a C object from a capsule attribute in a module. The
*name* parameter should specify the full name to the attribute, as in
``module.attribute``. The *name* stored in the capsule must match this
string exactly. If *no_block* is true, import the module without blocking
(using :c:func:`PyImport_ImportModuleNoBlock`). If *no_block* is false,
import the module conventionally (using :c:func:`PyImport_ImportModule`).
Return the capsule's internal *pointer* on success. On failure, set an
exception and return *NULL*.
.. c:function:: int PyCapsule_IsValid(PyObject *capsule, const char *name)
Determines whether or not *capsule* is a valid capsule. A valid capsule is
non-*NULL*, passes :c:func:`PyCapsule_CheckExact`, has a non-*NULL* pointer
stored in it, and its internal name matches the *name* parameter. (See
:c:func:`PyCapsule_GetPointer` for information on how capsule names are
compared.)
In other words, if :c:func:`PyCapsule_IsValid` returns a true value, calls to
any of the accessors (any function starting with :c:func:`PyCapsule_Get`) are
guaranteed to succeed.
Return a nonzero value if the object is valid and matches the name passed in.
Return ``0`` otherwise. This function will not fail.
.. c:function:: int PyCapsule_SetContext(PyObject *capsule, void *context)
Set the context pointer inside *capsule* to *context*.
Return ``0`` on success. Return nonzero and set an exception on failure.
.. c:function:: int PyCapsule_SetDestructor(PyObject *capsule, PyCapsule_Destructor destructor)
Set the destructor inside *capsule* to *destructor*.
Return ``0`` on success. Return nonzero and set an exception on failure.
.. c:function:: int PyCapsule_SetName(PyObject *capsule, const char *name)
Set the name inside *capsule* to *name*. If non-*NULL*, the name must
outlive the capsule. If the previous *name* stored in the capsule was not
*NULL*, no attempt is made to free it.
Return ``0`` on success. Return nonzero and set an exception on failure.
.. c:function:: int PyCapsule_SetPointer(PyObject *capsule, void *pointer)
Set the void pointer inside *capsule* to *pointer*. The pointer may not be
*NULL*.
Return ``0`` on success. Return nonzero and set an exception on failure.

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.. highlightlang:: c
.. _cell-objects:
Cell Objects
------------
"Cell" objects are used to implement variables referenced by multiple scopes.
For each such variable, a cell object is created to store the value; the local
variables of each stack frame that references the value contains a reference to
the cells from outer scopes which also use that variable. When the value is
accessed, the value contained in the cell is used instead of the cell object
itself. This de-referencing of the cell object requires support from the
generated byte-code; these are not automatically de-referenced when accessed.
Cell objects are not likely to be useful elsewhere.
.. c:type:: PyCellObject
The C structure used for cell objects.
.. c:var:: PyTypeObject PyCell_Type
The type object corresponding to cell objects.
.. c:function:: int PyCell_Check(ob)
Return true if *ob* is a cell object; *ob* must not be *NULL*.
.. c:function:: PyObject* PyCell_New(PyObject *ob)
Create and return a new cell object containing the value *ob*. The parameter may
be *NULL*.
.. c:function:: PyObject* PyCell_Get(PyObject *cell)
Return the contents of the cell *cell*.
.. c:function:: PyObject* PyCell_GET(PyObject *cell)
Return the contents of the cell *cell*, but without checking that *cell* is
non-*NULL* and a cell object.
.. c:function:: int PyCell_Set(PyObject *cell, PyObject *value)
Set the contents of the cell object *cell* to *value*. This releases the
reference to any current content of the cell. *value* may be *NULL*. *cell*
must be non-*NULL*; if it is not a cell object, ``-1`` will be returned. On
success, ``0`` will be returned.
.. c:function:: void PyCell_SET(PyObject *cell, PyObject *value)
Sets the value of the cell object *cell* to *value*. No reference counts are
adjusted, and no checks are made for safety; *cell* must be non-*NULL* and must
be a cell object.

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.. highlightlang:: c
.. _codeobjects:
.. index:: object; code, code object
Code Objects
------------
.. sectionauthor:: Jeffrey Yasskin <jyasskin@gmail.com>
Code objects are a low-level detail of the CPython implementation.
Each one represents a chunk of executable code that hasn't yet been
bound into a function.
.. c:type:: PyCodeObject
The C structure of the objects used to describe code objects. The
fields of this type are subject to change at any time.
.. c:var:: PyTypeObject PyCode_Type
This is an instance of :c:type:`PyTypeObject` representing the Python
:class:`code` type.
.. c:function:: int PyCode_Check(PyObject *co)
Return true if *co* is a :class:`code` object.
.. c:function:: int PyCode_GetNumFree(PyCodeObject *co)
Return the number of free variables in *co*.
.. c:function:: PyCodeObject* PyCode_New(int argcount, int kwonlyargcount, int nlocals, int stacksize, int flags, PyObject *code, PyObject *consts, PyObject *names, PyObject *varnames, PyObject *freevars, PyObject *cellvars, PyObject *filename, PyObject *name, int firstlineno, PyObject *lnotab)
Return a new code object. If you need a dummy code object to
create a frame, use :c:func:`PyCode_NewEmpty` instead. Calling
:c:func:`PyCode_New` directly can bind you to a precise Python
version since the definition of the bytecode changes often.
.. c:function:: PyCodeObject* PyCode_NewEmpty(const char *filename, const char *funcname, int firstlineno)
Return a new empty code object with the specified filename,
function name, and first line number. It is illegal to
:func:`exec` or :func:`eval` the resulting code object.

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.. _codec-registry:
Codec registry and support functions
====================================
.. c:function:: int PyCodec_Register(PyObject *search_function)
Register a new codec search function.
As side effect, this tries to load the :mod:`encodings` package, if not yet
done, to make sure that it is always first in the list of search functions.
.. c:function:: int PyCodec_KnownEncoding(const char *encoding)
Return ``1`` or ``0`` depending on whether there is a registered codec for
the given *encoding*. This function always succeeds.
.. c:function:: PyObject* PyCodec_Encode(PyObject *object, const char *encoding, const char *errors)
Generic codec based encoding API.
*object* is passed through the encoder function found for the given
*encoding* using the error handling method defined by *errors*. *errors* may
be *NULL* to use the default method defined for the codec. Raises a
:exc:`LookupError` if no encoder can be found.
.. c:function:: PyObject* PyCodec_Decode(PyObject *object, const char *encoding, const char *errors)
Generic codec based decoding API.
*object* is passed through the decoder function found for the given
*encoding* using the error handling method defined by *errors*. *errors* may
be *NULL* to use the default method defined for the codec. Raises a
:exc:`LookupError` if no encoder can be found.
Codec lookup API
----------------
In the following functions, the *encoding* string is looked up converted to all
lower-case characters, which makes encodings looked up through this mechanism
effectively case-insensitive. If no codec is found, a :exc:`KeyError` is set
and *NULL* returned.
.. c:function:: PyObject* PyCodec_Encoder(const char *encoding)
Get an encoder function for the given *encoding*.
.. c:function:: PyObject* PyCodec_Decoder(const char *encoding)
Get a decoder function for the given *encoding*.
.. c:function:: PyObject* PyCodec_IncrementalEncoder(const char *encoding, const char *errors)
Get an :class:`~codecs.IncrementalEncoder` object for the given *encoding*.
.. c:function:: PyObject* PyCodec_IncrementalDecoder(const char *encoding, const char *errors)
Get an :class:`~codecs.IncrementalDecoder` object for the given *encoding*.
.. c:function:: PyObject* PyCodec_StreamReader(const char *encoding, PyObject *stream, const char *errors)
Get a :class:`~codecs.StreamReader` factory function for the given *encoding*.
.. c:function:: PyObject* PyCodec_StreamWriter(const char *encoding, PyObject *stream, const char *errors)
Get a :class:`~codecs.StreamWriter` factory function for the given *encoding*.
Registry API for Unicode encoding error handlers
------------------------------------------------
.. c:function:: int PyCodec_RegisterError(const char *name, PyObject *error)
Register the error handling callback function *error* under the given *name*.
This callback function will be called by a codec when it encounters
unencodable characters/undecodable bytes and *name* is specified as the error
parameter in the call to the encode/decode function.
The callback gets a single argument, an instance of
:exc:`UnicodeEncodeError`, :exc:`UnicodeDecodeError` or
:exc:`UnicodeTranslateError` that holds information about the problematic
sequence of characters or bytes and their offset in the original string (see
:ref:`unicodeexceptions` for functions to extract this information). The
callback must either raise the given exception, or return a two-item tuple
containing the replacement for the problematic sequence, and an integer
giving the offset in the original string at which encoding/decoding should be
resumed.
Return ``0`` on success, ``-1`` on error.
.. c:function:: PyObject* PyCodec_LookupError(const char *name)
Lookup the error handling callback function registered under *name*. As a
special case *NULL* can be passed, in which case the error handling callback
for "strict" will be returned.
.. c:function:: PyObject* PyCodec_StrictErrors(PyObject *exc)
Raise *exc* as an exception.
.. c:function:: PyObject* PyCodec_IgnoreErrors(PyObject *exc)
Ignore the unicode error, skipping the faulty input.
.. c:function:: PyObject* PyCodec_ReplaceErrors(PyObject *exc)
Replace the unicode encode error with ``?`` or ``U+FFFD``.
.. c:function:: PyObject* PyCodec_XMLCharRefReplaceErrors(PyObject *exc)
Replace the unicode encode error with XML character references.
.. c:function:: PyObject* PyCodec_BackslashReplaceErrors(PyObject *exc)
Replace the unicode encode error with backslash escapes (``\x``, ``\u`` and
``\U``).
.. c:function:: PyObject* PyCodec_NameReplaceErrors(PyObject *exc)
Replace the unicode encode error with ``\N{...}`` escapes.
.. versionadded:: 3.5

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.. highlightlang:: c
.. _complexobjects:
Complex Number Objects
----------------------
.. index:: object: complex number
Python's complex number objects are implemented as two distinct types when
viewed from the C API: one is the Python object exposed to Python programs, and
the other is a C structure which represents the actual complex number value.
The API provides functions for working with both.
Complex Numbers as C Structures
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Note that the functions which accept these structures as parameters and return
them as results do so *by value* rather than dereferencing them through
pointers. This is consistent throughout the API.
.. c:type:: Py_complex
The C structure which corresponds to the value portion of a Python complex
number object. Most of the functions for dealing with complex number objects
use structures of this type as input or output values, as appropriate. It is
defined as::
typedef struct {
double real;
double imag;
} Py_complex;
.. c:function:: Py_complex _Py_c_sum(Py_complex left, Py_complex right)
Return the sum of two complex numbers, using the C :c:type:`Py_complex`
representation.
.. c:function:: Py_complex _Py_c_diff(Py_complex left, Py_complex right)
Return the difference between two complex numbers, using the C
:c:type:`Py_complex` representation.
.. c:function:: Py_complex _Py_c_neg(Py_complex complex)
Return the negation of the complex number *complex*, using the C
:c:type:`Py_complex` representation.
.. c:function:: Py_complex _Py_c_prod(Py_complex left, Py_complex right)
Return the product of two complex numbers, using the C :c:type:`Py_complex`
representation.
.. c:function:: Py_complex _Py_c_quot(Py_complex dividend, Py_complex divisor)
Return the quotient of two complex numbers, using the C :c:type:`Py_complex`
representation.
If *divisor* is null, this method returns zero and sets
:c:data:`errno` to :c:data:`EDOM`.
.. c:function:: Py_complex _Py_c_pow(Py_complex num, Py_complex exp)
Return the exponentiation of *num* by *exp*, using the C :c:type:`Py_complex`
representation.
If *num* is null and *exp* is not a positive real number,
this method returns zero and sets :c:data:`errno` to :c:data:`EDOM`.
Complex Numbers as Python Objects
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. c:type:: PyComplexObject
This subtype of :c:type:`PyObject` represents a Python complex number object.
.. c:var:: PyTypeObject PyComplex_Type
This instance of :c:type:`PyTypeObject` represents the Python complex number
type. It is the same object as :class:`complex` in the Python layer.
.. c:function:: int PyComplex_Check(PyObject *p)
Return true if its argument is a :c:type:`PyComplexObject` or a subtype of
:c:type:`PyComplexObject`.
.. c:function:: int PyComplex_CheckExact(PyObject *p)
Return true if its argument is a :c:type:`PyComplexObject`, but not a subtype of
:c:type:`PyComplexObject`.
.. c:function:: PyObject* PyComplex_FromCComplex(Py_complex v)
Create a new Python complex number object from a C :c:type:`Py_complex` value.
.. c:function:: PyObject* PyComplex_FromDoubles(double real, double imag)
Return a new :c:type:`PyComplexObject` object from *real* and *imag*.
.. c:function:: double PyComplex_RealAsDouble(PyObject *op)
Return the real part of *op* as a C :c:type:`double`.
.. c:function:: double PyComplex_ImagAsDouble(PyObject *op)
Return the imaginary part of *op* as a C :c:type:`double`.
.. c:function:: Py_complex PyComplex_AsCComplex(PyObject *op)
Return the :c:type:`Py_complex` value of the complex number *op*.
If *op* is not a Python complex number object but has a :meth:`__complex__`
method, this method will first be called to convert *op* to a Python complex
number object. Upon failure, this method returns ``-1.0`` as a real value.

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.. highlightlang:: c
.. _concrete:
**********************
Concrete Objects Layer
**********************
The functions in this chapter are specific to certain Python object types.
Passing them an object of the wrong type is not a good idea; if you receive an
object from a Python program and you are not sure that it has the right type,
you must perform a type check first; for example, to check that an object is a
dictionary, use :c:func:`PyDict_Check`. The chapter is structured like the
"family tree" of Python object types.
.. warning::
While the functions described in this chapter carefully check the type of the
objects which are passed in, many of them do not check for *NULL* being passed
instead of a valid object. Allowing *NULL* to be passed in can cause memory
access violations and immediate termination of the interpreter.
.. _fundamental:
Fundamental Objects
===================
This section describes Python type objects and the singleton object ``None``.
.. toctree::
type.rst
none.rst
.. _numericobjects:
Numeric Objects
===============
.. index:: object: numeric
.. toctree::
long.rst
bool.rst
float.rst
complex.rst
.. _sequenceobjects:
Sequence Objects
================
.. index:: object: sequence
Generic operations on sequence objects were discussed in the previous chapter;
this section deals with the specific kinds of sequence objects that are
intrinsic to the Python language.
.. XXX sort out unicode, str, bytes and bytearray
.. toctree::
bytes.rst
bytearray.rst
unicode.rst
tuple.rst
list.rst
.. _mapobjects:
Container Objects
=================
.. index:: object: mapping
.. toctree::
dict.rst
set.rst
.. _otherobjects:
Function Objects
================
.. toctree::
function.rst
method.rst
cell.rst
code.rst
Other Objects
=============
.. toctree::
file.rst
module.rst
iterator.rst
descriptor.rst
slice.rst
memoryview.rst
weakref.rst
capsule.rst
gen.rst
coro.rst
datetime.rst

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.. highlightlang:: c
.. _string-conversion:
String conversion and formatting
================================
Functions for number conversion and formatted string output.
.. c:function:: int PyOS_snprintf(char *str, size_t size, const char *format, ...)
Output not more than *size* bytes to *str* according to the format string
*format* and the extra arguments. See the Unix man page :manpage:`snprintf(2)`.
.. c:function:: int PyOS_vsnprintf(char *str, size_t size, const char *format, va_list va)
Output not more than *size* bytes to *str* according to the format string
*format* and the variable argument list *va*. Unix man page
:manpage:`vsnprintf(2)`.
:c:func:`PyOS_snprintf` and :c:func:`PyOS_vsnprintf` wrap the Standard C library
functions :c:func:`snprintf` and :c:func:`vsnprintf`. Their purpose is to
guarantee consistent behavior in corner cases, which the Standard C functions do
not.
The wrappers ensure that *str*[*size*-1] is always ``'\0'`` upon return. They
never write more than *size* bytes (including the trailing ``'\0'``) into str.
Both functions require that ``str != NULL``, ``size > 0`` and ``format !=
NULL``.
If the platform doesn't have :c:func:`vsnprintf` and the buffer size needed to
avoid truncation exceeds *size* by more than 512 bytes, Python aborts with a
*Py_FatalError*.
The return value (*rv*) for these functions should be interpreted as follows:
* When ``0 <= rv < size``, the output conversion was successful and *rv*
characters were written to *str* (excluding the trailing ``'\0'`` byte at
*str*[*rv*]).
* When ``rv >= size``, the output conversion was truncated and a buffer with
``rv + 1`` bytes would have been needed to succeed. *str*[*size*-1] is ``'\0'``
in this case.
* When ``rv < 0``, "something bad happened." *str*[*size*-1] is ``'\0'`` in
this case too, but the rest of *str* is undefined. The exact cause of the error
depends on the underlying platform.
The following functions provide locale-independent string to number conversions.
.. c:function:: double PyOS_string_to_double(const char *s, char **endptr, PyObject *overflow_exception)
Convert a string ``s`` to a :c:type:`double`, raising a Python
exception on failure. The set of accepted strings corresponds to
the set of strings accepted by Python's :func:`float` constructor,
except that ``s`` must not have leading or trailing whitespace.
The conversion is independent of the current locale.
If ``endptr`` is ``NULL``, convert the whole string. Raise
ValueError and return ``-1.0`` if the string is not a valid
representation of a floating-point number.
If endptr is not ``NULL``, convert as much of the string as
possible and set ``*endptr`` to point to the first unconverted
character. If no initial segment of the string is the valid
representation of a floating-point number, set ``*endptr`` to point
to the beginning of the string, raise ValueError, and return
``-1.0``.
If ``s`` represents a value that is too large to store in a float
(for example, ``"1e500"`` is such a string on many platforms) then
if ``overflow_exception`` is ``NULL`` return ``Py_HUGE_VAL`` (with
an appropriate sign) and don't set any exception. Otherwise,
``overflow_exception`` must point to a Python exception object;
raise that exception and return ``-1.0``. In both cases, set
``*endptr`` to point to the first character after the converted value.
If any other error occurs during the conversion (for example an
out-of-memory error), set the appropriate Python exception and
return ``-1.0``.
.. versionadded:: 3.1
.. c:function:: char* PyOS_double_to_string(double val, char format_code, int precision, int flags, int *ptype)
Convert a :c:type:`double` *val* to a string using supplied
*format_code*, *precision*, and *flags*.
*format_code* must be one of ``'e'``, ``'E'``, ``'f'``, ``'F'``,
``'g'``, ``'G'`` or ``'r'``. For ``'r'``, the supplied *precision*
must be 0 and is ignored. The ``'r'`` format code specifies the
standard :func:`repr` format.
*flags* can be zero or more of the values *Py_DTSF_SIGN*,
*Py_DTSF_ADD_DOT_0*, or *Py_DTSF_ALT*, or-ed together:
* *Py_DTSF_SIGN* means to always precede the returned string with a sign
character, even if *val* is non-negative.
* *Py_DTSF_ADD_DOT_0* means to ensure that the returned string will not look
like an integer.
* *Py_DTSF_ALT* means to apply "alternate" formatting rules. See the
documentation for the :c:func:`PyOS_snprintf` ``'#'`` specifier for
details.
If *ptype* is non-NULL, then the value it points to will be set to one of
*Py_DTST_FINITE*, *Py_DTST_INFINITE*, or *Py_DTST_NAN*, signifying that
*val* is a finite number, an infinite number, or not a number, respectively.
The return value is a pointer to *buffer* with the converted string or
*NULL* if the conversion failed. The caller is responsible for freeing the
returned string by calling :c:func:`PyMem_Free`.
.. versionadded:: 3.1
.. c:function:: int PyOS_stricmp(const char *s1, const char *s2)
Case insensitive comparison of strings. The function works almost
identically to :c:func:`strcmp` except that it ignores the case.
.. c:function:: int PyOS_strnicmp(const char *s1, const char *s2, Py_ssize_t size)
Case insensitive comparison of strings. The function works almost
identically to :c:func:`strncmp` except that it ignores the case.

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.. highlightlang:: c
.. _coro-objects:
Coroutine Objects
-----------------
.. versionadded:: 3.5
Coroutine objects are what functions declared with an ``async`` keyword
return.
.. c:type:: PyCoroObject
The C structure used for coroutine objects.
.. c:var:: PyTypeObject PyCoro_Type
The type object corresponding to coroutine objects.
.. c:function:: int PyCoro_CheckExact(PyObject *ob)
Return true if *ob*'s type is *PyCoro_Type*; *ob* must not be *NULL*.
.. c:function:: PyObject* PyCoro_New(PyFrameObject *frame, PyObject *name, PyObject *qualname)
Create and return a new coroutine object based on the *frame* object,
with ``__name__`` and ``__qualname__`` set to *name* and *qualname*.
A reference to *frame* is stolen by this function. The *frame* argument
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.. highlightlang:: c
.. _datetimeobjects:
DateTime Objects
----------------
Various date and time objects are supplied by the :mod:`datetime` module.
Before using any of these functions, the header file :file:`datetime.h` must be
included in your source (note that this is not included by :file:`Python.h`),
and the macro :c:macro:`PyDateTime_IMPORT` must be invoked, usually as part of
the module initialisation function. The macro puts a pointer to a C structure
into a static variable, :c:data:`PyDateTimeAPI`, that is used by the following
macros.
Type-check macros:
.. c:function:: int PyDate_Check(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DateType` or a subtype of
:c:data:`PyDateTime_DateType`. *ob* must not be *NULL*.
.. c:function:: int PyDate_CheckExact(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DateType`. *ob* must not be
*NULL*.
.. c:function:: int PyDateTime_Check(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DateTimeType` or a subtype of
:c:data:`PyDateTime_DateTimeType`. *ob* must not be *NULL*.
.. c:function:: int PyDateTime_CheckExact(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DateTimeType`. *ob* must not
be *NULL*.
.. c:function:: int PyTime_Check(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_TimeType` or a subtype of
:c:data:`PyDateTime_TimeType`. *ob* must not be *NULL*.
.. c:function:: int PyTime_CheckExact(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_TimeType`. *ob* must not be
*NULL*.
.. c:function:: int PyDelta_Check(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DeltaType` or a subtype of
:c:data:`PyDateTime_DeltaType`. *ob* must not be *NULL*.
.. c:function:: int PyDelta_CheckExact(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_DeltaType`. *ob* must not be
*NULL*.
.. c:function:: int PyTZInfo_Check(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_TZInfoType` or a subtype of
:c:data:`PyDateTime_TZInfoType`. *ob* must not be *NULL*.
.. c:function:: int PyTZInfo_CheckExact(PyObject *ob)
Return true if *ob* is of type :c:data:`PyDateTime_TZInfoType`. *ob* must not be
*NULL*.
Macros to create objects:
.. c:function:: PyObject* PyDate_FromDate(int year, int month, int day)
Return a ``datetime.date`` object with the specified year, month and day.
.. c:function:: PyObject* PyDateTime_FromDateAndTime(int year, int month, int day, int hour, int minute, int second, int usecond)
Return a ``datetime.datetime`` object with the specified year, month, day, hour,
minute, second and microsecond.
.. c:function:: PyObject* PyTime_FromTime(int hour, int minute, int second, int usecond)
Return a ``datetime.time`` object with the specified hour, minute, second and
microsecond.
.. c:function:: PyObject* PyDelta_FromDSU(int days, int seconds, int useconds)
Return a ``datetime.timedelta`` object representing the given number of days,
seconds and microseconds. Normalization is performed so that the resulting
number of microseconds and seconds lie in the ranges documented for
``datetime.timedelta`` objects.
Macros to extract fields from date objects. The argument must be an instance of
:c:data:`PyDateTime_Date`, including subclasses (such as
:c:data:`PyDateTime_DateTime`). The argument must not be *NULL*, and the type is
not checked:
.. c:function:: int PyDateTime_GET_YEAR(PyDateTime_Date *o)
Return the year, as a positive int.
.. c:function:: int PyDateTime_GET_MONTH(PyDateTime_Date *o)
Return the month, as an int from 1 through 12.
.. c:function:: int PyDateTime_GET_DAY(PyDateTime_Date *o)
Return the day, as an int from 1 through 31.
Macros to extract fields from datetime objects. The argument must be an
instance of :c:data:`PyDateTime_DateTime`, including subclasses. The argument
must not be *NULL*, and the type is not checked:
.. c:function:: int PyDateTime_DATE_GET_HOUR(PyDateTime_DateTime *o)
Return the hour, as an int from 0 through 23.
.. c:function:: int PyDateTime_DATE_GET_MINUTE(PyDateTime_DateTime *o)
Return the minute, as an int from 0 through 59.
.. c:function:: int PyDateTime_DATE_GET_SECOND(PyDateTime_DateTime *o)
Return the second, as an int from 0 through 59.
.. c:function:: int PyDateTime_DATE_GET_MICROSECOND(PyDateTime_DateTime *o)
Return the microsecond, as an int from 0 through 999999.
Macros to extract fields from time objects. The argument must be an instance of
:c:data:`PyDateTime_Time`, including subclasses. The argument must not be *NULL*,
and the type is not checked:
.. c:function:: int PyDateTime_TIME_GET_HOUR(PyDateTime_Time *o)
Return the hour, as an int from 0 through 23.
.. c:function:: int PyDateTime_TIME_GET_MINUTE(PyDateTime_Time *o)
Return the minute, as an int from 0 through 59.
.. c:function:: int PyDateTime_TIME_GET_SECOND(PyDateTime_Time *o)
Return the second, as an int from 0 through 59.
.. c:function:: int PyDateTime_TIME_GET_MICROSECOND(PyDateTime_Time *o)
Return the microsecond, as an int from 0 through 999999.
Macros to extract fields from time delta objects. The argument must be an
instance of :c:data:`PyDateTime_Delta`, including subclasses. The argument must
not be *NULL*, and the type is not checked:
.. c:function:: int PyDateTime_DELTA_GET_DAYS(PyDateTime_Delta *o)
Return the number of days, as an int from -999999999 to 999999999.
.. versionadded:: 3.3
.. c:function:: int PyDateTime_DELTA_GET_SECONDS(PyDateTime_Delta *o)
Return the number of seconds, as an int from 0 through 86399.
.. versionadded:: 3.3
.. c:function:: int PyDateTime_DELTA_GET_MICROSECONDS(PyDateTime_Delta *o)
Return the number of microseconds, as an int from 0 through 999999.
.. versionadded:: 3.3
Macros for the convenience of modules implementing the DB API:
.. c:function:: PyObject* PyDateTime_FromTimestamp(PyObject *args)
Create and return a new ``datetime.datetime`` object given an argument tuple
suitable for passing to ``datetime.datetime.fromtimestamp()``.
.. c:function:: PyObject* PyDate_FromTimestamp(PyObject *args)
Create and return a new ``datetime.date`` object given an argument tuple
suitable for passing to ``datetime.date.fromtimestamp()``.

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.. highlightlang:: c
.. _descriptor-objects:
Descriptor Objects
------------------
"Descriptors" are objects that describe some attribute of an object. They are
found in the dictionary of type objects.
.. XXX document these!
.. c:var:: PyTypeObject PyProperty_Type
The type object for the built-in descriptor types.
.. c:function:: PyObject* PyDescr_NewGetSet(PyTypeObject *type, struct PyGetSetDef *getset)
.. c:function:: PyObject* PyDescr_NewMember(PyTypeObject *type, struct PyMemberDef *meth)
.. c:function:: PyObject* PyDescr_NewMethod(PyTypeObject *type, struct PyMethodDef *meth)
.. c:function:: PyObject* PyDescr_NewWrapper(PyTypeObject *type, struct wrapperbase *wrapper, void *wrapped)
.. c:function:: PyObject* PyDescr_NewClassMethod(PyTypeObject *type, PyMethodDef *method)
.. c:function:: int PyDescr_IsData(PyObject *descr)
Return true if the descriptor objects *descr* describes a data attribute, or
false if it describes a method. *descr* must be a descriptor object; there is
no error checking.
.. c:function:: PyObject* PyWrapper_New(PyObject *, PyObject *)

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.. highlightlang:: c
.. _dictobjects:
Dictionary Objects
------------------
.. index:: object: dictionary
.. c:type:: PyDictObject
This subtype of :c:type:`PyObject` represents a Python dictionary object.
.. c:var:: PyTypeObject PyDict_Type
This instance of :c:type:`PyTypeObject` represents the Python dictionary
type. This is the same object as :class:`dict` in the Python layer.
.. c:function:: int PyDict_Check(PyObject *p)
Return true if *p* is a dict object or an instance of a subtype of the dict
type.
.. c:function:: int PyDict_CheckExact(PyObject *p)
Return true if *p* is a dict object, but not an instance of a subtype of
the dict type.
.. c:function:: PyObject* PyDict_New()
Return a new empty dictionary, or *NULL* on failure.
.. c:function:: PyObject* PyDictProxy_New(PyObject *mapping)
Return a :class:`types.MappingProxyType` object for a mapping which
enforces read-only behavior. This is normally used to create a view to
prevent modification of the dictionary for non-dynamic class types.
.. c:function:: void PyDict_Clear(PyObject *p)
Empty an existing dictionary of all key-value pairs.
.. c:function:: int PyDict_Contains(PyObject *p, PyObject *key)
Determine if dictionary *p* contains *key*. If an item in *p* is matches
*key*, return ``1``, otherwise return ``0``. On error, return ``-1``.
This is equivalent to the Python expression ``key in p``.
.. c:function:: PyObject* PyDict_Copy(PyObject *p)
Return a new dictionary that contains the same key-value pairs as *p*.
.. c:function:: int PyDict_SetItem(PyObject *p, PyObject *key, PyObject *val)
Insert *value* into the dictionary *p* with a key of *key*. *key* must be
:term:`hashable`; if it isn't, :exc:`TypeError` will be raised. Return
``0`` on success or ``-1`` on failure.
.. c:function:: int PyDict_SetItemString(PyObject *p, const char *key, PyObject *val)
.. index:: single: PyUnicode_FromString()
Insert *value* into the dictionary *p* using *key* as a key. *key* should
be a :c:type:`char\*`. The key object is created using
``PyUnicode_FromString(key)``. Return ``0`` on success or ``-1`` on
failure.
.. c:function:: int PyDict_DelItem(PyObject *p, PyObject *key)
Remove the entry in dictionary *p* with key *key*. *key* must be hashable;
if it isn't, :exc:`TypeError` is raised. Return ``0`` on success or ``-1``
on failure.
.. c:function:: int PyDict_DelItemString(PyObject *p, const char *key)
Remove the entry in dictionary *p* which has a key specified by the string
*key*. Return ``0`` on success or ``-1`` on failure.
.. c:function:: PyObject* PyDict_GetItem(PyObject *p, PyObject *key)
Return the object from dictionary *p* which has a key *key*. Return *NULL*
if the key *key* is not present, but *without* setting an exception.
Note that exceptions which occur while calling :meth:`__hash__` and
:meth:`__eq__` methods will get suppressed.
To get error reporting use :c:func:`PyDict_GetItemWithError()` instead.
.. c:function:: PyObject* PyDict_GetItemWithError(PyObject *p, PyObject *key)
Variant of :c:func:`PyDict_GetItem` that does not suppress
exceptions. Return *NULL* **with** an exception set if an exception
occurred. Return *NULL* **without** an exception set if the key
wasn't present.
.. c:function:: PyObject* PyDict_GetItemString(PyObject *p, const char *key)
This is the same as :c:func:`PyDict_GetItem`, but *key* is specified as a
:c:type:`char\*`, rather than a :c:type:`PyObject\*`.
Note that exceptions which occur while calling :meth:`__hash__` and
:meth:`__eq__` methods and creating a temporary string object
will get suppressed.
To get error reporting use :c:func:`PyDict_GetItemWithError()` instead.
.. c:function:: PyObject* PyDict_SetDefault(PyObject *p, PyObject *key, PyObject *default)
This is the same as the Python-level :meth:`dict.setdefault`. If present, it
returns the value corresponding to *key* from the dictionary *p*. If the key
is not in the dict, it is inserted with value *defaultobj* and *defaultobj*
is returned. This function evaluates the hash function of *key* only once,
instead of evaluating it independently for the lookup and the insertion.
.. versionadded:: 3.4
.. c:function:: PyObject* PyDict_Items(PyObject *p)
Return a :c:type:`PyListObject` containing all the items from the dictionary.
.. c:function:: PyObject* PyDict_Keys(PyObject *p)
Return a :c:type:`PyListObject` containing all the keys from the dictionary.
.. c:function:: PyObject* PyDict_Values(PyObject *p)
Return a :c:type:`PyListObject` containing all the values from the dictionary
*p*.
.. c:function:: Py_ssize_t PyDict_Size(PyObject *p)
.. index:: builtin: len
Return the number of items in the dictionary. This is equivalent to
``len(p)`` on a dictionary.
.. c:function:: int PyDict_Next(PyObject *p, Py_ssize_t *ppos, PyObject **pkey, PyObject **pvalue)
Iterate over all key-value pairs in the dictionary *p*. The
:c:type:`Py_ssize_t` referred to by *ppos* must be initialized to ``0``
prior to the first call to this function to start the iteration; the
function returns true for each pair in the dictionary, and false once all
pairs have been reported. The parameters *pkey* and *pvalue* should either
point to :c:type:`PyObject\*` variables that will be filled in with each key
and value, respectively, or may be *NULL*. Any references returned through
them are borrowed. *ppos* should not be altered during iteration. Its
value represents offsets within the internal dictionary structure, and
since the structure is sparse, the offsets are not consecutive.
For example::
PyObject *key, *value;
Py_ssize_t pos = 0;
while (PyDict_Next(self->dict, &pos, &key, &value)) {
/* do something interesting with the values... */
...
}
The dictionary *p* should not be mutated during iteration. It is safe to
modify the values of the keys as you iterate over the dictionary, but only
so long as the set of keys does not change. For example::
PyObject *key, *value;
Py_ssize_t pos = 0;
while (PyDict_Next(self->dict, &pos, &key, &value)) {
long i = PyLong_AsLong(value);
if (i == -1 && PyErr_Occurred()) {
return -1;
}
PyObject *o = PyLong_FromLong(i + 1);
if (o == NULL)
return -1;
if (PyDict_SetItem(self->dict, key, o) < 0) {
Py_DECREF(o);
return -1;
}
Py_DECREF(o);
}
.. c:function:: int PyDict_Merge(PyObject *a, PyObject *b, int override)
Iterate over mapping object *b* adding key-value pairs to dictionary *a*.
*b* may be a dictionary, or any object supporting :c:func:`PyMapping_Keys`
and :c:func:`PyObject_GetItem`. If *override* is true, existing pairs in *a*
will be replaced if a matching key is found in *b*, otherwise pairs will
only be added if there is not a matching key in *a*. Return ``0`` on
success or ``-1`` if an exception was raised.
.. c:function:: int PyDict_Update(PyObject *a, PyObject *b)
This is the same as ``PyDict_Merge(a, b, 1)`` in C, and is similar to
``a.update(b)`` in Python except that :c:func:`PyDict_Update` doesn't fall
back to the iterating over a sequence of key value pairs if the second
argument has no "keys" attribute. Return ``0`` on success or ``-1`` if an
exception was raised.
.. c:function:: int PyDict_MergeFromSeq2(PyObject *a, PyObject *seq2, int override)
Update or merge into dictionary *a*, from the key-value pairs in *seq2*.
*seq2* must be an iterable object producing iterable objects of length 2,
viewed as key-value pairs. In case of duplicate keys, the last wins if
*override* is true, else the first wins. Return ``0`` on success or ``-1``
if an exception was raised. Equivalent Python (except for the return
value)::
def PyDict_MergeFromSeq2(a, seq2, override):
for key, value in seq2:
if override or key not in a:
a[key] = value
.. c:function:: int PyDict_ClearFreeList()
Clear the free list. Return the total number of freed items.
.. versionadded:: 3.3

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.. highlightlang:: c
.. _fileobjects:
File Objects
------------
.. index:: object: file
These APIs are a minimal emulation of the Python 2 C API for built-in file
objects, which used to rely on the buffered I/O (:c:type:`FILE\*`) support
from the C standard library. In Python 3, files and streams use the new
:mod:`io` module, which defines several layers over the low-level unbuffered
I/O of the operating system. The functions described below are
convenience C wrappers over these new APIs, and meant mostly for internal
error reporting in the interpreter; third-party code is advised to access
the :mod:`io` APIs instead.
.. c:function:: PyFile_FromFd(int fd, const char *name, const char *mode, int buffering, const char *encoding, const char *errors, const char *newline, int closefd)
Create a Python file object from the file descriptor of an already
opened file *fd*. The arguments *name*, *encoding*, *errors* and *newline*
can be *NULL* to use the defaults; *buffering* can be *-1* to use the
default. *name* is ignored and kept for backward compatibility. Return
*NULL* on failure. For a more comprehensive description of the arguments,
please refer to the :func:`io.open` function documentation.
.. warning::
Since Python streams have their own buffering layer, mixing them with
OS-level file descriptors can produce various issues (such as unexpected
ordering of data).
.. versionchanged:: 3.2
Ignore *name* attribute.
.. c:function:: int PyObject_AsFileDescriptor(PyObject *p)
Return the file descriptor associated with *p* as an :c:type:`int`. If the
object is an integer, its value is returned. If not, the
object's :meth:`~io.IOBase.fileno` method is called if it exists; the
method must return an integer, which is returned as the file descriptor
value. Sets an exception and returns ``-1`` on failure.
.. c:function:: PyObject* PyFile_GetLine(PyObject *p, int n)
.. index:: single: EOFError (built-in exception)
Equivalent to ``p.readline([n])``, this function reads one line from the
object *p*. *p* may be a file object or any object with a
:meth:`~io.IOBase.readline`
method. If *n* is ``0``, exactly one line is read, regardless of the length of
the line. If *n* is greater than ``0``, no more than *n* bytes will be read
from the file; a partial line can be returned. In both cases, an empty string
is returned if the end of the file is reached immediately. If *n* is less than
``0``, however, one line is read regardless of length, but :exc:`EOFError` is
raised if the end of the file is reached immediately.
.. c:function:: int PyFile_WriteObject(PyObject *obj, PyObject *p, int flags)
.. index:: single: Py_PRINT_RAW
Write object *obj* to file object *p*. The only supported flag for *flags* is
:const:`Py_PRINT_RAW`; if given, the :func:`str` of the object is written
instead of the :func:`repr`. Return ``0`` on success or ``-1`` on failure; the
appropriate exception will be set.
.. c:function:: int PyFile_WriteString(const char *s, PyObject *p)
Write string *s* to file object *p*. Return ``0`` on success or ``-1`` on
failure; the appropriate exception will be set.

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.. highlightlang:: c
.. _floatobjects:
Floating Point Objects
----------------------
.. index:: object: floating point
.. c:type:: PyFloatObject
This subtype of :c:type:`PyObject` represents a Python floating point object.
.. c:var:: PyTypeObject PyFloat_Type
This instance of :c:type:`PyTypeObject` represents the Python floating point
type. This is the same object as :class:`float` in the Python layer.
.. c:function:: int PyFloat_Check(PyObject *p)
Return true if its argument is a :c:type:`PyFloatObject` or a subtype of
:c:type:`PyFloatObject`.
.. c:function:: int PyFloat_CheckExact(PyObject *p)
Return true if its argument is a :c:type:`PyFloatObject`, but not a subtype of
:c:type:`PyFloatObject`.
.. c:function:: PyObject* PyFloat_FromString(PyObject *str)
Create a :c:type:`PyFloatObject` object based on the string value in *str*, or
*NULL* on failure.
.. c:function:: PyObject* PyFloat_FromDouble(double v)
Create a :c:type:`PyFloatObject` object from *v*, or *NULL* on failure.
.. c:function:: double PyFloat_AsDouble(PyObject *pyfloat)
Return a C :c:type:`double` representation of the contents of *pyfloat*. If
*pyfloat* is not a Python floating point object but has a :meth:`__float__`
method, this method will first be called to convert *pyfloat* into a float.
This method returns ``-1.0`` upon failure, so one should call
:c:func:`PyErr_Occurred` to check for errors.
.. c:function:: double PyFloat_AS_DOUBLE(PyObject *pyfloat)
Return a C :c:type:`double` representation of the contents of *pyfloat*, but
without error checking.
.. c:function:: PyObject* PyFloat_GetInfo(void)
Return a structseq instance which contains information about the
precision, minimum and maximum values of a float. It's a thin wrapper
around the header file :file:`float.h`.
.. c:function:: double PyFloat_GetMax()
Return the maximum representable finite float *DBL_MAX* as C :c:type:`double`.
.. c:function:: double PyFloat_GetMin()
Return the minimum normalized positive float *DBL_MIN* as C :c:type:`double`.
.. c:function:: int PyFloat_ClearFreeList()
Clear the float free list. Return the number of items that could not
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.. highlightlang:: c
.. _function-objects:
Function Objects
----------------
.. index:: object: function
There are a few functions specific to Python functions.
.. c:type:: PyFunctionObject
The C structure used for functions.
.. c:var:: PyTypeObject PyFunction_Type
.. index:: single: MethodType (in module types)
This is an instance of :c:type:`PyTypeObject` and represents the Python function
type. It is exposed to Python programmers as ``types.FunctionType``.
.. c:function:: int PyFunction_Check(PyObject *o)
Return true if *o* is a function object (has type :c:data:`PyFunction_Type`).
The parameter must not be *NULL*.
.. c:function:: PyObject* PyFunction_New(PyObject *code, PyObject *globals)
Return a new function object associated with the code object *code*. *globals*
must be a dictionary with the global variables accessible to the function.
The function's docstring and name are retrieved from the code object. *__module__*
is retrieved from *globals*. The argument defaults, annotations and closure are
set to *NULL*. *__qualname__* is set to the same value as the function's name.
.. c:function:: PyObject* PyFunction_NewWithQualName(PyObject *code, PyObject *globals, PyObject *qualname)
As :c:func:`PyFunction_New`, but also allows setting the function object's
``__qualname__`` attribute. *qualname* should be a unicode object or NULL;
if NULL, the ``__qualname__`` attribute is set to the same value as its
``__name__`` attribute.
.. versionadded:: 3.3
.. c:function:: PyObject* PyFunction_GetCode(PyObject *op)
Return the code object associated with the function object *op*.
.. c:function:: PyObject* PyFunction_GetGlobals(PyObject *op)
Return the globals dictionary associated with the function object *op*.
.. c:function:: PyObject* PyFunction_GetModule(PyObject *op)
Return the *__module__* attribute of the function object *op*. This is normally
a string containing the module name, but can be set to any other object by
Python code.
.. c:function:: PyObject* PyFunction_GetDefaults(PyObject *op)
Return the argument default values of the function object *op*. This can be a
tuple of arguments or *NULL*.
.. c:function:: int PyFunction_SetDefaults(PyObject *op, PyObject *defaults)
Set the argument default values for the function object *op*. *defaults* must be
*Py_None* or a tuple.
Raises :exc:`SystemError` and returns ``-1`` on failure.
.. c:function:: PyObject* PyFunction_GetClosure(PyObject *op)
Return the closure associated with the function object *op*. This can be *NULL*
or a tuple of cell objects.
.. c:function:: int PyFunction_SetClosure(PyObject *op, PyObject *closure)
Set the closure associated with the function object *op*. *closure* must be
*Py_None* or a tuple of cell objects.
Raises :exc:`SystemError` and returns ``-1`` on failure.
.. c:function:: PyObject *PyFunction_GetAnnotations(PyObject *op)
Return the annotations of the function object *op*. This can be a
mutable dictionary or *NULL*.
.. c:function:: int PyFunction_SetAnnotations(PyObject *op, PyObject *annotations)
Set the annotations for the function object *op*. *annotations*
must be a dictionary or *Py_None*.
Raises :exc:`SystemError` and returns ``-1`` on failure.

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.. highlightlang:: c
.. _supporting-cycle-detection:
Supporting Cyclic Garbage Collection
====================================
Python's support for detecting and collecting garbage which involves circular
references requires support from object types which are "containers" for other
objects which may also be containers. Types which do not store references to
other objects, or which only store references to atomic types (such as numbers
or strings), do not need to provide any explicit support for garbage
collection.
To create a container type, the :c:member:`~PyTypeObject.tp_flags` field of the type object must
include the :const:`Py_TPFLAGS_HAVE_GC` and provide an implementation of the
:c:member:`~PyTypeObject.tp_traverse` handler. If instances of the type are mutable, a
:c:member:`~PyTypeObject.tp_clear` implementation must also be provided.
.. data:: Py_TPFLAGS_HAVE_GC
:noindex:
Objects with a type with this flag set must conform with the rules
documented here. For convenience these objects will be referred to as
container objects.
Constructors for container types must conform to two rules:
#. The memory for the object must be allocated using :c:func:`PyObject_GC_New`
or :c:func:`PyObject_GC_NewVar`.
#. Once all the fields which may contain references to other containers are
initialized, it must call :c:func:`PyObject_GC_Track`.
.. c:function:: TYPE* PyObject_GC_New(TYPE, PyTypeObject *type)
Analogous to :c:func:`PyObject_New` but for container objects with the
:const:`Py_TPFLAGS_HAVE_GC` flag set.
.. c:function:: TYPE* PyObject_GC_NewVar(TYPE, PyTypeObject *type, Py_ssize_t size)
Analogous to :c:func:`PyObject_NewVar` but for container objects with the
:const:`Py_TPFLAGS_HAVE_GC` flag set.
.. c:function:: TYPE* PyObject_GC_Resize(TYPE, PyVarObject *op, Py_ssize_t newsize)
Resize an object allocated by :c:func:`PyObject_NewVar`. Returns the
resized object or *NULL* on failure. *op* must not be tracked by the collector yet.
.. c:function:: void PyObject_GC_Track(PyObject *op)
Adds the object *op* to the set of container objects tracked by the
collector. The collector can run at unexpected times so objects must be
valid while being tracked. This should be called once all the fields
followed by the :c:member:`~PyTypeObject.tp_traverse` handler become valid, usually near the
end of the constructor.
.. c:function:: void _PyObject_GC_TRACK(PyObject *op)
A macro version of :c:func:`PyObject_GC_Track`. It should not be used for
extension modules.
.. deprecated:: 3.6
This macro is removed from Python 3.8.
Similarly, the deallocator for the object must conform to a similar pair of
rules:
#. Before fields which refer to other containers are invalidated,
:c:func:`PyObject_GC_UnTrack` must be called.
#. The object's memory must be deallocated using :c:func:`PyObject_GC_Del`.
.. c:function:: void PyObject_GC_Del(void *op)
Releases memory allocated to an object using :c:func:`PyObject_GC_New` or
:c:func:`PyObject_GC_NewVar`.
.. c:function:: void PyObject_GC_UnTrack(void *op)
Remove the object *op* from the set of container objects tracked by the
collector. Note that :c:func:`PyObject_GC_Track` can be called again on
this object to add it back to the set of tracked objects. The deallocator
(:c:member:`~PyTypeObject.tp_dealloc` handler) should call this for the object before any of
the fields used by the :c:member:`~PyTypeObject.tp_traverse` handler become invalid.
.. c:function:: void _PyObject_GC_UNTRACK(PyObject *op)
A macro version of :c:func:`PyObject_GC_UnTrack`. It should not be used for
extension modules.
.. deprecated:: 3.6
This macro is removed from Python 3.8.
The :c:member:`~PyTypeObject.tp_traverse` handler accepts a function parameter of this type:
.. c:type:: int (*visitproc)(PyObject *object, void *arg)
Type of the visitor function passed to the :c:member:`~PyTypeObject.tp_traverse` handler.
The function should be called with an object to traverse as *object* and
the third parameter to the :c:member:`~PyTypeObject.tp_traverse` handler as *arg*. The
Python core uses several visitor functions to implement cyclic garbage
detection; it's not expected that users will need to write their own
visitor functions.
The :c:member:`~PyTypeObject.tp_traverse` handler must have the following type:
.. c:type:: int (*traverseproc)(PyObject *self, visitproc visit, void *arg)
Traversal function for a container object. Implementations must call the
*visit* function for each object directly contained by *self*, with the
parameters to *visit* being the contained object and the *arg* value passed
to the handler. The *visit* function must not be called with a *NULL*
object argument. If *visit* returns a non-zero value that value should be
returned immediately.
To simplify writing :c:member:`~PyTypeObject.tp_traverse` handlers, a :c:func:`Py_VISIT` macro is
provided. In order to use this macro, the :c:member:`~PyTypeObject.tp_traverse` implementation
must name its arguments exactly *visit* and *arg*:
.. c:function:: void Py_VISIT(PyObject *o)
If *o* is not *NULL*, call the *visit* callback, with arguments *o*
and *arg*. If *visit* returns a non-zero value, then return it.
Using this macro, :c:member:`~PyTypeObject.tp_traverse` handlers
look like::
static int
my_traverse(Noddy *self, visitproc visit, void *arg)
{
Py_VISIT(self->foo);
Py_VISIT(self->bar);
return 0;
}
The :c:member:`~PyTypeObject.tp_clear` handler must be of the :c:type:`inquiry` type, or *NULL*
if the object is immutable.
.. c:type:: int (*inquiry)(PyObject *self)
Drop references that may have created reference cycles. Immutable objects
do not have to define this method since they can never directly create
reference cycles. Note that the object must still be valid after calling
this method (don't just call :c:func:`Py_DECREF` on a reference). The
collector will call this method if it detects that this object is involved
in a reference cycle.

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.. highlightlang:: c
.. _gen-objects:
Generator Objects
-----------------
Generator objects are what Python uses to implement generator iterators. They
are normally created by iterating over a function that yields values, rather
than explicitly calling :c:func:`PyGen_New` or :c:func:`PyGen_NewWithQualName`.
.. c:type:: PyGenObject
The C structure used for generator objects.
.. c:var:: PyTypeObject PyGen_Type
The type object corresponding to generator objects.
.. c:function:: int PyGen_Check(PyObject *ob)
Return true if *ob* is a generator object; *ob* must not be *NULL*.
.. c:function:: int PyGen_CheckExact(PyObject *ob)
Return true if *ob*'s type is *PyGen_Type*; *ob* must not be *NULL*.
.. c:function:: PyObject* PyGen_New(PyFrameObject *frame)
Create and return a new generator object based on the *frame* object.
A reference to *frame* is stolen by this function. The argument must not be
*NULL*.
.. c:function:: PyObject* PyGen_NewWithQualName(PyFrameObject *frame, PyObject *name, PyObject *qualname)
Create and return a new generator object based on the *frame* object,
with ``__name__`` and ``__qualname__`` set to *name* and *qualname*.
A reference to *frame* is stolen by this function. The *frame* argument
must not be *NULL*.

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.. highlightlang:: c
.. _importing:
Importing Modules
=================
.. c:function:: PyObject* PyImport_ImportModule(const char *name)
.. index::
single: package variable; __all__
single: __all__ (package variable)
single: modules (in module sys)
This is a simplified interface to :c:func:`PyImport_ImportModuleEx` below,
leaving the *globals* and *locals* arguments set to *NULL* and *level* set
to 0. When the *name*
argument contains a dot (when it specifies a submodule of a package), the
*fromlist* argument is set to the list ``['*']`` so that the return value is the
named module rather than the top-level package containing it as would otherwise
be the case. (Unfortunately, this has an additional side effect when *name* in
fact specifies a subpackage instead of a submodule: the submodules specified in
the package's ``__all__`` variable are loaded.) Return a new reference to the
imported module, or *NULL* with an exception set on failure. A failing
import of a module doesn't leave the module in :data:`sys.modules`.
This function always uses absolute imports.
.. c:function:: PyObject* PyImport_ImportModuleNoBlock(const char *name)
This function is a deprecated alias of :c:func:`PyImport_ImportModule`.
.. versionchanged:: 3.3
This function used to fail immediately when the import lock was held
by another thread. In Python 3.3 though, the locking scheme switched
to per-module locks for most purposes, so this function's special
behaviour isn't needed anymore.
.. c:function:: PyObject* PyImport_ImportModuleEx(const char *name, PyObject *globals, PyObject *locals, PyObject *fromlist)
.. index:: builtin: __import__
Import a module. This is best described by referring to the built-in Python
function :func:`__import__`.
The return value is a new reference to the imported module or top-level
package, or *NULL* with an exception set on failure. Like for
:func:`__import__`, the return value when a submodule of a package was
requested is normally the top-level package, unless a non-empty *fromlist*
was given.
Failing imports remove incomplete module objects, like with
:c:func:`PyImport_ImportModule`.
.. c:function:: PyObject* PyImport_ImportModuleLevelObject(PyObject *name, PyObject *globals, PyObject *locals, PyObject *fromlist, int level)
Import a module. This is best described by referring to the built-in Python
function :func:`__import__`, as the standard :func:`__import__` function calls
this function directly.
The return value is a new reference to the imported module or top-level package,
or *NULL* with an exception set on failure. Like for :func:`__import__`,
the return value when a submodule of a package was requested is normally the
top-level package, unless a non-empty *fromlist* was given.
.. versionadded:: 3.3
.. c:function:: PyObject* PyImport_ImportModuleLevel(const char *name, PyObject *globals, PyObject *locals, PyObject *fromlist, int level)
Similar to :c:func:`PyImport_ImportModuleLevelObject`, but the name is a
UTF-8 encoded string instead of a Unicode object.
.. versionchanged:: 3.3
Negative values for *level* are no longer accepted.
.. c:function:: PyObject* PyImport_Import(PyObject *name)
This is a higher-level interface that calls the current "import hook
function" (with an explicit *level* of 0, meaning absolute import). It
invokes the :func:`__import__` function from the ``__builtins__`` of the
current globals. This means that the import is done using whatever import
hooks are installed in the current environment.
This function always uses absolute imports.
.. c:function:: PyObject* PyImport_ReloadModule(PyObject *m)
Reload a module. Return a new reference to the reloaded module, or *NULL* with
an exception set on failure (the module still exists in this case).
.. c:function:: PyObject* PyImport_AddModuleObject(PyObject *name)
Return the module object corresponding to a module name. The *name* argument
may be of the form ``package.module``. First check the modules dictionary if
there's one there, and if not, create a new one and insert it in the modules
dictionary. Return *NULL* with an exception set on failure.
.. note::
This function does not load or import the module; if the module wasn't already
loaded, you will get an empty module object. Use :c:func:`PyImport_ImportModule`
or one of its variants to import a module. Package structures implied by a
dotted name for *name* are not created if not already present.
.. versionadded:: 3.3
.. c:function:: PyObject* PyImport_AddModule(const char *name)
Similar to :c:func:`PyImport_AddModuleObject`, but the name is a UTF-8
encoded string instead of a Unicode object.
.. c:function:: PyObject* PyImport_ExecCodeModule(const char *name, PyObject *co)
.. index:: builtin: compile
Given a module name (possibly of the form ``package.module``) and a code object
read from a Python bytecode file or obtained from the built-in function
:func:`compile`, load the module. Return a new reference to the module object,
or *NULL* with an exception set if an error occurred. *name*
is removed from :attr:`sys.modules` in error cases, even if *name* was already
in :attr:`sys.modules` on entry to :c:func:`PyImport_ExecCodeModule`. Leaving
incompletely initialized modules in :attr:`sys.modules` is dangerous, as imports of
such modules have no way to know that the module object is an unknown (and
probably damaged with respect to the module author's intents) state.
The module's :attr:`__spec__` and :attr:`__loader__` will be set, if
not set already, with the appropriate values. The spec's loader will
be set to the module's ``__loader__`` (if set) and to an instance of
:class:`SourceFileLoader` otherwise.
The module's :attr:`__file__` attribute will be set to the code object's
:c:member:`co_filename`. If applicable, :attr:`__cached__` will also
be set.
This function will reload the module if it was already imported. See
:c:func:`PyImport_ReloadModule` for the intended way to reload a module.
If *name* points to a dotted name of the form ``package.module``, any package
structures not already created will still not be created.
See also :c:func:`PyImport_ExecCodeModuleEx` and
:c:func:`PyImport_ExecCodeModuleWithPathnames`.
.. c:function:: PyObject* PyImport_ExecCodeModuleEx(const char *name, PyObject *co, const char *pathname)
Like :c:func:`PyImport_ExecCodeModule`, but the :attr:`__file__` attribute of
the module object is set to *pathname* if it is non-``NULL``.
See also :c:func:`PyImport_ExecCodeModuleWithPathnames`.
.. c:function:: PyObject* PyImport_ExecCodeModuleObject(PyObject *name, PyObject *co, PyObject *pathname, PyObject *cpathname)
Like :c:func:`PyImport_ExecCodeModuleEx`, but the :attr:`__cached__`
attribute of the module object is set to *cpathname* if it is
non-``NULL``. Of the three functions, this is the preferred one to use.
.. versionadded:: 3.3
.. c:function:: PyObject* PyImport_ExecCodeModuleWithPathnames(const char *name, PyObject *co, const char *pathname, const char *cpathname)
Like :c:func:`PyImport_ExecCodeModuleObject`, but *name*, *pathname* and
*cpathname* are UTF-8 encoded strings. Attempts are also made to figure out
what the value for *pathname* should be from *cpathname* if the former is
set to ``NULL``.
.. versionadded:: 3.2
.. versionchanged:: 3.3
Uses :func:`imp.source_from_cache()` in calculating the source path if
only the bytecode path is provided.
.. c:function:: long PyImport_GetMagicNumber()
Return the magic number for Python bytecode files (a.k.a. :file:`.pyc` file).
The magic number should be present in the first four bytes of the bytecode
file, in little-endian byte order. Returns ``-1`` on error.
.. versionchanged:: 3.3
Return value of ``-1`` upon failure.
.. c:function:: const char * PyImport_GetMagicTag()
Return the magic tag string for :pep:`3147` format Python bytecode file
names. Keep in mind that the value at ``sys.implementation.cache_tag`` is
authoritative and should be used instead of this function.
.. versionadded:: 3.2
.. c:function:: PyObject* PyImport_GetModuleDict()
Return the dictionary used for the module administration (a.k.a.
``sys.modules``). Note that this is a per-interpreter variable.
.. c:function:: PyObject* PyImport_GetImporter(PyObject *path)
Return a finder object for a :data:`sys.path`/:attr:`pkg.__path__` item
*path*, possibly by fetching it from the :data:`sys.path_importer_cache`
dict. If it wasn't yet cached, traverse :data:`sys.path_hooks` until a hook
is found that can handle the path item. Return ``None`` if no hook could;
this tells our caller that the :term:`path based finder` could not find a
finder for this path item. Cache the result in :data:`sys.path_importer_cache`.
Return a new reference to the finder object.
.. c:function:: void _PyImport_Init()
Initialize the import mechanism. For internal use only.
.. c:function:: void PyImport_Cleanup()
Empty the module table. For internal use only.
.. c:function:: void _PyImport_Fini()
Finalize the import mechanism. For internal use only.
.. c:function:: PyObject* _PyImport_FindExtension(char *, char *)
For internal use only.
.. c:function:: int PyImport_ImportFrozenModuleObject(PyObject *name)
Load a frozen module named *name*. Return ``1`` for success, ``0`` if the
module is not found, and ``-1`` with an exception set if the initialization
failed. To access the imported module on a successful load, use
:c:func:`PyImport_ImportModule`. (Note the misnomer --- this function would
reload the module if it was already imported.)
.. versionadded:: 3.3
.. versionchanged:: 3.4
The ``__file__`` attribute is no longer set on the module.
.. c:function:: int PyImport_ImportFrozenModule(const char *name)
Similar to :c:func:`PyImport_ImportFrozenModuleObject`, but the name is a
UTF-8 encoded string instead of a Unicode object.
.. c:type:: struct _frozen
.. index:: single: freeze utility
This is the structure type definition for frozen module descriptors, as
generated by the :program:`freeze` utility (see :file:`Tools/freeze/` in the
Python source distribution). Its definition, found in :file:`Include/import.h`,
is::
struct _frozen {
char *name;
unsigned char *code;
int size;
};
.. c:var:: const struct _frozen* PyImport_FrozenModules
This pointer is initialized to point to an array of :c:type:`struct _frozen`
records, terminated by one whose members are all *NULL* or zero. When a frozen
module is imported, it is searched in this table. Third-party code could play
tricks with this to provide a dynamically created collection of frozen modules.
.. c:function:: int PyImport_AppendInittab(const char *name, PyObject* (*initfunc)(void))
Add a single module to the existing table of built-in modules. This is a
convenience wrapper around :c:func:`PyImport_ExtendInittab`, returning ``-1`` if
the table could not be extended. The new module can be imported by the name
*name*, and uses the function *initfunc* as the initialization function called
on the first attempted import. This should be called before
:c:func:`Py_Initialize`.
.. c:type:: struct _inittab
Structure describing a single entry in the list of built-in modules. Each of
these structures gives the name and initialization function for a module built
into the interpreter. The name is an ASCII encoded string. Programs which
embed Python may use an array of these structures in conjunction with
:c:func:`PyImport_ExtendInittab` to provide additional built-in modules.
The structure is defined in :file:`Include/import.h` as::
struct _inittab {
char *name; /* ASCII encoded string */
PyObject* (*initfunc)(void);
};
.. c:function:: int PyImport_ExtendInittab(struct _inittab *newtab)
Add a collection of modules to the table of built-in modules. The *newtab*
array must end with a sentinel entry which contains *NULL* for the :attr:`name`
field; failure to provide the sentinel value can result in a memory fault.
Returns ``0`` on success or ``-1`` if insufficient memory could be allocated to
extend the internal table. In the event of failure, no modules are added to the
internal table. This should be called before :c:func:`Py_Initialize`.

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.. _c-api-index:
##################################
Python/C API Reference Manual
##################################
This manual documents the API used by C and C++ programmers who want to write
extension modules or embed Python. It is a companion to :ref:`extending-index`,
which describes the general principles of extension writing but does not
document the API functions in detail.
.. toctree::
:maxdepth: 2
intro.rst
stable.rst
veryhigh.rst
refcounting.rst
exceptions.rst
utilities.rst
abstract.rst
concrete.rst
init.rst
memory.rst
objimpl.rst
apiabiversion.rst

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.. highlightlang:: c
.. _api-intro:
************
Introduction
************
The Application Programmer's Interface to Python gives C and C++ programmers
access to the Python interpreter at a variety of levels. The API is equally
usable from C++, but for brevity it is generally referred to as the Python/C
API. There are two fundamentally different reasons for using the Python/C API.
The first reason is to write *extension modules* for specific purposes; these
are C modules that extend the Python interpreter. This is probably the most
common use. The second reason is to use Python as a component in a larger
application; this technique is generally referred to as :dfn:`embedding` Python
in an application.
Writing an extension module is a relatively well-understood process, where a
"cookbook" approach works well. There are several tools that automate the
process to some extent. While people have embedded Python in other
applications since its early existence, the process of embedding Python is less
straightforward than writing an extension.
Many API functions are useful independent of whether you're embedding or
extending Python; moreover, most applications that embed Python will need to
provide a custom extension as well, so it's probably a good idea to become
familiar with writing an extension before attempting to embed Python in a real
application.
.. _api-includes:
Include Files
=============
All function, type and macro definitions needed to use the Python/C API are
included in your code by the following line::
#include "Python.h"
This implies inclusion of the following standard headers: ``<stdio.h>``,
``<string.h>``, ``<errno.h>``, ``<limits.h>``, ``<assert.h>`` and ``<stdlib.h>``
(if available).
.. note::
Since Python may define some pre-processor definitions which affect the standard
headers on some systems, you *must* include :file:`Python.h` before any standard
headers are included.
All user visible names defined by Python.h (except those defined by the included
standard headers) have one of the prefixes ``Py`` or ``_Py``. Names beginning
with ``_Py`` are for internal use by the Python implementation and should not be
used by extension writers. Structure member names do not have a reserved prefix.
**Important:** user code should never define names that begin with ``Py`` or
``_Py``. This confuses the reader, and jeopardizes the portability of the user
code to future Python versions, which may define additional names beginning with
one of these prefixes.
The header files are typically installed with Python. On Unix, these are
located in the directories :file:`{prefix}/include/pythonversion/` and
:file:`{exec_prefix}/include/pythonversion/`, where :envvar:`prefix` and
:envvar:`exec_prefix` are defined by the corresponding parameters to Python's
:program:`configure` script and *version* is
``'%d.%d' % sys.version_info[:2]``. On Windows, the headers are installed
in :file:`{prefix}/include`, where :envvar:`prefix` is the installation
directory specified to the installer.
To include the headers, place both directories (if different) on your compiler's
search path for includes. Do *not* place the parent directories on the search
path and then use ``#include <pythonX.Y/Python.h>``; this will break on
multi-platform builds since the platform independent headers under
:envvar:`prefix` include the platform specific headers from
:envvar:`exec_prefix`.
C++ users should note that though the API is defined entirely using C, the
header files do properly declare the entry points to be ``extern "C"``, so there
is no need to do anything special to use the API from C++.
.. _api-objects:
Objects, Types and Reference Counts
===================================
.. index:: object: type
Most Python/C API functions have one or more arguments as well as a return value
of type :c:type:`PyObject\*`. This type is a pointer to an opaque data type
representing an arbitrary Python object. Since all Python object types are
treated the same way by the Python language in most situations (e.g.,
assignments, scope rules, and argument passing), it is only fitting that they
should be represented by a single C type. Almost all Python objects live on the
heap: you never declare an automatic or static variable of type
:c:type:`PyObject`, only pointer variables of type :c:type:`PyObject\*` can be
declared. The sole exception are the type objects; since these must never be
deallocated, they are typically static :c:type:`PyTypeObject` objects.
All Python objects (even Python integers) have a :dfn:`type` and a
:dfn:`reference count`. An object's type determines what kind of object it is
(e.g., an integer, a list, or a user-defined function; there are many more as
explained in :ref:`types`). For each of the well-known types there is a macro
to check whether an object is of that type; for instance, ``PyList_Check(a)`` is
true if (and only if) the object pointed to by *a* is a Python list.
.. _api-refcounts:
Reference Counts
----------------
The reference count is important because today's computers have a finite (and
often severely limited) memory size; it counts how many different places there
are that have a reference to an object. Such a place could be another object,
or a global (or static) C variable, or a local variable in some C function.
When an object's reference count becomes zero, the object is deallocated. If
it contains references to other objects, their reference count is decremented.
Those other objects may be deallocated in turn, if this decrement makes their
reference count become zero, and so on. (There's an obvious problem with
objects that reference each other here; for now, the solution is "don't do
that.")
.. index::
single: Py_INCREF()
single: Py_DECREF()
Reference counts are always manipulated explicitly. The normal way is to use
the macro :c:func:`Py_INCREF` to increment an object's reference count by one,
and :c:func:`Py_DECREF` to decrement it by one. The :c:func:`Py_DECREF` macro
is considerably more complex than the incref one, since it must check whether
the reference count becomes zero and then cause the object's deallocator to be
called. The deallocator is a function pointer contained in the object's type
structure. The type-specific deallocator takes care of decrementing the
reference counts for other objects contained in the object if this is a compound
object type, such as a list, as well as performing any additional finalization
that's needed. There's no chance that the reference count can overflow; at
least as many bits are used to hold the reference count as there are distinct
memory locations in virtual memory (assuming ``sizeof(Py_ssize_t) >= sizeof(void*)``).
Thus, the reference count increment is a simple operation.
It is not necessary to increment an object's reference count for every local
variable that contains a pointer to an object. In theory, the object's
reference count goes up by one when the variable is made to point to it and it
goes down by one when the variable goes out of scope. However, these two
cancel each other out, so at the end the reference count hasn't changed. The
only real reason to use the reference count is to prevent the object from being
deallocated as long as our variable is pointing to it. If we know that there
is at least one other reference to the object that lives at least as long as
our variable, there is no need to increment the reference count temporarily.
An important situation where this arises is in objects that are passed as
arguments to C functions in an extension module that are called from Python;
the call mechanism guarantees to hold a reference to every argument for the
duration of the call.
However, a common pitfall is to extract an object from a list and hold on to it
for a while without incrementing its reference count. Some other operation might
conceivably remove the object from the list, decrementing its reference count
and possible deallocating it. The real danger is that innocent-looking
operations may invoke arbitrary Python code which could do this; there is a code
path which allows control to flow back to the user from a :c:func:`Py_DECREF`, so
almost any operation is potentially dangerous.
A safe approach is to always use the generic operations (functions whose name
begins with ``PyObject_``, ``PyNumber_``, ``PySequence_`` or ``PyMapping_``).
These operations always increment the reference count of the object they return.
This leaves the caller with the responsibility to call :c:func:`Py_DECREF` when
they are done with the result; this soon becomes second nature.
.. _api-refcountdetails:
Reference Count Details
^^^^^^^^^^^^^^^^^^^^^^^
The reference count behavior of functions in the Python/C API is best explained
in terms of *ownership of references*. Ownership pertains to references, never
to objects (objects are not owned: they are always shared). "Owning a
reference" means being responsible for calling Py_DECREF on it when the
reference is no longer needed. Ownership can also be transferred, meaning that
the code that receives ownership of the reference then becomes responsible for
eventually decref'ing it by calling :c:func:`Py_DECREF` or :c:func:`Py_XDECREF`
when it's no longer needed---or passing on this responsibility (usually to its
caller). When a function passes ownership of a reference on to its caller, the
caller is said to receive a *new* reference. When no ownership is transferred,
the caller is said to *borrow* the reference. Nothing needs to be done for a
borrowed reference.
Conversely, when a calling function passes in a reference to an object, there
are two possibilities: the function *steals* a reference to the object, or it
does not. *Stealing a reference* means that when you pass a reference to a
function, that function assumes that it now owns that reference, and you are not
responsible for it any longer.
.. index::
single: PyList_SetItem()
single: PyTuple_SetItem()
Few functions steal references; the two notable exceptions are
:c:func:`PyList_SetItem` and :c:func:`PyTuple_SetItem`, which steal a reference
to the item (but not to the tuple or list into which the item is put!). These
functions were designed to steal a reference because of a common idiom for
populating a tuple or list with newly created objects; for example, the code to
create the tuple ``(1, 2, "three")`` could look like this (forgetting about
error handling for the moment; a better way to code this is shown below)::
PyObject *t;
t = PyTuple_New(3);
PyTuple_SetItem(t, 0, PyLong_FromLong(1L));
PyTuple_SetItem(t, 1, PyLong_FromLong(2L));
PyTuple_SetItem(t, 2, PyUnicode_FromString("three"));
Here, :c:func:`PyLong_FromLong` returns a new reference which is immediately
stolen by :c:func:`PyTuple_SetItem`. When you want to keep using an object
although the reference to it will be stolen, use :c:func:`Py_INCREF` to grab
another reference before calling the reference-stealing function.
Incidentally, :c:func:`PyTuple_SetItem` is the *only* way to set tuple items;
:c:func:`PySequence_SetItem` and :c:func:`PyObject_SetItem` refuse to do this
since tuples are an immutable data type. You should only use
:c:func:`PyTuple_SetItem` for tuples that you are creating yourself.
Equivalent code for populating a list can be written using :c:func:`PyList_New`
and :c:func:`PyList_SetItem`.
However, in practice, you will rarely use these ways of creating and populating
a tuple or list. There's a generic function, :c:func:`Py_BuildValue`, that can
create most common objects from C values, directed by a :dfn:`format string`.
For example, the above two blocks of code could be replaced by the following
(which also takes care of the error checking)::
PyObject *tuple, *list;
tuple = Py_BuildValue("(iis)", 1, 2, "three");
list = Py_BuildValue("[iis]", 1, 2, "three");
It is much more common to use :c:func:`PyObject_SetItem` and friends with items
whose references you are only borrowing, like arguments that were passed in to
the function you are writing. In that case, their behaviour regarding reference
counts is much saner, since you don't have to increment a reference count so you
can give a reference away ("have it be stolen"). For example, this function
sets all items of a list (actually, any mutable sequence) to a given item::
int
set_all(PyObject *target, PyObject *item)
{
Py_ssize_t i, n;
n = PyObject_Length(target);
if (n < 0)
return -1;
for (i = 0; i < n; i++) {
PyObject *index = PyLong_FromSsize_t(i);
if (!index)
return -1;
if (PyObject_SetItem(target, index, item) < 0) {
Py_DECREF(index);
return -1;
}
Py_DECREF(index);
}
return 0;
}
.. index:: single: set_all()
The situation is slightly different for function return values. While passing
a reference to most functions does not change your ownership responsibilities
for that reference, many functions that return a reference to an object give
you ownership of the reference. The reason is simple: in many cases, the
returned object is created on the fly, and the reference you get is the only
reference to the object. Therefore, the generic functions that return object
references, like :c:func:`PyObject_GetItem` and :c:func:`PySequence_GetItem`,
always return a new reference (the caller becomes the owner of the reference).
It is important to realize that whether you own a reference returned by a
function depends on which function you call only --- *the plumage* (the type of
the object passed as an argument to the function) *doesn't enter into it!*
Thus, if you extract an item from a list using :c:func:`PyList_GetItem`, you
don't own the reference --- but if you obtain the same item from the same list
using :c:func:`PySequence_GetItem` (which happens to take exactly the same
arguments), you do own a reference to the returned object.
.. index::
single: PyList_GetItem()
single: PySequence_GetItem()
Here is an example of how you could write a function that computes the sum of
the items in a list of integers; once using :c:func:`PyList_GetItem`, and once
using :c:func:`PySequence_GetItem`. ::
long
sum_list(PyObject *list)
{
Py_ssize_t i, n;
long total = 0, value;
PyObject *item;
n = PyList_Size(list);
if (n < 0)
return -1; /* Not a list */
for (i = 0; i < n; i++) {
item = PyList_GetItem(list, i); /* Can't fail */
if (!PyLong_Check(item)) continue; /* Skip non-integers */
value = PyLong_AsLong(item);
if (value == -1 && PyErr_Occurred())
/* Integer too big to fit in a C long, bail out */
return -1;
total += value;
}
return total;
}
.. index:: single: sum_list()
::
long
sum_sequence(PyObject *sequence)
{
Py_ssize_t i, n;
long total = 0, value;
PyObject *item;
n = PySequence_Length(sequence);
if (n < 0)
return -1; /* Has no length */
for (i = 0; i < n; i++) {
item = PySequence_GetItem(sequence, i);
if (item == NULL)
return -1; /* Not a sequence, or other failure */
if (PyLong_Check(item)) {
value = PyLong_AsLong(item);
Py_DECREF(item);
if (value == -1 && PyErr_Occurred())
/* Integer too big to fit in a C long, bail out */
return -1;
total += value;
}
else {
Py_DECREF(item); /* Discard reference ownership */
}
}
return total;
}
.. index:: single: sum_sequence()
.. _api-types:
Types
-----
There are few other data types that play a significant role in the Python/C
API; most are simple C types such as :c:type:`int`, :c:type:`long`,
:c:type:`double` and :c:type:`char\*`. A few structure types are used to
describe static tables used to list the functions exported by a module or the
data attributes of a new object type, and another is used to describe the value
of a complex number. These will be discussed together with the functions that
use them.
.. _api-exceptions:
Exceptions
==========
The Python programmer only needs to deal with exceptions if specific error
handling is required; unhandled exceptions are automatically propagated to the
caller, then to the caller's caller, and so on, until they reach the top-level
interpreter, where they are reported to the user accompanied by a stack
traceback.
.. index:: single: PyErr_Occurred()
For C programmers, however, error checking always has to be explicit. All
functions in the Python/C API can raise exceptions, unless an explicit claim is
made otherwise in a function's documentation. In general, when a function
encounters an error, it sets an exception, discards any object references that
it owns, and returns an error indicator. If not documented otherwise, this
indicator is either *NULL* or ``-1``, depending on the function's return type.
A few functions return a Boolean true/false result, with false indicating an
error. Very few functions return no explicit error indicator or have an
ambiguous return value, and require explicit testing for errors with
:c:func:`PyErr_Occurred`. These exceptions are always explicitly documented.
.. index::
single: PyErr_SetString()
single: PyErr_Clear()
Exception state is maintained in per-thread storage (this is equivalent to
using global storage in an unthreaded application). A thread can be in one of
two states: an exception has occurred, or not. The function
:c:func:`PyErr_Occurred` can be used to check for this: it returns a borrowed
reference to the exception type object when an exception has occurred, and
*NULL* otherwise. There are a number of functions to set the exception state:
:c:func:`PyErr_SetString` is the most common (though not the most general)
function to set the exception state, and :c:func:`PyErr_Clear` clears the
exception state.
The full exception state consists of three objects (all of which can be
*NULL*): the exception type, the corresponding exception value, and the
traceback. These have the same meanings as the Python result of
``sys.exc_info()``; however, they are not the same: the Python objects represent
the last exception being handled by a Python :keyword:`try` ...
:keyword:`except` statement, while the C level exception state only exists while
an exception is being passed on between C functions until it reaches the Python
bytecode interpreter's main loop, which takes care of transferring it to
``sys.exc_info()`` and friends.
.. index:: single: exc_info() (in module sys)
Note that starting with Python 1.5, the preferred, thread-safe way to access the
exception state from Python code is to call the function :func:`sys.exc_info`,
which returns the per-thread exception state for Python code. Also, the
semantics of both ways to access the exception state have changed so that a
function which catches an exception will save and restore its thread's exception
state so as to preserve the exception state of its caller. This prevents common
bugs in exception handling code caused by an innocent-looking function
overwriting the exception being handled; it also reduces the often unwanted
lifetime extension for objects that are referenced by the stack frames in the
traceback.
As a general principle, a function that calls another function to perform some
task should check whether the called function raised an exception, and if so,
pass the exception state on to its caller. It should discard any object
references that it owns, and return an error indicator, but it should *not* set
another exception --- that would overwrite the exception that was just raised,
and lose important information about the exact cause of the error.
.. index:: single: sum_sequence()
A simple example of detecting exceptions and passing them on is shown in the
:c:func:`sum_sequence` example above. It so happens that this example doesn't
need to clean up any owned references when it detects an error. The following
example function shows some error cleanup. First, to remind you why you like
Python, we show the equivalent Python code::
def incr_item(dict, key):
try:
item = dict[key]
except KeyError:
item = 0
dict[key] = item + 1
.. index:: single: incr_item()
Here is the corresponding C code, in all its glory::
int
incr_item(PyObject *dict, PyObject *key)
{
/* Objects all initialized to NULL for Py_XDECREF */
PyObject *item = NULL, *const_one = NULL, *incremented_item = NULL;
int rv = -1; /* Return value initialized to -1 (failure) */
item = PyObject_GetItem(dict, key);
if (item == NULL) {
/* Handle KeyError only: */
if (!PyErr_ExceptionMatches(PyExc_KeyError))
goto error;
/* Clear the error and use zero: */
PyErr_Clear();
item = PyLong_FromLong(0L);
if (item == NULL)
goto error;
}
const_one = PyLong_FromLong(1L);
if (const_one == NULL)
goto error;
incremented_item = PyNumber_Add(item, const_one);
if (incremented_item == NULL)
goto error;
if (PyObject_SetItem(dict, key, incremented_item) < 0)
goto error;
rv = 0; /* Success */
/* Continue with cleanup code */
error:
/* Cleanup code, shared by success and failure path */
/* Use Py_XDECREF() to ignore NULL references */
Py_XDECREF(item);
Py_XDECREF(const_one);
Py_XDECREF(incremented_item);
return rv; /* -1 for error, 0 for success */
}
.. index:: single: incr_item()
.. index::
single: PyErr_ExceptionMatches()
single: PyErr_Clear()
single: Py_XDECREF()
This example represents an endorsed use of the ``goto`` statement in C!
It illustrates the use of :c:func:`PyErr_ExceptionMatches` and
:c:func:`PyErr_Clear` to handle specific exceptions, and the use of
:c:func:`Py_XDECREF` to dispose of owned references that may be *NULL* (note the
``'X'`` in the name; :c:func:`Py_DECREF` would crash when confronted with a
*NULL* reference). It is important that the variables used to hold owned
references are initialized to *NULL* for this to work; likewise, the proposed
return value is initialized to ``-1`` (failure) and only set to success after
the final call made is successful.
.. _api-embedding:
Embedding Python
================
The one important task that only embedders (as opposed to extension writers) of
the Python interpreter have to worry about is the initialization, and possibly
the finalization, of the Python interpreter. Most functionality of the
interpreter can only be used after the interpreter has been initialized.
.. index::
single: Py_Initialize()
module: builtins
module: __main__
module: sys
triple: module; search; path
single: path (in module sys)
The basic initialization function is :c:func:`Py_Initialize`. This initializes
the table of loaded modules, and creates the fundamental modules
:mod:`builtins`, :mod:`__main__`, and :mod:`sys`. It also
initializes the module search path (``sys.path``).
.. index:: single: PySys_SetArgvEx()
:c:func:`Py_Initialize` does not set the "script argument list" (``sys.argv``).
If this variable is needed by Python code that will be executed later, it must
be set explicitly with a call to ``PySys_SetArgvEx(argc, argv, updatepath)``
after the call to :c:func:`Py_Initialize`.
On most systems (in particular, on Unix and Windows, although the details are
slightly different), :c:func:`Py_Initialize` calculates the module search path
based upon its best guess for the location of the standard Python interpreter
executable, assuming that the Python library is found in a fixed location
relative to the Python interpreter executable. In particular, it looks for a
directory named :file:`lib/python{X.Y}` relative to the parent directory
where the executable named :file:`python` is found on the shell command search
path (the environment variable :envvar:`PATH`).
For instance, if the Python executable is found in
:file:`/usr/local/bin/python`, it will assume that the libraries are in
:file:`/usr/local/lib/python{X.Y}`. (In fact, this particular path is also
the "fallback" location, used when no executable file named :file:`python` is
found along :envvar:`PATH`.) The user can override this behavior by setting the
environment variable :envvar:`PYTHONHOME`, or insert additional directories in
front of the standard path by setting :envvar:`PYTHONPATH`.
.. index::
single: Py_SetProgramName()
single: Py_GetPath()
single: Py_GetPrefix()
single: Py_GetExecPrefix()
single: Py_GetProgramFullPath()
The embedding application can steer the search by calling
``Py_SetProgramName(file)`` *before* calling :c:func:`Py_Initialize`. Note that
:envvar:`PYTHONHOME` still overrides this and :envvar:`PYTHONPATH` is still
inserted in front of the standard path. An application that requires total
control has to provide its own implementation of :c:func:`Py_GetPath`,
:c:func:`Py_GetPrefix`, :c:func:`Py_GetExecPrefix`, and
:c:func:`Py_GetProgramFullPath` (all defined in :file:`Modules/getpath.c`).
.. index:: single: Py_IsInitialized()
Sometimes, it is desirable to "uninitialize" Python. For instance, the
application may want to start over (make another call to
:c:func:`Py_Initialize`) or the application is simply done with its use of
Python and wants to free memory allocated by Python. This can be accomplished
by calling :c:func:`Py_FinalizeEx`. The function :c:func:`Py_IsInitialized` returns
true if Python is currently in the initialized state. More information about
these functions is given in a later chapter. Notice that :c:func:`Py_FinalizeEx`
does *not* free all memory allocated by the Python interpreter, e.g. memory
allocated by extension modules currently cannot be released.
.. _api-debugging:
Debugging Builds
================
Python can be built with several macros to enable extra checks of the
interpreter and extension modules. These checks tend to add a large amount of
overhead to the runtime so they are not enabled by default.
A full list of the various types of debugging builds is in the file
:file:`Misc/SpecialBuilds.txt` in the Python source distribution. Builds are
available that support tracing of reference counts, debugging the memory
allocator, or low-level profiling of the main interpreter loop. Only the most
frequently-used builds will be described in the remainder of this section.
Compiling the interpreter with the :c:macro:`Py_DEBUG` macro defined produces
what is generally meant by "a debug build" of Python. :c:macro:`Py_DEBUG` is
enabled in the Unix build by adding ``--with-pydebug`` to the
:file:`./configure` command. It is also implied by the presence of the
not-Python-specific :c:macro:`_DEBUG` macro. When :c:macro:`Py_DEBUG` is enabled
in the Unix build, compiler optimization is disabled.
In addition to the reference count debugging described below, the following
extra checks are performed:
* Extra checks are added to the object allocator.
* Extra checks are added to the parser and compiler.
* Downcasts from wide types to narrow types are checked for loss of information.
* A number of assertions are added to the dictionary and set implementations.
In addition, the set object acquires a :meth:`test_c_api` method.
* Sanity checks of the input arguments are added to frame creation.
* The storage for ints is initialized with a known invalid pattern to catch
reference to uninitialized digits.
* Low-level tracing and extra exception checking are added to the runtime
virtual machine.
* Extra checks are added to the memory arena implementation.
* Extra debugging is added to the thread module.
There may be additional checks not mentioned here.
Defining :c:macro:`Py_TRACE_REFS` enables reference tracing. When defined, a
circular doubly linked list of active objects is maintained by adding two extra
fields to every :c:type:`PyObject`. Total allocations are tracked as well. Upon
exit, all existing references are printed. (In interactive mode this happens
after every statement run by the interpreter.) Implied by :c:macro:`Py_DEBUG`.
Please refer to :file:`Misc/SpecialBuilds.txt` in the Python source distribution
for more detailed information.

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.. highlightlang:: c
.. _iterator:
Iterator Protocol
=================
There are two functions specifically for working with iterators.
.. c:function:: int PyIter_Check(PyObject *o)
Return true if the object *o* supports the iterator protocol.
.. c:function:: PyObject* PyIter_Next(PyObject *o)
Return the next value from the iteration *o*. The object must be an iterator
(it is up to the caller to check this). If there are no remaining values,
returns *NULL* with no exception set. If an error occurs while retrieving
the item, returns *NULL* and passes along the exception.
To write a loop which iterates over an iterator, the C code should look
something like this::
PyObject *iterator = PyObject_GetIter(obj);
PyObject *item;
if (iterator == NULL) {
/* propagate error */
}
while (item = PyIter_Next(iterator)) {
/* do something with item */
...
/* release reference when done */
Py_DECREF(item);
}
Py_DECREF(iterator);
if (PyErr_Occurred()) {
/* propagate error */
}
else {
/* continue doing useful work */
}

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.. highlightlang:: c
.. _iterator-objects:
Iterator Objects
----------------
Python provides two general-purpose iterator objects. The first, a sequence
iterator, works with an arbitrary sequence supporting the :meth:`__getitem__`
method. The second works with a callable object and a sentinel value, calling
the callable for each item in the sequence, and ending the iteration when the
sentinel value is returned.
.. c:var:: PyTypeObject PySeqIter_Type
Type object for iterator objects returned by :c:func:`PySeqIter_New` and the
one-argument form of the :func:`iter` built-in function for built-in sequence
types.
.. c:function:: int PySeqIter_Check(op)
Return true if the type of *op* is :c:data:`PySeqIter_Type`.
.. c:function:: PyObject* PySeqIter_New(PyObject *seq)
Return an iterator that works with a general sequence object, *seq*. The
iteration ends when the sequence raises :exc:`IndexError` for the subscripting
operation.
.. c:var:: PyTypeObject PyCallIter_Type
Type object for iterator objects returned by :c:func:`PyCallIter_New` and the
two-argument form of the :func:`iter` built-in function.
.. c:function:: int PyCallIter_Check(op)
Return true if the type of *op* is :c:data:`PyCallIter_Type`.
.. c:function:: PyObject* PyCallIter_New(PyObject *callable, PyObject *sentinel)
Return a new iterator. The first parameter, *callable*, can be any Python
callable object that can be called with no parameters; each call to it should
return the next item in the iteration. When *callable* returns a value equal to
*sentinel*, the iteration will be terminated.

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.. highlightlang:: c
.. _listobjects:
List Objects
------------
.. index:: object: list
.. c:type:: PyListObject
This subtype of :c:type:`PyObject` represents a Python list object.
.. c:var:: PyTypeObject PyList_Type
This instance of :c:type:`PyTypeObject` represents the Python list type.
This is the same object as :class:`list` in the Python layer.
.. c:function:: int PyList_Check(PyObject *p)
Return true if *p* is a list object or an instance of a subtype of the list
type.
.. c:function:: int PyList_CheckExact(PyObject *p)
Return true if *p* is a list object, but not an instance of a subtype of
the list type.
.. c:function:: PyObject* PyList_New(Py_ssize_t len)
Return a new list of length *len* on success, or *NULL* on failure.
.. note::
If *len* is greater than zero, the returned list object's items are
set to ``NULL``. Thus you cannot use abstract API functions such as
:c:func:`PySequence_SetItem` or expose the object to Python code before
setting all items to a real object with :c:func:`PyList_SetItem`.
.. c:function:: Py_ssize_t PyList_Size(PyObject *list)
.. index:: builtin: len
Return the length of the list object in *list*; this is equivalent to
``len(list)`` on a list object.
.. c:function:: Py_ssize_t PyList_GET_SIZE(PyObject *list)
Macro form of :c:func:`PyList_Size` without error checking.
.. c:function:: PyObject* PyList_GetItem(PyObject *list, Py_ssize_t index)
Return the object at position *index* in the list pointed to by *list*. The
position must be positive, indexing from the end of the list is not
supported. If *index* is out of bounds, return *NULL* and set an
:exc:`IndexError` exception.
.. c:function:: PyObject* PyList_GET_ITEM(PyObject *list, Py_ssize_t i)
Macro form of :c:func:`PyList_GetItem` without error checking.
.. c:function:: int PyList_SetItem(PyObject *list, Py_ssize_t index, PyObject *item)
Set the item at index *index* in list to *item*. Return ``0`` on success
or ``-1`` on failure.
.. note::
This function "steals" a reference to *item* and discards a reference to
an item already in the list at the affected position.
.. c:function:: void PyList_SET_ITEM(PyObject *list, Py_ssize_t i, PyObject *o)
Macro form of :c:func:`PyList_SetItem` without error checking. This is
normally only used to fill in new lists where there is no previous content.
.. note::
This macro "steals" a reference to *item*, and, unlike
:c:func:`PyList_SetItem`, does *not* discard a reference to any item that
is being replaced; any reference in *list* at position *i* will be
leaked.
.. c:function:: int PyList_Insert(PyObject *list, Py_ssize_t index, PyObject *item)
Insert the item *item* into list *list* in front of index *index*. Return
``0`` if successful; return ``-1`` and set an exception if unsuccessful.
Analogous to ``list.insert(index, item)``.
.. c:function:: int PyList_Append(PyObject *list, PyObject *item)
Append the object *item* at the end of list *list*. Return ``0`` if
successful; return ``-1`` and set an exception if unsuccessful. Analogous
to ``list.append(item)``.
.. c:function:: PyObject* PyList_GetSlice(PyObject *list, Py_ssize_t low, Py_ssize_t high)
Return a list of the objects in *list* containing the objects *between* *low*
and *high*. Return *NULL* and set an exception if unsuccessful. Analogous
to ``list[low:high]``. Negative indices, as when slicing from Python, are not
supported.
.. c:function:: int PyList_SetSlice(PyObject *list, Py_ssize_t low, Py_ssize_t high, PyObject *itemlist)
Set the slice of *list* between *low* and *high* to the contents of
*itemlist*. Analogous to ``list[low:high] = itemlist``. The *itemlist* may
be *NULL*, indicating the assignment of an empty list (slice deletion).
Return ``0`` on success, ``-1`` on failure. Negative indices, as when
slicing from Python, are not supported.
.. c:function:: int PyList_Sort(PyObject *list)
Sort the items of *list* in place. Return ``0`` on success, ``-1`` on
failure. This is equivalent to ``list.sort()``.
.. c:function:: int PyList_Reverse(PyObject *list)
Reverse the items of *list* in place. Return ``0`` on success, ``-1`` on
failure. This is the equivalent of ``list.reverse()``.
.. c:function:: PyObject* PyList_AsTuple(PyObject *list)
.. index:: builtin: tuple
Return a new tuple object containing the contents of *list*; equivalent to
``tuple(list)``.
.. c:function:: int PyList_ClearFreeList()
Clear the free list. Return the total number of freed items.
.. versionadded:: 3.3

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.. highlightlang:: c
.. _longobjects:
Integer Objects
---------------
.. index:: object: long integer
object: integer
All integers are implemented as "long" integer objects of arbitrary size.
On error, most ``PyLong_As*`` APIs return ``(return type)-1`` which cannot be
distinguished from a number. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:type:: PyLongObject
This subtype of :c:type:`PyObject` represents a Python integer object.
.. c:var:: PyTypeObject PyLong_Type
This instance of :c:type:`PyTypeObject` represents the Python integer type.
This is the same object as :class:`int` in the Python layer.
.. c:function:: int PyLong_Check(PyObject *p)
Return true if its argument is a :c:type:`PyLongObject` or a subtype of
:c:type:`PyLongObject`.
.. c:function:: int PyLong_CheckExact(PyObject *p)
Return true if its argument is a :c:type:`PyLongObject`, but not a subtype of
:c:type:`PyLongObject`.
.. c:function:: PyObject* PyLong_FromLong(long v)
Return a new :c:type:`PyLongObject` object from *v*, or *NULL* on failure.
The current implementation keeps an array of integer objects for all integers
between ``-5`` and ``256``, when you create an int in that range you actually
just get back a reference to the existing object. So it should be possible to
change the value of ``1``. I suspect the behaviour of Python in this case is
undefined. :-)
.. c:function:: PyObject* PyLong_FromUnsignedLong(unsigned long v)
Return a new :c:type:`PyLongObject` object from a C :c:type:`unsigned long`, or
*NULL* on failure.
.. c:function:: PyObject* PyLong_FromSsize_t(Py_ssize_t v)
Return a new :c:type:`PyLongObject` object from a C :c:type:`Py_ssize_t`, or
*NULL* on failure.
.. c:function:: PyObject* PyLong_FromSize_t(size_t v)
Return a new :c:type:`PyLongObject` object from a C :c:type:`size_t`, or
*NULL* on failure.
.. c:function:: PyObject* PyLong_FromLongLong(long long v)
Return a new :c:type:`PyLongObject` object from a C :c:type:`long long`, or *NULL*
on failure.
.. c:function:: PyObject* PyLong_FromUnsignedLongLong(unsigned long long v)
Return a new :c:type:`PyLongObject` object from a C :c:type:`unsigned long long`,
or *NULL* on failure.
.. c:function:: PyObject* PyLong_FromDouble(double v)
Return a new :c:type:`PyLongObject` object from the integer part of *v*, or
*NULL* on failure.
.. c:function:: PyObject* PyLong_FromString(const char *str, char **pend, int base)
Return a new :c:type:`PyLongObject` based on the string value in *str*, which
is interpreted according to the radix in *base*. If *pend* is non-*NULL*,
*\*pend* will point to the first character in *str* which follows the
representation of the number. If *base* is ``0``, *str* is interpreted using
the :ref:`integers` definition; in this case, leading zeros in a
non-zero decimal number raises a :exc:`ValueError`. If *base* is not ``0``,
it must be between ``2`` and ``36``, inclusive. Leading spaces and single
underscores after a base specifier and between digits are ignored. If there
are no digits, :exc:`ValueError` will be raised.
.. c:function:: PyObject* PyLong_FromUnicode(Py_UNICODE *u, Py_ssize_t length, int base)
Convert a sequence of Unicode digits to a Python integer value. The Unicode
string is first encoded to a byte string using :c:func:`PyUnicode_EncodeDecimal`
and then converted using :c:func:`PyLong_FromString`.
.. deprecated-removed:: 3.3 4.0
Part of the old-style :c:type:`Py_UNICODE` API; please migrate to using
:c:func:`PyLong_FromUnicodeObject`.
.. c:function:: PyObject* PyLong_FromUnicodeObject(PyObject *u, int base)
Convert a sequence of Unicode digits in the string *u* to a Python integer
value. The Unicode string is first encoded to a byte string using
:c:func:`PyUnicode_EncodeDecimal` and then converted using
:c:func:`PyLong_FromString`.
.. versionadded:: 3.3
.. c:function:: PyObject* PyLong_FromVoidPtr(void *p)
Create a Python integer from the pointer *p*. The pointer value can be
retrieved from the resulting value using :c:func:`PyLong_AsVoidPtr`.
.. XXX alias PyLong_AS_LONG (for now)
.. c:function:: long PyLong_AsLong(PyObject *obj)
.. index::
single: LONG_MAX
single: OverflowError (built-in exception)
Return a C :c:type:`long` representation of *obj*. If *obj* is not an
instance of :c:type:`PyLongObject`, first call its :meth:`__int__` method
(if present) to convert it to a :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *obj* is out of range for a
:c:type:`long`.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: long PyLong_AsLongAndOverflow(PyObject *obj, int *overflow)
Return a C :c:type:`long` representation of *obj*. If *obj* is not an
instance of :c:type:`PyLongObject`, first call its :meth:`__int__` method
(if present) to convert it to a :c:type:`PyLongObject`.
If the value of *obj* is greater than :const:`LONG_MAX` or less than
:const:`LONG_MIN`, set *\*overflow* to ``1`` or ``-1``, respectively, and
return ``-1``; otherwise, set *\*overflow* to ``0``. If any other exception
occurs set *\*overflow* to ``0`` and return ``-1`` as usual.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: long long PyLong_AsLongLong(PyObject *obj)
.. index::
single: OverflowError (built-in exception)
Return a C :c:type:`long long` representation of *obj*. If *obj* is not an
instance of :c:type:`PyLongObject`, first call its :meth:`__int__` method
(if present) to convert it to a :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *obj* is out of range for a
:c:type:`long`.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: long long PyLong_AsLongLongAndOverflow(PyObject *obj, int *overflow)
Return a C :c:type:`long long` representation of *obj*. If *obj* is not an
instance of :c:type:`PyLongObject`, first call its :meth:`__int__` method
(if present) to convert it to a :c:type:`PyLongObject`.
If the value of *obj* is greater than :const:`PY_LLONG_MAX` or less than
:const:`PY_LLONG_MIN`, set *\*overflow* to ``1`` or ``-1``, respectively,
and return ``-1``; otherwise, set *\*overflow* to ``0``. If any other
exception occurs set *\*overflow* to ``0`` and return ``-1`` as usual.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. versionadded:: 3.2
.. c:function:: Py_ssize_t PyLong_AsSsize_t(PyObject *pylong)
.. index::
single: PY_SSIZE_T_MAX
single: OverflowError (built-in exception)
Return a C :c:type:`Py_ssize_t` representation of *pylong*. *pylong* must
be an instance of :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *pylong* is out of range for a
:c:type:`Py_ssize_t`.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: unsigned long PyLong_AsUnsignedLong(PyObject *pylong)
.. index::
single: ULONG_MAX
single: OverflowError (built-in exception)
Return a C :c:type:`unsigned long` representation of *pylong*. *pylong*
must be an instance of :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *pylong* is out of range for a
:c:type:`unsigned long`.
Returns ``(unsigned long)-1`` on error.
Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: size_t PyLong_AsSize_t(PyObject *pylong)
.. index::
single: SIZE_MAX
single: OverflowError (built-in exception)
Return a C :c:type:`size_t` representation of *pylong*. *pylong* must be
an instance of :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *pylong* is out of range for a
:c:type:`size_t`.
Returns ``(size_t)-1`` on error.
Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: unsigned long long PyLong_AsUnsignedLongLong(PyObject *pylong)
.. index::
single: OverflowError (built-in exception)
Return a C :c:type:`unsigned long long` representation of *pylong*. *pylong*
must be an instance of :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *pylong* is out of range for an
:c:type:`unsigned long long`.
Returns ``(unsigned long long)-1`` on error.
Use :c:func:`PyErr_Occurred` to disambiguate.
.. versionchanged:: 3.1
A negative *pylong* now raises :exc:`OverflowError`, not :exc:`TypeError`.
.. c:function:: unsigned long PyLong_AsUnsignedLongMask(PyObject *obj)
Return a C :c:type:`unsigned long` representation of *obj*. If *obj*
is not an instance of :c:type:`PyLongObject`, first call its :meth:`__int__`
method (if present) to convert it to a :c:type:`PyLongObject`.
If the value of *obj* is out of range for an :c:type:`unsigned long`,
return the reduction of that value modulo ``ULONG_MAX + 1``.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: unsigned long long PyLong_AsUnsignedLongLongMask(PyObject *obj)
Return a C :c:type:`unsigned long long` representation of *obj*. If *obj*
is not an instance of :c:type:`PyLongObject`, first call its :meth:`__int__`
method (if present) to convert it to a :c:type:`PyLongObject`.
If the value of *obj* is out of range for an :c:type:`unsigned long long`,
return the reduction of that value modulo ``PY_ULLONG_MAX + 1``.
Returns ``-1`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: double PyLong_AsDouble(PyObject *pylong)
Return a C :c:type:`double` representation of *pylong*. *pylong* must be
an instance of :c:type:`PyLongObject`.
Raise :exc:`OverflowError` if the value of *pylong* is out of range for a
:c:type:`double`.
Returns ``-1.0`` on error. Use :c:func:`PyErr_Occurred` to disambiguate.
.. c:function:: void* PyLong_AsVoidPtr(PyObject *pylong)
Convert a Python integer *pylong* to a C :c:type:`void` pointer.
If *pylong* cannot be converted, an :exc:`OverflowError` will be raised. This
is only assured to produce a usable :c:type:`void` pointer for values created
with :c:func:`PyLong_FromVoidPtr`.
Returns *NULL* on error. Use :c:func:`PyErr_Occurred` to disambiguate.

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.. highlightlang:: c
.. _mapping:
Mapping Protocol
================
See also :c:func:`PyObject_GetItem`, :c:func:`PyObject_SetItem` and
:c:func:`PyObject_DelItem`.
.. c:function:: int PyMapping_Check(PyObject *o)
Return ``1`` if the object provides mapping protocol or supports slicing,
and ``0`` otherwise. Note that it returns ``1`` for Python classes with
a :meth:`__getitem__` method since in general case it is impossible to
determine what the type of keys it supports. This function always
succeeds.
.. c:function:: Py_ssize_t PyMapping_Size(PyObject *o)
Py_ssize_t PyMapping_Length(PyObject *o)
.. index:: builtin: len
Returns the number of keys in object *o* on success, and ``-1`` on failure.
This is equivalent to the Python expression ``len(o)``.
.. c:function:: PyObject* PyMapping_GetItemString(PyObject *o, const char *key)
Return element of *o* corresponding to the string *key* or *NULL* on failure.
This is the equivalent of the Python expression ``o[key]``.
See also :c:func:`PyObject_GetItem`.
.. c:function:: int PyMapping_SetItemString(PyObject *o, const char *key, PyObject *v)
Map the string *key* to the value *v* in object *o*. Returns ``-1`` on
failure. This is the equivalent of the Python statement ``o[key] = v``.
See also :c:func:`PyObject_SetItem`.
.. c:function:: int PyMapping_DelItem(PyObject *o, PyObject *key)
Remove the mapping for the object *key* from the object *o*. Return ``-1``
on failure. This is equivalent to the Python statement ``del o[key]``.
This is an alias of :c:func:`PyObject_DelItem`.
.. c:function:: int PyMapping_DelItemString(PyObject *o, const char *key)
Remove the mapping for the string *key* from the object *o*. Return ``-1``
on failure. This is equivalent to the Python statement ``del o[key]``.
.. c:function:: int PyMapping_HasKey(PyObject *o, PyObject *key)
Return ``1`` if the mapping object has the key *key* and ``0`` otherwise.
This is equivalent to the Python expression ``key in o``.
This function always succeeds.
Note that exceptions which occur while calling the :meth:`__getitem__`
method will get suppressed.
To get error reporting use :c:func:`PyObject_GetItem()` instead.
.. c:function:: int PyMapping_HasKeyString(PyObject *o, const char *key)
Return ``1`` if the mapping object has the key *key* and ``0`` otherwise.
This is equivalent to the Python expression ``key in o``.
This function always succeeds.
Note that exceptions which occur while calling the :meth:`__getitem__`
method and creating a temporary string object will get suppressed.
To get error reporting use :c:func:`PyMapping_GetItemString()` instead.
.. c:function:: PyObject* PyMapping_Keys(PyObject *o)
On success, return a list or tuple of the keys in object *o*. On failure,
return *NULL*.
.. c:function:: PyObject* PyMapping_Values(PyObject *o)
On success, return a list or tuple of the values in object *o*. On failure,
return *NULL*.
.. c:function:: PyObject* PyMapping_Items(PyObject *o)
On success, return a list or tuple of the items in object *o*, where each item
is a tuple containing a key-value pair. On failure, return *NULL*.

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.. highlightlang:: c
.. _marshalling-utils:
Data marshalling support
========================
These routines allow C code to work with serialized objects using the same
data format as the :mod:`marshal` module. There are functions to write data
into the serialization format, and additional functions that can be used to
read the data back. Files used to store marshalled data must be opened in
binary mode.
Numeric values are stored with the least significant byte first.
The module supports two versions of the data format: version 0 is the
historical version, version 1 shares interned strings in the file, and upon
unmarshalling. Version 2 uses a binary format for floating point numbers.
*Py_MARSHAL_VERSION* indicates the current file format (currently 2).
.. c:function:: void PyMarshal_WriteLongToFile(long value, FILE *file, int version)
Marshal a :c:type:`long` integer, *value*, to *file*. This will only write
the least-significant 32 bits of *value*; regardless of the size of the
native :c:type:`long` type. *version* indicates the file format.
.. c:function:: void PyMarshal_WriteObjectToFile(PyObject *value, FILE *file, int version)
Marshal a Python object, *value*, to *file*.
*version* indicates the file format.
.. c:function:: PyObject* PyMarshal_WriteObjectToString(PyObject *value, int version)
Return a bytes object containing the marshalled representation of *value*.
*version* indicates the file format.
The following functions allow marshalled values to be read back in.
.. c:function:: long PyMarshal_ReadLongFromFile(FILE *file)
Return a C :c:type:`long` from the data stream in a :c:type:`FILE\*` opened
for reading. Only a 32-bit value can be read in using this function,
regardless of the native size of :c:type:`long`.
On error, sets the appropriate exception (:exc:`EOFError`) and returns
``-1``.
.. c:function:: int PyMarshal_ReadShortFromFile(FILE *file)
Return a C :c:type:`short` from the data stream in a :c:type:`FILE\*` opened
for reading. Only a 16-bit value can be read in using this function,
regardless of the native size of :c:type:`short`.
On error, sets the appropriate exception (:exc:`EOFError`) and returns
``-1``.
.. c:function:: PyObject* PyMarshal_ReadObjectFromFile(FILE *file)
Return a Python object from the data stream in a :c:type:`FILE\*` opened for
reading.
On error, sets the appropriate exception (:exc:`EOFError`, :exc:`ValueError`
or :exc:`TypeError`) and returns *NULL*.
.. c:function:: PyObject* PyMarshal_ReadLastObjectFromFile(FILE *file)
Return a Python object from the data stream in a :c:type:`FILE\*` opened for
reading. Unlike :c:func:`PyMarshal_ReadObjectFromFile`, this function
assumes that no further objects will be read from the file, allowing it to
aggressively load file data into memory so that the de-serialization can
operate from data in memory rather than reading a byte at a time from the
file. Only use these variant if you are certain that you won't be reading
anything else from the file.
On error, sets the appropriate exception (:exc:`EOFError`, :exc:`ValueError`
or :exc:`TypeError`) and returns *NULL*.
.. c:function:: PyObject* PyMarshal_ReadObjectFromString(const char *data, Py_ssize_t len)
Return a Python object from the data stream in a byte buffer
containing *len* bytes pointed to by *data*.
On error, sets the appropriate exception (:exc:`EOFError`, :exc:`ValueError`
or :exc:`TypeError`) and returns *NULL*.

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.. highlightlang:: c
.. _memory:
*****************
Memory Management
*****************
.. sectionauthor:: Vladimir Marangozov <Vladimir.Marangozov@inrialpes.fr>
.. _memoryoverview:
Overview
========
Memory management in Python involves a private heap containing all Python
objects and data structures. The management of this private heap is ensured
internally by the *Python memory manager*. The Python memory manager has
different components which deal with various dynamic storage management aspects,
like sharing, segmentation, preallocation or caching.
At the lowest level, a raw memory allocator ensures that there is enough room in
the private heap for storing all Python-related data by interacting with the
memory manager of the operating system. On top of the raw memory allocator,
several object-specific allocators operate on the same heap and implement
distinct memory management policies adapted to the peculiarities of every object
type. For example, integer objects are managed differently within the heap than
strings, tuples or dictionaries because integers imply different storage
requirements and speed/space tradeoffs. The Python memory manager thus delegates
some of the work to the object-specific allocators, but ensures that the latter
operate within the bounds of the private heap.
It is important to understand that the management of the Python heap is
performed by the interpreter itself and that the user has no control over it,
even if they regularly manipulate object pointers to memory blocks inside that
heap. The allocation of heap space for Python objects and other internal
buffers is performed on demand by the Python memory manager through the Python/C
API functions listed in this document.
.. index::
single: malloc()
single: calloc()
single: realloc()
single: free()
To avoid memory corruption, extension writers should never try to operate on
Python objects with the functions exported by the C library: :c:func:`malloc`,
:c:func:`calloc`, :c:func:`realloc` and :c:func:`free`. This will result in mixed
calls between the C allocator and the Python memory manager with fatal
consequences, because they implement different algorithms and operate on
different heaps. However, one may safely allocate and release memory blocks
with the C library allocator for individual purposes, as shown in the following
example::
PyObject *res;
char *buf = (char *) malloc(BUFSIZ); /* for I/O */
if (buf == NULL)
return PyErr_NoMemory();
...Do some I/O operation involving buf...
res = PyBytes_FromString(buf);
free(buf); /* malloc'ed */
return res;
In this example, the memory request for the I/O buffer is handled by the C
library allocator. The Python memory manager is involved only in the allocation
of the string object returned as a result.
In most situations, however, it is recommended to allocate memory from the
Python heap specifically because the latter is under control of the Python
memory manager. For example, this is required when the interpreter is extended
with new object types written in C. Another reason for using the Python heap is
the desire to *inform* the Python memory manager about the memory needs of the
extension module. Even when the requested memory is used exclusively for
internal, highly-specific purposes, delegating all memory requests to the Python
memory manager causes the interpreter to have a more accurate image of its
memory footprint as a whole. Consequently, under certain circumstances, the
Python memory manager may or may not trigger appropriate actions, like garbage
collection, memory compaction or other preventive procedures. Note that by using
the C library allocator as shown in the previous example, the allocated memory
for the I/O buffer escapes completely the Python memory manager.
.. seealso::
The :envvar:`PYTHONMALLOC` environment variable can be used to configure
the memory allocators used by Python.
The :envvar:`PYTHONMALLOCSTATS` environment variable can be used to print
statistics of the :ref:`pymalloc memory allocator <pymalloc>` every time a
new pymalloc object arena is created, and on shutdown.
Raw Memory Interface
====================
The following function sets are wrappers to the system allocator. These
functions are thread-safe, the :term:`GIL <global interpreter lock>` does not
need to be held.
The default raw memory block allocator uses the following functions:
:c:func:`malloc`, :c:func:`calloc`, :c:func:`realloc` and :c:func:`free`; call
``malloc(1)`` (or ``calloc(1, 1)``) when requesting zero bytes.
.. versionadded:: 3.4
.. c:function:: void* PyMem_RawMalloc(size_t n)
Allocates *n* bytes and returns a pointer of type :c:type:`void\*` to the
allocated memory, or *NULL* if the request fails.
Requesting zero bytes returns a distinct non-*NULL* pointer if possible, as
if ``PyMem_RawMalloc(1)`` had been called instead. The memory will not have
been initialized in any way.
.. c:function:: void* PyMem_RawCalloc(size_t nelem, size_t elsize)
Allocates *nelem* elements each whose size in bytes is *elsize* and returns
a pointer of type :c:type:`void\*` to the allocated memory, or *NULL* if the
request fails. The memory is initialized to zeros.
Requesting zero elements or elements of size zero bytes returns a distinct
non-*NULL* pointer if possible, as if ``PyMem_RawCalloc(1, 1)`` had been
called instead.
.. versionadded:: 3.5
.. c:function:: void* PyMem_RawRealloc(void *p, size_t n)
Resizes the memory block pointed to by *p* to *n* bytes. The contents will
be unchanged to the minimum of the old and the new sizes.
If *p* is *NULL*, the call is equivalent to ``PyMem_RawMalloc(n)``; else if
*n* is equal to zero, the memory block is resized but is not freed, and the
returned pointer is non-*NULL*.
Unless *p* is *NULL*, it must have been returned by a previous call to
:c:func:`PyMem_RawMalloc`, :c:func:`PyMem_RawRealloc` or
:c:func:`PyMem_RawCalloc`.
If the request fails, :c:func:`PyMem_RawRealloc` returns *NULL* and *p*
remains a valid pointer to the previous memory area.
.. c:function:: void PyMem_RawFree(void *p)
Frees the memory block pointed to by *p*, which must have been returned by a
previous call to :c:func:`PyMem_RawMalloc`, :c:func:`PyMem_RawRealloc` or
:c:func:`PyMem_RawCalloc`. Otherwise, or if ``PyMem_RawFree(p)`` has been
called before, undefined behavior occurs.
If *p* is *NULL*, no operation is performed.
.. _memoryinterface:
Memory Interface
================
The following function sets, modeled after the ANSI C standard, but specifying
behavior when requesting zero bytes, are available for allocating and releasing
memory from the Python heap.
By default, these functions use :ref:`pymalloc memory allocator <pymalloc>`.
.. warning::
The :term:`GIL <global interpreter lock>` must be held when using these
functions.
.. versionchanged:: 3.6
The default allocator is now pymalloc instead of system :c:func:`malloc`.
.. c:function:: void* PyMem_Malloc(size_t n)
Allocates *n* bytes and returns a pointer of type :c:type:`void\*` to the
allocated memory, or *NULL* if the request fails.
Requesting zero bytes returns a distinct non-*NULL* pointer if possible, as
if ``PyMem_Malloc(1)`` had been called instead. The memory will not have
been initialized in any way.
.. c:function:: void* PyMem_Calloc(size_t nelem, size_t elsize)
Allocates *nelem* elements each whose size in bytes is *elsize* and returns
a pointer of type :c:type:`void\*` to the allocated memory, or *NULL* if the
request fails. The memory is initialized to zeros.
Requesting zero elements or elements of size zero bytes returns a distinct
non-*NULL* pointer if possible, as if ``PyMem_Calloc(1, 1)`` had been called
instead.
.. versionadded:: 3.5
.. c:function:: void* PyMem_Realloc(void *p, size_t n)
Resizes the memory block pointed to by *p* to *n* bytes. The contents will be
unchanged to the minimum of the old and the new sizes.
If *p* is *NULL*, the call is equivalent to ``PyMem_Malloc(n)``; else if *n*
is equal to zero, the memory block is resized but is not freed, and the
returned pointer is non-*NULL*.
Unless *p* is *NULL*, it must have been returned by a previous call to
:c:func:`PyMem_Malloc`, :c:func:`PyMem_Realloc` or :c:func:`PyMem_Calloc`.
If the request fails, :c:func:`PyMem_Realloc` returns *NULL* and *p* remains
a valid pointer to the previous memory area.
.. c:function:: void PyMem_Free(void *p)
Frees the memory block pointed to by *p*, which must have been returned by a
previous call to :c:func:`PyMem_Malloc`, :c:func:`PyMem_Realloc` or
:c:func:`PyMem_Calloc`. Otherwise, or if ``PyMem_Free(p)`` has been called
before, undefined behavior occurs.
If *p* is *NULL*, no operation is performed.
The following type-oriented macros are provided for convenience. Note that
*TYPE* refers to any C type.
.. c:function:: TYPE* PyMem_New(TYPE, size_t n)
Same as :c:func:`PyMem_Malloc`, but allocates ``(n * sizeof(TYPE))`` bytes of
memory. Returns a pointer cast to :c:type:`TYPE\*`. The memory will not have
been initialized in any way.
.. c:function:: TYPE* PyMem_Resize(void *p, TYPE, size_t n)
Same as :c:func:`PyMem_Realloc`, but the memory block is resized to ``(n *
sizeof(TYPE))`` bytes. Returns a pointer cast to :c:type:`TYPE\*`. On return,
*p* will be a pointer to the new memory area, or *NULL* in the event of
failure.
This is a C preprocessor macro; *p* is always reassigned. Save the original
value of *p* to avoid losing memory when handling errors.
.. c:function:: void PyMem_Del(void *p)
Same as :c:func:`PyMem_Free`.
In addition, the following macro sets are provided for calling the Python memory
allocator directly, without involving the C API functions listed above. However,
note that their use does not preserve binary compatibility across Python
versions and is therefore deprecated in extension modules.
* ``PyMem_MALLOC(size)``
* ``PyMem_NEW(type, size)``
* ``PyMem_REALLOC(ptr, size)``
* ``PyMem_RESIZE(ptr, type, size)``
* ``PyMem_FREE(ptr)``
* ``PyMem_DEL(ptr)``
Object allocators
=================
The following function sets, modeled after the ANSI C standard, but specifying
behavior when requesting zero bytes, are available for allocating and releasing
memory from the Python heap.
By default, these functions use :ref:`pymalloc memory allocator <pymalloc>`.
.. warning::
The :term:`GIL <global interpreter lock>` must be held when using these
functions.
.. c:function:: void* PyObject_Malloc(size_t n)
Allocates *n* bytes and returns a pointer of type :c:type:`void\*` to the
allocated memory, or *NULL* if the request fails.
Requesting zero bytes returns a distinct non-*NULL* pointer if possible, as
if ``PyObject_Malloc(1)`` had been called instead. The memory will not have
been initialized in any way.
.. c:function:: void* PyObject_Calloc(size_t nelem, size_t elsize)
Allocates *nelem* elements each whose size in bytes is *elsize* and returns
a pointer of type :c:type:`void\*` to the allocated memory, or *NULL* if the
request fails. The memory is initialized to zeros.
Requesting zero elements or elements of size zero bytes returns a distinct
non-*NULL* pointer if possible, as if ``PyObject_Calloc(1, 1)`` had been called
instead.
.. versionadded:: 3.5
.. c:function:: void* PyObject_Realloc(void *p, size_t n)
Resizes the memory block pointed to by *p* to *n* bytes. The contents will be
unchanged to the minimum of the old and the new sizes.
If *p* is *NULL*, the call is equivalent to ``PyObject_Malloc(n)``; else if *n*
is equal to zero, the memory block is resized but is not freed, and the
returned pointer is non-*NULL*.
Unless *p* is *NULL*, it must have been returned by a previous call to
:c:func:`PyObject_Malloc`, :c:func:`PyObject_Realloc` or :c:func:`PyObject_Calloc`.
If the request fails, :c:func:`PyObject_Realloc` returns *NULL* and *p* remains
a valid pointer to the previous memory area.
.. c:function:: void PyObject_Free(void *p)
Frees the memory block pointed to by *p*, which must have been returned by a
previous call to :c:func:`PyObject_Malloc`, :c:func:`PyObject_Realloc` or
:c:func:`PyObject_Calloc`. Otherwise, or if ``PyObject_Free(p)`` has been called
before, undefined behavior occurs.
If *p* is *NULL*, no operation is performed.
Customize Memory Allocators
===========================
.. versionadded:: 3.4
.. c:type:: PyMemAllocatorEx
Structure used to describe a memory block allocator. The structure has
four fields:
+----------------------------------------------------------+---------------------------------------+
| Field | Meaning |
+==========================================================+=======================================+
| ``void *ctx`` | user context passed as first argument |
+----------------------------------------------------------+---------------------------------------+
| ``void* malloc(void *ctx, size_t size)`` | allocate a memory block |
+----------------------------------------------------------+---------------------------------------+
| ``void* calloc(void *ctx, size_t nelem, size_t elsize)`` | allocate a memory block initialized |
| | with zeros |
+----------------------------------------------------------+---------------------------------------+
| ``void* realloc(void *ctx, void *ptr, size_t new_size)`` | allocate or resize a memory block |
+----------------------------------------------------------+---------------------------------------+
| ``void free(void *ctx, void *ptr)`` | free a memory block |
+----------------------------------------------------------+---------------------------------------+
.. versionchanged:: 3.5
The :c:type:`PyMemAllocator` structure was renamed to
:c:type:`PyMemAllocatorEx` and a new ``calloc`` field was added.
.. c:type:: PyMemAllocatorDomain
Enum used to identify an allocator domain. Domains:
.. c:var:: PYMEM_DOMAIN_RAW
Functions:
* :c:func:`PyMem_RawMalloc`
* :c:func:`PyMem_RawRealloc`
* :c:func:`PyMem_RawCalloc`
* :c:func:`PyMem_RawFree`
.. c:var:: PYMEM_DOMAIN_MEM
Functions:
* :c:func:`PyMem_Malloc`,
* :c:func:`PyMem_Realloc`
* :c:func:`PyMem_Calloc`
* :c:func:`PyMem_Free`
.. c:var:: PYMEM_DOMAIN_OBJ
Functions:
* :c:func:`PyObject_Malloc`
* :c:func:`PyObject_Realloc`
* :c:func:`PyObject_Calloc`
* :c:func:`PyObject_Free`
.. c:function:: void PyMem_GetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)
Get the memory block allocator of the specified domain.
.. c:function:: void PyMem_SetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)
Set the memory block allocator of the specified domain.
The new allocator must return a distinct non-NULL pointer when requesting
zero bytes.
For the :c:data:`PYMEM_DOMAIN_RAW` domain, the allocator must be
thread-safe: the :term:`GIL <global interpreter lock>` is not held when the
allocator is called.
If the new allocator is not a hook (does not call the previous allocator),
the :c:func:`PyMem_SetupDebugHooks` function must be called to reinstall the
debug hooks on top on the new allocator.
.. c:function:: void PyMem_SetupDebugHooks(void)
Setup hooks to detect bugs in the Python memory allocator functions.
Newly allocated memory is filled with the byte ``0xCB``, freed memory is
filled with the byte ``0xDB``.
Runtime checks:
- Detect API violations, ex: :c:func:`PyObject_Free` called on a buffer
allocated by :c:func:`PyMem_Malloc`
- Detect write before the start of the buffer (buffer underflow)
- Detect write after the end of the buffer (buffer overflow)
- Check that the :term:`GIL <global interpreter lock>` is held when
allocator functions of :c:data:`PYMEM_DOMAIN_OBJ` (ex:
:c:func:`PyObject_Malloc`) and :c:data:`PYMEM_DOMAIN_MEM` (ex:
:c:func:`PyMem_Malloc`) domains are called
On error, the debug hooks use the :mod:`tracemalloc` module to get the
traceback where a memory block was allocated. The traceback is only
displayed if :mod:`tracemalloc` is tracing Python memory allocations and the
memory block was traced.
These hooks are installed by default if Python is compiled in debug
mode. The :envvar:`PYTHONMALLOC` environment variable can be used to install
debug hooks on a Python compiled in release mode.
.. versionchanged:: 3.6
This function now also works on Python compiled in release mode.
On error, the debug hooks now use :mod:`tracemalloc` to get the traceback
where a memory block was allocated. The debug hooks now also check
if the GIL is held when functions of :c:data:`PYMEM_DOMAIN_OBJ` and
:c:data:`PYMEM_DOMAIN_MEM` domains are called.
.. _pymalloc:
The pymalloc allocator
======================
Python has a *pymalloc* allocator optimized for small objects (smaller or equal
to 512 bytes) with a short lifetime. It uses memory mappings called "arenas"
with a fixed size of 256 KB. It falls back to :c:func:`PyMem_RawMalloc` and
:c:func:`PyMem_RawRealloc` for allocations larger than 512 bytes.
*pymalloc* is the default allocator of the :c:data:`PYMEM_DOMAIN_MEM` (ex:
:c:func:`PyMem_Malloc`) and :c:data:`PYMEM_DOMAIN_OBJ` (ex:
:c:func:`PyObject_Malloc`) domains.
The arena allocator uses the following functions:
* :c:func:`VirtualAlloc` and :c:func:`VirtualFree` on Windows,
* :c:func:`mmap` and :c:func:`munmap` if available,
* :c:func:`malloc` and :c:func:`free` otherwise.
Customize pymalloc Arena Allocator
----------------------------------
.. versionadded:: 3.4
.. c:type:: PyObjectArenaAllocator
Structure used to describe an arena allocator. The structure has
three fields:
+--------------------------------------------------+---------------------------------------+
| Field | Meaning |
+==================================================+=======================================+
| ``void *ctx`` | user context passed as first argument |
+--------------------------------------------------+---------------------------------------+
| ``void* alloc(void *ctx, size_t size)`` | allocate an arena of size bytes |
+--------------------------------------------------+---------------------------------------+
| ``void free(void *ctx, size_t size, void *ptr)`` | free an arena |
+--------------------------------------------------+---------------------------------------+
.. c:function:: PyObject_GetArenaAllocator(PyObjectArenaAllocator *allocator)
Get the arena allocator.
.. c:function:: PyObject_SetArenaAllocator(PyObjectArenaAllocator *allocator)
Set the arena allocator.
.. _memoryexamples:
Examples
========
Here is the example from section :ref:`memoryoverview`, rewritten so that the
I/O buffer is allocated from the Python heap by using the first function set::
PyObject *res;
char *buf = (char *) PyMem_Malloc(BUFSIZ); /* for I/O */
if (buf == NULL)
return PyErr_NoMemory();
/* ...Do some I/O operation involving buf... */
res = PyBytes_FromString(buf);
PyMem_Free(buf); /* allocated with PyMem_Malloc */
return res;
The same code using the type-oriented function set::
PyObject *res;
char *buf = PyMem_New(char, BUFSIZ); /* for I/O */
if (buf == NULL)
return PyErr_NoMemory();
/* ...Do some I/O operation involving buf... */
res = PyBytes_FromString(buf);
PyMem_Del(buf); /* allocated with PyMem_New */
return res;
Note that in the two examples above, the buffer is always manipulated via
functions belonging to the same set. Indeed, it is required to use the same
memory API family for a given memory block, so that the risk of mixing different
allocators is reduced to a minimum. The following code sequence contains two
errors, one of which is labeled as *fatal* because it mixes two different
allocators operating on different heaps. ::
char *buf1 = PyMem_New(char, BUFSIZ);
char *buf2 = (char *) malloc(BUFSIZ);
char *buf3 = (char *) PyMem_Malloc(BUFSIZ);
...
PyMem_Del(buf3); /* Wrong -- should be PyMem_Free() */
free(buf2); /* Right -- allocated via malloc() */
free(buf1); /* Fatal -- should be PyMem_Del() */
In addition to the functions aimed at handling raw memory blocks from the Python
heap, objects in Python are allocated and released with :c:func:`PyObject_New`,
:c:func:`PyObject_NewVar` and :c:func:`PyObject_Del`.
These will be explained in the next chapter on defining and implementing new
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.. highlightlang:: c
.. _memoryview-objects:
.. index::
object: memoryview
MemoryView objects
------------------
A :class:`memoryview` object exposes the C level :ref:`buffer interface
<bufferobjects>` as a Python object which can then be passed around like
any other object.
.. c:function:: PyObject *PyMemoryView_FromObject(PyObject *obj)
Create a memoryview object from an object that provides the buffer interface.
If *obj* supports writable buffer exports, the memoryview object will be
read/write, otherwise it may be either read-only or read/write at the
discretion of the exporter.
.. c:function:: PyObject *PyMemoryView_FromMemory(char *mem, Py_ssize_t size, int flags)
Create a memoryview object using *mem* as the underlying buffer.
*flags* can be one of :c:macro:`PyBUF_READ` or :c:macro:`PyBUF_WRITE`.
.. versionadded:: 3.3
.. c:function:: PyObject *PyMemoryView_FromBuffer(Py_buffer *view)
Create a memoryview object wrapping the given buffer structure *view*.
For simple byte buffers, :c:func:`PyMemoryView_FromMemory` is the preferred
function.
.. c:function:: PyObject *PyMemoryView_GetContiguous(PyObject *obj, int buffertype, char order)
Create a memoryview object to a :term:`contiguous` chunk of memory (in either
'C' or 'F'ortran *order*) from an object that defines the buffer
interface. If memory is contiguous, the memoryview object points to the
original memory. Otherwise, a copy is made and the memoryview points to a
new bytes object.
.. c:function:: int PyMemoryView_Check(PyObject *obj)
Return true if the object *obj* is a memoryview object. It is not
currently allowed to create subclasses of :class:`memoryview`.
.. c:function:: Py_buffer *PyMemoryView_GET_BUFFER(PyObject *mview)
Return a pointer to the memoryview's private copy of the exporter's buffer.
*mview* **must** be a memoryview instance; this macro doesn't check its type,
you must do it yourself or you will risk crashes.
.. c:function:: Py_buffer *PyMemoryView_GET_BASE(PyObject *mview)
Return either a pointer to the exporting object that the memoryview is based
on or *NULL* if the memoryview has been created by one of the functions
:c:func:`PyMemoryView_FromMemory` or :c:func:`PyMemoryView_FromBuffer`.
*mview* **must** be a memoryview instance.

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.. highlightlang:: c
.. _instancemethod-objects:
Instance Method Objects
-----------------------
.. index:: object: instancemethod
An instance method is a wrapper for a :c:data:`PyCFunction` and the new way
to bind a :c:data:`PyCFunction` to a class object. It replaces the former call
``PyMethod_New(func, NULL, class)``.
.. c:var:: PyTypeObject PyInstanceMethod_Type
This instance of :c:type:`PyTypeObject` represents the Python instance
method type. It is not exposed to Python programs.
.. c:function:: int PyInstanceMethod_Check(PyObject *o)
Return true if *o* is an instance method object (has type
:c:data:`PyInstanceMethod_Type`). The parameter must not be *NULL*.
.. c:function:: PyObject* PyInstanceMethod_New(PyObject *func)
Return a new instance method object, with *func* being any callable object
*func* is the function that will be called when the instance method is
called.
.. c:function:: PyObject* PyInstanceMethod_Function(PyObject *im)
Return the function object associated with the instance method *im*.
.. c:function:: PyObject* PyInstanceMethod_GET_FUNCTION(PyObject *im)
Macro version of :c:func:`PyInstanceMethod_Function` which avoids error checking.
.. _method-objects:
Method Objects
--------------
.. index:: object: method
Methods are bound function objects. Methods are always bound to an instance of
a user-defined class. Unbound methods (methods bound to a class object) are
no longer available.
.. c:var:: PyTypeObject PyMethod_Type
.. index:: single: MethodType (in module types)
This instance of :c:type:`PyTypeObject` represents the Python method type. This
is exposed to Python programs as ``types.MethodType``.
.. c:function:: int PyMethod_Check(PyObject *o)
Return true if *o* is a method object (has type :c:data:`PyMethod_Type`). The
parameter must not be *NULL*.
.. c:function:: PyObject* PyMethod_New(PyObject *func, PyObject *self)
Return a new method object, with *func* being any callable object and *self*
the instance the method should be bound. *func* is the function that will
be called when the method is called. *self* must not be *NULL*.
.. c:function:: PyObject* PyMethod_Function(PyObject *meth)
Return the function object associated with the method *meth*.
.. c:function:: PyObject* PyMethod_GET_FUNCTION(PyObject *meth)
Macro version of :c:func:`PyMethod_Function` which avoids error checking.
.. c:function:: PyObject* PyMethod_Self(PyObject *meth)
Return the instance associated with the method *meth*.
.. c:function:: PyObject* PyMethod_GET_SELF(PyObject *meth)
Macro version of :c:func:`PyMethod_Self` which avoids error checking.
.. c:function:: int PyMethod_ClearFreeList()
Clear the free list. Return the total number of freed items.

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.. highlightlang:: c
.. _moduleobjects:
Module Objects
--------------
.. index:: object: module
.. c:var:: PyTypeObject PyModule_Type
.. index:: single: ModuleType (in module types)
This instance of :c:type:`PyTypeObject` represents the Python module type. This
is exposed to Python programs as ``types.ModuleType``.
.. c:function:: int PyModule_Check(PyObject *p)
Return true if *p* is a module object, or a subtype of a module object.
.. c:function:: int PyModule_CheckExact(PyObject *p)
Return true if *p* is a module object, but not a subtype of
:c:data:`PyModule_Type`.
.. c:function:: PyObject* PyModule_NewObject(PyObject *name)
.. index::
single: __name__ (module attribute)
single: __doc__ (module attribute)
single: __file__ (module attribute)
single: __package__ (module attribute)
single: __loader__ (module attribute)
Return a new module object with the :attr:`__name__` attribute set to *name*.
The module's :attr:`__name__`, :attr:`__doc__`, :attr:`__package__`, and
:attr:`__loader__` attributes are filled in (all but :attr:`__name__` are set
to ``None``); the caller is responsible for providing a :attr:`__file__`
attribute.
.. versionadded:: 3.3
.. versionchanged:: 3.4
:attr:`__package__` and :attr:`__loader__` are set to ``None``.
.. c:function:: PyObject* PyModule_New(const char *name)
Similar to :c:func:`PyModule_NewObject`, but the name is a UTF-8 encoded
string instead of a Unicode object.
.. c:function:: PyObject* PyModule_GetDict(PyObject *module)
.. index:: single: __dict__ (module attribute)
Return the dictionary object that implements *module*'s namespace; this object
is the same as the :attr:`~object.__dict__` attribute of the module object.
If *module* is not a module object (or a subtype of a module object),
:exc:`SystemError` is raised and *NULL* is returned.
It is recommended extensions use other :c:func:`PyModule_\*` and
:c:func:`PyObject_\*` functions rather than directly manipulate a module's
:attr:`~object.__dict__`.
.. c:function:: PyObject* PyModule_GetNameObject(PyObject *module)
.. index::
single: __name__ (module attribute)
single: SystemError (built-in exception)
Return *module*'s :attr:`__name__` value. If the module does not provide one,
or if it is not a string, :exc:`SystemError` is raised and *NULL* is returned.
.. versionadded:: 3.3
.. c:function:: char* PyModule_GetName(PyObject *module)
Similar to :c:func:`PyModule_GetNameObject` but return the name encoded to
``'utf-8'``.
.. c:function:: void* PyModule_GetState(PyObject *module)
Return the "state" of the module, that is, a pointer to the block of memory
allocated at module creation time, or *NULL*. See
:c:member:`PyModuleDef.m_size`.
.. c:function:: PyModuleDef* PyModule_GetDef(PyObject *module)
Return a pointer to the :c:type:`PyModuleDef` struct from which the module was
created, or *NULL* if the module wasn't created from a definition.
.. c:function:: PyObject* PyModule_GetFilenameObject(PyObject *module)
.. index::
single: __file__ (module attribute)
single: SystemError (built-in exception)
Return the name of the file from which *module* was loaded using *module*'s
:attr:`__file__` attribute. If this is not defined, or if it is not a
unicode string, raise :exc:`SystemError` and return *NULL*; otherwise return
a reference to a Unicode object.
.. versionadded:: 3.2
.. c:function:: char* PyModule_GetFilename(PyObject *module)
Similar to :c:func:`PyModule_GetFilenameObject` but return the filename
encoded to 'utf-8'.
.. deprecated:: 3.2
:c:func:`PyModule_GetFilename` raises :c:type:`UnicodeEncodeError` on
unencodable filenames, use :c:func:`PyModule_GetFilenameObject` instead.
.. _initializing-modules:
Initializing C modules
^^^^^^^^^^^^^^^^^^^^^^
Modules objects are usually created from extension modules (shared libraries
which export an initialization function), or compiled-in modules
(where the initialization function is added using :c:func:`PyImport_AppendInittab`).
See :ref:`building` or :ref:`extending-with-embedding` for details.
The initialization function can either pass a module definition instance
to :c:func:`PyModule_Create`, and return the resulting module object,
or request "multi-phase initialization" by returning the definition struct itself.
.. c:type:: PyModuleDef
The module definition struct, which holds all information needed to create
a module object. There is usually only one statically initialized variable
of this type for each module.
.. c:member:: PyModuleDef_Base m_base
Always initialize this member to :const:`PyModuleDef_HEAD_INIT`.
.. c:member:: char* m_name
Name for the new module.
.. c:member:: char* m_doc
Docstring for the module; usually a docstring variable created with
:c:func:`PyDoc_STRVAR` is used.
.. c:member:: Py_ssize_t m_size
Module state may be kept in a per-module memory area that can be
retrieved with :c:func:`PyModule_GetState`, rather than in static globals.
This makes modules safe for use in multiple sub-interpreters.
This memory area is allocated based on *m_size* on module creation,
and freed when the module object is deallocated, after the
:c:member:`m_free` function has been called, if present.
Setting ``m_size`` to ``-1`` means that the module does not support
sub-interpreters, because it has global state.
Setting it to a non-negative value means that the module can be
re-initialized and specifies the additional amount of memory it requires
for its state. Non-negative ``m_size`` is required for multi-phase
initialization.
See :PEP:`3121` for more details.
.. c:member:: PyMethodDef* m_methods
A pointer to a table of module-level functions, described by
:c:type:`PyMethodDef` values. Can be *NULL* if no functions are present.
.. c:member:: PyModuleDef_Slot* m_slots
An array of slot definitions for multi-phase initialization, terminated by
a ``{0, NULL}`` entry.
When using single-phase initialization, *m_slots* must be *NULL*.
.. versionchanged:: 3.5
Prior to version 3.5, this member was always set to *NULL*,
and was defined as:
.. c:member:: inquiry m_reload
.. c:member:: traverseproc m_traverse
A traversal function to call during GC traversal of the module object, or
*NULL* if not needed. This function may be called before module state
is allocated (:c:func:`PyModule_GetState()` may return `NULL`),
and before the :c:member:`Py_mod_exec` function is executed.
.. c:member:: inquiry m_clear
A clear function to call during GC clearing of the module object, or
*NULL* if not needed. This function may be called before module state
is allocated (:c:func:`PyModule_GetState()` may return `NULL`),
and before the :c:member:`Py_mod_exec` function is executed.
.. c:member:: freefunc m_free
A function to call during deallocation of the module object, or *NULL* if
not needed. This function may be called before module state
is allocated (:c:func:`PyModule_GetState()` may return `NULL`),
and before the :c:member:`Py_mod_exec` function is executed.
Single-phase initialization
...........................
The module initialization function may create and return the module object
directly. This is referred to as "single-phase initialization", and uses one
of the following two module creation functions:
.. c:function:: PyObject* PyModule_Create(PyModuleDef *def)
Create a new module object, given the definition in *def*. This behaves
like :c:func:`PyModule_Create2` with *module_api_version* set to
:const:`PYTHON_API_VERSION`.
.. c:function:: PyObject* PyModule_Create2(PyModuleDef *def, int module_api_version)
Create a new module object, given the definition in *def*, assuming the
API version *module_api_version*. If that version does not match the version
of the running interpreter, a :exc:`RuntimeWarning` is emitted.
.. note::
Most uses of this function should be using :c:func:`PyModule_Create`
instead; only use this if you are sure you need it.
Before it is returned from in the initialization function, the resulting module
object is typically populated using functions like :c:func:`PyModule_AddObject`.
.. _multi-phase-initialization:
Multi-phase initialization
..........................
An alternate way to specify extensions is to request "multi-phase initialization".
Extension modules created this way behave more like Python modules: the
initialization is split between the *creation phase*, when the module object
is created, and the *execution phase*, when it is populated.
The distinction is similar to the :py:meth:`__new__` and :py:meth:`__init__` methods
of classes.
Unlike modules created using single-phase initialization, these modules are not
singletons: if the *sys.modules* entry is removed and the module is re-imported,
a new module object is created, and the old module is subject to normal garbage
collection -- as with Python modules.
By default, multiple modules created from the same definition should be
independent: changes to one should not affect the others.
This means that all state should be specific to the module object (using e.g.
using :c:func:`PyModule_GetState`), or its contents (such as the module's
:attr:`__dict__` or individual classes created with :c:func:`PyType_FromSpec`).
All modules created using multi-phase initialization are expected to support
:ref:`sub-interpreters <sub-interpreter-support>`. Making sure multiple modules
are independent is typically enough to achieve this.
To request multi-phase initialization, the initialization function
(PyInit_modulename) returns a :c:type:`PyModuleDef` instance with non-empty
:c:member:`~PyModuleDef.m_slots`. Before it is returned, the ``PyModuleDef``
instance must be initialized with the following function:
.. c:function:: PyObject* PyModuleDef_Init(PyModuleDef *def)
Ensures a module definition is a properly initialized Python object that
correctly reports its type and reference count.
Returns *def* cast to ``PyObject*``, or *NULL* if an error occurred.
.. versionadded:: 3.5
The *m_slots* member of the module definition must point to an array of
``PyModuleDef_Slot`` structures:
.. c:type:: PyModuleDef_Slot
.. c:member:: int slot
A slot ID, chosen from the available values explained below.
.. c:member:: void* value
Value of the slot, whose meaning depends on the slot ID.
.. versionadded:: 3.5
The *m_slots* array must be terminated by a slot with id 0.
The available slot types are:
.. c:var:: Py_mod_create
Specifies a function that is called to create the module object itself.
The *value* pointer of this slot must point to a function of the signature:
.. c:function:: PyObject* create_module(PyObject *spec, PyModuleDef *def)
The function receives a :py:class:`~importlib.machinery.ModuleSpec`
instance, as defined in :PEP:`451`, and the module definition.
It should return a new module object, or set an error
and return *NULL*.
This function should be kept minimal. In particular, it should not
call arbitrary Python code, as trying to import the same module again may
result in an infinite loop.
Multiple ``Py_mod_create`` slots may not be specified in one module
definition.
If ``Py_mod_create`` is not specified, the import machinery will create
a normal module object using :c:func:`PyModule_New`. The name is taken from
*spec*, not the definition, to allow extension modules to dynamically adjust
to their place in the module hierarchy and be imported under different
names through symlinks, all while sharing a single module definition.
There is no requirement for the returned object to be an instance of
:c:type:`PyModule_Type`. Any type can be used, as long as it supports
setting and getting import-related attributes.
However, only ``PyModule_Type`` instances may be returned if the
``PyModuleDef`` has non-*NULL* ``m_traverse``, ``m_clear``,
``m_free``; non-zero ``m_size``; or slots other than ``Py_mod_create``.
.. c:var:: Py_mod_exec
Specifies a function that is called to *execute* the module.
This is equivalent to executing the code of a Python module: typically,
this function adds classes and constants to the module.
The signature of the function is:
.. c:function:: int exec_module(PyObject* module)
If multiple ``Py_mod_exec`` slots are specified, they are processed in the
order they appear in the *m_slots* array.
See :PEP:`489` for more details on multi-phase initialization.
Low-level module creation functions
...................................
The following functions are called under the hood when using multi-phase
initialization. They can be used directly, for example when creating module
objects dynamically. Note that both ``PyModule_FromDefAndSpec`` and
``PyModule_ExecDef`` must be called to fully initialize a module.
.. c:function:: PyObject * PyModule_FromDefAndSpec(PyModuleDef *def, PyObject *spec)
Create a new module object, given the definition in *module* and the
ModuleSpec *spec*. This behaves like :c:func:`PyModule_FromDefAndSpec2`
with *module_api_version* set to :const:`PYTHON_API_VERSION`.
.. versionadded:: 3.5
.. c:function:: PyObject * PyModule_FromDefAndSpec2(PyModuleDef *def, PyObject *spec, int module_api_version)
Create a new module object, given the definition in *module* and the
ModuleSpec *spec*, assuming the API version *module_api_version*.
If that version does not match the version of the running interpreter,
a :exc:`RuntimeWarning` is emitted.
.. note::
Most uses of this function should be using :c:func:`PyModule_FromDefAndSpec`
instead; only use this if you are sure you need it.
.. versionadded:: 3.5
.. c:function:: int PyModule_ExecDef(PyObject *module, PyModuleDef *def)
Process any execution slots (:c:data:`Py_mod_exec`) given in *def*.
.. versionadded:: 3.5
.. c:function:: int PyModule_SetDocString(PyObject *module, const char *docstring)
Set the docstring for *module* to *docstring*.
This function is called automatically when creating a module from
``PyModuleDef``, using either ``PyModule_Create`` or
``PyModule_FromDefAndSpec``.
.. versionadded:: 3.5
.. c:function:: int PyModule_AddFunctions(PyObject *module, PyMethodDef *functions)
Add the functions from the *NULL* terminated *functions* array to *module*.
Refer to the :c:type:`PyMethodDef` documentation for details on individual
entries (due to the lack of a shared module namespace, module level
"functions" implemented in C typically receive the module as their first
parameter, making them similar to instance methods on Python classes).
This function is called automatically when creating a module from
``PyModuleDef``, using either ``PyModule_Create`` or
``PyModule_FromDefAndSpec``.
.. versionadded:: 3.5
Support functions
.................
The module initialization function (if using single phase initialization) or
a function called from a module execution slot (if using multi-phase
initialization), can use the following functions to help initialize the module
state:
.. c:function:: int PyModule_AddObject(PyObject *module, const char *name, PyObject *value)
Add an object to *module* as *name*. This is a convenience function which can
be used from the module's initialization function. This steals a reference to
*value*. Return ``-1`` on error, ``0`` on success.
.. c:function:: int PyModule_AddIntConstant(PyObject *module, const char *name, long value)
Add an integer constant to *module* as *name*. This convenience function can be
used from the module's initialization function. Return ``-1`` on error, ``0`` on
success.
.. c:function:: int PyModule_AddStringConstant(PyObject *module, const char *name, const char *value)
Add a string constant to *module* as *name*. This convenience function can be
used from the module's initialization function. The string *value* must be
*NULL*-terminated. Return ``-1`` on error, ``0`` on success.
.. c:function:: int PyModule_AddIntMacro(PyObject *module, macro)
Add an int constant to *module*. The name and the value are taken from
*macro*. For example ``PyModule_AddIntMacro(module, AF_INET)`` adds the int
constant *AF_INET* with the value of *AF_INET* to *module*.
Return ``-1`` on error, ``0`` on success.
.. c:function:: int PyModule_AddStringMacro(PyObject *module, macro)
Add a string constant to *module*.
Module lookup
^^^^^^^^^^^^^
Single-phase initialization creates singleton modules that can be looked up
in the context of the current interpreter. This allows the module object to be
retrieved later with only a reference to the module definition.
These functions will not work on modules created using multi-phase initialization,
since multiple such modules can be created from a single definition.
.. c:function:: PyObject* PyState_FindModule(PyModuleDef *def)
Returns the module object that was created from *def* for the current interpreter.
This method requires that the module object has been attached to the interpreter state with
:c:func:`PyState_AddModule` beforehand. In case the corresponding module object is not
found or has not been attached to the interpreter state yet, it returns *NULL*.
.. c:function:: int PyState_AddModule(PyObject *module, PyModuleDef *def)
Attaches the module object passed to the function to the interpreter state. This allows
the module object to be accessible via :c:func:`PyState_FindModule`.
Only effective on modules created using single-phase initialization.
.. versionadded:: 3.3
.. c:function:: int PyState_RemoveModule(PyModuleDef *def)
Removes the module object created from *def* from the interpreter state.
.. versionadded:: 3.3

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.. highlightlang:: c
.. _noneobject:
The ``None`` Object
-------------------
.. index:: object: None
Note that the :c:type:`PyTypeObject` for ``None`` is not directly exposed in the
Python/C API. Since ``None`` is a singleton, testing for object identity (using
``==`` in C) is sufficient. There is no :c:func:`PyNone_Check` function for the
same reason.
.. c:var:: PyObject* Py_None
The Python ``None`` object, denoting lack of value. This object has no methods.
It needs to be treated just like any other object with respect to reference
counts.
.. c:macro:: Py_RETURN_NONE
Properly handle returning :c:data:`Py_None` from within a C function (that is,
increment the reference count of ``None`` and return it.)

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.. highlightlang:: c
.. _number:
Number Protocol
===============
.. c:function:: int PyNumber_Check(PyObject *o)
Returns ``1`` if the object *o* provides numeric protocols, and false otherwise.
This function always succeeds.
.. c:function:: PyObject* PyNumber_Add(PyObject *o1, PyObject *o2)
Returns the result of adding *o1* and *o2*, or *NULL* on failure. This is the
equivalent of the Python expression ``o1 + o2``.
.. c:function:: PyObject* PyNumber_Subtract(PyObject *o1, PyObject *o2)
Returns the result of subtracting *o2* from *o1*, or *NULL* on failure. This is
the equivalent of the Python expression ``o1 - o2``.
.. c:function:: PyObject* PyNumber_Multiply(PyObject *o1, PyObject *o2)
Returns the result of multiplying *o1* and *o2*, or *NULL* on failure. This is
the equivalent of the Python expression ``o1 * o2``.
.. c:function:: PyObject* PyNumber_MatrixMultiply(PyObject *o1, PyObject *o2)
Returns the result of matrix multiplication on *o1* and *o2*, or *NULL* on
failure. This is the equivalent of the Python expression ``o1 @ o2``.
.. versionadded:: 3.5
.. c:function:: PyObject* PyNumber_FloorDivide(PyObject *o1, PyObject *o2)
Return the floor of *o1* divided by *o2*, or *NULL* on failure. This is
equivalent to the "classic" division of integers.
.. c:function:: PyObject* PyNumber_TrueDivide(PyObject *o1, PyObject *o2)
Return a reasonable approximation for the mathematical value of *o1* divided by
*o2*, or *NULL* on failure. The return value is "approximate" because binary
floating point numbers are approximate; it is not possible to represent all real
numbers in base two. This function can return a floating point value when
passed two integers.
.. c:function:: PyObject* PyNumber_Remainder(PyObject *o1, PyObject *o2)
Returns the remainder of dividing *o1* by *o2*, or *NULL* on failure. This is
the equivalent of the Python expression ``o1 % o2``.
.. c:function:: PyObject* PyNumber_Divmod(PyObject *o1, PyObject *o2)
.. index:: builtin: divmod
See the built-in function :func:`divmod`. Returns *NULL* on failure. This is
the equivalent of the Python expression ``divmod(o1, o2)``.
.. c:function:: PyObject* PyNumber_Power(PyObject *o1, PyObject *o2, PyObject *o3)
.. index:: builtin: pow
See the built-in function :func:`pow`. Returns *NULL* on failure. This is the
equivalent of the Python expression ``pow(o1, o2, o3)``, where *o3* is optional.
If *o3* is to be ignored, pass :c:data:`Py_None` in its place (passing *NULL* for
*o3* would cause an illegal memory access).
.. c:function:: PyObject* PyNumber_Negative(PyObject *o)
Returns the negation of *o* on success, or *NULL* on failure. This is the
equivalent of the Python expression ``-o``.
.. c:function:: PyObject* PyNumber_Positive(PyObject *o)
Returns *o* on success, or *NULL* on failure. This is the equivalent of the
Python expression ``+o``.
.. c:function:: PyObject* PyNumber_Absolute(PyObject *o)
.. index:: builtin: abs
Returns the absolute value of *o*, or *NULL* on failure. This is the equivalent
of the Python expression ``abs(o)``.
.. c:function:: PyObject* PyNumber_Invert(PyObject *o)
Returns the bitwise negation of *o* on success, or *NULL* on failure. This is
the equivalent of the Python expression ``~o``.
.. c:function:: PyObject* PyNumber_Lshift(PyObject *o1, PyObject *o2)
Returns the result of left shifting *o1* by *o2* on success, or *NULL* on
failure. This is the equivalent of the Python expression ``o1 << o2``.
.. c:function:: PyObject* PyNumber_Rshift(PyObject *o1, PyObject *o2)
Returns the result of right shifting *o1* by *o2* on success, or *NULL* on
failure. This is the equivalent of the Python expression ``o1 >> o2``.
.. c:function:: PyObject* PyNumber_And(PyObject *o1, PyObject *o2)
Returns the "bitwise and" of *o1* and *o2* on success and *NULL* on failure.
This is the equivalent of the Python expression ``o1 & o2``.
.. c:function:: PyObject* PyNumber_Xor(PyObject *o1, PyObject *o2)
Returns the "bitwise exclusive or" of *o1* by *o2* on success, or *NULL* on
failure. This is the equivalent of the Python expression ``o1 ^ o2``.
.. c:function:: PyObject* PyNumber_Or(PyObject *o1, PyObject *o2)
Returns the "bitwise or" of *o1* and *o2* on success, or *NULL* on failure.
This is the equivalent of the Python expression ``o1 | o2``.
.. c:function:: PyObject* PyNumber_InPlaceAdd(PyObject *o1, PyObject *o2)
Returns the result of adding *o1* and *o2*, or *NULL* on failure. The operation
is done *in-place* when *o1* supports it. This is the equivalent of the Python
statement ``o1 += o2``.
.. c:function:: PyObject* PyNumber_InPlaceSubtract(PyObject *o1, PyObject *o2)
Returns the result of subtracting *o2* from *o1*, or *NULL* on failure. The
operation is done *in-place* when *o1* supports it. This is the equivalent of
the Python statement ``o1 -= o2``.
.. c:function:: PyObject* PyNumber_InPlaceMultiply(PyObject *o1, PyObject *o2)
Returns the result of multiplying *o1* and *o2*, or *NULL* on failure. The
operation is done *in-place* when *o1* supports it. This is the equivalent of
the Python statement ``o1 *= o2``.
.. c:function:: PyObject* PyNumber_InPlaceMatrixMultiply(PyObject *o1, PyObject *o2)
Returns the result of matrix multiplication on *o1* and *o2*, or *NULL* on
failure. The operation is done *in-place* when *o1* supports it. This is
the equivalent of the Python statement ``o1 @= o2``.
.. versionadded:: 3.5
.. c:function:: PyObject* PyNumber_InPlaceFloorDivide(PyObject *o1, PyObject *o2)
Returns the mathematical floor of dividing *o1* by *o2*, or *NULL* on failure.
The operation is done *in-place* when *o1* supports it. This is the equivalent
of the Python statement ``o1 //= o2``.
.. c:function:: PyObject* PyNumber_InPlaceTrueDivide(PyObject *o1, PyObject *o2)
Return a reasonable approximation for the mathematical value of *o1* divided by
*o2*, or *NULL* on failure. The return value is "approximate" because binary
floating point numbers are approximate; it is not possible to represent all real
numbers in base two. This function can return a floating point value when
passed two integers. The operation is done *in-place* when *o1* supports it.
.. c:function:: PyObject* PyNumber_InPlaceRemainder(PyObject *o1, PyObject *o2)
Returns the remainder of dividing *o1* by *o2*, or *NULL* on failure. The
operation is done *in-place* when *o1* supports it. This is the equivalent of
the Python statement ``o1 %= o2``.
.. c:function:: PyObject* PyNumber_InPlacePower(PyObject *o1, PyObject *o2, PyObject *o3)
.. index:: builtin: pow
See the built-in function :func:`pow`. Returns *NULL* on failure. The operation
is done *in-place* when *o1* supports it. This is the equivalent of the Python
statement ``o1 **= o2`` when o3 is :c:data:`Py_None`, or an in-place variant of
``pow(o1, o2, o3)`` otherwise. If *o3* is to be ignored, pass :c:data:`Py_None`
in its place (passing *NULL* for *o3* would cause an illegal memory access).
.. c:function:: PyObject* PyNumber_InPlaceLshift(PyObject *o1, PyObject *o2)
Returns the result of left shifting *o1* by *o2* on success, or *NULL* on
failure. The operation is done *in-place* when *o1* supports it. This is the
equivalent of the Python statement ``o1 <<= o2``.
.. c:function:: PyObject* PyNumber_InPlaceRshift(PyObject *o1, PyObject *o2)
Returns the result of right shifting *o1* by *o2* on success, or *NULL* on
failure. The operation is done *in-place* when *o1* supports it. This is the
equivalent of the Python statement ``o1 >>= o2``.
.. c:function:: PyObject* PyNumber_InPlaceAnd(PyObject *o1, PyObject *o2)
Returns the "bitwise and" of *o1* and *o2* on success and *NULL* on failure. The
operation is done *in-place* when *o1* supports it. This is the equivalent of
the Python statement ``o1 &= o2``.
.. c:function:: PyObject* PyNumber_InPlaceXor(PyObject *o1, PyObject *o2)
Returns the "bitwise exclusive or" of *o1* by *o2* on success, or *NULL* on
failure. The operation is done *in-place* when *o1* supports it. This is the
equivalent of the Python statement ``o1 ^= o2``.
.. c:function:: PyObject* PyNumber_InPlaceOr(PyObject *o1, PyObject *o2)
Returns the "bitwise or" of *o1* and *o2* on success, or *NULL* on failure. The
operation is done *in-place* when *o1* supports it. This is the equivalent of
the Python statement ``o1 |= o2``.
.. c:function:: PyObject* PyNumber_Long(PyObject *o)
.. index:: builtin: int
Returns the *o* converted to an integer object on success, or *NULL* on
failure. This is the equivalent of the Python expression ``int(o)``.
.. c:function:: PyObject* PyNumber_Float(PyObject *o)
.. index:: builtin: float
Returns the *o* converted to a float object on success, or *NULL* on failure.
This is the equivalent of the Python expression ``float(o)``.
.. c:function:: PyObject* PyNumber_Index(PyObject *o)
Returns the *o* converted to a Python int on success or *NULL* with a
:exc:`TypeError` exception raised on failure.
.. c:function:: PyObject* PyNumber_ToBase(PyObject *n, int base)
Returns the integer *n* converted to base *base* as a string. The *base*
argument must be one of 2, 8, 10, or 16. For base 2, 8, or 16, the
returned string is prefixed with a base marker of ``'0b'``, ``'0o'``, or
``'0x'``, respectively. If *n* is not a Python int, it is converted with
:c:func:`PyNumber_Index` first.
.. c:function:: Py_ssize_t PyNumber_AsSsize_t(PyObject *o, PyObject *exc)
Returns *o* converted to a Py_ssize_t value if *o* can be interpreted as an
integer. If the call fails, an exception is raised and ``-1`` is returned.
If *o* can be converted to a Python int but the attempt to
convert to a Py_ssize_t value would raise an :exc:`OverflowError`, then the
*exc* argument is the type of exception that will be raised (usually
:exc:`IndexError` or :exc:`OverflowError`). If *exc* is *NULL*, then the
exception is cleared and the value is clipped to *PY_SSIZE_T_MIN* for a negative
integer or *PY_SSIZE_T_MAX* for a positive integer.
.. c:function:: int PyIndex_Check(PyObject *o)
Returns ``1`` if *o* is an index integer (has the nb_index slot of the
tp_as_number structure filled in), and ``0`` otherwise.
This function always succeeds.

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.. highlightlang:: c
Old Buffer Protocol
-------------------
.. deprecated:: 3.0
These functions were part of the "old buffer protocol" API in Python 2.
In Python 3, this protocol doesn't exist anymore but the functions are still
exposed to ease porting 2.x code. They act as a compatibility wrapper
around the :ref:`new buffer protocol <bufferobjects>`, but they don't give
you control over the lifetime of the resources acquired when a buffer is
exported.
Therefore, it is recommended that you call :c:func:`PyObject_GetBuffer`
(or the ``y*`` or ``w*`` :ref:`format codes <arg-parsing>` with the
:c:func:`PyArg_ParseTuple` family of functions) to get a buffer view over
an object, and :c:func:`PyBuffer_Release` when the buffer view can be released.
.. c:function:: int PyObject_AsCharBuffer(PyObject *obj, const char **buffer, Py_ssize_t *buffer_len)
Returns a pointer to a read-only memory location usable as character-based
input. The *obj* argument must support the single-segment character buffer
interface. On success, returns ``0``, sets *buffer* to the memory location
and *buffer_len* to the buffer length. Returns ``-1`` and sets a
:exc:`TypeError` on error.
.. c:function:: int PyObject_AsReadBuffer(PyObject *obj, const void **buffer, Py_ssize_t *buffer_len)
Returns a pointer to a read-only memory location containing arbitrary data.
The *obj* argument must support the single-segment readable buffer
interface. On success, returns ``0``, sets *buffer* to the memory location
and *buffer_len* to the buffer length. Returns ``-1`` and sets a
:exc:`TypeError` on error.
.. c:function:: int PyObject_CheckReadBuffer(PyObject *o)
Returns ``1`` if *o* supports the single-segment readable buffer interface.
Otherwise returns ``0``. This function always succeeds.
Note that this function tries to get and release a buffer, and exceptions
which occur while calling correspoding functions will get suppressed.
To get error reporting use :c:func:`PyObject_GetBuffer()` instead.
.. c:function:: int PyObject_AsWriteBuffer(PyObject *obj, void **buffer, Py_ssize_t *buffer_len)
Returns a pointer to a writable memory location. The *obj* argument must
support the single-segment, character buffer interface. On success,
returns ``0``, sets *buffer* to the memory location and *buffer_len* to the
buffer length. Returns ``-1`` and sets a :exc:`TypeError` on error.

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.. highlightlang:: c
.. _object:
Object Protocol
===============
.. c:var:: PyObject* Py_NotImplemented
The ``NotImplemented`` singleton, used to signal that an operation is
not implemented for the given type combination.
.. c:macro:: Py_RETURN_NOTIMPLEMENTED
Properly handle returning :c:data:`Py_NotImplemented` from within a C
function (that is, increment the reference count of NotImplemented and
return it).
.. c:function:: int PyObject_Print(PyObject *o, FILE *fp, int flags)
Print an object *o*, on file *fp*. Returns ``-1`` on error. The flags argument
is used to enable certain printing options. The only option currently supported
is :const:`Py_PRINT_RAW`; if given, the :func:`str` of the object is written
instead of the :func:`repr`.
.. c:function:: int PyObject_HasAttr(PyObject *o, PyObject *attr_name)
Returns ``1`` if *o* has the attribute *attr_name*, and ``0`` otherwise. This
is equivalent to the Python expression ``hasattr(o, attr_name)``. This function
always succeeds.
Note that exceptions which occur while calling :meth:`__getattr__` and
:meth:`__getattribute__` methods will get suppressed.
To get error reporting use :c:func:`PyObject_GetAttr()` instead.
.. c:function:: int PyObject_HasAttrString(PyObject *o, const char *attr_name)
Returns ``1`` if *o* has the attribute *attr_name*, and ``0`` otherwise. This
is equivalent to the Python expression ``hasattr(o, attr_name)``. This function
always succeeds.
Note that exceptions which occur while calling :meth:`__getattr__` and
:meth:`__getattribute__` methods and creating a temporary string object
will get suppressed.
To get error reporting use :c:func:`PyObject_GetAttrString()` instead.
.. c:function:: PyObject* PyObject_GetAttr(PyObject *o, PyObject *attr_name)
Retrieve an attribute named *attr_name* from object *o*. Returns the attribute
value on success, or *NULL* on failure. This is the equivalent of the Python
expression ``o.attr_name``.
.. c:function:: PyObject* PyObject_GetAttrString(PyObject *o, const char *attr_name)
Retrieve an attribute named *attr_name* from object *o*. Returns the attribute
value on success, or *NULL* on failure. This is the equivalent of the Python
expression ``o.attr_name``.
.. c:function:: PyObject* PyObject_GenericGetAttr(PyObject *o, PyObject *name)
Generic attribute getter function that is meant to be put into a type
object's ``tp_getattro`` slot. It looks for a descriptor in the dictionary
of classes in the object's MRO as well as an attribute in the object's
:attr:`~object.__dict__` (if present). As outlined in :ref:`descriptors`,
data descriptors take preference over instance attributes, while non-data
descriptors don't. Otherwise, an :exc:`AttributeError` is raised.
.. c:function:: int PyObject_SetAttr(PyObject *o, PyObject *attr_name, PyObject *v)
Set the value of the attribute named *attr_name*, for object *o*, to the value
*v*. Raise an exception and return ``-1`` on failure;
return ``0`` on success. This is the equivalent of the Python statement
``o.attr_name = v``.
If *v* is *NULL*, the attribute is deleted, however this feature is
deprecated in favour of using :c:func:`PyObject_DelAttr`.
.. c:function:: int PyObject_SetAttrString(PyObject *o, const char *attr_name, PyObject *v)
Set the value of the attribute named *attr_name*, for object *o*, to the value
*v*. Raise an exception and return ``-1`` on failure;
return ``0`` on success. This is the equivalent of the Python statement
``o.attr_name = v``.
If *v* is *NULL*, the attribute is deleted, however this feature is
deprecated in favour of using :c:func:`PyObject_DelAttrString`.
.. c:function:: int PyObject_GenericSetAttr(PyObject *o, PyObject *name, PyObject *value)
Generic attribute setter and deleter function that is meant
to be put into a type object's :c:member:`~PyTypeObject.tp_setattro`
slot. It looks for a data descriptor in the
dictionary of classes in the object's MRO, and if found it takes preference
over setting or deleting the attribute in the instance dictionary. Otherwise, the
attribute is set or deleted in the object's :attr:`~object.__dict__` (if present).
On success, ``0`` is returned, otherwise an :exc:`AttributeError`
is raised and ``-1`` is returned.
.. c:function:: int PyObject_DelAttr(PyObject *o, PyObject *attr_name)
Delete attribute named *attr_name*, for object *o*. Returns ``-1`` on failure.
This is the equivalent of the Python statement ``del o.attr_name``.
.. c:function:: int PyObject_DelAttrString(PyObject *o, const char *attr_name)
Delete attribute named *attr_name*, for object *o*. Returns ``-1`` on failure.
This is the equivalent of the Python statement ``del o.attr_name``.
.. c:function:: PyObject* PyObject_GenericGetDict(PyObject *o, void *context)
A generic implementation for the getter of a ``__dict__`` descriptor. It
creates the dictionary if necessary.
.. versionadded:: 3.3
.. c:function:: int PyObject_GenericSetDict(PyObject *o, void *context)
A generic implementation for the setter of a ``__dict__`` descriptor. This
implementation does not allow the dictionary to be deleted.
.. versionadded:: 3.3
.. c:function:: PyObject* PyObject_RichCompare(PyObject *o1, PyObject *o2, int opid)
Compare the values of *o1* and *o2* using the operation specified by *opid*,
which must be one of :const:`Py_LT`, :const:`Py_LE`, :const:`Py_EQ`,
:const:`Py_NE`, :const:`Py_GT`, or :const:`Py_GE`, corresponding to ``<``,
``<=``, ``==``, ``!=``, ``>``, or ``>=`` respectively. This is the equivalent of
the Python expression ``o1 op o2``, where ``op`` is the operator corresponding
to *opid*. Returns the value of the comparison on success, or *NULL* on failure.
.. c:function:: int PyObject_RichCompareBool(PyObject *o1, PyObject *o2, int opid)
Compare the values of *o1* and *o2* using the operation specified by *opid*,
which must be one of :const:`Py_LT`, :const:`Py_LE`, :const:`Py_EQ`,
:const:`Py_NE`, :const:`Py_GT`, or :const:`Py_GE`, corresponding to ``<``,
``<=``, ``==``, ``!=``, ``>``, or ``>=`` respectively. Returns ``-1`` on error,
``0`` if the result is false, ``1`` otherwise. This is the equivalent of the
Python expression ``o1 op o2``, where ``op`` is the operator corresponding to
*opid*.
.. note::
If *o1* and *o2* are the same object, :c:func:`PyObject_RichCompareBool`
will always return ``1`` for :const:`Py_EQ` and ``0`` for :const:`Py_NE`.
.. c:function:: PyObject* PyObject_Repr(PyObject *o)
.. index:: builtin: repr
Compute a string representation of object *o*. Returns the string
representation on success, *NULL* on failure. This is the equivalent of the
Python expression ``repr(o)``. Called by the :func:`repr` built-in function.
.. versionchanged:: 3.4
This function now includes a debug assertion to help ensure that it
does not silently discard an active exception.
.. c:function:: PyObject* PyObject_ASCII(PyObject *o)
.. index:: builtin: ascii
As :c:func:`PyObject_Repr`, compute a string representation of object *o*, but
escape the non-ASCII characters in the string returned by
:c:func:`PyObject_Repr` with ``\x``, ``\u`` or ``\U`` escapes. This generates
a string similar to that returned by :c:func:`PyObject_Repr` in Python 2.
Called by the :func:`ascii` built-in function.
.. index:: string; PyObject_Str (C function)
.. c:function:: PyObject* PyObject_Str(PyObject *o)
Compute a string representation of object *o*. Returns the string
representation on success, *NULL* on failure. This is the equivalent of the
Python expression ``str(o)``. Called by the :func:`str` built-in function
and, therefore, by the :func:`print` function.
.. versionchanged:: 3.4
This function now includes a debug assertion to help ensure that it
does not silently discard an active exception.
.. c:function:: PyObject* PyObject_Bytes(PyObject *o)
.. index:: builtin: bytes
Compute a bytes representation of object *o*. *NULL* is returned on
failure and a bytes object on success. This is equivalent to the Python
expression ``bytes(o)``, when *o* is not an integer. Unlike ``bytes(o)``,
a TypeError is raised when *o* is an integer instead of a zero-initialized
bytes object.
.. c:function:: int PyObject_IsSubclass(PyObject *derived, PyObject *cls)
Return ``1`` if the class *derived* is identical to or derived from the class
*cls*, otherwise return ``0``. In case of an error, return ``-1``.
If *cls* is a tuple, the check will be done against every entry in *cls*.
The result will be ``1`` when at least one of the checks returns ``1``,
otherwise it will be ``0``.
If *cls* has a :meth:`~class.__subclasscheck__` method, it will be called to
determine the subclass status as described in :pep:`3119`. Otherwise,
*derived* is a subclass of *cls* if it is a direct or indirect subclass,
i.e. contained in ``cls.__mro__``.
Normally only class objects, i.e. instances of :class:`type` or a derived
class, are considered classes. However, objects can override this by having
a :attr:`__bases__` attribute (which must be a tuple of base classes).
.. c:function:: int PyObject_IsInstance(PyObject *inst, PyObject *cls)
Return ``1`` if *inst* is an instance of the class *cls* or a subclass of
*cls*, or ``0`` if not. On error, returns ``-1`` and sets an exception.
If *cls* is a tuple, the check will be done against every entry in *cls*.
The result will be ``1`` when at least one of the checks returns ``1``,
otherwise it will be ``0``.
If *cls* has a :meth:`~class.__instancecheck__` method, it will be called to
determine the subclass status as described in :pep:`3119`. Otherwise, *inst*
is an instance of *cls* if its class is a subclass of *cls*.
An instance *inst* can override what is considered its class by having a
:attr:`__class__` attribute.
An object *cls* can override if it is considered a class, and what its base
classes are, by having a :attr:`__bases__` attribute (which must be a tuple
of base classes).
.. c:function:: int PyCallable_Check(PyObject *o)
Determine if the object *o* is callable. Return ``1`` if the object is callable
and ``0`` otherwise. This function always succeeds.
.. c:function:: PyObject* PyObject_Call(PyObject *callable_object, PyObject *args, PyObject *kw)
Call a callable Python object *callable_object*, with arguments given by the
tuple *args*, and named arguments given by the dictionary *kw*. If no named
arguments are needed, *kw* may be *NULL*. *args* must not be *NULL*, use an
empty tuple if no arguments are needed. Returns the result of the call on
success, or *NULL* on failure. This is the equivalent of the Python expression
``callable_object(*args, **kw)``.
.. c:function:: PyObject* PyObject_CallObject(PyObject *callable_object, PyObject *args)
Call a callable Python object *callable_object*, with arguments given by the
tuple *args*. If no arguments are needed, then *args* may be *NULL*. Returns
the result of the call on success, or *NULL* on failure. This is the equivalent
of the Python expression ``callable_object(*args)``.
.. c:function:: PyObject* PyObject_CallFunction(PyObject *callable, const char *format, ...)
Call a callable Python object *callable*, with a variable number of C arguments.
The C arguments are described using a :c:func:`Py_BuildValue` style format
string. The format may be *NULL*, indicating that no arguments are provided.
Returns the result of the call on success, or *NULL* on failure. This is the
equivalent of the Python expression ``callable(*args)``. Note that if you only
pass :c:type:`PyObject \*` args, :c:func:`PyObject_CallFunctionObjArgs` is a
faster alternative.
.. versionchanged:: 3.4
The type of *format* was changed from ``char *``.
.. c:function:: PyObject* PyObject_CallMethod(PyObject *o, const char *method, const char *format, ...)
Call the method named *method* of object *o* with a variable number of C
arguments. The C arguments are described by a :c:func:`Py_BuildValue` format
string that should produce a tuple. The format may be *NULL*, indicating that
no arguments are provided. Returns the result of the call on success, or *NULL*
on failure. This is the equivalent of the Python expression ``o.method(args)``.
Note that if you only pass :c:type:`PyObject \*` args,
:c:func:`PyObject_CallMethodObjArgs` is a faster alternative.
.. versionchanged:: 3.4
The types of *method* and *format* were changed from ``char *``.
.. c:function:: PyObject* PyObject_CallFunctionObjArgs(PyObject *callable, ..., NULL)
Call a callable Python object *callable*, with a variable number of
:c:type:`PyObject\*` arguments. The arguments are provided as a variable number
of parameters followed by *NULL*. Returns the result of the call on success, or
*NULL* on failure.
.. c:function:: PyObject* PyObject_CallMethodObjArgs(PyObject *o, PyObject *name, ..., NULL)
Calls a method of the object *o*, where the name of the method is given as a
Python string object in *name*. It is called with a variable number of
:c:type:`PyObject\*` arguments. The arguments are provided as a variable number
of parameters followed by *NULL*. Returns the result of the call on success, or
*NULL* on failure.
.. c:function:: Py_hash_t PyObject_Hash(PyObject *o)
.. index:: builtin: hash
Compute and return the hash value of an object *o*. On failure, return ``-1``.
This is the equivalent of the Python expression ``hash(o)``.
.. versionchanged:: 3.2
The return type is now Py_hash_t. This is a signed integer the same size
as Py_ssize_t.
.. c:function:: Py_hash_t PyObject_HashNotImplemented(PyObject *o)
Set a :exc:`TypeError` indicating that ``type(o)`` is not hashable and return ``-1``.
This function receives special treatment when stored in a ``tp_hash`` slot,
allowing a type to explicitly indicate to the interpreter that it is not
hashable.
.. c:function:: int PyObject_IsTrue(PyObject *o)
Returns ``1`` if the object *o* is considered to be true, and ``0`` otherwise.
This is equivalent to the Python expression ``not not o``. On failure, return
``-1``.
.. c:function:: int PyObject_Not(PyObject *o)
Returns ``0`` if the object *o* is considered to be true, and ``1`` otherwise.
This is equivalent to the Python expression ``not o``. On failure, return
``-1``.
.. c:function:: PyObject* PyObject_Type(PyObject *o)
.. index:: builtin: type
When *o* is non-*NULL*, returns a type object corresponding to the object type
of object *o*. On failure, raises :exc:`SystemError` and returns *NULL*. This
is equivalent to the Python expression ``type(o)``. This function increments the
reference count of the return value. There's really no reason to use this
function instead of the common expression ``o->ob_type``, which returns a
pointer of type :c:type:`PyTypeObject\*`, except when the incremented reference
count is needed.
.. c:function:: int PyObject_TypeCheck(PyObject *o, PyTypeObject *type)
Return true if the object *o* is of type *type* or a subtype of *type*. Both
parameters must be non-*NULL*.
.. c:function:: Py_ssize_t PyObject_Size(PyObject *o)
Py_ssize_t PyObject_Length(PyObject *o)
.. index:: builtin: len
Return the length of object *o*. If the object *o* provides either the sequence
and mapping protocols, the sequence length is returned. On error, ``-1`` is
returned. This is the equivalent to the Python expression ``len(o)``.
.. c:function:: Py_ssize_t PyObject_LengthHint(PyObject *o, Py_ssize_t default)
Return an estimated length for the object *o*. First try to return its
actual length, then an estimate using :meth:`~object.__length_hint__`, and
finally return the default value. On error return ``-1``. This is the
equivalent to the Python expression ``operator.length_hint(o, default)``.
.. versionadded:: 3.4
.. c:function:: PyObject* PyObject_GetItem(PyObject *o, PyObject *key)
Return element of *o* corresponding to the object *key* or *NULL* on failure.
This is the equivalent of the Python expression ``o[key]``.
.. c:function:: int PyObject_SetItem(PyObject *o, PyObject *key, PyObject *v)
Map the object *key* to the value *v*. Raise an exception and
return ``-1`` on failure; return ``0`` on success. This is the
equivalent of the Python statement ``o[key] = v``.
.. c:function:: int PyObject_DelItem(PyObject *o, PyObject *key)
Remove the mapping for the object *key* from the object *o*. Return ``-1``
on failure. This is equivalent to the Python statement ``del o[key]``.
.. c:function:: PyObject* PyObject_Dir(PyObject *o)
This is equivalent to the Python expression ``dir(o)``, returning a (possibly
empty) list of strings appropriate for the object argument, or *NULL* if there
was an error. If the argument is *NULL*, this is like the Python ``dir()``,
returning the names of the current locals; in this case, if no execution frame
is active then *NULL* is returned but :c:func:`PyErr_Occurred` will return false.
.. c:function:: PyObject* PyObject_GetIter(PyObject *o)
This is equivalent to the Python expression ``iter(o)``. It returns a new
iterator for the object argument, or the object itself if the object is already
an iterator. Raises :exc:`TypeError` and returns *NULL* if the object cannot be
iterated.

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.. highlightlang:: c
.. _newtypes:
*****************************
Object Implementation Support
*****************************
This chapter describes the functions, types, and macros used when defining new
object types.
.. toctree::
allocation.rst
structures.rst
typeobj.rst
gcsupport.rst

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.. highlightlang:: c
.. _countingrefs:
******************
Reference Counting
******************
The macros in this section are used for managing reference counts of Python
objects.
.. c:function:: void Py_INCREF(PyObject *o)
Increment the reference count for object *o*. The object must not be *NULL*; if
you aren't sure that it isn't *NULL*, use :c:func:`Py_XINCREF`.
.. c:function:: void Py_XINCREF(PyObject *o)
Increment the reference count for object *o*. The object may be *NULL*, in
which case the macro has no effect.
.. c:function:: void Py_DECREF(PyObject *o)
Decrement the reference count for object *o*. The object must not be *NULL*; if
you aren't sure that it isn't *NULL*, use :c:func:`Py_XDECREF`. If the reference
count reaches zero, the object's type's deallocation function (which must not be
*NULL*) is invoked.
.. warning::
The deallocation function can cause arbitrary Python code to be invoked (e.g.
when a class instance with a :meth:`__del__` method is deallocated). While
exceptions in such code are not propagated, the executed code has free access to
all Python global variables. This means that any object that is reachable from
a global variable should be in a consistent state before :c:func:`Py_DECREF` is
invoked. For example, code to delete an object from a list should copy a
reference to the deleted object in a temporary variable, update the list data
structure, and then call :c:func:`Py_DECREF` for the temporary variable.
.. c:function:: void Py_XDECREF(PyObject *o)
Decrement the reference count for object *o*. The object may be *NULL*, in
which case the macro has no effect; otherwise the effect is the same as for
:c:func:`Py_DECREF`, and the same warning applies.
.. c:function:: void Py_CLEAR(PyObject *o)
Decrement the reference count for object *o*. The object may be *NULL*, in
which case the macro has no effect; otherwise the effect is the same as for
:c:func:`Py_DECREF`, except that the argument is also set to *NULL*. The warning
for :c:func:`Py_DECREF` does not apply with respect to the object passed because
the macro carefully uses a temporary variable and sets the argument to *NULL*
before decrementing its reference count.
It is a good idea to use this macro whenever decrementing the value of a
variable that might be traversed during garbage collection.
The following functions are for runtime dynamic embedding of Python:
``Py_IncRef(PyObject *o)``, ``Py_DecRef(PyObject *o)``. They are
simply exported function versions of :c:func:`Py_XINCREF` and
:c:func:`Py_XDECREF`, respectively.
The following functions or macros are only for use within the interpreter core:
:c:func:`_Py_Dealloc`, :c:func:`_Py_ForgetReference`, :c:func:`_Py_NewReference`,
as well as the global variable :c:data:`_Py_RefTotal`.

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.. highlightlang:: c
.. _reflection:
Reflection
==========
.. c:function:: PyObject* PyEval_GetBuiltins()
Return a dictionary of the builtins in the current execution frame,
or the interpreter of the thread state if no frame is currently executing.
.. c:function:: PyObject* PyEval_GetLocals()
Return a dictionary of the local variables in the current execution frame,
or *NULL* if no frame is currently executing.
.. c:function:: PyObject* PyEval_GetGlobals()
Return a dictionary of the global variables in the current execution frame,
or *NULL* if no frame is currently executing.
.. c:function:: PyFrameObject* PyEval_GetFrame()
Return the current thread state's frame, which is *NULL* if no frame is
currently executing.
.. c:function:: int PyFrame_GetLineNumber(PyFrameObject *frame)
Return the line number that *frame* is currently executing.
.. c:function:: const char* PyEval_GetFuncName(PyObject *func)
Return the name of *func* if it is a function, class or instance object, else the
name of *func*\s type.
.. c:function:: const char* PyEval_GetFuncDesc(PyObject *func)
Return a description string, depending on the type of *func*.
Return values include "()" for functions and methods, " constructor",
" instance", and " object". Concatenated with the result of
:c:func:`PyEval_GetFuncName`, the result will be a description of
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.. highlightlang:: c
.. _sequence:
Sequence Protocol
=================
.. c:function:: int PySequence_Check(PyObject *o)
Return ``1`` if the object provides sequence protocol, and ``0`` otherwise.
Note that it returns ``1`` for Python classes with a :meth:`__getitem__`
method unless they are :class:`dict` subclasses since in general case it
is impossible to determine what the type of keys it supports. This
function always succeeds.
.. c:function:: Py_ssize_t PySequence_Size(PyObject *o)
Py_ssize_t PySequence_Length(PyObject *o)
.. index:: builtin: len
Returns the number of objects in sequence *o* on success, and ``-1`` on
failure. This is equivalent to the Python expression ``len(o)``.
.. c:function:: PyObject* PySequence_Concat(PyObject *o1, PyObject *o2)
Return the concatenation of *o1* and *o2* on success, and *NULL* on failure.
This is the equivalent of the Python expression ``o1 + o2``.
.. c:function:: PyObject* PySequence_Repeat(PyObject *o, Py_ssize_t count)
Return the result of repeating sequence object *o* *count* times, or *NULL* on
failure. This is the equivalent of the Python expression ``o * count``.
.. c:function:: PyObject* PySequence_InPlaceConcat(PyObject *o1, PyObject *o2)
Return the concatenation of *o1* and *o2* on success, and *NULL* on failure.
The operation is done *in-place* when *o1* supports it. This is the equivalent
of the Python expression ``o1 += o2``.
.. c:function:: PyObject* PySequence_InPlaceRepeat(PyObject *o, Py_ssize_t count)
Return the result of repeating sequence object *o* *count* times, or *NULL* on
failure. The operation is done *in-place* when *o* supports it. This is the
equivalent of the Python expression ``o *= count``.
.. c:function:: PyObject* PySequence_GetItem(PyObject *o, Py_ssize_t i)
Return the *i*\ th element of *o*, or *NULL* on failure. This is the equivalent of
the Python expression ``o[i]``.
.. c:function:: PyObject* PySequence_GetSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2)
Return the slice of sequence object *o* between *i1* and *i2*, or *NULL* on
failure. This is the equivalent of the Python expression ``o[i1:i2]``.
.. c:function:: int PySequence_SetItem(PyObject *o, Py_ssize_t i, PyObject *v)
Assign object *v* to the *i*\ th element of *o*. Raise an exception
and return ``-1`` on failure; return ``0`` on success. This
is the equivalent of the Python statement ``o[i] = v``. This function *does
not* steal a reference to *v*.
If *v* is *NULL*, the element is deleted, however this feature is
deprecated in favour of using :c:func:`PySequence_DelItem`.
.. c:function:: int PySequence_DelItem(PyObject *o, Py_ssize_t i)
Delete the *i*\ th element of object *o*. Returns ``-1`` on failure. This is the
equivalent of the Python statement ``del o[i]``.
.. c:function:: int PySequence_SetSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2, PyObject *v)
Assign the sequence object *v* to the slice in sequence object *o* from *i1* to
*i2*. This is the equivalent of the Python statement ``o[i1:i2] = v``.
.. c:function:: int PySequence_DelSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2)
Delete the slice in sequence object *o* from *i1* to *i2*. Returns ``-1`` on
failure. This is the equivalent of the Python statement ``del o[i1:i2]``.
.. c:function:: Py_ssize_t PySequence_Count(PyObject *o, PyObject *value)
Return the number of occurrences of *value* in *o*, that is, return the number
of keys for which ``o[key] == value``. On failure, return ``-1``. This is
equivalent to the Python expression ``o.count(value)``.
.. c:function:: int PySequence_Contains(PyObject *o, PyObject *value)
Determine if *o* contains *value*. If an item in *o* is equal to *value*,
return ``1``, otherwise return ``0``. On error, return ``-1``. This is
equivalent to the Python expression ``value in o``.
.. c:function:: Py_ssize_t PySequence_Index(PyObject *o, PyObject *value)
Return the first index *i* for which ``o[i] == value``. On error, return
``-1``. This is equivalent to the Python expression ``o.index(value)``.
.. c:function:: PyObject* PySequence_List(PyObject *o)
Return a list object with the same contents as the sequence or iterable *o*,
or *NULL* on failure. The returned list is guaranteed to be new. This is
equivalent to the Python expression ``list(o)``.
.. c:function:: PyObject* PySequence_Tuple(PyObject *o)
.. index:: builtin: tuple
Return a tuple object with the same contents as the sequence or iterable *o*,
or *NULL* on failure. If *o* is a tuple, a new reference will be returned,
otherwise a tuple will be constructed with the appropriate contents. This is
equivalent to the Python expression ``tuple(o)``.
.. c:function:: PyObject* PySequence_Fast(PyObject *o, const char *m)
Return the sequence or iterable *o* as a list, unless it is already a tuple or list, in
which case *o* is returned. Use :c:func:`PySequence_Fast_GET_ITEM` to access
the members of the result. Returns *NULL* on failure. If the object is not
a sequence or iterable, raises :exc:`TypeError` with *m* as the message text.
.. c:function:: Py_ssize_t PySequence_Fast_GET_SIZE(PyObject *o)
Returns the length of *o*, assuming that *o* was returned by
:c:func:`PySequence_Fast` and that *o* is not *NULL*. The size can also be
gotten by calling :c:func:`PySequence_Size` on *o*, but
:c:func:`PySequence_Fast_GET_SIZE` is faster because it can assume *o* is a list
or tuple.
.. c:function:: PyObject* PySequence_Fast_GET_ITEM(PyObject *o, Py_ssize_t i)
Return the *i*\ th element of *o*, assuming that *o* was returned by
:c:func:`PySequence_Fast`, *o* is not *NULL*, and that *i* is within bounds.
.. c:function:: PyObject** PySequence_Fast_ITEMS(PyObject *o)
Return the underlying array of PyObject pointers. Assumes that *o* was returned
by :c:func:`PySequence_Fast` and *o* is not *NULL*.
Note, if a list gets resized, the reallocation may relocate the items array.
So, only use the underlying array pointer in contexts where the sequence
cannot change.
.. c:function:: PyObject* PySequence_ITEM(PyObject *o, Py_ssize_t i)
Return the *i*\ th element of *o* or *NULL* on failure. Macro form of
:c:func:`PySequence_GetItem` but without checking that
:c:func:`PySequence_Check` on *o* is true and without adjustment for negative
indices.

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.. highlightlang:: c
.. _setobjects:
Set Objects
-----------
.. sectionauthor:: Raymond D. Hettinger <python@rcn.com>
.. index::
object: set
object: frozenset
This section details the public API for :class:`set` and :class:`frozenset`
objects. Any functionality not listed below is best accessed using the either
the abstract object protocol (including :c:func:`PyObject_CallMethod`,
:c:func:`PyObject_RichCompareBool`, :c:func:`PyObject_Hash`,
:c:func:`PyObject_Repr`, :c:func:`PyObject_IsTrue`, :c:func:`PyObject_Print`, and
:c:func:`PyObject_GetIter`) or the abstract number protocol (including
:c:func:`PyNumber_And`, :c:func:`PyNumber_Subtract`, :c:func:`PyNumber_Or`,
:c:func:`PyNumber_Xor`, :c:func:`PyNumber_InPlaceAnd`,
:c:func:`PyNumber_InPlaceSubtract`, :c:func:`PyNumber_InPlaceOr`, and
:c:func:`PyNumber_InPlaceXor`).
.. c:type:: PySetObject
This subtype of :c:type:`PyObject` is used to hold the internal data for both
:class:`set` and :class:`frozenset` objects. It is like a :c:type:`PyDictObject`
in that it is a fixed size for small sets (much like tuple storage) and will
point to a separate, variable sized block of memory for medium and large sized
sets (much like list storage). None of the fields of this structure should be
considered public and are subject to change. All access should be done through
the documented API rather than by manipulating the values in the structure.
.. c:var:: PyTypeObject PySet_Type
This is an instance of :c:type:`PyTypeObject` representing the Python
:class:`set` type.
.. c:var:: PyTypeObject PyFrozenSet_Type
This is an instance of :c:type:`PyTypeObject` representing the Python
:class:`frozenset` type.
The following type check macros work on pointers to any Python object. Likewise,
the constructor functions work with any iterable Python object.
.. c:function:: int PySet_Check(PyObject *p)
Return true if *p* is a :class:`set` object or an instance of a subtype.
.. c:function:: int PyFrozenSet_Check(PyObject *p)
Return true if *p* is a :class:`frozenset` object or an instance of a
subtype.
.. c:function:: int PyAnySet_Check(PyObject *p)
Return true if *p* is a :class:`set` object, a :class:`frozenset` object, or an
instance of a subtype.
.. c:function:: int PyAnySet_CheckExact(PyObject *p)
Return true if *p* is a :class:`set` object or a :class:`frozenset` object but
not an instance of a subtype.
.. c:function:: int PyFrozenSet_CheckExact(PyObject *p)
Return true if *p* is a :class:`frozenset` object but not an instance of a
subtype.
.. c:function:: PyObject* PySet_New(PyObject *iterable)
Return a new :class:`set` containing objects returned by the *iterable*. The
*iterable* may be *NULL* to create a new empty set. Return the new set on
success or *NULL* on failure. Raise :exc:`TypeError` if *iterable* is not
actually iterable. The constructor is also useful for copying a set
(``c=set(s)``).
.. c:function:: PyObject* PyFrozenSet_New(PyObject *iterable)
Return a new :class:`frozenset` containing objects returned by the *iterable*.
The *iterable* may be *NULL* to create a new empty frozenset. Return the new
set on success or *NULL* on failure. Raise :exc:`TypeError` if *iterable* is
not actually iterable.
The following functions and macros are available for instances of :class:`set`
or :class:`frozenset` or instances of their subtypes.
.. c:function:: Py_ssize_t PySet_Size(PyObject *anyset)
.. index:: builtin: len
Return the length of a :class:`set` or :class:`frozenset` object. Equivalent to
``len(anyset)``. Raises a :exc:`PyExc_SystemError` if *anyset* is not a
:class:`set`, :class:`frozenset`, or an instance of a subtype.
.. c:function:: Py_ssize_t PySet_GET_SIZE(PyObject *anyset)
Macro form of :c:func:`PySet_Size` without error checking.
.. c:function:: int PySet_Contains(PyObject *anyset, PyObject *key)
Return ``1`` if found, ``0`` if not found, and ``-1`` if an error is encountered. Unlike
the Python :meth:`__contains__` method, this function does not automatically
convert unhashable sets into temporary frozensets. Raise a :exc:`TypeError` if
the *key* is unhashable. Raise :exc:`PyExc_SystemError` if *anyset* is not a
:class:`set`, :class:`frozenset`, or an instance of a subtype.
.. c:function:: int PySet_Add(PyObject *set, PyObject *key)
Add *key* to a :class:`set` instance. Also works with :class:`frozenset`
instances (like :c:func:`PyTuple_SetItem` it can be used to fill-in the values
of brand new frozensets before they are exposed to other code). Return ``0`` on
success or ``-1`` on failure. Raise a :exc:`TypeError` if the *key* is
unhashable. Raise a :exc:`MemoryError` if there is no room to grow. Raise a
:exc:`SystemError` if *set* is not an instance of :class:`set` or its
subtype.
The following functions are available for instances of :class:`set` or its
subtypes but not for instances of :class:`frozenset` or its subtypes.
.. c:function:: int PySet_Discard(PyObject *set, PyObject *key)
Return ``1`` if found and removed, ``0`` if not found (no action taken), and ``-1`` if an
error is encountered. Does not raise :exc:`KeyError` for missing keys. Raise a
:exc:`TypeError` if the *key* is unhashable. Unlike the Python :meth:`~set.discard`
method, this function does not automatically convert unhashable sets into
temporary frozensets. Raise :exc:`PyExc_SystemError` if *set* is not an
instance of :class:`set` or its subtype.
.. c:function:: PyObject* PySet_Pop(PyObject *set)
Return a new reference to an arbitrary object in the *set*, and removes the
object from the *set*. Return *NULL* on failure. Raise :exc:`KeyError` if the
set is empty. Raise a :exc:`SystemError` if *set* is not an instance of
:class:`set` or its subtype.
.. c:function:: int PySet_Clear(PyObject *set)
Empty an existing set of all elements.
.. c:function:: int PySet_ClearFreeList()
Clear the free list. Return the total number of freed items.
.. versionadded:: 3.3

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.. highlightlang:: c
.. _slice-objects:
Slice Objects
-------------
.. c:var:: PyTypeObject PySlice_Type
The type object for slice objects. This is the same as :class:`slice` in the
Python layer.
.. c:function:: int PySlice_Check(PyObject *ob)
Return true if *ob* is a slice object; *ob* must not be *NULL*.
.. c:function:: PyObject* PySlice_New(PyObject *start, PyObject *stop, PyObject *step)
Return a new slice object with the given values. The *start*, *stop*, and
*step* parameters are used as the values of the slice object attributes of
the same names. Any of the values may be *NULL*, in which case the
``None`` will be used for the corresponding attribute. Return *NULL* if
the new object could not be allocated.
.. c:function:: int PySlice_GetIndices(PyObject *slice, Py_ssize_t length, Py_ssize_t *start, Py_ssize_t *stop, Py_ssize_t *step)
Retrieve the start, stop and step indices from the slice object *slice*,
assuming a sequence of length *length*. Treats indices greater than
*length* as errors.
Returns ``0`` on success and ``-1`` on error with no exception set (unless one of
the indices was not :const:`None` and failed to be converted to an integer,
in which case ``-1`` is returned with an exception set).
You probably do not want to use this function.
.. versionchanged:: 3.2
The parameter type for the *slice* parameter was ``PySliceObject*``
before.
.. c:function:: int PySlice_GetIndicesEx(PyObject *slice, Py_ssize_t length, Py_ssize_t *start, Py_ssize_t *stop, Py_ssize_t *step, Py_ssize_t *slicelength)
Usable replacement for :c:func:`PySlice_GetIndices`. Retrieve the start,
stop, and step indices from the slice object *slice* assuming a sequence of
length *length*, and store the length of the slice in *slicelength*. Out
of bounds indices are clipped in a manner consistent with the handling of
normal slices.
Returns ``0`` on success and ``-1`` on error with exception set.
.. versionchanged:: 3.2
The parameter type for the *slice* parameter was ``PySliceObject*``
before.
Ellipsis Object
---------------
.. c:var:: PyObject *Py_Ellipsis
The Python ``Ellipsis`` object. This object has no methods. It needs to be
treated just like any other object with respect to reference counts. Like
:c:data:`Py_None` it is a singleton object.

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.. highlightlang:: c
.. _stable:
***********************************
Stable Application Binary Interface
***********************************
Traditionally, the C API of Python will change with every release. Most changes
will be source-compatible, typically by only adding API, rather than changing
existing API or removing API (although some interfaces do get removed after
being deprecated first).
Unfortunately, the API compatibility does not extend to binary compatibility
(the ABI). The reason is primarily the evolution of struct definitions, where
addition of a new field, or changing the type of a field, might not break the
API, but can break the ABI. As a consequence, extension modules need to be
recompiled for every Python release (although an exception is possible on Unix
when none of the affected interfaces are used). In addition, on Windows,
extension modules link with a specific pythonXY.dll and need to be recompiled to
link with a newer one.
Since Python 3.2, a subset of the API has been declared to guarantee a stable
ABI. Extension modules wishing to use this API (called "limited API") need to
define ``Py_LIMITED_API``. A number of interpreter details then become hidden
from the extension module; in return, a module is built that works on any 3.x
version (x>=2) without recompilation.
In some cases, the stable ABI needs to be extended with new functions.
Extension modules wishing to use these new APIs need to set ``Py_LIMITED_API``
to the ``PY_VERSION_HEX`` value (see :ref:`apiabiversion`) of the minimum Python
version they want to support (e.g. ``0x03030000`` for Python 3.3). Such modules
will work on all subsequent Python releases, but fail to load (because of
missing symbols) on the older releases.
As of Python 3.2, the set of functions available to the limited API is
documented in :pep:`384`. In the C API documentation, API elements that are not
part of the limited API are marked as "Not part of the limited API."

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.. highlightlang:: c
.. _common-structs:
Common Object Structures
========================
There are a large number of structures which are used in the definition of
object types for Python. This section describes these structures and how they
are used.
All Python objects ultimately share a small number of fields at the beginning
of the object's representation in memory. These are represented by the
:c:type:`PyObject` and :c:type:`PyVarObject` types, which are defined, in turn,
by the expansions of some macros also used, whether directly or indirectly, in
the definition of all other Python objects.
.. c:type:: PyObject
All object types are extensions of this type. This is a type which
contains the information Python needs to treat a pointer to an object as an
object. In a normal "release" build, it contains only the object's
reference count and a pointer to the corresponding type object.
Nothing is actually declared to be a :c:type:`PyObject`, but every pointer
to a Python object can be cast to a :c:type:`PyObject*`. Access to the
members must be done by using the macros :c:macro:`Py_REFCNT` and
:c:macro:`Py_TYPE`.
.. c:type:: PyVarObject
This is an extension of :c:type:`PyObject` that adds the :attr:`ob_size`
field. This is only used for objects that have some notion of *length*.
This type does not often appear in the Python/C API.
Access to the members must be done by using the macros
:c:macro:`Py_REFCNT`, :c:macro:`Py_TYPE`, and :c:macro:`Py_SIZE`.
.. c:macro:: PyObject_HEAD
This is a macro used when declaring new types which represent objects
without a varying length. The PyObject_HEAD macro expands to::
PyObject ob_base;
See documentation of :c:type:`PyObject` above.
.. c:macro:: PyObject_VAR_HEAD
This is a macro used when declaring new types which represent objects
with a length that varies from instance to instance.
The PyObject_VAR_HEAD macro expands to::
PyVarObject ob_base;
See documentation of :c:type:`PyVarObject` above.
.. c:macro:: Py_TYPE(o)
This macro is used to access the :attr:`ob_type` member of a Python object.
It expands to::
(((PyObject*)(o))->ob_type)
.. c:macro:: Py_REFCNT(o)
This macro is used to access the :attr:`ob_refcnt` member of a Python
object.
It expands to::
(((PyObject*)(o))->ob_refcnt)
.. c:macro:: Py_SIZE(o)
This macro is used to access the :attr:`ob_size` member of a Python object.
It expands to::
(((PyVarObject*)(o))->ob_size)
.. c:macro:: PyObject_HEAD_INIT(type)
This is a macro which expands to initialization values for a new
:c:type:`PyObject` type. This macro expands to::
_PyObject_EXTRA_INIT
1, type,
.. c:macro:: PyVarObject_HEAD_INIT(type, size)
This is a macro which expands to initialization values for a new
:c:type:`PyVarObject` type, including the :attr:`ob_size` field.
This macro expands to::
_PyObject_EXTRA_INIT
1, type, size,
.. c:type:: PyCFunction
Type of the functions used to implement most Python callables in C.
Functions of this type take two :c:type:`PyObject\*` parameters and return
one such value. If the return value is *NULL*, an exception shall have
been set. If not *NULL*, the return value is interpreted as the return
value of the function as exposed in Python. The function must return a new
reference.
.. c:type:: PyCFunctionWithKeywords
Type of the functions used to implement Python callables in C that take
keyword arguments: they take three :c:type:`PyObject\*` parameters and return
one such value. See :c:type:`PyCFunction` above for the meaning of the return
value.
.. c:type:: PyMethodDef
Structure used to describe a method of an extension type. This structure has
four fields:
+------------------+-------------+-------------------------------+
| Field | C Type | Meaning |
+==================+=============+===============================+
| :attr:`ml_name` | char \* | name of the method |
+------------------+-------------+-------------------------------+
| :attr:`ml_meth` | PyCFunction | pointer to the C |
| | | implementation |
+------------------+-------------+-------------------------------+
| :attr:`ml_flags` | int | flag bits indicating how the |
| | | call should be constructed |
+------------------+-------------+-------------------------------+
| :attr:`ml_doc` | char \* | points to the contents of the |
| | | docstring |
+------------------+-------------+-------------------------------+
The :attr:`ml_meth` is a C function pointer. The functions may be of different
types, but they always return :c:type:`PyObject\*`. If the function is not of
the :c:type:`PyCFunction`, the compiler will require a cast in the method table.
Even though :c:type:`PyCFunction` defines the first parameter as
:c:type:`PyObject\*`, it is common that the method implementation uses the
specific C type of the *self* object.
The :attr:`ml_flags` field is a bitfield which can include the following flags.
The individual flags indicate either a calling convention or a binding
convention. Of the calling convention flags, only :const:`METH_VARARGS` and
:const:`METH_KEYWORDS` can be combined. Any of the calling convention flags
can be combined with a binding flag.
.. data:: METH_VARARGS
This is the typical calling convention, where the methods have the type
:c:type:`PyCFunction`. The function expects two :c:type:`PyObject\*` values.
The first one is the *self* object for methods; for module functions, it is
the module object. The second parameter (often called *args*) is a tuple
object representing all arguments. This parameter is typically processed
using :c:func:`PyArg_ParseTuple` or :c:func:`PyArg_UnpackTuple`.
.. data:: METH_KEYWORDS
Methods with these flags must be of type :c:type:`PyCFunctionWithKeywords`.
The function expects three parameters: *self*, *args*, and a dictionary of
all the keyword arguments. The flag must be combined with
:const:`METH_VARARGS`, and the parameters are typically processed using
:c:func:`PyArg_ParseTupleAndKeywords`.
.. data:: METH_NOARGS
Methods without parameters don't need to check whether arguments are given if
they are listed with the :const:`METH_NOARGS` flag. They need to be of type
:c:type:`PyCFunction`. The first parameter is typically named *self* and will
hold a reference to the module or object instance. In all cases the second
parameter will be *NULL*.
.. data:: METH_O
Methods with a single object argument can be listed with the :const:`METH_O`
flag, instead of invoking :c:func:`PyArg_ParseTuple` with a ``"O"`` argument.
They have the type :c:type:`PyCFunction`, with the *self* parameter, and a
:c:type:`PyObject\*` parameter representing the single argument.
These two constants are not used to indicate the calling convention but the
binding when use with methods of classes. These may not be used for functions
defined for modules. At most one of these flags may be set for any given
method.
.. data:: METH_CLASS
.. index:: builtin: classmethod
The method will be passed the type object as the first parameter rather
than an instance of the type. This is used to create *class methods*,
similar to what is created when using the :func:`classmethod` built-in
function.
.. data:: METH_STATIC
.. index:: builtin: staticmethod
The method will be passed *NULL* as the first parameter rather than an
instance of the type. This is used to create *static methods*, similar to
what is created when using the :func:`staticmethod` built-in function.
One other constant controls whether a method is loaded in place of another
definition with the same method name.
.. data:: METH_COEXIST
The method will be loaded in place of existing definitions. Without
*METH_COEXIST*, the default is to skip repeated definitions. Since slot
wrappers are loaded before the method table, the existence of a
*sq_contains* slot, for example, would generate a wrapped method named
:meth:`__contains__` and preclude the loading of a corresponding
PyCFunction with the same name. With the flag defined, the PyCFunction
will be loaded in place of the wrapper object and will co-exist with the
slot. This is helpful because calls to PyCFunctions are optimized more
than wrapper object calls.
.. c:type:: PyMemberDef
Structure which describes an attribute of a type which corresponds to a C
struct member. Its fields are:
+------------------+-------------+-------------------------------+
| Field | C Type | Meaning |
+==================+=============+===============================+
| :attr:`name` | char \* | name of the member |
+------------------+-------------+-------------------------------+
| :attr:`!type` | int | the type of the member in the |
| | | C struct |
+------------------+-------------+-------------------------------+
| :attr:`offset` | Py_ssize_t | the offset in bytes that the |
| | | member is located on the |
| | | type's object struct |
+------------------+-------------+-------------------------------+
| :attr:`flags` | int | flag bits indicating if the |
| | | field should be read-only or |
| | | writable |
+------------------+-------------+-------------------------------+
| :attr:`doc` | char \* | points to the contents of the |
| | | docstring |
+------------------+-------------+-------------------------------+
:attr:`!type` can be one of many ``T_`` macros corresponding to various C
types. When the member is accessed in Python, it will be converted to the
equivalent Python type.
=============== ==================
Macro name C type
=============== ==================
T_SHORT short
T_INT int
T_LONG long
T_FLOAT float
T_DOUBLE double
T_STRING char \*
T_OBJECT PyObject \*
T_OBJECT_EX PyObject \*
T_CHAR char
T_BYTE char
T_UBYTE unsigned char
T_UINT unsigned int
T_USHORT unsigned short
T_ULONG unsigned long
T_BOOL char
T_LONGLONG long long
T_ULONGLONG unsigned long long
T_PYSSIZET Py_ssize_t
=============== ==================
:c:macro:`T_OBJECT` and :c:macro:`T_OBJECT_EX` differ in that
:c:macro:`T_OBJECT` returns ``None`` if the member is *NULL* and
:c:macro:`T_OBJECT_EX` raises an :exc:`AttributeError`. Try to use
:c:macro:`T_OBJECT_EX` over :c:macro:`T_OBJECT` because :c:macro:`T_OBJECT_EX`
handles use of the :keyword:`del` statement on that attribute more correctly
than :c:macro:`T_OBJECT`.
:attr:`flags` can be ``0`` for write and read access or :c:macro:`READONLY` for
read-only access. Using :c:macro:`T_STRING` for :attr:`type` implies
:c:macro:`READONLY`. :c:macro:`T_STRING` data is interpreted as UTF-8.
Only :c:macro:`T_OBJECT` and :c:macro:`T_OBJECT_EX`
members can be deleted. (They are set to *NULL*).
.. c:type:: PyGetSetDef
Structure to define property-like access for a type. See also description of
the :c:member:`PyTypeObject.tp_getset` slot.
+-------------+------------------+-----------------------------------+
| Field | C Type | Meaning |
+=============+==================+===================================+
| name | char \* | attribute name |
+-------------+------------------+-----------------------------------+
| get | getter | C Function to get the attribute |
+-------------+------------------+-----------------------------------+
| set | setter | optional C function to set or |
| | | delete the attribute, if omitted |
| | | the attribute is readonly |
+-------------+------------------+-----------------------------------+
| doc | char \* | optional docstring |
+-------------+------------------+-----------------------------------+
| closure | void \* | optional function pointer, |
| | | providing additional data for |
| | | getter and setter |
+-------------+------------------+-----------------------------------+
The ``get`` function takes one :c:type:`PyObject\*` parameter (the
instance) and a function pointer (the associated ``closure``)::
typedef PyObject *(*getter)(PyObject *, void *);
It should return a new reference on success or *NULL* with a set exception
on failure.
``set`` functions take two :c:type:`PyObject\*` parameters (the instance and
the value to be set) and a function pointer (the associated ``closure``)::
typedef int (*setter)(PyObject *, PyObject *, void *);
In case the attribute should be deleted the second parameter is *NULL*.
Should return ``0`` on success or ``-1`` with a set exception on failure.

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.. highlightlang:: c
.. _os:
Operating System Utilities
==========================
.. c:function:: PyObject* PyOS_FSPath(PyObject *path)
Return the file system representation for *path*. If the object is a
:class:`str` or :class:`bytes` object, then its reference count is
incremented. If the object implements the :class:`os.PathLike` interface,
then :meth:`~os.PathLike.__fspath__` is returned as long as it is a
:class:`str` or :class:`bytes` object. Otherwise :exc:`TypeError` is raised
and ``NULL`` is returned.
.. versionadded:: 3.6
.. c:function:: int Py_FdIsInteractive(FILE *fp, const char *filename)
Return true (nonzero) if the standard I/O file *fp* with name *filename* is
deemed interactive. This is the case for files for which ``isatty(fileno(fp))``
is true. If the global flag :c:data:`Py_InteractiveFlag` is true, this function
also returns true if the *filename* pointer is *NULL* or if the name is equal to
one of the strings ``'<stdin>'`` or ``'???'``.
.. c:function:: void PyOS_AfterFork()
Function to update some internal state after a process fork; this should be
called in the new process if the Python interpreter will continue to be used.
If a new executable is loaded into the new process, this function does not need
to be called.
.. c:function:: int PyOS_CheckStack()
Return true when the interpreter runs out of stack space. This is a reliable
check, but is only available when :const:`USE_STACKCHECK` is defined (currently
on Windows using the Microsoft Visual C++ compiler). :const:`USE_STACKCHECK`
will be defined automatically; you should never change the definition in your
own code.
.. c:function:: PyOS_sighandler_t PyOS_getsig(int i)
Return the current signal handler for signal *i*. This is a thin wrapper around
either :c:func:`sigaction` or :c:func:`signal`. Do not call those functions
directly! :c:type:`PyOS_sighandler_t` is a typedef alias for :c:type:`void
(\*)(int)`.
.. c:function:: PyOS_sighandler_t PyOS_setsig(int i, PyOS_sighandler_t h)
Set the signal handler for signal *i* to be *h*; return the old signal handler.
This is a thin wrapper around either :c:func:`sigaction` or :c:func:`signal`. Do
not call those functions directly! :c:type:`PyOS_sighandler_t` is a typedef
alias for :c:type:`void (\*)(int)`.
.. c:function:: wchar_t* Py_DecodeLocale(const char* arg, size_t *size)
Decode a byte string from the locale encoding with the :ref:`surrogateescape
error handler <surrogateescape>`: undecodable bytes are decoded as
characters in range U+DC80..U+DCFF. If a byte sequence can be decoded as a
surrogate character, escape the bytes using the surrogateescape error
handler instead of decoding them.
Encoding, highest priority to lowest priority:
* ``UTF-8`` on macOS and Android;
* ``ASCII`` if the ``LC_CTYPE`` locale is ``"C"``,
``nl_langinfo(CODESET)`` returns the ``ASCII`` encoding (or an alias),
and :c:func:`mbstowcs` and :c:func:`wcstombs` functions use the
``ISO-8859-1`` encoding.
* the current locale encoding (``LC_CTYPE`` locale).
Return a pointer to a newly allocated wide character string, use
:c:func:`PyMem_RawFree` to free the memory. If size is not ``NULL``, write
the number of wide characters excluding the null character into ``*size``.
Return ``NULL`` on decoding error or memory allocation error. If *size* is
not ``NULL``, ``*size`` is set to ``(size_t)-1`` on memory error or set to
``(size_t)-2`` on decoding error.
Decoding errors should never happen, unless there is a bug in the C
library.
Use the :c:func:`Py_EncodeLocale` function to encode the character string
back to a byte string.
.. seealso::
The :c:func:`PyUnicode_DecodeFSDefaultAndSize` and
:c:func:`PyUnicode_DecodeLocaleAndSize` functions.
.. versionadded:: 3.5
.. c:function:: char* Py_EncodeLocale(const wchar_t *text, size_t *error_pos)
Encode a wide character string to the locale encoding with the
:ref:`surrogateescape error handler <surrogateescape>`: surrogate characters
in the range U+DC80..U+DCFF are converted to bytes 0x80..0xFF.
Encoding, highest priority to lowest priority:
* ``UTF-8`` on macOS and Android;
* ``ASCII`` if the ``LC_CTYPE`` locale is ``"C"``,
``nl_langinfo(CODESET)`` returns the ``ASCII`` encoding (or an alias),
and :c:func:`mbstowcs` and :c:func:`wcstombs` functions uses the
``ISO-8859-1`` encoding.
* the current locale encoding.
Return a pointer to a newly allocated byte string, use :c:func:`PyMem_Free`
to free the memory. Return ``NULL`` on encoding error or memory allocation
error
If error_pos is not ``NULL``, ``*error_pos`` is set to the index of the
invalid character on encoding error, or set to ``(size_t)-1`` otherwise.
Use the :c:func:`Py_DecodeLocale` function to decode the bytes string back
to a wide character string.
.. seealso::
The :c:func:`PyUnicode_EncodeFSDefault` and
:c:func:`PyUnicode_EncodeLocale` functions.
.. versionadded:: 3.5
.. _systemfunctions:
System Functions
================
These are utility functions that make functionality from the :mod:`sys` module
accessible to C code. They all work with the current interpreter thread's
:mod:`sys` module's dict, which is contained in the internal thread state structure.
.. c:function:: PyObject *PySys_GetObject(const char *name)
Return the object *name* from the :mod:`sys` module or *NULL* if it does
not exist, without setting an exception.
.. c:function:: int PySys_SetObject(const char *name, PyObject *v)
Set *name* in the :mod:`sys` module to *v* unless *v* is *NULL*, in which
case *name* is deleted from the sys module. Returns ``0`` on success, ``-1``
on error.
.. c:function:: void PySys_ResetWarnOptions()
Reset :data:`sys.warnoptions` to an empty list.
.. c:function:: void PySys_AddWarnOption(wchar_t *s)
Append *s* to :data:`sys.warnoptions`.
.. c:function:: void PySys_AddWarnOptionUnicode(PyObject *unicode)
Append *unicode* to :data:`sys.warnoptions`.
.. c:function:: void PySys_SetPath(wchar_t *path)
Set :data:`sys.path` to a list object of paths found in *path* which should
be a list of paths separated with the platform's search path delimiter
(``:`` on Unix, ``;`` on Windows).
.. c:function:: void PySys_WriteStdout(const char *format, ...)
Write the output string described by *format* to :data:`sys.stdout`. No
exceptions are raised, even if truncation occurs (see below).
*format* should limit the total size of the formatted output string to
1000 bytes or less -- after 1000 bytes, the output string is truncated.
In particular, this means that no unrestricted "%s" formats should occur;
these should be limited using "%.<N>s" where <N> is a decimal number
calculated so that <N> plus the maximum size of other formatted text does not
exceed 1000 bytes. Also watch out for "%f", which can print hundreds of
digits for very large numbers.
If a problem occurs, or :data:`sys.stdout` is unset, the formatted message
is written to the real (C level) *stdout*.
.. c:function:: void PySys_WriteStderr(const char *format, ...)
As :c:func:`PySys_WriteStdout`, but write to :data:`sys.stderr` or *stderr*
instead.
.. c:function:: void PySys_FormatStdout(const char *format, ...)
Function similar to PySys_WriteStdout() but format the message using
:c:func:`PyUnicode_FromFormatV` and don't truncate the message to an
arbitrary length.
.. versionadded:: 3.2
.. c:function:: void PySys_FormatStderr(const char *format, ...)
As :c:func:`PySys_FormatStdout`, but write to :data:`sys.stderr` or *stderr*
instead.
.. versionadded:: 3.2
.. c:function:: void PySys_AddXOption(const wchar_t *s)
Parse *s* as a set of :option:`-X` options and add them to the current
options mapping as returned by :c:func:`PySys_GetXOptions`.
.. versionadded:: 3.2
.. c:function:: PyObject *PySys_GetXOptions()
Return the current dictionary of :option:`-X` options, similarly to
:data:`sys._xoptions`. On error, *NULL* is returned and an exception is
set.
.. versionadded:: 3.2
.. _processcontrol:
Process Control
===============
.. c:function:: void Py_FatalError(const char *message)
.. index:: single: abort()
Print a fatal error message and kill the process. No cleanup is performed.
This function should only be invoked when a condition is detected that would
make it dangerous to continue using the Python interpreter; e.g., when the
object administration appears to be corrupted. On Unix, the standard C library
function :c:func:`abort` is called which will attempt to produce a :file:`core`
file.
.. c:function:: void Py_Exit(int status)
.. index::
single: Py_FinalizeEx()
single: exit()
Exit the current process. This calls :c:func:`Py_FinalizeEx` and then calls the
standard C library function ``exit(status)``. If :c:func:`Py_FinalizeEx`
indicates an error, the exit status is set to 120.
.. versionchanged:: 3.6
Errors from finalization no longer ignored.
.. c:function:: int Py_AtExit(void (*func) ())
.. index::
single: Py_FinalizeEx()
single: cleanup functions
Register a cleanup function to be called by :c:func:`Py_FinalizeEx`. The cleanup
function will be called with no arguments and should return no value. At most
32 cleanup functions can be registered. When the registration is successful,
:c:func:`Py_AtExit` returns ``0``; on failure, it returns ``-1``. The cleanup
function registered last is called first. Each cleanup function will be called
at most once. Since Python's internal finalization will have completed before
the cleanup function, no Python APIs should be called by *func*.

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.. highlightlang:: c
.. _tupleobjects:
Tuple Objects
-------------
.. index:: object: tuple
.. c:type:: PyTupleObject
This subtype of :c:type:`PyObject` represents a Python tuple object.
.. c:var:: PyTypeObject PyTuple_Type
This instance of :c:type:`PyTypeObject` represents the Python tuple type; it
is the same object as :class:`tuple` in the Python layer.
.. c:function:: int PyTuple_Check(PyObject *p)
Return true if *p* is a tuple object or an instance of a subtype of the tuple
type.
.. c:function:: int PyTuple_CheckExact(PyObject *p)
Return true if *p* is a tuple object, but not an instance of a subtype of the
tuple type.
.. c:function:: PyObject* PyTuple_New(Py_ssize_t len)
Return a new tuple object of size *len*, or *NULL* on failure.
.. c:function:: PyObject* PyTuple_Pack(Py_ssize_t n, ...)
Return a new tuple object of size *n*, or *NULL* on failure. The tuple values
are initialized to the subsequent *n* C arguments pointing to Python objects.
``PyTuple_Pack(2, a, b)`` is equivalent to ``Py_BuildValue("(OO)", a, b)``.
.. c:function:: Py_ssize_t PyTuple_Size(PyObject *p)
Take a pointer to a tuple object, and return the size of that tuple.
.. c:function:: Py_ssize_t PyTuple_GET_SIZE(PyObject *p)
Return the size of the tuple *p*, which must be non-*NULL* and point to a tuple;
no error checking is performed.
.. c:function:: PyObject* PyTuple_GetItem(PyObject *p, Py_ssize_t pos)
Return the object at position *pos* in the tuple pointed to by *p*. If *pos* is
out of bounds, return *NULL* and sets an :exc:`IndexError` exception.
.. c:function:: PyObject* PyTuple_GET_ITEM(PyObject *p, Py_ssize_t pos)
Like :c:func:`PyTuple_GetItem`, but does no checking of its arguments.
.. c:function:: PyObject* PyTuple_GetSlice(PyObject *p, Py_ssize_t low, Py_ssize_t high)
Take a slice of the tuple pointed to by *p* from *low* to *high* and return it
as a new tuple.
.. c:function:: int PyTuple_SetItem(PyObject *p, Py_ssize_t pos, PyObject *o)
Insert a reference to object *o* at position *pos* of the tuple pointed to by
*p*. Return ``0`` on success.
.. note::
This function "steals" a reference to *o*.
.. c:function:: void PyTuple_SET_ITEM(PyObject *p, Py_ssize_t pos, PyObject *o)
Like :c:func:`PyTuple_SetItem`, but does no error checking, and should *only* be
used to fill in brand new tuples.
.. note::
This function "steals" a reference to *o*.
.. c:function:: int _PyTuple_Resize(PyObject **p, Py_ssize_t newsize)
Can be used to resize a tuple. *newsize* will be the new length of the tuple.
Because tuples are *supposed* to be immutable, this should only be used if there
is only one reference to the object. Do *not* use this if the tuple may already
be known to some other part of the code. The tuple will always grow or shrink
at the end. Think of this as destroying the old tuple and creating a new one,
only more efficiently. Returns ``0`` on success. Client code should never
assume that the resulting value of ``*p`` will be the same as before calling
this function. If the object referenced by ``*p`` is replaced, the original
``*p`` is destroyed. On failure, returns ``-1`` and sets ``*p`` to *NULL*, and
raises :exc:`MemoryError` or :exc:`SystemError`.
.. c:function:: int PyTuple_ClearFreeList()
Clear the free list. Return the total number of freed items.
Struct Sequence Objects
-----------------------
Struct sequence objects are the C equivalent of :func:`~collections.namedtuple`
objects, i.e. a sequence whose items can also be accessed through attributes.
To create a struct sequence, you first have to create a specific struct sequence
type.
.. c:function:: PyTypeObject* PyStructSequence_NewType(PyStructSequence_Desc *desc)
Create a new struct sequence type from the data in *desc*, described below. Instances
of the resulting type can be created with :c:func:`PyStructSequence_New`.
.. c:function:: void PyStructSequence_InitType(PyTypeObject *type, PyStructSequence_Desc *desc)
Initializes a struct sequence type *type* from *desc* in place.
.. c:function:: int PyStructSequence_InitType2(PyTypeObject *type, PyStructSequence_Desc *desc)
The same as ``PyStructSequence_InitType``, but returns ``0`` on success and ``-1`` on
failure.
.. versionadded:: 3.4
.. c:type:: PyStructSequence_Desc
Contains the meta information of a struct sequence type to create.
+-------------------+------------------------------+------------------------------------+
| Field | C Type | Meaning |
+===================+==============================+====================================+
| ``name`` | ``char *`` | name of the struct sequence type |
+-------------------+------------------------------+------------------------------------+
| ``doc`` | ``char *`` | pointer to docstring for the type |
| | | or NULL to omit |
+-------------------+------------------------------+------------------------------------+
| ``fields`` | ``PyStructSequence_Field *`` | pointer to *NULL*-terminated array |
| | | with field names of the new type |
+-------------------+------------------------------+------------------------------------+
| ``n_in_sequence`` | ``int`` | number of fields visible to the |
| | | Python side (if used as tuple) |
+-------------------+------------------------------+------------------------------------+
.. c:type:: PyStructSequence_Field
Describes a field of a struct sequence. As a struct sequence is modeled as a
tuple, all fields are typed as :c:type:`PyObject\*`. The index in the
:attr:`fields` array of the :c:type:`PyStructSequence_Desc` determines which
field of the struct sequence is described.
+-----------+---------------+--------------------------------------+
| Field | C Type | Meaning |
+===========+===============+======================================+
| ``name`` | ``char *`` | name for the field or *NULL* to end |
| | | the list of named fields, set to |
| | | PyStructSequence_UnnamedField to |
| | | leave unnamed |
+-----------+---------------+--------------------------------------+
| ``doc`` | ``char *`` | field docstring or *NULL* to omit |
+-----------+---------------+--------------------------------------+
.. c:var:: char* PyStructSequence_UnnamedField
Special value for a field name to leave it unnamed.
.. c:function:: PyObject* PyStructSequence_New(PyTypeObject *type)
Creates an instance of *type*, which must have been created with
:c:func:`PyStructSequence_NewType`.
.. c:function:: PyObject* PyStructSequence_GetItem(PyObject *p, Py_ssize_t pos)
Return the object at position *pos* in the struct sequence pointed to by *p*.
No bounds checking is performed.
.. c:function:: PyObject* PyStructSequence_GET_ITEM(PyObject *p, Py_ssize_t pos)
Macro equivalent of :c:func:`PyStructSequence_GetItem`.
.. c:function:: void PyStructSequence_SetItem(PyObject *p, Py_ssize_t pos, PyObject *o)
Sets the field at index *pos* of the struct sequence *p* to value *o*. Like
:c:func:`PyTuple_SET_ITEM`, this should only be used to fill in brand new
instances.
.. note::
This function "steals" a reference to *o*.
.. c:function:: void PyStructSequence_SET_ITEM(PyObject *p, Py_ssize_t *pos, PyObject *o)
Macro equivalent of :c:func:`PyStructSequence_SetItem`.
.. note::
This function "steals" a reference to *o*.

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.. highlightlang:: c
.. _typeobjects:
Type Objects
------------
.. index:: object: type
.. c:type:: PyTypeObject
The C structure of the objects used to describe built-in types.
.. c:var:: PyObject* PyType_Type
This is the type object for type objects; it is the same object as
:class:`type` in the Python layer.
.. c:function:: int PyType_Check(PyObject *o)
Return true if the object *o* is a type object, including instances of types
derived from the standard type object. Return false in all other cases.
.. c:function:: int PyType_CheckExact(PyObject *o)
Return true if the object *o* is a type object, but not a subtype of the
standard type object. Return false in all other cases.
.. c:function:: unsigned int PyType_ClearCache()
Clear the internal lookup cache. Return the current version tag.
.. c:function:: unsigned long PyType_GetFlags(PyTypeObject* type)
Return the :c:member:`~PyTypeObject.tp_flags` member of *type*. This function is primarily
meant for use with `Py_LIMITED_API`; the individual flag bits are
guaranteed to be stable across Python releases, but access to
:c:member:`~PyTypeObject.tp_flags` itself is not part of the limited API.
.. versionadded:: 3.2
.. versionchanged:: 3.4
The return type is now ``unsigned long`` rather than ``long``.
.. c:function:: void PyType_Modified(PyTypeObject *type)
Invalidate the internal lookup cache for the type and all of its
subtypes. This function must be called after any manual
modification of the attributes or base classes of the type.
.. c:function:: int PyType_HasFeature(PyTypeObject *o, int feature)
Return true if the type object *o* sets the feature *feature*. Type features
are denoted by single bit flags.
.. c:function:: int PyType_IS_GC(PyTypeObject *o)
Return true if the type object includes support for the cycle detector; this
tests the type flag :const:`Py_TPFLAGS_HAVE_GC`.
.. c:function:: int PyType_IsSubtype(PyTypeObject *a, PyTypeObject *b)
Return true if *a* is a subtype of *b*.
This function only checks for actual subtypes, which means that
:meth:`~class.__subclasscheck__` is not called on *b*. Call
:c:func:`PyObject_IsSubclass` to do the same check that :func:`issubclass`
would do.
.. c:function:: PyObject* PyType_GenericAlloc(PyTypeObject *type, Py_ssize_t nitems)
Generic handler for the :c:member:`~PyTypeObject.tp_alloc` slot of a type object. Use
Python's default memory allocation mechanism to allocate a new instance and
initialize all its contents to *NULL*.
.. c:function:: PyObject* PyType_GenericNew(PyTypeObject *type, PyObject *args, PyObject *kwds)
Generic handler for the :c:member:`~PyTypeObject.tp_new` slot of a type object. Create a
new instance using the type's :c:member:`~PyTypeObject.tp_alloc` slot.
.. c:function:: int PyType_Ready(PyTypeObject *type)
Finalize a type object. This should be called on all type objects to finish
their initialization. This function is responsible for adding inherited slots
from a type's base class. Return ``0`` on success, or return ``-1`` and sets an
exception on error.
.. c:function:: PyObject* PyType_FromSpec(PyType_Spec *spec)
Creates and returns a heap type object from the *spec* passed to the function.
.. c:function:: PyObject* PyType_FromSpecWithBases(PyType_Spec *spec, PyObject *bases)
Creates and returns a heap type object from the *spec*. In addition to that,
the created heap type contains all types contained by the *bases* tuple as base
types. This allows the caller to reference other heap types as base types.
.. versionadded:: 3.3
.. c:function:: void* PyType_GetSlot(PyTypeObject *type, int slot)
Return the function pointer stored in the given slot. If the
result is *NULL*, this indicates that either the slot is *NULL*,
or that the function was called with invalid parameters.
Callers will typically cast the result pointer into the appropriate
function type.
.. versionadded:: 3.4

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.. highlightlang:: c
.. _utilities:
*********
Utilities
*********
The functions in this chapter perform various utility tasks, ranging from
helping C code be more portable across platforms, using Python modules from C,
and parsing function arguments and constructing Python values from C values.
.. toctree::
sys.rst
import.rst
marshal.rst
arg.rst
conversion.rst
reflection.rst
codec.rst

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.. highlightlang:: c
.. _veryhigh:
*************************
The Very High Level Layer
*************************
The functions in this chapter will let you execute Python source code given in a
file or a buffer, but they will not let you interact in a more detailed way with
the interpreter.
Several of these functions accept a start symbol from the grammar as a
parameter. The available start symbols are :const:`Py_eval_input`,
:const:`Py_file_input`, and :const:`Py_single_input`. These are described
following the functions which accept them as parameters.
Note also that several of these functions take :c:type:`FILE\*` parameters. One
particular issue which needs to be handled carefully is that the :c:type:`FILE`
structure for different C libraries can be different and incompatible. Under
Windows (at least), it is possible for dynamically linked extensions to actually
use different libraries, so care should be taken that :c:type:`FILE\*` parameters
are only passed to these functions if it is certain that they were created by
the same library that the Python runtime is using.
.. c:function:: int Py_Main(int argc, wchar_t **argv)
The main program for the standard interpreter. This is made available for
programs which embed Python. The *argc* and *argv* parameters should be
prepared exactly as those which are passed to a C program's :c:func:`main`
function (converted to wchar_t according to the user's locale). It is
important to note that the argument list may be modified (but the contents of
the strings pointed to by the argument list are not). The return value will
be ``0`` if the interpreter exits normally (i.e., without an exception),
``1`` if the interpreter exits due to an exception, or ``2`` if the parameter
list does not represent a valid Python command line.
Note that if an otherwise unhandled :exc:`SystemExit` is raised, this
function will not return ``1``, but exit the process, as long as
``Py_InspectFlag`` is not set.
.. c:function:: int PyRun_AnyFile(FILE *fp, const char *filename)
This is a simplified interface to :c:func:`PyRun_AnyFileExFlags` below, leaving
*closeit* set to ``0`` and *flags* set to *NULL*.
.. c:function:: int PyRun_AnyFileFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
This is a simplified interface to :c:func:`PyRun_AnyFileExFlags` below, leaving
the *closeit* argument set to ``0``.
.. c:function:: int PyRun_AnyFileEx(FILE *fp, const char *filename, int closeit)
This is a simplified interface to :c:func:`PyRun_AnyFileExFlags` below, leaving
the *flags* argument set to *NULL*.
.. c:function:: int PyRun_AnyFileExFlags(FILE *fp, const char *filename, int closeit, PyCompilerFlags *flags)
If *fp* refers to a file associated with an interactive device (console or
terminal input or Unix pseudo-terminal), return the value of
:c:func:`PyRun_InteractiveLoop`, otherwise return the result of
:c:func:`PyRun_SimpleFile`. *filename* is decoded from the filesystem
encoding (:func:`sys.getfilesystemencoding`). If *filename* is *NULL*, this
function uses ``"???"`` as the filename.
.. c:function:: int PyRun_SimpleString(const char *command)
This is a simplified interface to :c:func:`PyRun_SimpleStringFlags` below,
leaving the *PyCompilerFlags\** argument set to NULL.
.. c:function:: int PyRun_SimpleStringFlags(const char *command, PyCompilerFlags *flags)
Executes the Python source code from *command* in the :mod:`__main__` module
according to the *flags* argument. If :mod:`__main__` does not already exist, it
is created. Returns ``0`` on success or ``-1`` if an exception was raised. If
there was an error, there is no way to get the exception information. For the
meaning of *flags*, see below.
Note that if an otherwise unhandled :exc:`SystemExit` is raised, this
function will not return ``-1``, but exit the process, as long as
``Py_InspectFlag`` is not set.
.. c:function:: int PyRun_SimpleFile(FILE *fp, const char *filename)
This is a simplified interface to :c:func:`PyRun_SimpleFileExFlags` below,
leaving *closeit* set to ``0`` and *flags* set to *NULL*.
.. c:function:: int PyRun_SimpleFileEx(FILE *fp, const char *filename, int closeit)
This is a simplified interface to :c:func:`PyRun_SimpleFileExFlags` below,
leaving *flags* set to *NULL*.
.. c:function:: int PyRun_SimpleFileExFlags(FILE *fp, const char *filename, int closeit, PyCompilerFlags *flags)
Similar to :c:func:`PyRun_SimpleStringFlags`, but the Python source code is read
from *fp* instead of an in-memory string. *filename* should be the name of
the file, it is decoded from the filesystem encoding
(:func:`sys.getfilesystemencoding`). If *closeit* is true, the file is
closed before PyRun_SimpleFileExFlags returns.
.. c:function:: int PyRun_InteractiveOne(FILE *fp, const char *filename)
This is a simplified interface to :c:func:`PyRun_InteractiveOneFlags` below,
leaving *flags* set to *NULL*.
.. c:function:: int PyRun_InteractiveOneFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
Read and execute a single statement from a file associated with an
interactive device according to the *flags* argument. The user will be
prompted using ``sys.ps1`` and ``sys.ps2``. *filename* is decoded from the
filesystem encoding (:func:`sys.getfilesystemencoding`).
Returns ``0`` when the input was
executed successfully, ``-1`` if there was an exception, or an error code
from the :file:`errcode.h` include file distributed as part of Python if
there was a parse error. (Note that :file:`errcode.h` is not included by
:file:`Python.h`, so must be included specifically if needed.)
.. c:function:: int PyRun_InteractiveLoop(FILE *fp, const char *filename)
This is a simplified interface to :c:func:`PyRun_InteractiveLoopFlags` below,
leaving *flags* set to *NULL*.
.. c:function:: int PyRun_InteractiveLoopFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
Read and execute statements from a file associated with an interactive device
until EOF is reached. The user will be prompted using ``sys.ps1`` and
``sys.ps2``. *filename* is decoded from the filesystem encoding
(:func:`sys.getfilesystemencoding`). Returns ``0`` at EOF or a negative
number upon failure.
.. c:var:: int (*PyOS_InputHook)(void)
Can be set to point to a function with the prototype
``int func(void)``. The function will be called when Python's
interpreter prompt is about to become idle and wait for user input
from the terminal. The return value is ignored. Overriding this
hook can be used to integrate the interpreter's prompt with other
event loops, as done in the :file:`Modules/_tkinter.c` in the
Python source code.
.. c:var:: char* (*PyOS_ReadlineFunctionPointer)(FILE *, FILE *, const char *)
Can be set to point to a function with the prototype
``char *func(FILE *stdin, FILE *stdout, char *prompt)``,
overriding the default function used to read a single line of input
at the interpreter's prompt. The function is expected to output
the string *prompt* if it's not *NULL*, and then read a line of
input from the provided standard input file, returning the
resulting string. For example, The :mod:`readline` module sets
this hook to provide line-editing and tab-completion features.
The result must be a string allocated by :c:func:`PyMem_RawMalloc` or
:c:func:`PyMem_RawRealloc`, or *NULL* if an error occurred.
.. versionchanged:: 3.4
The result must be allocated by :c:func:`PyMem_RawMalloc` or
:c:func:`PyMem_RawRealloc`, instead of being allocated by
:c:func:`PyMem_Malloc` or :c:func:`PyMem_Realloc`.
.. c:function:: struct _node* PyParser_SimpleParseString(const char *str, int start)
This is a simplified interface to
:c:func:`PyParser_SimpleParseStringFlagsFilename` below, leaving *filename* set
to *NULL* and *flags* set to ``0``.
.. c:function:: struct _node* PyParser_SimpleParseStringFlags( const char *str, int start, int flags)
This is a simplified interface to
:c:func:`PyParser_SimpleParseStringFlagsFilename` below, leaving *filename* set
to *NULL*.
.. c:function:: struct _node* PyParser_SimpleParseStringFlagsFilename( const char *str, const char *filename, int start, int flags)
Parse Python source code from *str* using the start token *start* according to
the *flags* argument. The result can be used to create a code object which can
be evaluated efficiently. This is useful if a code fragment must be evaluated
many times. *filename* is decoded from the filesystem encoding
(:func:`sys.getfilesystemencoding`).
.. c:function:: struct _node* PyParser_SimpleParseFile(FILE *fp, const char *filename, int start)
This is a simplified interface to :c:func:`PyParser_SimpleParseFileFlags` below,
leaving *flags* set to ``0``.
.. c:function:: struct _node* PyParser_SimpleParseFileFlags(FILE *fp, const char *filename, int start, int flags)
Similar to :c:func:`PyParser_SimpleParseStringFlagsFilename`, but the Python
source code is read from *fp* instead of an in-memory string.
.. c:function:: PyObject* PyRun_String(const char *str, int start, PyObject *globals, PyObject *locals)
This is a simplified interface to :c:func:`PyRun_StringFlags` below, leaving
*flags* set to *NULL*.
.. c:function:: PyObject* PyRun_StringFlags(const char *str, int start, PyObject *globals, PyObject *locals, PyCompilerFlags *flags)
Execute Python source code from *str* in the context specified by the
objects *globals* and *locals* with the compiler flags specified by
*flags*. *globals* must be a dictionary; *locals* can be any object
that implements the mapping protocol. The parameter *start* specifies
the start token that should be used to parse the source code.
Returns the result of executing the code as a Python object, or *NULL* if an
exception was raised.
.. c:function:: PyObject* PyRun_File(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals)
This is a simplified interface to :c:func:`PyRun_FileExFlags` below, leaving
*closeit* set to ``0`` and *flags* set to *NULL*.
.. c:function:: PyObject* PyRun_FileEx(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, int closeit)
This is a simplified interface to :c:func:`PyRun_FileExFlags` below, leaving
*flags* set to *NULL*.
.. c:function:: PyObject* PyRun_FileFlags(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, PyCompilerFlags *flags)
This is a simplified interface to :c:func:`PyRun_FileExFlags` below, leaving
*closeit* set to ``0``.
.. c:function:: PyObject* PyRun_FileExFlags(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, int closeit, PyCompilerFlags *flags)
Similar to :c:func:`PyRun_StringFlags`, but the Python source code is read from
*fp* instead of an in-memory string. *filename* should be the name of the file,
it is decoded from the filesystem encoding (:func:`sys.getfilesystemencoding`).
If *closeit* is true, the file is closed before :c:func:`PyRun_FileExFlags`
returns.
.. c:function:: PyObject* Py_CompileString(const char *str, const char *filename, int start)
This is a simplified interface to :c:func:`Py_CompileStringFlags` below, leaving
*flags* set to *NULL*.
.. c:function:: PyObject* Py_CompileStringFlags(const char *str, const char *filename, int start, PyCompilerFlags *flags)
This is a simplified interface to :c:func:`Py_CompileStringExFlags` below, with
*optimize* set to ``-1``.
.. c:function:: PyObject* Py_CompileStringObject(const char *str, PyObject *filename, int start, PyCompilerFlags *flags, int optimize)
Parse and compile the Python source code in *str*, returning the resulting code
object. The start token is given by *start*; this can be used to constrain the
code which can be compiled and should be :const:`Py_eval_input`,
:const:`Py_file_input`, or :const:`Py_single_input`. The filename specified by
*filename* is used to construct the code object and may appear in tracebacks or
:exc:`SyntaxError` exception messages. This returns *NULL* if the code
cannot be parsed or compiled.
The integer *optimize* specifies the optimization level of the compiler; a
value of ``-1`` selects the optimization level of the interpreter as given by
:option:`-O` options. Explicit levels are ``0`` (no optimization;
``__debug__`` is true), ``1`` (asserts are removed, ``__debug__`` is false)
or ``2`` (docstrings are removed too).
.. versionadded:: 3.4
.. c:function:: PyObject* Py_CompileStringExFlags(const char *str, const char *filename, int start, PyCompilerFlags *flags, int optimize)
Like :c:func:`Py_CompileStringObject`, but *filename* is a byte string
decoded from the filesystem encoding (:func:`os.fsdecode`).
.. versionadded:: 3.2
.. c:function:: PyObject* PyEval_EvalCode(PyObject *co, PyObject *globals, PyObject *locals)
This is a simplified interface to :c:func:`PyEval_EvalCodeEx`, with just
the code object, and global and local variables. The other arguments are
set to *NULL*.
.. c:function:: PyObject* PyEval_EvalCodeEx(PyObject *co, PyObject *globals, PyObject *locals, PyObject **args, int argcount, PyObject **kws, int kwcount, PyObject **defs, int defcount, PyObject *kwdefs, PyObject *closure)
Evaluate a precompiled code object, given a particular environment for its
evaluation. This environment consists of a dictionary of global variables,
a mapping object of local variables, arrays of arguments, keywords and
defaults, a dictionary of default values for :ref:`keyword-only
<keyword-only_parameter>` arguments and a closure tuple of cells.
.. c:type:: PyFrameObject
The C structure of the objects used to describe frame objects. The
fields of this type are subject to change at any time.
.. c:function:: PyObject* PyEval_EvalFrame(PyFrameObject *f)
Evaluate an execution frame. This is a simplified interface to
:c:func:`PyEval_EvalFrameEx`, for backward compatibility.
.. c:function:: PyObject* PyEval_EvalFrameEx(PyFrameObject *f, int throwflag)
This is the main, unvarnished function of Python interpretation. It is
literally 2000 lines long. The code object associated with the execution
frame *f* is executed, interpreting bytecode and executing calls as needed.
The additional *throwflag* parameter can mostly be ignored - if true, then
it causes an exception to immediately be thrown; this is used for the
:meth:`~generator.throw` methods of generator objects.
.. versionchanged:: 3.4
This function now includes a debug assertion to help ensure that it
does not silently discard an active exception.
.. c:function:: int PyEval_MergeCompilerFlags(PyCompilerFlags *cf)
This function changes the flags of the current evaluation frame, and returns
true on success, false on failure.
.. c:var:: int Py_eval_input
.. index:: single: Py_CompileString()
The start symbol from the Python grammar for isolated expressions; for use with
:c:func:`Py_CompileString`.
.. c:var:: int Py_file_input
.. index:: single: Py_CompileString()
The start symbol from the Python grammar for sequences of statements as read
from a file or other source; for use with :c:func:`Py_CompileString`. This is
the symbol to use when compiling arbitrarily long Python source code.
.. c:var:: int Py_single_input
.. index:: single: Py_CompileString()
The start symbol from the Python grammar for a single statement; for use with
:c:func:`Py_CompileString`. This is the symbol used for the interactive
interpreter loop.
.. c:type:: struct PyCompilerFlags
This is the structure used to hold compiler flags. In cases where code is only
being compiled, it is passed as ``int flags``, and in cases where code is being
executed, it is passed as ``PyCompilerFlags *flags``. In this case, ``from
__future__ import`` can modify *flags*.
Whenever ``PyCompilerFlags *flags`` is *NULL*, :attr:`cf_flags` is treated as
equal to ``0``, and any modification due to ``from __future__ import`` is
discarded. ::
struct PyCompilerFlags {
int cf_flags;
}
.. c:var:: int CO_FUTURE_DIVISION
This bit can be set in *flags* to cause division operator ``/`` to be
interpreted as "true division" according to :pep:`238`.

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.. highlightlang:: c
.. _weakrefobjects:
Weak Reference Objects
----------------------
Python supports *weak references* as first-class objects. There are two
specific object types which directly implement weak references. The first is a
simple reference object, and the second acts as a proxy for the original object
as much as it can.
.. c:function:: int PyWeakref_Check(ob)
Return true if *ob* is either a reference or proxy object.
.. c:function:: int PyWeakref_CheckRef(ob)
Return true if *ob* is a reference object.
.. c:function:: int PyWeakref_CheckProxy(ob)
Return true if *ob* is a proxy object.
.. c:function:: PyObject* PyWeakref_NewRef(PyObject *ob, PyObject *callback)
Return a weak reference object for the object *ob*. This will always return
a new reference, but is not guaranteed to create a new object; an existing
reference object may be returned. The second parameter, *callback*, can be a
callable object that receives notification when *ob* is garbage collected; it
should accept a single parameter, which will be the weak reference object
itself. *callback* may also be ``None`` or *NULL*. If *ob* is not a
weakly-referencable object, or if *callback* is not callable, ``None``, or
*NULL*, this will return *NULL* and raise :exc:`TypeError`.
.. c:function:: PyObject* PyWeakref_NewProxy(PyObject *ob, PyObject *callback)
Return a weak reference proxy object for the object *ob*. This will always
return a new reference, but is not guaranteed to create a new object; an
existing proxy object may be returned. The second parameter, *callback*, can
be a callable object that receives notification when *ob* is garbage
collected; it should accept a single parameter, which will be the weak
reference object itself. *callback* may also be ``None`` or *NULL*. If *ob*
is not a weakly-referencable object, or if *callback* is not callable,
``None``, or *NULL*, this will return *NULL* and raise :exc:`TypeError`.
.. c:function:: PyObject* PyWeakref_GetObject(PyObject *ref)
Return the referenced object from a weak reference, *ref*. If the referent is
no longer live, returns :const:`Py_None`.
.. note::
This function returns a **borrowed reference** to the referenced object.
This means that you should always call :c:func:`Py_INCREF` on the object
except if you know that it cannot be destroyed while you are still
using it.
.. c:function:: PyObject* PyWeakref_GET_OBJECT(PyObject *ref)
Similar to :c:func:`PyWeakref_GetObject`, but implemented as a macro that does no
error checking.

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#
# Python documentation build configuration file
#
# This file is execfile()d with the current directory set to its containing dir.
#
# The contents of this file are pickled, so don't put values in the namespace
# that aren't pickleable (module imports are okay, they're removed automatically).
import sys, os, time
sys.path.append(os.path.abspath('tools/extensions'))
# General configuration
# ---------------------
extensions = ['sphinx.ext.coverage', 'sphinx.ext.doctest',
'pyspecific', 'c_annotations', 'escape4chm']
# General substitutions.
project = 'Python'
copyright = '2001-%s, Python Software Foundation' % time.strftime('%Y')
# We look for the Include/patchlevel.h file in the current Python source tree
# and replace the values accordingly.
import patchlevel
version, release = patchlevel.get_version_info()
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
today = ''
# Else, today_fmt is used as the format for a strftime call.
today_fmt = '%B %d, %Y'
# By default, highlight as Python 3.
highlight_language = 'python3'
# Require Sphinx 1.2 for build.
needs_sphinx = '1.2'
# Ignore any .rst files in the venv/ directory.
venvdir = os.getenv('VENVDIR', 'venv')
exclude_patterns = [venvdir+'/*', 'README.rst']
# Avoid a warning with Sphinx >= 2.0
master_doc = 'contents'
# Options for HTML output
# -----------------------
# Use our custom theme.
html_theme = 'pydoctheme'
html_theme_path = ['tools']
html_theme_options = {'collapsiblesidebar': True}
# Short title used e.g. for <title> HTML tags.
html_short_title = '%s Documentation' % release
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
html_last_updated_fmt = '%b %d, %Y'
# Path to find HTML templates.
templates_path = ['tools/templates']
# Custom sidebar templates, filenames relative to this file.
html_sidebars = {
# Defaults taken from http://www.sphinx-doc.org/en/stable/config.html#confval-html_sidebars
# Removes the quick search block
'**': ['localtoc.html', 'relations.html', 'customsourcelink.html'],
'index': ['indexsidebar.html'],
}
# Additional templates that should be rendered to pages.
html_additional_pages = {
'download': 'download.html',
'index': 'indexcontent.html',
}
# Output an OpenSearch description file.
html_use_opensearch = 'https://docs.python.org/' + version
# Additional static files.
html_static_path = ['tools/static']
# Output file base name for HTML help builder.
htmlhelp_basename = 'python' + release.replace('.', '')
# Split the index
html_split_index = True
# Options for LaTeX output
# ------------------------
latex_engine = 'xelatex'
# Get LaTeX to handle Unicode correctly
latex_elements = {
}
# Additional stuff for the LaTeX preamble.
latex_elements['preamble'] = r'''
\authoraddress{
\sphinxstrong{Python Software Foundation}\\
Email: \sphinxemail{docs@python.org}
}
\let\Verbatim=\OriginalVerbatim
\let\endVerbatim=\endOriginalVerbatim
'''
# The paper size ('letter' or 'a4').
latex_elements['papersize'] = 'a4'
# The font size ('10pt', '11pt' or '12pt').
latex_elements['pointsize'] = '10pt'
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title, author, document class [howto/manual]).
_stdauthor = r'Guido van Rossum\\and the Python development team'
latex_documents = [
('c-api/index', 'c-api.tex',
'The Python/C API', _stdauthor, 'manual'),
('distributing/index', 'distributing.tex',
'Distributing Python Modules', _stdauthor, 'manual'),
('extending/index', 'extending.tex',
'Extending and Embedding Python', _stdauthor, 'manual'),
('installing/index', 'installing.tex',
'Installing Python Modules', _stdauthor, 'manual'),
('library/index', 'library.tex',
'The Python Library Reference', _stdauthor, 'manual'),
('reference/index', 'reference.tex',
'The Python Language Reference', _stdauthor, 'manual'),
('tutorial/index', 'tutorial.tex',
'Python Tutorial', _stdauthor, 'manual'),
('using/index', 'using.tex',
'Python Setup and Usage', _stdauthor, 'manual'),
('faq/index', 'faq.tex',
'Python Frequently Asked Questions', _stdauthor, 'manual'),
('whatsnew/' + version, 'whatsnew.tex',
'What\'s New in Python', 'A. M. Kuchling', 'howto'),
]
# Collect all HOWTOs individually
latex_documents.extend(('howto/' + fn[:-4], 'howto-' + fn[:-4] + '.tex',
'', _stdauthor, 'howto')
for fn in os.listdir('howto')
if fn.endswith('.rst') and fn != 'index.rst')
# Documents to append as an appendix to all manuals.
latex_appendices = ['glossary', 'about', 'license', 'copyright']
# Options for Epub output
# -----------------------
epub_author = 'Python Documentation Authors'
epub_publisher = 'Python Software Foundation'
# Options for the coverage checker
# --------------------------------
# The coverage checker will ignore all modules/functions/classes whose names
# match any of the following regexes (using re.match).
coverage_ignore_modules = [
r'[T|t][k|K]',
r'Tix',
r'distutils.*',
]
coverage_ignore_functions = [
'test($|_)',
]
coverage_ignore_classes = [
]
# Glob patterns for C source files for C API coverage, relative to this directory.
coverage_c_path = [
'../Include/*.h',
]
# Regexes to find C items in the source files.
coverage_c_regexes = {
'cfunction': (r'^PyAPI_FUNC\(.*\)\s+([^_][\w_]+)'),
'data': (r'^PyAPI_DATA\(.*\)\s+([^_][\w_]+)'),
'macro': (r'^#define ([^_][\w_]+)\(.*\)[\s|\\]'),
}
# The coverage checker will ignore all C items whose names match these regexes
# (using re.match) -- the keys must be the same as in coverage_c_regexes.
coverage_ignore_c_items = {
# 'cfunction': [...]
}
# Options for the link checker
# ----------------------------
# Ignore certain URLs.
linkcheck_ignore = [r'https://bugs.python.org/(issue)?\d+',
# Ignore PEPs for now, they all have permanent redirects.
r'http://www.python.org/dev/peps/pep-\d+']
# Options for extensions
# ----------------------
# Relative filename of the reference count data file.
refcount_file = 'data/refcounts.dat'

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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Python Documentation contents
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. toctree::
whatsnew/index.rst
tutorial/index.rst
using/index.rst
reference/index.rst
library/index.rst
extending/index.rst
c-api/index.rst
distributing/index.rst
installing/index.rst
howto/index.rst
faq/index.rst
glossary.rst
about.rst
bugs.rst
copyright.rst
license.rst
.. to include legacy packaging docs in build
.. toctree::
:hidden:
distutils/index.rst
install/index.rst

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*********
Copyright
*********
Python and this documentation is:
Copyright © 2001-2021 Python Software Foundation. All rights reserved.
Copyright © 2000 BeOpen.com. All rights reserved.
Copyright © 1995-2000 Corporation for National Research Initiatives. All rights
reserved.
Copyright © 1991-1995 Stichting Mathematisch Centrum. All rights reserved.
-------
See :ref:`history-and-license` for complete license and permissions information.

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.. _distributing-index:
###############################
Distributing Python Modules
###############################
:Email: distutils-sig@python.org
As a popular open source development project, Python has an active
supporting community of contributors and users that also make their software
available for other Python developers to use under open source license terms.
This allows Python users to share and collaborate effectively, benefiting
from the solutions others have already created to common (and sometimes
even rare!) problems, as well as potentially contributing their own
solutions to the common pool.
This guide covers the distribution part of the process. For a guide to
installing other Python projects, refer to the
:ref:`installation guide <installing-index>`.
.. note::
For corporate and other institutional users, be aware that many
organisations have their own policies around using and contributing to
open source software. Please take such policies into account when making
use of the distribution and installation tools provided with Python.
Key terms
=========
* the `Python Packaging Index <https://pypi.org>`__ is a public
repository of open source licensed packages made available for use by
other Python users
* the `Python Packaging Authority
<https://www.pypa.io/>`__ are the group of
developers and documentation authors responsible for the maintenance and
evolution of the standard packaging tools and the associated metadata and
file format standards. They maintain a variety of tools, documentation
and issue trackers on both `GitHub <https://github.com/pypa>`__ and
`BitBucket <https://bitbucket.org/pypa/>`__.
* :mod:`distutils` is the original build and distribution system first added
to the Python standard library in 1998. While direct use of :mod:`distutils`
is being phased out, it still laid the foundation for the current packaging
and distribution infrastructure, and it not only remains part of the
standard library, but its name lives on in other ways (such as the name
of the mailing list used to coordinate Python packaging standards
development).
* `setuptools`_ is a (largely) drop-in replacement for :mod:`distutils` first
published in 2004. Its most notable addition over the unmodified
:mod:`distutils` tools was the ability to declare dependencies on other
packages. It is currently recommended as a more regularly updated
alternative to :mod:`distutils` that offers consistent support for more
recent packaging standards across a wide range of Python versions.
* `wheel`_ (in this context) is a project that adds the ``bdist_wheel``
command to :mod:`distutils`/`setuptools`_. This produces a cross platform
binary packaging format (called "wheels" or "wheel files" and defined in
:pep:`427`) that allows Python libraries, even those including binary
extensions, to be installed on a system without needing to be built
locally.
.. _setuptools: https://setuptools.readthedocs.io/en/latest/
.. _wheel: https://wheel.readthedocs.org
Open source licensing and collaboration
=======================================
In most parts of the world, software is automatically covered by copyright.
This means that other developers require explicit permission to copy, use,
modify and redistribute the software.
Open source licensing is a way of explicitly granting such permission in a
relatively consistent way, allowing developers to share and collaborate
efficiently by making common solutions to various problems freely available.
This leaves many developers free to spend more time focusing on the problems
that are relatively unique to their specific situation.
The distribution tools provided with Python are designed to make it
reasonably straightforward for developers to make their own contributions
back to that common pool of software if they choose to do so.
The same distribution tools can also be used to distribute software within
an organisation, regardless of whether that software is published as open
source software or not.
Installing the tools
====================
The standard library does not include build tools that support modern
Python packaging standards, as the core development team has found that it
is important to have standard tools that work consistently, even on older
versions of Python.
The currently recommended build and distribution tools can be installed
by invoking the ``pip`` module at the command line::
python -m pip install setuptools wheel twine
.. note::
For POSIX users (including Mac OS X and Linux users), these instructions
assume the use of a :term:`virtual environment`.
For Windows users, these instructions assume that the option to
adjust the system PATH environment variable was selected when installing
Python.
The Python Packaging User Guide includes more details on the `currently
recommended tools`_.
.. _currently recommended tools: https://packaging.python.org/en/latest/current/#packaging-tool-recommendations
Reading the guide
=================
The Python Packaging User Guide covers the various key steps and elements
involved in creating a project:
* `Project structure`_
* `Building and packaging the project`_
* `Uploading the project to the Python Packaging Index`_
.. _Project structure: \
https://packaging.python.org/en/latest/distributing/
.. _Building and packaging the project: \
https://packaging.python.org/en/latest/distributing/#packaging-your-project
.. _Uploading the project to the Python Packaging Index: \
https://packaging.python.org/en/latest/distributing/#uploading-your-project-to-pypi
How do I...?
============
These are quick answers or links for some common tasks.
... choose a name for my project?
---------------------------------
This isn't an easy topic, but here are a few tips:
* check the Python Packaging Index to see if the name is already in use
* check popular hosting sites like GitHub, BitBucket, etc to see if there
is already a project with that name
* check what comes up in a web search for the name you're considering
* avoid particularly common words, especially ones with multiple meanings,
as they can make it difficult for users to find your software when
searching for it
... create and distribute binary extensions?
--------------------------------------------
This is actually quite a complex topic, with a variety of alternatives
available depending on exactly what you're aiming to achieve. See the
Python Packaging User Guide for more information and recommendations.
.. seealso::
`Python Packaging User Guide: Binary Extensions
<https://packaging.python.org/en/latest/extensions>`__
.. other topics:
Once the Development & Deployment part of PPUG is fleshed out, some of
those sections should be linked from new questions here (most notably,
we should have a question about avoiding depending on PyPI that links to
https://packaging.python.org/en/latest/mirrors/)

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.. _built-dist:
****************************
Creating Built Distributions
****************************
A "built distribution" is what you're probably used to thinking of either as a
"binary package" or an "installer" (depending on your background). It's not
necessarily binary, though, because it might contain only Python source code
and/or byte-code; and we don't call it a package, because that word is already
spoken for in Python. (And "installer" is a term specific to the world of
mainstream desktop systems.)
A built distribution is how you make life as easy as possible for installers of
your module distribution: for users of RPM-based Linux systems, it's a binary
RPM; for Windows users, it's an executable installer; for Debian-based Linux
users, it's a Debian package; and so forth. Obviously, no one person will be
able to create built distributions for every platform under the sun, so the
Distutils are designed to enable module developers to concentrate on their
specialty---writing code and creating source distributions---while an
intermediary species called *packagers* springs up to turn source distributions
into built distributions for as many platforms as there are packagers.
Of course, the module developer could be their own packager; or the packager could
be a volunteer "out there" somewhere who has access to a platform which the
original developer does not; or it could be software periodically grabbing new
source distributions and turning them into built distributions for as many
platforms as the software has access to. Regardless of who they are, a packager
uses the setup script and the :command:`bdist` command family to generate built
distributions.
As a simple example, if I run the following command in the Distutils source
tree::
python setup.py bdist
then the Distutils builds my module distribution (the Distutils itself in this
case), does a "fake" installation (also in the :file:`build` directory), and
creates the default type of built distribution for my platform. The default
format for built distributions is a "dumb" tar file on Unix, and a simple
executable installer on Windows. (That tar file is considered "dumb" because it
has to be unpacked in a specific location to work.)
Thus, the above command on a Unix system creates
:file:`Distutils-1.0.{plat}.tar.gz`; unpacking this tarball from the right place
installs the Distutils just as though you had downloaded the source distribution
and run ``python setup.py install``. (The "right place" is either the root of
the filesystem or Python's :file:`{prefix}` directory, depending on the options
given to the :command:`bdist_dumb` command; the default is to make dumb
distributions relative to :file:`{prefix}`.)
Obviously, for pure Python distributions, this isn't any simpler than just
running ``python setup.py install``\ ---but for non-pure distributions, which
include extensions that would need to be compiled, it can mean the difference
between someone being able to use your extensions or not. And creating "smart"
built distributions, such as an RPM package or an executable installer for
Windows, is far more convenient for users even if your distribution doesn't
include any extensions.
The :command:`bdist` command has a :option:`!--formats` option, similar to the
:command:`sdist` command, which you can use to select the types of built
distribution to generate: for example, ::
python setup.py bdist --format=zip
would, when run on a Unix system, create
:file:`Distutils-1.0.{plat}.zip`\ ---again, this archive would be unpacked
from the root directory to install the Distutils.
The available formats for built distributions are:
+-------------+------------------------------+---------+
| Format | Description | Notes |
+=============+==============================+=========+
| ``gztar`` | gzipped tar file | \(1) |
| | (:file:`.tar.gz`) | |
+-------------+------------------------------+---------+
| ``bztar`` | bzipped tar file | |
| | (:file:`.tar.bz2`) | |
+-------------+------------------------------+---------+
| ``xztar`` | xzipped tar file | |
| | (:file:`.tar.xz`) | |
+-------------+------------------------------+---------+
| ``ztar`` | compressed tar file | \(3) |
| | (:file:`.tar.Z`) | |
+-------------+------------------------------+---------+
| ``tar`` | tar file (:file:`.tar`) | |
+-------------+------------------------------+---------+
| ``zip`` | zip file (:file:`.zip`) | (2),(4) |
+-------------+------------------------------+---------+
| ``rpm`` | RPM | \(5) |
+-------------+------------------------------+---------+
| ``pkgtool`` | Solaris :program:`pkgtool` | |
+-------------+------------------------------+---------+
| ``sdux`` | HP-UX :program:`swinstall` | |
+-------------+------------------------------+---------+
| ``wininst`` | self-extracting ZIP file for | \(4) |
| | Windows | |
+-------------+------------------------------+---------+
| ``msi`` | Microsoft Installer. | |
+-------------+------------------------------+---------+
.. versionchanged:: 3.5
Added support for the ``xztar`` format.
Notes:
(1)
default on Unix
(2)
default on Windows
(3)
requires external :program:`compress` utility.
(4)
requires either external :program:`zip` utility or :mod:`zipfile` module (part
of the standard Python library since Python 1.6)
(5)
requires external :program:`rpm` utility, version 3.0.4 or better (use ``rpm
--version`` to find out which version you have)
You don't have to use the :command:`bdist` command with the :option:`!--formats`
option; you can also use the command that directly implements the format you're
interested in. Some of these :command:`bdist` "sub-commands" actually generate
several similar formats; for instance, the :command:`bdist_dumb` command
generates all the "dumb" archive formats (``tar``, ``gztar``, ``bztar``,
``xztar``, ``ztar``, and ``zip``), and :command:`bdist_rpm` generates both
binary and source RPMs. The :command:`bdist` sub-commands, and the formats
generated by each, are:
+--------------------------+-------------------------------------+
| Command | Formats |
+==========================+=====================================+
| :command:`bdist_dumb` | tar, gztar, bztar, xztar, ztar, zip |
+--------------------------+-------------------------------------+
| :command:`bdist_rpm` | rpm, srpm |
+--------------------------+-------------------------------------+
| :command:`bdist_wininst` | wininst |
+--------------------------+-------------------------------------+
| :command:`bdist_msi` | msi |
+--------------------------+-------------------------------------+
The following sections give details on the individual :command:`bdist_\*`
commands.
.. .. _creating-dumb:
.. Creating dumb built distributions
.. =================================
.. XXX Need to document absolute vs. prefix-relative packages here, but first
I have to implement it!
.. _creating-rpms:
Creating RPM packages
=====================
The RPM format is used by many popular Linux distributions, including Red Hat,
SuSE, and Mandrake. If one of these (or any of the other RPM-based Linux
distributions) is your usual environment, creating RPM packages for other users
of that same distribution is trivial. Depending on the complexity of your module
distribution and differences between Linux distributions, you may also be able
to create RPMs that work on different RPM-based distributions.
The usual way to create an RPM of your module distribution is to run the
:command:`bdist_rpm` command::
python setup.py bdist_rpm
or the :command:`bdist` command with the :option:`!--format` option::
python setup.py bdist --formats=rpm
The former allows you to specify RPM-specific options; the latter allows you to
easily specify multiple formats in one run. If you need to do both, you can
explicitly specify multiple :command:`bdist_\*` commands and their options::
python setup.py bdist_rpm --packager="John Doe <jdoe@example.org>" \
bdist_wininst --target-version="2.0"
Creating RPM packages is driven by a :file:`.spec` file, much as using the
Distutils is driven by the setup script. To make your life easier, the
:command:`bdist_rpm` command normally creates a :file:`.spec` file based on the
information you supply in the setup script, on the command line, and in any
Distutils configuration files. Various options and sections in the
:file:`.spec` file are derived from options in the setup script as follows:
+------------------------------------------+----------------------------------------------+
| RPM :file:`.spec` file option or section | Distutils setup script option |
+==========================================+==============================================+
| Name | ``name`` |
+------------------------------------------+----------------------------------------------+
| Summary (in preamble) | ``description`` |
+------------------------------------------+----------------------------------------------+
| Version | ``version`` |
+------------------------------------------+----------------------------------------------+
| Vendor | ``author`` and ``author_email``, |
| | or --- & ``maintainer`` and |
| | ``maintainer_email`` |
+------------------------------------------+----------------------------------------------+
| Copyright | ``license`` |
+------------------------------------------+----------------------------------------------+
| Url | ``url`` |
+------------------------------------------+----------------------------------------------+
| %description (section) | ``long_description`` |
+------------------------------------------+----------------------------------------------+
Additionally, there are many options in :file:`.spec` files that don't have
corresponding options in the setup script. Most of these are handled through
options to the :command:`bdist_rpm` command as follows:
+-------------------------------+-----------------------------+-------------------------+
| RPM :file:`.spec` file option | :command:`bdist_rpm` option | default value |
| or section | | |
+===============================+=============================+=========================+
| Release | ``release`` | "1" |
+-------------------------------+-----------------------------+-------------------------+
| Group | ``group`` | "Development/Libraries" |
+-------------------------------+-----------------------------+-------------------------+
| Vendor | ``vendor`` | (see above) |
+-------------------------------+-----------------------------+-------------------------+
| Packager | ``packager`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Provides | ``provides`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Requires | ``requires`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Conflicts | ``conflicts`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Obsoletes | ``obsoletes`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Distribution | ``distribution_name`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| BuildRequires | ``build_requires`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
| Icon | ``icon`` | (none) |
+-------------------------------+-----------------------------+-------------------------+
Obviously, supplying even a few of these options on the command-line would be
tedious and error-prone, so it's usually best to put them in the setup
configuration file, :file:`setup.cfg`\ ---see section :ref:`setup-config`. If
you distribute or package many Python module distributions, you might want to
put options that apply to all of them in your personal Distutils configuration
file (:file:`~/.pydistutils.cfg`). If you want to temporarily disable
this file, you can pass the :option:`!--no-user-cfg` option to :file:`setup.py`.
There are three steps to building a binary RPM package, all of which are
handled automatically by the Distutils:
#. create a :file:`.spec` file, which describes the package (analogous to the
Distutils setup script; in fact, much of the information in the setup script
winds up in the :file:`.spec` file)
#. create the source RPM
#. create the "binary" RPM (which may or may not contain binary code, depending
on whether your module distribution contains Python extensions)
Normally, RPM bundles the last two steps together; when you use the Distutils,
all three steps are typically bundled together.
If you wish, you can separate these three steps. You can use the
:option:`!--spec-only` option to make :command:`bdist_rpm` just create the
:file:`.spec` file and exit; in this case, the :file:`.spec` file will be
written to the "distribution directory"---normally :file:`dist/`, but
customizable with the :option:`!--dist-dir` option. (Normally, the :file:`.spec`
file winds up deep in the "build tree," in a temporary directory created by
:command:`bdist_rpm`.)
.. % \XXX{this isn't implemented yet---is it needed?!}
.. % You can also specify a custom \file{.spec} file with the
.. % \longprogramopt{spec-file} option; used in conjunction with
.. % \longprogramopt{spec-only}, this gives you an opportunity to customize
.. % the \file{.spec} file manually:
.. %
.. % \ begin{verbatim}
.. % > python setup.py bdist_rpm --spec-only
.. % # ...edit dist/FooBar-1.0.spec
.. % > python setup.py bdist_rpm --spec-file=dist/FooBar-1.0.spec
.. % \ end{verbatim}
.. %
.. % (Although a better way to do this is probably to override the standard
.. % \command{bdist\_rpm} command with one that writes whatever else you want
.. % to the \file{.spec} file.)
.. _creating-wininst:
Creating Windows Installers
===========================
Executable installers are the natural format for binary distributions on
Windows. They display a nice graphical user interface, display some information
about the module distribution to be installed taken from the metadata in the
setup script, let the user select a few options, and start or cancel the
installation.
Since the metadata is taken from the setup script, creating Windows installers
is usually as easy as running::
python setup.py bdist_wininst
or the :command:`bdist` command with the :option:`!--formats` option::
python setup.py bdist --formats=wininst
If you have a pure module distribution (only containing pure Python modules and
packages), the resulting installer will be version independent and have a name
like :file:`foo-1.0.win32.exe`. These installers can even be created on Unix
platforms or Mac OS X.
If you have a non-pure distribution, the extensions can only be created on a
Windows platform, and will be Python version dependent. The installer filename
will reflect this and now has the form :file:`foo-1.0.win32-py2.0.exe`. You
have to create a separate installer for every Python version you want to
support.
The installer will try to compile pure modules into :term:`bytecode` after installation
on the target system in normal and optimizing mode. If you don't want this to
happen for some reason, you can run the :command:`bdist_wininst` command with
the :option:`!--no-target-compile` and/or the :option:`!--no-target-optimize`
option.
By default the installer will display the cool "Python Powered" logo when it is
run, but you can also supply your own 152x261 bitmap which must be a Windows
:file:`.bmp` file with the :option:`!--bitmap` option.
The installer will also display a large title on the desktop background window
when it is run, which is constructed from the name of your distribution and the
version number. This can be changed to another text by using the
:option:`!--title` option.
The installer file will be written to the "distribution directory" --- normally
:file:`dist/`, but customizable with the :option:`!--dist-dir` option.
.. _cross-compile-windows:
Cross-compiling on Windows
==========================
Starting with Python 2.6, distutils is capable of cross-compiling between
Windows platforms. In practice, this means that with the correct tools
installed, you can use a 32bit version of Windows to create 64bit extensions
and vice-versa.
To build for an alternate platform, specify the :option:`!--plat-name` option
to the build command. Valid values are currently 'win32', 'win-amd64' and
'win-ia64'. For example, on a 32bit version of Windows, you could execute::
python setup.py build --plat-name=win-amd64
to build a 64bit version of your extension. The Windows Installers also
support this option, so the command::
python setup.py build --plat-name=win-amd64 bdist_wininst
would create a 64bit installation executable on your 32bit version of Windows.
To cross-compile, you must download the Python source code and cross-compile
Python itself for the platform you are targeting - it is not possible from a
binary installation of Python (as the .lib etc file for other platforms are
not included.) In practice, this means the user of a 32 bit operating
system will need to use Visual Studio 2008 to open the
:file:`PCBuild/PCbuild.sln` solution in the Python source tree and build the
"x64" configuration of the 'pythoncore' project before cross-compiling
extensions is possible.
Note that by default, Visual Studio 2008 does not install 64bit compilers or
tools. You may need to reexecute the Visual Studio setup process and select
these tools (using Control Panel->[Add/Remove] Programs is a convenient way to
check or modify your existing install.)
.. _postinstallation-script:
The Postinstallation script
---------------------------
Starting with Python 2.3, a postinstallation script can be specified with the
:option:`!--install-script` option. The basename of the script must be
specified, and the script filename must also be listed in the scripts argument
to the setup function.
This script will be run at installation time on the target system after all the
files have been copied, with ``argv[1]`` set to :option:`!-install`, and again at
uninstallation time before the files are removed with ``argv[1]`` set to
:option:`!-remove`.
The installation script runs embedded in the windows installer, every output
(``sys.stdout``, ``sys.stderr``) is redirected into a buffer and will be
displayed in the GUI after the script has finished.
Some functions especially useful in this context are available as additional
built-in functions in the installation script.
.. function:: directory_created(path)
file_created(path)
These functions should be called when a directory or file is created by the
postinstall script at installation time. It will register *path* with the
uninstaller, so that it will be removed when the distribution is uninstalled.
To be safe, directories are only removed if they are empty.
.. function:: get_special_folder_path(csidl_string)
This function can be used to retrieve special folder locations on Windows like
the Start Menu or the Desktop. It returns the full path to the folder.
*csidl_string* must be one of the following strings::
"CSIDL_APPDATA"
"CSIDL_COMMON_STARTMENU"
"CSIDL_STARTMENU"
"CSIDL_COMMON_DESKTOPDIRECTORY"
"CSIDL_DESKTOPDIRECTORY"
"CSIDL_COMMON_STARTUP"
"CSIDL_STARTUP"
"CSIDL_COMMON_PROGRAMS"
"CSIDL_PROGRAMS"
"CSIDL_FONTS"
If the folder cannot be retrieved, :exc:`OSError` is raised.
Which folders are available depends on the exact Windows version, and probably
also the configuration. For details refer to Microsoft's documentation of the
:c:func:`SHGetSpecialFolderPath` function.
.. function:: create_shortcut(target, description, filename[, arguments[, workdir[, iconpath[, iconindex]]]])
This function creates a shortcut. *target* is the path to the program to be
started by the shortcut. *description* is the description of the shortcut.
*filename* is the title of the shortcut that the user will see. *arguments*
specifies the command line arguments, if any. *workdir* is the working directory
for the program. *iconpath* is the file containing the icon for the shortcut,
and *iconindex* is the index of the icon in the file *iconpath*. Again, for
details consult the Microsoft documentation for the :class:`IShellLink`
interface.
Vista User Access Control (UAC)
===============================
Starting with Python 2.6, bdist_wininst supports a :option:`!--user-access-control`
option. The default is 'none' (meaning no UAC handling is done), and other
valid values are 'auto' (meaning prompt for UAC elevation if Python was
installed for all users) and 'force' (meaning always prompt for elevation).

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@ -0,0 +1,104 @@
.. _reference:
*****************
Command Reference
*****************
.. % \section{Building modules: the \protect\command{build} command family}
.. % \label{build-cmds}
.. % \subsubsection{\protect\command{build}}
.. % \label{build-cmd}
.. % \subsubsection{\protect\command{build\_py}}
.. % \label{build-py-cmd}
.. % \subsubsection{\protect\command{build\_ext}}
.. % \label{build-ext-cmd}
.. % \subsubsection{\protect\command{build\_clib}}
.. % \label{build-clib-cmd}
.. _install-cmd:
Installing modules: the :command:`install` command family
=========================================================
The install command ensures that the build commands have been run and then runs
the subcommands :command:`install_lib`, :command:`install_data` and
:command:`install_scripts`.
.. % \subsubsection{\protect\command{install\_lib}}
.. % \label{install-lib-cmd}
.. _install-data-cmd:
:command:`install_data`
-----------------------
This command installs all data files provided with the distribution.
.. _install-scripts-cmd:
:command:`install_scripts`
--------------------------
This command installs all (Python) scripts in the distribution.
.. % \subsection{Cleaning up: the \protect\command{clean} command}
.. % \label{clean-cmd}
.. _sdist-cmd:
Creating a source distribution: the :command:`sdist` command
============================================================
.. XXX fragment moved down from above: needs context!
The manifest template commands are:
+-------------------------------------------+-----------------------------------------------+
| Command | Description |
+===========================================+===============================================+
| :command:`include pat1 pat2 ...` | include all files matching any of the listed |
| | patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`exclude pat1 pat2 ...` | exclude all files matching any of the listed |
| | patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`recursive-include dir pat1 pat2 | include all files under *dir* matching any of |
| ...` | the listed patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`recursive-exclude dir pat1 pat2 | exclude all files under *dir* matching any of |
| ...` | the listed patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`global-include pat1 pat2 ...` | include all files anywhere in the source tree |
| | matching --- & any of the listed patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`global-exclude pat1 pat2 ...` | exclude all files anywhere in the source tree |
| | matching --- & any of the listed patterns |
+-------------------------------------------+-----------------------------------------------+
| :command:`prune dir` | exclude all files under *dir* |
+-------------------------------------------+-----------------------------------------------+
| :command:`graft dir` | include all files under *dir* |
+-------------------------------------------+-----------------------------------------------+
The patterns here are Unix-style "glob" patterns: ``*`` matches any sequence of
regular filename characters, ``?`` matches any single regular filename
character, and ``[range]`` matches any of the characters in *range* (e.g.,
``a-z``, ``a-zA-Z``, ``a-f0-9_.``). The definition of "regular filename
character" is platform-specific: on Unix it is anything except slash; on Windows
anything except backslash or colon.
.. XXX Windows support not there yet
.. % \section{Creating a built distribution: the
.. % \protect\command{bdist} command family}
.. % \label{bdist-cmds}
.. % \subsection{\protect\command{bdist}}
.. % \subsection{\protect\command{bdist\_dumb}}
.. % \subsection{\protect\command{bdist\_rpm}}
.. % \subsection{\protect\command{bdist\_wininst}}

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.. _setup-config:
************************************
Writing the Setup Configuration File
************************************
Often, it's not possible to write down everything needed to build a distribution
*a priori*: you may need to get some information from the user, or from the
user's system, in order to proceed. As long as that information is fairly
simple---a list of directories to search for C header files or libraries, for
example---then providing a configuration file, :file:`setup.cfg`, for users to
edit is a cheap and easy way to solicit it. Configuration files also let you
provide default values for any command option, which the installer can then
override either on the command-line or by editing the config file.
The setup configuration file is a useful middle-ground between the setup
script---which, ideally, would be opaque to installers [#]_---and the command-line to
the setup script, which is outside of your control and entirely up to the
installer. In fact, :file:`setup.cfg` (and any other Distutils configuration
files present on the target system) are processed after the contents of the
setup script, but before the command-line. This has several useful
consequences:
.. % (If you have more advanced needs, such as determining which extensions
.. % to build based on what capabilities are present on the target system,
.. % then you need the Distutils ``auto-configuration'' facility. This
.. % started to appear in Distutils 0.9 but, as of this writing, isn't mature
.. % or stable enough yet for real-world use.)
* installers can override some of what you put in :file:`setup.py` by editing
:file:`setup.cfg`
* you can provide non-standard defaults for options that are not easily set in
:file:`setup.py`
* installers can override anything in :file:`setup.cfg` using the command-line
options to :file:`setup.py`
The basic syntax of the configuration file is simple:
.. code-block:: ini
[command]
option=value
...
where *command* is one of the Distutils commands (e.g. :command:`build_py`,
:command:`install`), and *option* is one of the options that command supports.
Any number of options can be supplied for each command, and any number of
command sections can be included in the file. Blank lines are ignored, as are
comments, which run from a ``'#'`` character until the end of the line. Long
option values can be split across multiple lines simply by indenting the
continuation lines.
You can find out the list of options supported by a particular command with the
universal :option:`!--help` option, e.g.
.. code-block:: shell-session
$ python setup.py --help build_ext
[...]
Options for 'build_ext' command:
--build-lib (-b) directory for compiled extension modules
--build-temp (-t) directory for temporary files (build by-products)
--inplace (-i) ignore build-lib and put compiled extensions into the
source directory alongside your pure Python modules
--include-dirs (-I) list of directories to search for header files
--define (-D) C preprocessor macros to define
--undef (-U) C preprocessor macros to undefine
--swig-opts list of SWIG command line options
[...]
Note that an option spelled :option:`!--foo-bar` on the command-line is spelled
``foo_bar`` in configuration files.
.. _distutils-build-ext-inplace:
For example, say you want your extensions to be built "in-place"---that is, you
have an extension :mod:`pkg.ext`, and you want the compiled extension file
(:file:`ext.so` on Unix, say) to be put in the same source directory as your
pure Python modules :mod:`pkg.mod1` and :mod:`pkg.mod2`. You can always use the
:option:`!--inplace` option on the command-line to ensure this:
.. code-block:: sh
python setup.py build_ext --inplace
But this requires that you always specify the :command:`build_ext` command
explicitly, and remember to provide :option:`!--inplace`. An easier way is to
"set and forget" this option, by encoding it in :file:`setup.cfg`, the
configuration file for this distribution:
.. code-block:: ini
[build_ext]
inplace=1
This will affect all builds of this module distribution, whether or not you
explicitly specify :command:`build_ext`. If you include :file:`setup.cfg` in
your source distribution, it will also affect end-user builds---which is
probably a bad idea for this option, since always building extensions in-place
would break installation of the module distribution. In certain peculiar cases,
though, modules are built right in their installation directory, so this is
conceivably a useful ability. (Distributing extensions that expect to be built
in their installation directory is almost always a bad idea, though.)
Another example: certain commands take a lot of options that don't change from
run to run; for example, :command:`bdist_rpm` needs to know everything required
to generate a "spec" file for creating an RPM distribution. Some of this
information comes from the setup script, and some is automatically generated by
the Distutils (such as the list of files installed). But some of it has to be
supplied as options to :command:`bdist_rpm`, which would be very tedious to do
on the command-line for every run. Hence, here is a snippet from the Distutils'
own :file:`setup.cfg`:
.. code-block:: ini
[bdist_rpm]
release = 1
packager = Greg Ward <gward@python.net>
doc_files = CHANGES.txt
README.txt
USAGE.txt
doc/
examples/
Note that the ``doc_files`` option is simply a whitespace-separated string
split across multiple lines for readability.
.. seealso::
:ref:`inst-config-syntax` in "Installing Python Modules"
More information on the configuration files is available in the manual for
system administrators.
.. rubric:: Footnotes
.. [#] This ideal probably won't be achieved until auto-configuration is fully
supported by the Distutils.

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.. _examples:
********
Examples
********
This chapter provides a number of basic examples to help get started with
distutils. Additional information about using distutils can be found in the
Distutils Cookbook.
.. seealso::
`Distutils Cookbook <https://wiki.python.org/moin/Distutils/Cookbook>`_
Collection of recipes showing how to achieve more control over distutils.
.. _pure-mod:
Pure Python distribution (by module)
====================================
If you're just distributing a couple of modules, especially if they don't live
in a particular package, you can specify them individually using the
``py_modules`` option in the setup script.
In the simplest case, you'll have two files to worry about: a setup script and
the single module you're distributing, :file:`foo.py` in this example::
<root>/
setup.py
foo.py
(In all diagrams in this section, *<root>* will refer to the distribution root
directory.) A minimal setup script to describe this situation would be::
from distutils.core import setup
setup(name='foo',
version='1.0',
py_modules=['foo'],
)
Note that the name of the distribution is specified independently with the
``name`` option, and there's no rule that says it has to be the same as
the name of the sole module in the distribution (although that's probably a good
convention to follow). However, the distribution name is used to generate
filenames, so you should stick to letters, digits, underscores, and hyphens.
Since ``py_modules`` is a list, you can of course specify multiple
modules, eg. if you're distributing modules :mod:`foo` and :mod:`bar`, your
setup might look like this::
<root>/
setup.py
foo.py
bar.py
and the setup script might be ::
from distutils.core import setup
setup(name='foobar',
version='1.0',
py_modules=['foo', 'bar'],
)
You can put module source files into another directory, but if you have enough
modules to do that, it's probably easier to specify modules by package rather
than listing them individually.
.. _pure-pkg:
Pure Python distribution (by package)
=====================================
If you have more than a couple of modules to distribute, especially if they are
in multiple packages, it's probably easier to specify whole packages rather than
individual modules. This works even if your modules are not in a package; you
can just tell the Distutils to process modules from the root package, and that
works the same as any other package (except that you don't have to have an
:file:`__init__.py` file).
The setup script from the last example could also be written as ::
from distutils.core import setup
setup(name='foobar',
version='1.0',
packages=[''],
)
(The empty string stands for the root package.)
If those two files are moved into a subdirectory, but remain in the root
package, e.g.::
<root>/
setup.py
src/ foo.py
bar.py
then you would still specify the root package, but you have to tell the
Distutils where source files in the root package live::
from distutils.core import setup
setup(name='foobar',
version='1.0',
package_dir={'': 'src'},
packages=[''],
)
More typically, though, you will want to distribute multiple modules in the same
package (or in sub-packages). For example, if the :mod:`foo` and :mod:`bar`
modules belong in package :mod:`foobar`, one way to layout your source tree is
::
<root>/
setup.py
foobar/
__init__.py
foo.py
bar.py
This is in fact the default layout expected by the Distutils, and the one that
requires the least work to describe in your setup script::
from distutils.core import setup
setup(name='foobar',
version='1.0',
packages=['foobar'],
)
If you want to put modules in directories not named for their package, then you
need to use the ``package_dir`` option again. For example, if the
:file:`src` directory holds modules in the :mod:`foobar` package::
<root>/
setup.py
src/
__init__.py
foo.py
bar.py
an appropriate setup script would be ::
from distutils.core import setup
setup(name='foobar',
version='1.0',
package_dir={'foobar': 'src'},
packages=['foobar'],
)
Or, you might put modules from your main package right in the distribution
root::
<root>/
setup.py
__init__.py
foo.py
bar.py
in which case your setup script would be ::
from distutils.core import setup
setup(name='foobar',
version='1.0',
package_dir={'foobar': ''},
packages=['foobar'],
)
(The empty string also stands for the current directory.)
If you have sub-packages, they must be explicitly listed in ``packages``,
but any entries in ``package_dir`` automatically extend to sub-packages.
(In other words, the Distutils does *not* scan your source tree, trying to
figure out which directories correspond to Python packages by looking for
:file:`__init__.py` files.) Thus, if the default layout grows a sub-package::
<root>/
setup.py
foobar/
__init__.py
foo.py
bar.py
subfoo/
__init__.py
blah.py
then the corresponding setup script would be ::
from distutils.core import setup
setup(name='foobar',
version='1.0',
packages=['foobar', 'foobar.subfoo'],
)
.. _single-ext:
Single extension module
=======================
Extension modules are specified using the ``ext_modules`` option.
``package_dir`` has no effect on where extension source files are found;
it only affects the source for pure Python modules. The simplest case, a
single extension module in a single C source file, is::
<root>/
setup.py
foo.c
If the :mod:`foo` extension belongs in the root package, the setup script for
this could be ::
from distutils.core import setup
from distutils.extension import Extension
setup(name='foobar',
version='1.0',
ext_modules=[Extension('foo', ['foo.c'])],
)
If the extension actually belongs in a package, say :mod:`foopkg`, then
With exactly the same source tree layout, this extension can be put in the
:mod:`foopkg` package simply by changing the name of the extension::
from distutils.core import setup
from distutils.extension import Extension
setup(name='foobar',
version='1.0',
ext_modules=[Extension('foopkg.foo', ['foo.c'])],
)
Checking a package
==================
The ``check`` command allows you to verify if your package meta-data
meet the minimum requirements to build a distribution.
To run it, just call it using your :file:`setup.py` script. If something is
missing, ``check`` will display a warning.
Let's take an example with a simple script::
from distutils.core import setup
setup(name='foobar')
Running the ``check`` command will display some warnings:
.. code-block:: shell-session
$ python setup.py check
running check
warning: check: missing required meta-data: version, url
warning: check: missing meta-data: either (author and author_email) or
(maintainer and maintainer_email) must be supplied
If you use the reStructuredText syntax in the ``long_description`` field and
`docutils`_ is installed you can check if the syntax is fine with the
``check`` command, using the ``restructuredtext`` option.
For example, if the :file:`setup.py` script is changed like this::
from distutils.core import setup
desc = """\
My description
==============
This is the description of the ``foobar`` package.
"""
setup(name='foobar', version='1', author='tarek',
author_email='tarek@ziade.org',
url='http://example.com', long_description=desc)
Where the long description is broken, ``check`` will be able to detect it
by using the :mod:`docutils` parser:
.. code-block:: shell-session
$ python setup.py check --restructuredtext
running check
warning: check: Title underline too short. (line 2)
warning: check: Could not finish the parsing.
Reading the metadata
=====================
The :func:`distutils.core.setup` function provides a command-line interface
that allows you to query the metadata fields of a project through the
``setup.py`` script of a given project:
.. code-block:: shell-session
$ python setup.py --name
distribute
This call reads the ``name`` metadata by running the
:func:`distutils.core.setup` function. Although, when a source or binary
distribution is created with Distutils, the metadata fields are written
in a static file called :file:`PKG-INFO`. When a Distutils-based project is
installed in Python, the :file:`PKG-INFO` file is copied alongside the modules
and packages of the distribution under :file:`NAME-VERSION-pyX.X.egg-info`,
where ``NAME`` is the name of the project, ``VERSION`` its version as defined
in the Metadata, and ``pyX.X`` the major and minor version of Python like
``2.7`` or ``3.2``.
You can read back this static file, by using the
:class:`distutils.dist.DistributionMetadata` class and its
:func:`read_pkg_file` method::
>>> from distutils.dist import DistributionMetadata
>>> metadata = DistributionMetadata()
>>> metadata.read_pkg_file(open('distribute-0.6.8-py2.7.egg-info'))
>>> metadata.name
'distribute'
>>> metadata.version
'0.6.8'
>>> metadata.description
'Easily download, build, install, upgrade, and uninstall Python packages'
Notice that the class can also be instantiated with a metadata file path to
loads its values::
>>> pkg_info_path = 'distribute-0.6.8-py2.7.egg-info'
>>> DistributionMetadata(pkg_info_path).name
'distribute'
.. % \section{Multiple extension modules}
.. % \label{multiple-ext}
.. % \section{Putting it all together}
.. _docutils: http://docutils.sourceforge.net

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.. _extending-distutils:
*******************
Extending Distutils
*******************
Distutils can be extended in various ways. Most extensions take the form of new
commands or replacements for existing commands. New commands may be written to
support new types of platform-specific packaging, for example, while
replacements for existing commands may be made to modify details of how the
command operates on a package.
Most extensions of the distutils are made within :file:`setup.py` scripts that
want to modify existing commands; many simply add a few file extensions that
should be copied into packages in addition to :file:`.py` files as a
convenience.
Most distutils command implementations are subclasses of the
:class:`distutils.cmd.Command` class. New commands may directly inherit from
:class:`Command`, while replacements often derive from :class:`Command`
indirectly, directly subclassing the command they are replacing. Commands are
required to derive from :class:`Command`.
.. % \section{Extending existing commands}
.. % \label{extend-existing}
.. % \section{Writing new commands}
.. % \label{new-commands}
.. % \XXX{Would an uninstall command be a good example here?}
Integrating new commands
========================
There are different ways to integrate new command implementations into
distutils. The most difficult is to lobby for the inclusion of the new features
in distutils itself, and wait for (and require) a version of Python that
provides that support. This is really hard for many reasons.
The most common, and possibly the most reasonable for most needs, is to include
the new implementations with your :file:`setup.py` script, and cause the
:func:`distutils.core.setup` function use them::
from distutils.command.build_py import build_py as _build_py
from distutils.core import setup
class build_py(_build_py):
"""Specialized Python source builder."""
# implement whatever needs to be different...
setup(cmdclass={'build_py': build_py},
...)
This approach is most valuable if the new implementations must be used to use a
particular package, as everyone interested in the package will need to have the
new command implementation.
Beginning with Python 2.4, a third option is available, intended to allow new
commands to be added which can support existing :file:`setup.py` scripts without
requiring modifications to the Python installation. This is expected to allow
third-party extensions to provide support for additional packaging systems, but
the commands can be used for anything distutils commands can be used for. A new
configuration option, ``command_packages`` (command-line option
:option:`!--command-packages`), can be used to specify additional packages to be
searched for modules implementing commands. Like all distutils options, this
can be specified on the command line or in a configuration file. This option
can only be set in the ``[global]`` section of a configuration file, or before
any commands on the command line. If set in a configuration file, it can be
overridden from the command line; setting it to an empty string on the command
line causes the default to be used. This should never be set in a configuration
file provided with a package.
This new option can be used to add any number of packages to the list of
packages searched for command implementations; multiple package names should be
separated by commas. When not specified, the search is only performed in the
:mod:`distutils.command` package. When :file:`setup.py` is run with the option
``--command-packages distcmds,buildcmds``, however, the packages
:mod:`distutils.command`, :mod:`distcmds`, and :mod:`buildcmds` will be searched
in that order. New commands are expected to be implemented in modules of the
same name as the command by classes sharing the same name. Given the example
command line option above, the command :command:`bdist_openpkg` could be
implemented by the class :class:`distcmds.bdist_openpkg.bdist_openpkg` or
:class:`buildcmds.bdist_openpkg.bdist_openpkg`.
Adding new distribution types
=============================
Commands that create distributions (files in the :file:`dist/` directory) need
to add ``(command, filename)`` pairs to ``self.distribution.dist_files`` so that
:command:`upload` can upload it to PyPI. The *filename* in the pair contains no
path information, only the name of the file itself. In dry-run mode, pairs
should still be added to represent what would have been created.

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.. _distutils-index:
##############################################
Distributing Python Modules (Legacy version)
##############################################
:Authors: Greg Ward, Anthony Baxter
:Email: distutils-sig@python.org
.. seealso::
:ref:`distributing-index`
The up to date module distribution documentations
This document describes the Python Distribution Utilities ("Distutils") from
the module developer's point of view, describing how to use the Distutils to
make Python modules and extensions easily available to a wider audience with
very little overhead for build/release/install mechanics.
.. note::
This guide only covers the basic tools for building and distributing
extensions that are provided as part of this version of Python. Third party
tools offer easier to use and more secure alternatives. Refer to the `quick
recommendations section <https://packaging.python.org/en/latest/current/>`__
in the Python Packaging User Guide for more information.
.. toctree::
:maxdepth: 2
:numbered:
introduction.rst
setupscript.rst
configfile.rst
sourcedist.rst
builtdist.rst
packageindex.rst
examples.rst
extending.rst
commandref.rst
apiref.rst

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.. _distutils-intro:
****************************
An Introduction to Distutils
****************************
This document covers using the Distutils to distribute your Python modules,
concentrating on the role of developer/distributor: if you're looking for
information on installing Python modules, you should refer to the
:ref:`install-index` chapter.
.. _distutils-concepts:
Concepts & Terminology
======================
Using the Distutils is quite simple, both for module developers and for
users/administrators installing third-party modules. As a developer, your
responsibilities (apart from writing solid, well-documented and well-tested
code, of course!) are:
* write a setup script (:file:`setup.py` by convention)
* (optional) write a setup configuration file
* create a source distribution
* (optional) create one or more built (binary) distributions
Each of these tasks is covered in this document.
Not all module developers have access to a multitude of platforms, so it's not
always feasible to expect them to create a multitude of built distributions. It
is hoped that a class of intermediaries, called *packagers*, will arise to
address this need. Packagers will take source distributions released by module
developers, build them on one or more platforms, and release the resulting built
distributions. Thus, users on the most popular platforms will be able to
install most popular Python module distributions in the most natural way for
their platform, without having to run a single setup script or compile a line of
code.
.. _distutils-simple-example:
A Simple Example
================
The setup script is usually quite simple, although since it's written in Python,
there are no arbitrary limits to what you can do with it, though you should be
careful about putting arbitrarily expensive operations in your setup script.
Unlike, say, Autoconf-style configure scripts, the setup script may be run
multiple times in the course of building and installing your module
distribution.
If all you want to do is distribute a module called :mod:`foo`, contained in a
file :file:`foo.py`, then your setup script can be as simple as this::
from distutils.core import setup
setup(name='foo',
version='1.0',
py_modules=['foo'],
)
Some observations:
* most information that you supply to the Distutils is supplied as keyword
arguments to the :func:`setup` function
* those keyword arguments fall into two categories: package metadata (name,
version number) and information about what's in the package (a list of pure
Python modules, in this case)
* modules are specified by module name, not filename (the same will hold true
for packages and extensions)
* it's recommended that you supply a little more metadata, in particular your
name, email address and a URL for the project (see section :ref:`setup-script`
for an example)
To create a source distribution for this module, you would create a setup
script, :file:`setup.py`, containing the above code, and run this command from a
terminal::
python setup.py sdist
For Windows, open a command prompt window (:menuselection:`Start -->
Accessories`) and change the command to::
setup.py sdist
:command:`sdist` will create an archive file (e.g., tarball on Unix, ZIP file on Windows)
containing your setup script :file:`setup.py`, and your module :file:`foo.py`.
The archive file will be named :file:`foo-1.0.tar.gz` (or :file:`.zip`), and
will unpack into a directory :file:`foo-1.0`.
If an end-user wishes to install your :mod:`foo` module, all they have to do is
download :file:`foo-1.0.tar.gz` (or :file:`.zip`), unpack it, and---from the
:file:`foo-1.0` directory---run ::
python setup.py install
which will ultimately copy :file:`foo.py` to the appropriate directory for
third-party modules in their Python installation.
This simple example demonstrates some fundamental concepts of the Distutils.
First, both developers and installers have the same basic user interface, i.e.
the setup script. The difference is which Distutils *commands* they use: the
:command:`sdist` command is almost exclusively for module developers, while
:command:`install` is more often for installers (although most developers will
want to install their own code occasionally).
If you want to make things really easy for your users, you can create one or
more built distributions for them. For instance, if you are running on a
Windows machine, and want to make things easy for other Windows users, you can
create an executable installer (the most appropriate type of built distribution
for this platform) with the :command:`bdist_wininst` command. For example::
python setup.py bdist_wininst
will create an executable installer, :file:`foo-1.0.win32.exe`, in the current
directory.
Other useful built distribution formats are RPM, implemented by the
:command:`bdist_rpm` command, Solaris :program:`pkgtool`
(:command:`bdist_pkgtool`), and HP-UX :program:`swinstall`
(:command:`bdist_sdux`). For example, the following command will create an RPM
file called :file:`foo-1.0.noarch.rpm`::
python setup.py bdist_rpm
(The :command:`bdist_rpm` command uses the :command:`rpm` executable, therefore
this has to be run on an RPM-based system such as Red Hat Linux, SuSE Linux, or
Mandrake Linux.)
You can find out what distribution formats are available at any time by running
::
python setup.py bdist --help-formats
.. _python-terms:
General Python terminology
==========================
If you're reading this document, you probably have a good idea of what modules,
extensions, and so forth are. Nevertheless, just to be sure that everyone is
operating from a common starting point, we offer the following glossary of
common Python terms:
module
the basic unit of code reusability in Python: a block of code imported by some
other code. Three types of modules concern us here: pure Python modules,
extension modules, and packages.
pure Python module
a module written in Python and contained in a single :file:`.py` file (and
possibly associated :file:`.pyc` files). Sometimes referred to as a
"pure module."
extension module
a module written in the low-level language of the Python implementation: C/C++
for Python, Java for Jython. Typically contained in a single dynamically
loadable pre-compiled file, e.g. a shared object (:file:`.so`) file for Python
extensions on Unix, a DLL (given the :file:`.pyd` extension) for Python
extensions on Windows, or a Java class file for Jython extensions. (Note that
currently, the Distutils only handles C/C++ extensions for Python.)
package
a module that contains other modules; typically contained in a directory in the
filesystem and distinguished from other directories by the presence of a file
:file:`__init__.py`.
root package
the root of the hierarchy of packages. (This isn't really a package, since it
doesn't have an :file:`__init__.py` file. But we have to call it something.)
The vast majority of the standard library is in the root package, as are many
small, standalone third-party modules that don't belong to a larger module
collection. Unlike regular packages, modules in the root package can be found in
many directories: in fact, every directory listed in ``sys.path`` contributes
modules to the root package.
.. _distutils-term:
Distutils-specific terminology
==============================
The following terms apply more specifically to the domain of distributing Python
modules using the Distutils:
module distribution
a collection of Python modules distributed together as a single downloadable
resource and meant to be installed *en masse*. Examples of some well-known
module distributions are NumPy, SciPy, Pillow,
or mxBase. (This would be called a *package*, except that term is
already taken in the Python context: a single module distribution may contain
zero, one, or many Python packages.)
pure module distribution
a module distribution that contains only pure Python modules and packages.
Sometimes referred to as a "pure distribution."
non-pure module distribution
a module distribution that contains at least one extension module. Sometimes
referred to as a "non-pure distribution."
distribution root
the top-level directory of your source tree (or source distribution); the
directory where :file:`setup.py` exists. Generally :file:`setup.py` will be
run from this directory.

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.. index::
single: Python Package Index (PyPI)
single: PyPI; (see Python Package Index (PyPI))
.. _package-index:
*******************************
The Python Package Index (PyPI)
*******************************
The `Python Package Index (PyPI)`_ stores :ref:`meta-data <meta-data>`
describing distributions packaged with distutils, as well as package data like
distribution files if a package author wishes.
Distutils provides the :command:`register` and :command:`upload` commands for
pushing meta-data and distribution files to PyPI, respectively. See
:ref:`package-commands` for information on these commands.
PyPI overview
=============
PyPI lets you submit any number of versions of your distribution to the index.
If you alter the meta-data for a particular version, you can submit it again
and the index will be updated.
PyPI holds a record for each (name, version) combination submitted. The first
user to submit information for a given name is designated the Owner of that
name. Changes can be submitted through the :command:`register` command or
through the web interface. Owners can designate other users as Owners or
Maintainers. Maintainers can edit the package information, but not designate
new Owners or Maintainers.
By default PyPI displays only the newest version of a given package. The web
interface lets one change this default behavior and manually select which
versions to display and hide.
For each version, PyPI displays a home page. The home page is created from
the ``long_description`` which can be submitted via the :command:`register`
command. See :ref:`package-display` for more information.
.. _package-commands:
Distutils commands
==================
Distutils exposes two commands for submitting package data to PyPI: the
:ref:`register <package-register>` command for submitting meta-data to PyPI
and the :ref:`upload <package-upload>` command for submitting distribution
files. Both commands read configuration data from a special file called a
:ref:`.pypirc file <pypirc>`.
.. _package-register:
The ``register`` command
------------------------
The distutils command :command:`register` is used to submit your distribution's
meta-data to an index server. It is invoked as follows::
python setup.py register
Distutils will respond with the following prompt::
running register
We need to know who you are, so please choose either:
1. use your existing login,
2. register as a new user,
3. have the server generate a new password for you (and email it to you), or
4. quit
Your selection [default 1]:
Note: if your username and password are saved locally, you will not see this
menu. Also, refer to :ref:`pypirc` for how to store your credentials in a
:file:`.pypirc` file.
If you have not registered with PyPI, then you will need to do so now. You
should choose option 2, and enter your details as required. Soon after
submitting your details, you will receive an email which will be used to confirm
your registration.
Once you are registered, you may choose option 1 from the menu. You will be
prompted for your PyPI username and password, and :command:`register` will then
submit your meta-data to the index.
See :ref:`package-cmdoptions` for options to the :command:`register` command.
.. _package-upload:
The ``upload`` command
----------------------
The distutils command :command:`upload` pushes the distribution files to PyPI.
The command is invoked immediately after building one or more distribution
files. For example, the command ::
python setup.py sdist bdist_wininst upload
will cause the source distribution and the Windows installer to be uploaded to
PyPI. Note that these will be uploaded even if they are built using an earlier
invocation of :file:`setup.py`, but that only distributions named on the command
line for the invocation including the :command:`upload` command are uploaded.
If a :command:`register` command was previously called in the same command,
and if the password was entered in the prompt, :command:`upload` will reuse the
entered password. This is useful if you do not want to store a password in
clear text in a :file:`.pypirc` file.
You can use the ``--sign`` option to tell :command:`upload` to sign each
uploaded file using GPG (GNU Privacy Guard). The :program:`gpg` program must
be available for execution on the system :envvar:`PATH`. You can also specify
which key to use for signing using the ``--identity=name`` option.
See :ref:`package-cmdoptions` for additional options to the :command:`upload`
command.
.. _package-cmdoptions:
Additional command options
--------------------------
This section describes options common to both the :command:`register` and
:command:`upload` commands.
The ``--repository`` or ``-r`` option lets you specify a PyPI server
different from the default. For example::
python setup.py sdist bdist_wininst upload -r https://example.com/pypi
For convenience, a name can be used in place of the URL when the
:file:`.pypirc` file is configured to do so. For example::
python setup.py register -r other
See :ref:`pypirc` for more information on defining alternate servers.
The ``--show-response`` option displays the full response text from the PyPI
server, which is useful when debugging problems with registering and uploading.
.. index::
single: .pypirc file
single: Python Package Index (PyPI); .pypirc file
.. _pypirc:
The ``.pypirc`` file
--------------------
The :command:`register` and :command:`upload` commands both check for the
existence of a :file:`.pypirc` file at the location :file:`$HOME/.pypirc`.
If this file exists, the command uses the username, password, and repository
URL configured in the file. The format of a :file:`.pypirc` file is as
follows:
.. code-block:: ini
[distutils]
index-servers =
pypi
[pypi]
repository: <repository-url>
username: <username>
password: <password>
The *distutils* section defines an *index-servers* variable that lists the
name of all sections describing a repository.
Each section describing a repository defines three variables:
- *repository*, that defines the url of the PyPI server. Defaults to
``https://upload.pypi.org/legacy/``.
- *username*, which is the registered username on the PyPI server.
- *password*, that will be used to authenticate. If omitted the user
will be prompt to type it when needed.
If you want to define another server a new section can be created and
listed in the *index-servers* variable:
.. code-block:: ini
[distutils]
index-servers =
pypi
other
[pypi]
repository: <repository-url>
username: <username>
password: <password>
[other]
repository: https://example.com/pypi
username: <username>
password: <password>
This allows the :command:`register` and :command:`upload` commands to be
called with the ``--repository`` option as described in
:ref:`package-cmdoptions`.
Specifically, you might want to add the `PyPI Test Repository
<https://wiki.python.org/moin/TestPyPI>`_ to your ``.pypirc`` to facilitate
testing before doing your first upload to ``PyPI`` itself.
.. _package-display:
PyPI package display
====================
The ``long_description`` field plays a special role at PyPI. It is used by
the server to display a home page for the registered package.
If you use the `reStructuredText <http://docutils.sourceforge.net/rst.html>`_
syntax for this field, PyPI will parse it and display an HTML output for
the package home page.
The ``long_description`` field can be attached to a text file located
in the package::
from distutils.core import setup
with open('README.txt') as file:
long_description = file.read()
setup(name='Distutils',
long_description=long_description)
In that case, :file:`README.txt` is a regular reStructuredText text file located
in the root of the package besides :file:`setup.py`.
To prevent registering broken reStructuredText content, you can use the
:program:`rst2html` program that is provided by the :mod:`docutils` package and
check the ``long_description`` from the command line:
.. code-block:: shell-session
$ python setup.py --long-description | rst2html.py > output.html
:mod:`docutils` will display a warning if there's something wrong with your
syntax. Because PyPI applies additional checks (e.g. by passing ``--no-raw``
to ``rst2html.py`` in the command above), being able to run the command above
without warnings does not guarantee that PyPI will convert the content
successfully.
.. _Python Package Index (PyPI): https://pypi.org

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.. _setup-script:
************************
Writing the Setup Script
************************
The setup script is the centre of all activity in building, distributing, and
installing modules using the Distutils. The main purpose of the setup script is
to describe your module distribution to the Distutils, so that the various
commands that operate on your modules do the right thing. As we saw in section
:ref:`distutils-simple-example` above, the setup script consists mainly of a call to
:func:`setup`, and most information supplied to the Distutils by the module
developer is supplied as keyword arguments to :func:`setup`.
Here's a slightly more involved example, which we'll follow for the next couple
of sections: the Distutils' own setup script. (Keep in mind that although the
Distutils are included with Python 1.6 and later, they also have an independent
existence so that Python 1.5.2 users can use them to install other module
distributions. The Distutils' own setup script, shown here, is used to install
the package into Python 1.5.2.) ::
#!/usr/bin/env python
from distutils.core import setup
setup(name='Distutils',
version='1.0',
description='Python Distribution Utilities',
author='Greg Ward',
author_email='gward@python.net',
url='https://www.python.org/sigs/distutils-sig/',
packages=['distutils', 'distutils.command'],
)
There are only two differences between this and the trivial one-file
distribution presented in section :ref:`distutils-simple-example`: more metadata, and the
specification of pure Python modules by package, rather than by module. This is
important since the Distutils consist of a couple of dozen modules split into
(so far) two packages; an explicit list of every module would be tedious to
generate and difficult to maintain. For more information on the additional
meta-data, see section :ref:`meta-data`.
Note that any pathnames (files or directories) supplied in the setup script
should be written using the Unix convention, i.e. slash-separated. The
Distutils will take care of converting this platform-neutral representation into
whatever is appropriate on your current platform before actually using the
pathname. This makes your setup script portable across operating systems, which
of course is one of the major goals of the Distutils. In this spirit, all
pathnames in this document are slash-separated.
This, of course, only applies to pathnames given to Distutils functions. If
you, for example, use standard Python functions such as :func:`glob.glob` or
:func:`os.listdir` to specify files, you should be careful to write portable
code instead of hardcoding path separators::
glob.glob(os.path.join('mydir', 'subdir', '*.html'))
os.listdir(os.path.join('mydir', 'subdir'))
.. _listing-packages:
Listing whole packages
======================
The ``packages`` option tells the Distutils to process (build, distribute,
install, etc.) all pure Python modules found in each package mentioned in the
``packages`` list. In order to do this, of course, there has to be a
correspondence between package names and directories in the filesystem. The
default correspondence is the most obvious one, i.e. package :mod:`distutils` is
found in the directory :file:`distutils` relative to the distribution root.
Thus, when you say ``packages = ['foo']`` in your setup script, you are
promising that the Distutils will find a file :file:`foo/__init__.py` (which
might be spelled differently on your system, but you get the idea) relative to
the directory where your setup script lives. If you break this promise, the
Distutils will issue a warning but still process the broken package anyway.
If you use a different convention to lay out your source directory, that's no
problem: you just have to supply the ``package_dir`` option to tell the
Distutils about your convention. For example, say you keep all Python source
under :file:`lib`, so that modules in the "root package" (i.e., not in any
package at all) are in :file:`lib`, modules in the :mod:`foo` package are in
:file:`lib/foo`, and so forth. Then you would put ::
package_dir = {'': 'lib'}
in your setup script. The keys to this dictionary are package names, and an
empty package name stands for the root package. The values are directory names
relative to your distribution root. In this case, when you say ``packages =
['foo']``, you are promising that the file :file:`lib/foo/__init__.py` exists.
Another possible convention is to put the :mod:`foo` package right in
:file:`lib`, the :mod:`foo.bar` package in :file:`lib/bar`, etc. This would be
written in the setup script as ::
package_dir = {'foo': 'lib'}
A ``package: dir`` entry in the ``package_dir`` dictionary implicitly
applies to all packages below *package*, so the :mod:`foo.bar` case is
automatically handled here. In this example, having ``packages = ['foo',
'foo.bar']`` tells the Distutils to look for :file:`lib/__init__.py` and
:file:`lib/bar/__init__.py`. (Keep in mind that although ``package_dir``
applies recursively, you must explicitly list all packages in
``packages``: the Distutils will *not* recursively scan your source tree
looking for any directory with an :file:`__init__.py` file.)
.. _listing-modules:
Listing individual modules
==========================
For a small module distribution, you might prefer to list all modules rather
than listing packages---especially the case of a single module that goes in the
"root package" (i.e., no package at all). This simplest case was shown in
section :ref:`distutils-simple-example`; here is a slightly more involved example::
py_modules = ['mod1', 'pkg.mod2']
This describes two modules, one of them in the "root" package, the other in the
:mod:`pkg` package. Again, the default package/directory layout implies that
these two modules can be found in :file:`mod1.py` and :file:`pkg/mod2.py`, and
that :file:`pkg/__init__.py` exists as well. And again, you can override the
package/directory correspondence using the ``package_dir`` option.
.. _describing-extensions:
Describing extension modules
============================
Just as writing Python extension modules is a bit more complicated than writing
pure Python modules, describing them to the Distutils is a bit more complicated.
Unlike pure modules, it's not enough just to list modules or packages and expect
the Distutils to go out and find the right files; you have to specify the
extension name, source file(s), and any compile/link requirements (include
directories, libraries to link with, etc.).
.. XXX read over this section
All of this is done through another keyword argument to :func:`setup`, the
``ext_modules`` option. ``ext_modules`` is just a list of
:class:`~distutils.core.Extension` instances, each of which describes a
single extension module.
Suppose your distribution includes a single extension, called :mod:`foo` and
implemented by :file:`foo.c`. If no additional instructions to the
compiler/linker are needed, describing this extension is quite simple::
Extension('foo', ['foo.c'])
The :class:`Extension` class can be imported from :mod:`distutils.core` along
with :func:`setup`. Thus, the setup script for a module distribution that
contains only this one extension and nothing else might be::
from distutils.core import setup, Extension
setup(name='foo',
version='1.0',
ext_modules=[Extension('foo', ['foo.c'])],
)
The :class:`Extension` class (actually, the underlying extension-building
machinery implemented by the :command:`build_ext` command) supports a great deal
of flexibility in describing Python extensions, which is explained in the
following sections.
Extension names and packages
----------------------------
The first argument to the :class:`~distutils.core.Extension` constructor is
always the name of the extension, including any package names. For example, ::
Extension('foo', ['src/foo1.c', 'src/foo2.c'])
describes an extension that lives in the root package, while ::
Extension('pkg.foo', ['src/foo1.c', 'src/foo2.c'])
describes the same extension in the :mod:`pkg` package. The source files and
resulting object code are identical in both cases; the only difference is where
in the filesystem (and therefore where in Python's namespace hierarchy) the
resulting extension lives.
If you have a number of extensions all in the same package (or all under the
same base package), use the ``ext_package`` keyword argument to
:func:`setup`. For example, ::
setup(...,
ext_package='pkg',
ext_modules=[Extension('foo', ['foo.c']),
Extension('subpkg.bar', ['bar.c'])],
)
will compile :file:`foo.c` to the extension :mod:`pkg.foo`, and :file:`bar.c` to
:mod:`pkg.subpkg.bar`.
Extension source files
----------------------
The second argument to the :class:`~distutils.core.Extension` constructor is
a list of source
files. Since the Distutils currently only support C, C++, and Objective-C
extensions, these are normally C/C++/Objective-C source files. (Be sure to use
appropriate extensions to distinguish C++ source files: :file:`.cc` and
:file:`.cpp` seem to be recognized by both Unix and Windows compilers.)
However, you can also include SWIG interface (:file:`.i`) files in the list; the
:command:`build_ext` command knows how to deal with SWIG extensions: it will run
SWIG on the interface file and compile the resulting C/C++ file into your
extension.
.. XXX SWIG support is rough around the edges and largely untested!
This warning notwithstanding, options to SWIG can be currently passed like
this::
setup(...,
ext_modules=[Extension('_foo', ['foo.i'],
swig_opts=['-modern', '-I../include'])],
py_modules=['foo'],
)
Or on the commandline like this::
> python setup.py build_ext --swig-opts="-modern -I../include"
On some platforms, you can include non-source files that are processed by the
compiler and included in your extension. Currently, this just means Windows
message text (:file:`.mc`) files and resource definition (:file:`.rc`) files for
Visual C++. These will be compiled to binary resource (:file:`.res`) files and
linked into the executable.
Preprocessor options
--------------------
Three optional arguments to :class:`~distutils.core.Extension` will help if
you need to specify include directories to search or preprocessor macros to
define/undefine: ``include_dirs``, ``define_macros``, and ``undef_macros``.
For example, if your extension requires header files in the :file:`include`
directory under your distribution root, use the ``include_dirs`` option::
Extension('foo', ['foo.c'], include_dirs=['include'])
You can specify absolute directories there; if you know that your extension will
only be built on Unix systems with X11R6 installed to :file:`/usr`, you can get
away with ::
Extension('foo', ['foo.c'], include_dirs=['/usr/include/X11'])
You should avoid this sort of non-portable usage if you plan to distribute your
code: it's probably better to write C code like ::
#include <X11/Xlib.h>
If you need to include header files from some other Python extension, you can
take advantage of the fact that header files are installed in a consistent way
by the Distutils :command:`install_headers` command. For example, the Numerical
Python header files are installed (on a standard Unix installation) to
:file:`/usr/local/include/python1.5/Numerical`. (The exact location will differ
according to your platform and Python installation.) Since the Python include
directory---\ :file:`/usr/local/include/python1.5` in this case---is always
included in the search path when building Python extensions, the best approach
is to write C code like ::
#include <Numerical/arrayobject.h>
If you must put the :file:`Numerical` include directory right into your header
search path, though, you can find that directory using the Distutils
:mod:`distutils.sysconfig` module::
from distutils.sysconfig import get_python_inc
incdir = os.path.join(get_python_inc(plat_specific=1), 'Numerical')
setup(...,
Extension(..., include_dirs=[incdir]),
)
Even though this is quite portable---it will work on any Python installation,
regardless of platform---it's probably easier to just write your C code in the
sensible way.
You can define and undefine pre-processor macros with the ``define_macros`` and
``undef_macros`` options. ``define_macros`` takes a list of ``(name, value)``
tuples, where ``name`` is the name of the macro to define (a string) and
``value`` is its value: either a string or ``None``. (Defining a macro ``FOO``
to ``None`` is the equivalent of a bare ``#define FOO`` in your C source: with
most compilers, this sets ``FOO`` to the string ``1``.) ``undef_macros`` is
just a list of macros to undefine.
For example::
Extension(...,
define_macros=[('NDEBUG', '1'),
('HAVE_STRFTIME', None)],
undef_macros=['HAVE_FOO', 'HAVE_BAR'])
is the equivalent of having this at the top of every C source file::
#define NDEBUG 1
#define HAVE_STRFTIME
#undef HAVE_FOO
#undef HAVE_BAR
Library options
---------------
You can also specify the libraries to link against when building your extension,
and the directories to search for those libraries. The ``libraries`` option is
a list of libraries to link against, ``library_dirs`` is a list of directories
to search for libraries at link-time, and ``runtime_library_dirs`` is a list of
directories to search for shared (dynamically loaded) libraries at run-time.
For example, if you need to link against libraries known to be in the standard
library search path on target systems ::
Extension(...,
libraries=['gdbm', 'readline'])
If you need to link with libraries in a non-standard location, you'll have to
include the location in ``library_dirs``::
Extension(...,
library_dirs=['/usr/X11R6/lib'],
libraries=['X11', 'Xt'])
(Again, this sort of non-portable construct should be avoided if you intend to
distribute your code.)
.. XXX Should mention clib libraries here or somewhere else!
Other options
-------------
There are still some other options which can be used to handle special cases.
The ``optional`` option is a boolean; if it is true,
a build failure in the extension will not abort the build process, but
instead simply not install the failing extension.
The ``extra_objects`` option is a list of object files to be passed to the
linker. These files must not have extensions, as the default extension for the
compiler is used.
``extra_compile_args`` and ``extra_link_args`` can be used to
specify additional command line options for the respective compiler and linker
command lines.
``export_symbols`` is only useful on Windows. It can contain a list of
symbols (functions or variables) to be exported. This option is not needed when
building compiled extensions: Distutils will automatically add ``initmodule``
to the list of exported symbols.
The ``depends`` option is a list of files that the extension depends on
(for example header files). The build command will call the compiler on the
sources to rebuild extension if any on this files has been modified since the
previous build.
Relationships between Distributions and Packages
================================================
A distribution may relate to packages in three specific ways:
#. It can require packages or modules.
#. It can provide packages or modules.
#. It can obsolete packages or modules.
These relationships can be specified using keyword arguments to the
:func:`distutils.core.setup` function.
Dependencies on other Python modules and packages can be specified by supplying
the *requires* keyword argument to :func:`setup`. The value must be a list of
strings. Each string specifies a package that is required, and optionally what
versions are sufficient.
To specify that any version of a module or package is required, the string
should consist entirely of the module or package name. Examples include
``'mymodule'`` and ``'xml.parsers.expat'``.
If specific versions are required, a sequence of qualifiers can be supplied in
parentheses. Each qualifier may consist of a comparison operator and a version
number. The accepted comparison operators are::
< > ==
<= >= !=
These can be combined by using multiple qualifiers separated by commas (and
optional whitespace). In this case, all of the qualifiers must be matched; a
logical AND is used to combine the evaluations.
Let's look at a bunch of examples:
+-------------------------+----------------------------------------------+
| Requires Expression | Explanation |
+=========================+==============================================+
| ``==1.0`` | Only version ``1.0`` is compatible |
+-------------------------+----------------------------------------------+
| ``>1.0, !=1.5.1, <2.0`` | Any version after ``1.0`` and before ``2.0`` |
| | is compatible, except ``1.5.1`` |
+-------------------------+----------------------------------------------+
Now that we can specify dependencies, we also need to be able to specify what we
provide that other distributions can require. This is done using the *provides*
keyword argument to :func:`setup`. The value for this keyword is a list of
strings, each of which names a Python module or package, and optionally
identifies the version. If the version is not specified, it is assumed to match
that of the distribution.
Some examples:
+---------------------+----------------------------------------------+
| Provides Expression | Explanation |
+=====================+==============================================+
| ``mypkg`` | Provide ``mypkg``, using the distribution |
| | version |
+---------------------+----------------------------------------------+
| ``mypkg (1.1)`` | Provide ``mypkg`` version 1.1, regardless of |
| | the distribution version |
+---------------------+----------------------------------------------+
A package can declare that it obsoletes other packages using the *obsoletes*
keyword argument. The value for this is similar to that of the *requires*
keyword: a list of strings giving module or package specifiers. Each specifier
consists of a module or package name optionally followed by one or more version
qualifiers. Version qualifiers are given in parentheses after the module or
package name.
The versions identified by the qualifiers are those that are obsoleted by the
distribution being described. If no qualifiers are given, all versions of the
named module or package are understood to be obsoleted.
.. _distutils-installing-scripts:
Installing Scripts
==================
So far we have been dealing with pure and non-pure Python modules, which are
usually not run by themselves but imported by scripts.
Scripts are files containing Python source code, intended to be started from the
command line. Scripts don't require Distutils to do anything very complicated.
The only clever feature is that if the first line of the script starts with
``#!`` and contains the word "python", the Distutils will adjust the first line
to refer to the current interpreter location. By default, it is replaced with
the current interpreter location. The :option:`!--executable` (or :option:`!-e`)
option will allow the interpreter path to be explicitly overridden.
The ``scripts`` option simply is a list of files to be handled in this
way. From the PyXML setup script::
setup(...,
scripts=['scripts/xmlproc_parse', 'scripts/xmlproc_val']
)
.. versionchanged:: 3.1
All the scripts will also be added to the ``MANIFEST`` file if no template is
provided. See :ref:`manifest`.
.. _distutils-installing-package-data:
Installing Package Data
=======================
Often, additional files need to be installed into a package. These files are
often data that's closely related to the package's implementation, or text files
containing documentation that might be of interest to programmers using the
package. These files are called :dfn:`package data`.
Package data can be added to packages using the ``package_data`` keyword
argument to the :func:`setup` function. The value must be a mapping from
package name to a list of relative path names that should be copied into the
package. The paths are interpreted as relative to the directory containing the
package (information from the ``package_dir`` mapping is used if appropriate);
that is, the files are expected to be part of the package in the source
directories. They may contain glob patterns as well.
The path names may contain directory portions; any necessary directories will be
created in the installation.
For example, if a package should contain a subdirectory with several data files,
the files can be arranged like this in the source tree::
setup.py
src/
mypkg/
__init__.py
module.py
data/
tables.dat
spoons.dat
forks.dat
The corresponding call to :func:`setup` might be::
setup(...,
packages=['mypkg'],
package_dir={'mypkg': 'src/mypkg'},
package_data={'mypkg': ['data/*.dat']},
)
.. versionchanged:: 3.1
All the files that match ``package_data`` will be added to the ``MANIFEST``
file if no template is provided. See :ref:`manifest`.
.. _distutils-additional-files:
Installing Additional Files
===========================
The ``data_files`` option can be used to specify additional files needed
by the module distribution: configuration files, message catalogs, data files,
anything which doesn't fit in the previous categories.
``data_files`` specifies a sequence of (*directory*, *files*) pairs in the
following way::
setup(...,
data_files=[('bitmaps', ['bm/b1.gif', 'bm/b2.gif']),
('config', ['cfg/data.cfg']),
('/etc/init.d', ['init-script'])]
)
Note that you can specify the directory names where the data files will be
installed, but you cannot rename the data files themselves.
Each (*directory*, *files*) pair in the sequence specifies the installation
directory and the files to install there. If *directory* is a relative path, it
is interpreted relative to the installation prefix (Python's ``sys.prefix`` for
pure-Python packages, ``sys.exec_prefix`` for packages that contain extension
modules). Each file name in *files* is interpreted relative to the
:file:`setup.py` script at the top of the package source distribution. No
directory information from *files* is used to determine the final location of
the installed file; only the name of the file is used.
You can specify the ``data_files`` options as a simple sequence of files
without specifying a target directory, but this is not recommended, and the
:command:`install` command will print a warning in this case. To install data
files directly in the target directory, an empty string should be given as the
directory.
.. versionchanged:: 3.1
All the files that match ``data_files`` will be added to the ``MANIFEST``
file if no template is provided. See :ref:`manifest`.
.. _meta-data:
Additional meta-data
====================
The setup script may include additional meta-data beyond the name and version.
This information includes:
+----------------------+---------------------------+-----------------+--------+
| Meta-Data | Description | Value | Notes |
+======================+===========================+=================+========+
| ``name`` | name of the package | short string | \(1) |
+----------------------+---------------------------+-----------------+--------+
| ``version`` | version of this release | short string | (1)(2) |
+----------------------+---------------------------+-----------------+--------+
| ``author`` | package author's name | short string | \(3) |
+----------------------+---------------------------+-----------------+--------+
| ``author_email`` | email address of the | email address | \(3) |
| | package author | | |
+----------------------+---------------------------+-----------------+--------+
| ``maintainer`` | package maintainer's name | short string | \(3) |
+----------------------+---------------------------+-----------------+--------+
| ``maintainer_email`` | email address of the | email address | \(3) |
| | package maintainer | | |
+----------------------+---------------------------+-----------------+--------+
| ``url`` | home page for the package | URL | \(1) |
+----------------------+---------------------------+-----------------+--------+
| ``description`` | short, summary | short string | |
| | description of the | | |
| | package | | |
+----------------------+---------------------------+-----------------+--------+
| ``long_description`` | longer description of the | long string | \(5) |
| | package | | |
+----------------------+---------------------------+-----------------+--------+
| ``download_url`` | location where the | URL | \(4) |
| | package may be downloaded | | |
+----------------------+---------------------------+-----------------+--------+
| ``classifiers`` | a list of classifiers | list of strings | \(4) |
+----------------------+---------------------------+-----------------+--------+
| ``platforms`` | a list of platforms | list of strings | |
+----------------------+---------------------------+-----------------+--------+
| ``license`` | license for the package | short string | \(6) |
+----------------------+---------------------------+-----------------+--------+
Notes:
(1)
These fields are required.
(2)
It is recommended that versions take the form *major.minor[.patch[.sub]]*.
(3)
Either the author or the maintainer must be identified. If maintainer is
provided, distutils lists it as the author in :file:`PKG-INFO`.
(4)
These fields should not be used if your package is to be compatible with Python
versions prior to 2.2.3 or 2.3. The list is available from the `PyPI website
<https://pypi.org/>`_.
(5)
The ``long_description`` field is used by PyPI when you are
:ref:`registering <package-register>` a package, to
:ref:`build its home page <package-display>`.
(6)
The ``license`` field is a text indicating the license covering the
package where the license is not a selection from the "License" Trove
classifiers. See the ``Classifier`` field. Notice that
there's a ``licence`` distribution option which is deprecated but still
acts as an alias for ``license``.
'short string'
A single line of text, not more than 200 characters.
'long string'
Multiple lines of plain text in reStructuredText format (see
http://docutils.sourceforge.net/).
'list of strings'
See below.
Encoding the version information is an art in itself. Python packages generally
adhere to the version format *major.minor[.patch][sub]*. The major number is 0
for initial, experimental releases of software. It is incremented for releases
that represent major milestones in a package. The minor number is incremented
when important new features are added to the package. The patch number
increments when bug-fix releases are made. Additional trailing version
information is sometimes used to indicate sub-releases. These are
"a1,a2,...,aN" (for alpha releases, where functionality and API may change),
"b1,b2,...,bN" (for beta releases, which only fix bugs) and "pr1,pr2,...,prN"
(for final pre-release release testing). Some examples:
0.1.0
the first, experimental release of a package
1.0.1a2
the second alpha release of the first patch version of 1.0
``classifiers`` are specified in a Python list::
setup(...,
classifiers=[
'Development Status :: 4 - Beta',
'Environment :: Console',
'Environment :: Web Environment',
'Intended Audience :: End Users/Desktop',
'Intended Audience :: Developers',
'Intended Audience :: System Administrators',
'License :: OSI Approved :: Python Software Foundation License',
'Operating System :: MacOS :: MacOS X',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Programming Language :: Python',
'Topic :: Communications :: Email',
'Topic :: Office/Business',
'Topic :: Software Development :: Bug Tracking',
],
)
.. _debug-setup-script:
Debugging the setup script
==========================
Sometimes things go wrong, and the setup script doesn't do what the developer
wants.
Distutils catches any exceptions when running the setup script, and print a
simple error message before the script is terminated. The motivation for this
behaviour is to not confuse administrators who don't know much about Python and
are trying to install a package. If they get a big long traceback from deep
inside the guts of Distutils, they may think the package or the Python
installation is broken because they don't read all the way down to the bottom
and see that it's a permission problem.
On the other hand, this doesn't help the developer to find the cause of the
failure. For this purpose, the :envvar:`DISTUTILS_DEBUG` environment variable can be set
to anything except an empty string, and distutils will now print detailed
information about what it is doing, dump the full traceback when an exception
occurs, and print the whole command line when an external program (like a C
compiler) fails.

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.. _source-dist:
******************************
Creating a Source Distribution
******************************
As shown in section :ref:`distutils-simple-example`, you use the :command:`sdist` command
to create a source distribution. In the simplest case, ::
python setup.py sdist
(assuming you haven't specified any :command:`sdist` options in the setup script
or config file), :command:`sdist` creates the archive of the default format for
the current platform. The default format is a gzip'ed tar file
(:file:`.tar.gz`) on Unix, and ZIP file on Windows.
You can specify as many formats as you like using the :option:`!--formats`
option, for example::
python setup.py sdist --formats=gztar,zip
to create a gzipped tarball and a zip file. The available formats are:
+-----------+-------------------------+---------+
| Format | Description | Notes |
+===========+=========================+=========+
| ``zip`` | zip file (:file:`.zip`) | (1),(3) |
+-----------+-------------------------+---------+
| ``gztar`` | gzip'ed tar file | \(2) |
| | (:file:`.tar.gz`) | |
+-----------+-------------------------+---------+
| ``bztar`` | bzip2'ed tar file | |
| | (:file:`.tar.bz2`) | |
+-----------+-------------------------+---------+
| ``xztar`` | xz'ed tar file | |
| | (:file:`.tar.xz`) | |
+-----------+-------------------------+---------+
| ``ztar`` | compressed tar file | \(4) |
| | (:file:`.tar.Z`) | |
+-----------+-------------------------+---------+
| ``tar`` | tar file (:file:`.tar`) | |
+-----------+-------------------------+---------+
.. versionchanged:: 3.5
Added support for the ``xztar`` format.
Notes:
(1)
default on Windows
(2)
default on Unix
(3)
requires either external :program:`zip` utility or :mod:`zipfile` module (part
of the standard Python library since Python 1.6)
(4)
requires the :program:`compress` program. Notice that this format is now
pending for deprecation and will be removed in the future versions of Python.
When using any ``tar`` format (``gztar``, ``bztar``, ``xztar``, ``ztar`` or
``tar``), under Unix you can specify the ``owner`` and ``group`` names
that will be set for each member of the archive.
For example, if you want all files of the archive to be owned by root::
python setup.py sdist --owner=root --group=root
.. _manifest:
Specifying the files to distribute
==================================
If you don't supply an explicit list of files (or instructions on how to
generate one), the :command:`sdist` command puts a minimal default set into the
source distribution:
* all Python source files implied by the ``py_modules`` and
``packages`` options
* all C source files mentioned in the ``ext_modules`` or
``libraries`` options
.. XXX getting C library sources currently broken---no
:meth:`get_source_files` method in :file:`build_clib.py`!
* scripts identified by the ``scripts`` option
See :ref:`distutils-installing-scripts`.
* anything that looks like a test script: :file:`test/test\*.py` (currently, the
Distutils don't do anything with test scripts except include them in source
distributions, but in the future there will be a standard for testing Python
module distributions)
* :file:`README.txt` (or :file:`README`), :file:`setup.py` (or whatever you
called your setup script), and :file:`setup.cfg`
* all files that matches the ``package_data`` metadata.
See :ref:`distutils-installing-package-data`.
* all files that matches the ``data_files`` metadata.
See :ref:`distutils-additional-files`.
Sometimes this is enough, but usually you will want to specify additional files
to distribute. The typical way to do this is to write a *manifest template*,
called :file:`MANIFEST.in` by default. The manifest template is just a list of
instructions for how to generate your manifest file, :file:`MANIFEST`, which is
the exact list of files to include in your source distribution. The
:command:`sdist` command processes this template and generates a manifest based
on its instructions and what it finds in the filesystem.
If you prefer to roll your own manifest file, the format is simple: one filename
per line, regular files (or symlinks to them) only. If you do supply your own
:file:`MANIFEST`, you must specify everything: the default set of files
described above does not apply in this case.
.. versionchanged:: 3.1
An existing generated :file:`MANIFEST` will be regenerated without
:command:`sdist` comparing its modification time to the one of
:file:`MANIFEST.in` or :file:`setup.py`.
.. versionchanged:: 3.1.3
:file:`MANIFEST` files start with a comment indicating they are generated.
Files without this comment are not overwritten or removed.
.. versionchanged:: 3.2.2
:command:`sdist` will read a :file:`MANIFEST` file if no :file:`MANIFEST.in`
exists, like it used to do.
The manifest template has one command per line, where each command specifies a
set of files to include or exclude from the source distribution. For an
example, again we turn to the Distutils' own manifest template:
.. code-block:: none
include *.txt
recursive-include examples *.txt *.py
prune examples/sample?/build
The meanings should be fairly clear: include all files in the distribution root
matching :file:`\*.txt`, all files anywhere under the :file:`examples` directory
matching :file:`\*.txt` or :file:`\*.py`, and exclude all directories matching
:file:`examples/sample?/build`. All of this is done *after* the standard
include set, so you can exclude files from the standard set with explicit
instructions in the manifest template. (Or, you can use the
:option:`!--no-defaults` option to disable the standard set entirely.) There are
several other commands available in the manifest template mini-language; see
section :ref:`sdist-cmd`.
The order of commands in the manifest template matters: initially, we have the
list of default files as described above, and each command in the template adds
to or removes from that list of files. Once we have fully processed the
manifest template, we remove files that should not be included in the source
distribution:
* all files in the Distutils "build" tree (default :file:`build/`)
* all files in directories named :file:`RCS`, :file:`CVS`, :file:`.svn`,
:file:`.hg`, :file:`.git`, :file:`.bzr` or :file:`_darcs`
Now we have our complete list of files, which is written to the manifest for
future reference, and then used to build the source distribution archive(s).
You can disable the default set of included files with the
:option:`!--no-defaults` option, and you can disable the standard exclude set
with :option:`!--no-prune`.
Following the Distutils' own manifest template, let's trace how the
:command:`sdist` command builds the list of files to include in the Distutils
source distribution:
#. include all Python source files in the :file:`distutils` and
:file:`distutils/command` subdirectories (because packages corresponding to
those two directories were mentioned in the ``packages`` option in the
setup script---see section :ref:`setup-script`)
#. include :file:`README.txt`, :file:`setup.py`, and :file:`setup.cfg` (standard
files)
#. include :file:`test/test\*.py` (standard files)
#. include :file:`\*.txt` in the distribution root (this will find
:file:`README.txt` a second time, but such redundancies are weeded out later)
#. include anything matching :file:`\*.txt` or :file:`\*.py` in the sub-tree
under :file:`examples`,
#. exclude all files in the sub-trees starting at directories matching
:file:`examples/sample?/build`\ ---this may exclude files included by the
previous two steps, so it's important that the ``prune`` command in the manifest
template comes after the ``recursive-include`` command
#. exclude the entire :file:`build` tree, and any :file:`RCS`, :file:`CVS`,
:file:`.svn`, :file:`.hg`, :file:`.git`, :file:`.bzr` and :file:`_darcs`
directories
Just like in the setup script, file and directory names in the manifest template
should always be slash-separated; the Distutils will take care of converting
them to the standard representation on your platform. That way, the manifest
template is portable across operating systems.
.. _manifest-options:
Manifest-related options
========================
The normal course of operations for the :command:`sdist` command is as follows:
* if the manifest file (:file:`MANIFEST` by default) exists and the first line
does not have a comment indicating it is generated from :file:`MANIFEST.in`,
then it is used as is, unaltered
* if the manifest file doesn't exist or has been previously automatically
generated, read :file:`MANIFEST.in` and create the manifest
* if neither :file:`MANIFEST` nor :file:`MANIFEST.in` exist, create a manifest
with just the default file set
* use the list of files now in :file:`MANIFEST` (either just generated or read
in) to create the source distribution archive(s)
There are a couple of options that modify this behaviour. First, use the
:option:`!--no-defaults` and :option:`!--no-prune` to disable the standard
"include" and "exclude" sets.
Second, you might just want to (re)generate the manifest, but not create a source
distribution::
python setup.py sdist --manifest-only
:option:`!-o` is a shortcut for :option:`!--manifest-only`.

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:orphan:
***************************************
Uploading Packages to the Package Index
***************************************
The contents of this page have moved to the section :ref:`package-index`.

2
third_party/python/Doc/docutils.conf vendored Normal file
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[restructuredtext parser]
smartquotes-locales: ja: ""''

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.. highlightlang:: c
.. _building:
*****************************
Building C and C++ Extensions
*****************************
A C extension for CPython is a shared library (e.g. a ``.so`` file on Linux,
``.pyd`` on Windows), which exports an *initialization function*.
To be importable, the shared library must be available on :envvar:`PYTHONPATH`,
and must be named after the module name, with an appropriate extension.
When using distutils, the correct filename is generated automatically.
The initialization function has the signature:
.. c:function:: PyObject* PyInit_modulename(void)
It returns either a fully-initialized module, or a :c:type:`PyModuleDef`
instance. See :ref:`initializing-modules` for details.
.. highlightlang:: python
For modules with ASCII-only names, the function must be named
``PyInit_<modulename>``, with ``<modulename>`` replaced by the name of the
module. When using :ref:`multi-phase-initialization`, non-ASCII module names
are allowed. In this case, the initialization function name is
``PyInitU_<modulename>``, with ``<modulename>`` encoded using Python's
*punycode* encoding with hyphens replaced by underscores. In Python::
def initfunc_name(name):
try:
suffix = b'_' + name.encode('ascii')
except UnicodeEncodeError:
suffix = b'U_' + name.encode('punycode').replace(b'-', b'_')
return b'PyInit' + suffix
It is possible to export multiple modules from a single shared library by
defining multiple initialization functions. However, importing them requires
using symbolic links or a custom importer, because by default only the
function corresponding to the filename is found.
See the *"Multiple modules in one library"* section in :pep:`489` for details.
.. highlightlang:: c
Building C and C++ Extensions with distutils
============================================
.. sectionauthor:: Martin v. Löwis <martin@v.loewis.de>
Extension modules can be built using distutils, which is included in Python.
Since distutils also supports creation of binary packages, users don't
necessarily need a compiler and distutils to install the extension.
A distutils package contains a driver script, :file:`setup.py`. This is a plain
Python file, which, in the most simple case, could look like this:
.. code-block:: python3
from distutils.core import setup, Extension
module1 = Extension('demo',
sources = ['demo.c'])
setup (name = 'PackageName',
version = '1.0',
description = 'This is a demo package',
ext_modules = [module1])
With this :file:`setup.py`, and a file :file:`demo.c`, running ::
python setup.py build
will compile :file:`demo.c`, and produce an extension module named ``demo`` in
the :file:`build` directory. Depending on the system, the module file will end
up in a subdirectory :file:`build/lib.system`, and may have a name like
:file:`demo.so` or :file:`demo.pyd`.
In the :file:`setup.py`, all execution is performed by calling the ``setup``
function. This takes a variable number of keyword arguments, of which the
example above uses only a subset. Specifically, the example specifies
meta-information to build packages, and it specifies the contents of the
package. Normally, a package will contain additional modules, like Python
source modules, documentation, subpackages, etc. Please refer to the distutils
documentation in :ref:`distutils-index` to learn more about the features of
distutils; this section explains building extension modules only.
It is common to pre-compute arguments to :func:`setup`, to better structure the
driver script. In the example above, the ``ext_modules`` argument to
:func:`~distutils.core.setup` is a list of extension modules, each of which is
an instance of
the :class:`~distutils.extension.Extension`. In the example, the instance
defines an extension named ``demo`` which is build by compiling a single source
file, :file:`demo.c`.
In many cases, building an extension is more complex, since additional
preprocessor defines and libraries may be needed. This is demonstrated in the
example below.
.. code-block:: python3
from distutils.core import setup, Extension
module1 = Extension('demo',
define_macros = [('MAJOR_VERSION', '1'),
('MINOR_VERSION', '0')],
include_dirs = ['/usr/local/include'],
libraries = ['tcl83'],
library_dirs = ['/usr/local/lib'],
sources = ['demo.c'])
setup (name = 'PackageName',
version = '1.0',
description = 'This is a demo package',
author = 'Martin v. Loewis',
author_email = 'martin@v.loewis.de',
url = 'https://docs.python.org/extending/building',
long_description = '''
This is really just a demo package.
''',
ext_modules = [module1])
In this example, :func:`~distutils.core.setup` is called with additional
meta-information, which
is recommended when distribution packages have to be built. For the extension
itself, it specifies preprocessor defines, include directories, library
directories, and libraries. Depending on the compiler, distutils passes this
information in different ways to the compiler. For example, on Unix, this may
result in the compilation commands ::
gcc -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC -DMAJOR_VERSION=1 -DMINOR_VERSION=0 -I/usr/local/include -I/usr/local/include/python2.2 -c demo.c -o build/temp.linux-i686-2.2/demo.o
gcc -shared build/temp.linux-i686-2.2/demo.o -L/usr/local/lib -ltcl83 -o build/lib.linux-i686-2.2/demo.so
These lines are for demonstration purposes only; distutils users should trust
that distutils gets the invocations right.
.. _distributing:
Distributing your extension modules
===================================
When an extension has been successfully build, there are three ways to use it.
End-users will typically want to install the module, they do so by running ::
python setup.py install
Module maintainers should produce source packages; to do so, they run ::
python setup.py sdist
In some cases, additional files need to be included in a source distribution;
this is done through a :file:`MANIFEST.in` file; see :ref:`manifest` for details.
If the source distribution has been build successfully, maintainers can also
create binary distributions. Depending on the platform, one of the following
commands can be used to do so. ::
python setup.py bdist_wininst
python setup.py bdist_rpm
python setup.py bdist_dumb

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.. highlightlang:: c
.. _embedding:
***************************************
Embedding Python in Another Application
***************************************
The previous chapters discussed how to extend Python, that is, how to extend the
functionality of Python by attaching a library of C functions to it. It is also
possible to do it the other way around: enrich your C/C++ application by
embedding Python in it. Embedding provides your application with the ability to
implement some of the functionality of your application in Python rather than C
or C++. This can be used for many purposes; one example would be to allow users
to tailor the application to their needs by writing some scripts in Python. You
can also use it yourself if some of the functionality can be written in Python
more easily.
Embedding Python is similar to extending it, but not quite. The difference is
that when you extend Python, the main program of the application is still the
Python interpreter, while if you embed Python, the main program may have nothing
to do with Python --- instead, some parts of the application occasionally call
the Python interpreter to run some Python code.
So if you are embedding Python, you are providing your own main program. One of
the things this main program has to do is initialize the Python interpreter. At
the very least, you have to call the function :c:func:`Py_Initialize`. There are
optional calls to pass command line arguments to Python. Then later you can
call the interpreter from any part of the application.
There are several different ways to call the interpreter: you can pass a string
containing Python statements to :c:func:`PyRun_SimpleString`, or you can pass a
stdio file pointer and a file name (for identification in error messages only)
to :c:func:`PyRun_SimpleFile`. You can also call the lower-level operations
described in the previous chapters to construct and use Python objects.
.. seealso::
:ref:`c-api-index`
The details of Python's C interface are given in this manual. A great deal of
necessary information can be found here.
.. _high-level-embedding:
Very High Level Embedding
=========================
The simplest form of embedding Python is the use of the very high level
interface. This interface is intended to execute a Python script without needing
to interact with the application directly. This can for example be used to
perform some operation on a file. ::
#include <Python.h>
int
main(int argc, char *argv[])
{
wchar_t *program = Py_DecodeLocale(argv[0], NULL);
if (program == NULL) {
fprintf(stderr, "Fatal error: cannot decode argv[0]\n");
exit(1);
}
Py_SetProgramName(program); /* optional but recommended */
Py_Initialize();
PyRun_SimpleString("from time import time,ctime\n"
"print('Today is', ctime(time()))\n");
if (Py_FinalizeEx() < 0) {
exit(120);
}
PyMem_RawFree(program);
return 0;
}
The :c:func:`Py_SetProgramName` function should be called before
:c:func:`Py_Initialize` to inform the interpreter about paths to Python run-time
libraries. Next, the Python interpreter is initialized with
:c:func:`Py_Initialize`, followed by the execution of a hard-coded Python script
that prints the date and time. Afterwards, the :c:func:`Py_FinalizeEx` call shuts
the interpreter down, followed by the end of the program. In a real program,
you may want to get the Python script from another source, perhaps a text-editor
routine, a file, or a database. Getting the Python code from a file can better
be done by using the :c:func:`PyRun_SimpleFile` function, which saves you the
trouble of allocating memory space and loading the file contents.
.. _lower-level-embedding:
Beyond Very High Level Embedding: An overview
=============================================
The high level interface gives you the ability to execute arbitrary pieces of
Python code from your application, but exchanging data values is quite
cumbersome to say the least. If you want that, you should use lower level calls.
At the cost of having to write more C code, you can achieve almost anything.
It should be noted that extending Python and embedding Python is quite the same
activity, despite the different intent. Most topics discussed in the previous
chapters are still valid. To show this, consider what the extension code from
Python to C really does:
#. Convert data values from Python to C,
#. Perform a function call to a C routine using the converted values, and
#. Convert the data values from the call from C to Python.
When embedding Python, the interface code does:
#. Convert data values from C to Python,
#. Perform a function call to a Python interface routine using the converted
values, and
#. Convert the data values from the call from Python to C.
As you can see, the data conversion steps are simply swapped to accommodate the
different direction of the cross-language transfer. The only difference is the
routine that you call between both data conversions. When extending, you call a
C routine, when embedding, you call a Python routine.
This chapter will not discuss how to convert data from Python to C and vice
versa. Also, proper use of references and dealing with errors is assumed to be
understood. Since these aspects do not differ from extending the interpreter,
you can refer to earlier chapters for the required information.
.. _pure-embedding:
Pure Embedding
==============
The first program aims to execute a function in a Python script. Like in the
section about the very high level interface, the Python interpreter does not
directly interact with the application (but that will change in the next
section).
The code to run a function defined in a Python script is:
.. literalinclude:: ../includes/run-func.c
This code loads a Python script using ``argv[1]``, and calls the function named
in ``argv[2]``. Its integer arguments are the other values of the ``argv``
array. If you :ref:`compile and link <compiling>` this program (let's call
the finished executable :program:`call`), and use it to execute a Python
script, such as:
.. code-block:: python
def multiply(a,b):
print("Will compute", a, "times", b)
c = 0
for i in range(0, a):
c = c + b
return c
then the result should be:
.. code-block:: shell-session
$ call multiply multiply 3 2
Will compute 3 times 2
Result of call: 6
Although the program is quite large for its functionality, most of the code is
for data conversion between Python and C, and for error reporting. The
interesting part with respect to embedding Python starts with ::
Py_Initialize();
pName = PyUnicode_DecodeFSDefault(argv[1]);
/* Error checking of pName left out */
pModule = PyImport_Import(pName);
After initializing the interpreter, the script is loaded using
:c:func:`PyImport_Import`. This routine needs a Python string as its argument,
which is constructed using the :c:func:`PyUnicode_FromString` data conversion
routine. ::
pFunc = PyObject_GetAttrString(pModule, argv[2]);
/* pFunc is a new reference */
if (pFunc && PyCallable_Check(pFunc)) {
...
}
Py_XDECREF(pFunc);
Once the script is loaded, the name we're looking for is retrieved using
:c:func:`PyObject_GetAttrString`. If the name exists, and the object returned is
callable, you can safely assume that it is a function. The program then
proceeds by constructing a tuple of arguments as normal. The call to the Python
function is then made with::
pValue = PyObject_CallObject(pFunc, pArgs);
Upon return of the function, ``pValue`` is either *NULL* or it contains a
reference to the return value of the function. Be sure to release the reference
after examining the value.
.. _extending-with-embedding:
Extending Embedded Python
=========================
Until now, the embedded Python interpreter had no access to functionality from
the application itself. The Python API allows this by extending the embedded
interpreter. That is, the embedded interpreter gets extended with routines
provided by the application. While it sounds complex, it is not so bad. Simply
forget for a while that the application starts the Python interpreter. Instead,
consider the application to be a set of subroutines, and write some glue code
that gives Python access to those routines, just like you would write a normal
Python extension. For example::
static int numargs=0;
/* Return the number of arguments of the application command line */
static PyObject*
emb_numargs(PyObject *self, PyObject *args)
{
if(!PyArg_ParseTuple(args, ":numargs"))
return NULL;
return PyLong_FromLong(numargs);
}
static PyMethodDef EmbMethods[] = {
{"numargs", emb_numargs, METH_VARARGS,
"Return the number of arguments received by the process."},
{NULL, NULL, 0, NULL}
};
static PyModuleDef EmbModule = {
PyModuleDef_HEAD_INIT, "emb", NULL, -1, EmbMethods,
NULL, NULL, NULL, NULL
};
static PyObject*
PyInit_emb(void)
{
return PyModule_Create(&EmbModule);
}
Insert the above code just above the :c:func:`main` function. Also, insert the
following two statements before the call to :c:func:`Py_Initialize`::
numargs = argc;
PyImport_AppendInittab("emb", &PyInit_emb);
These two lines initialize the ``numargs`` variable, and make the
:func:`emb.numargs` function accessible to the embedded Python interpreter.
With these extensions, the Python script can do things like
.. code-block:: python
import emb
print("Number of arguments", emb.numargs())
In a real application, the methods will expose an API of the application to
Python.
.. TODO: threads, code examples do not really behave well if errors happen
(what to watch out for)
.. _embeddingincplusplus:
Embedding Python in C++
=======================
It is also possible to embed Python in a C++ program; precisely how this is done
will depend on the details of the C++ system used; in general you will need to
write the main program in C++, and use the C++ compiler to compile and link your
program. There is no need to recompile Python itself using C++.
.. _compiling:
Compiling and Linking under Unix-like systems
=============================================
It is not necessarily trivial to find the right flags to pass to your
compiler (and linker) in order to embed the Python interpreter into your
application, particularly because Python needs to load library modules
implemented as C dynamic extensions (:file:`.so` files) linked against
it.
To find out the required compiler and linker flags, you can execute the
:file:`python{X.Y}-config` script which is generated as part of the
installation process (a :file:`python3-config` script may also be
available). This script has several options, of which the following will
be directly useful to you:
* ``pythonX.Y-config --cflags`` will give you the recommended flags when
compiling:
.. code-block:: shell-session
$ /opt/bin/python3.4-config --cflags
-I/opt/include/python3.4m -I/opt/include/python3.4m -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes
* ``pythonX.Y-config --ldflags`` will give you the recommended flags when
linking:
.. code-block:: shell-session
$ /opt/bin/python3.4-config --ldflags
-L/opt/lib/python3.4/config-3.4m -lpthread -ldl -lutil -lm -lpython3.4m -Xlinker -export-dynamic
.. note::
To avoid confusion between several Python installations (and especially
between the system Python and your own compiled Python), it is recommended
that you use the absolute path to :file:`python{X.Y}-config`, as in the above
example.
If this procedure doesn't work for you (it is not guaranteed to work for
all Unix-like platforms; however, we welcome :ref:`bug reports <reporting-bugs>`)
you will have to read your system's documentation about dynamic linking and/or
examine Python's :file:`Makefile` (use :func:`sysconfig.get_makefile_filename`
to find its location) and compilation
options. In this case, the :mod:`sysconfig` module is a useful tool to
programmatically extract the configuration values that you will want to
combine together. For example:
.. code-block:: pycon
>>> import sysconfig
>>> sysconfig.get_config_var('LIBS')
'-lpthread -ldl -lutil'
>>> sysconfig.get_config_var('LINKFORSHARED')
'-Xlinker -export-dynamic'
.. XXX similar documentation for Windows missing

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