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I am new to Python. I was asked to update to the latest Python version using conda. So far, I have installed Anaconda on my Mac. So I am mainly using the Terminal. Thank you in advance. If you want a working copy of an already-released version of Python, i.e., a version in maintenance mode, you can checkout a release branch. For instance, to checkout a working copy of Python 3.8, do git checkout 3.8. You will need to re-compile CPython when you do such an update. Now we know for certain that we're using Python 3.7.3 and pip will update alongside it without any manual aliasing between versions. Using Moshe's recommendation to use a version manager (pyenv) enables us to easily accept future upgrades without getting confused about which Python we are running at a given time.
These instructions cover how to get a working copy of the source code and acompiled version of the CPython interpreter (CPython is the version of Pythonavailable from https://www.python.org/). It also gives an overview of thedirectory structure of the CPython source code.
Alternatively, if you have Docker installed youmight want to use our official images. Thesecontain the latest releases of several Python versions, along with git head,and are provided for development and testing purposes only.
See also
The Quick Reference gives brief summary of the process frominstalling git to submitting a pull request.
1.1. Install git
¶
CPython is developed using git for version control. The gitcommand line program is named git
; this is also used to refer to gititself. git is easily available for all common operating systems.
Install
As the CPython repo is hosted on GitHub, please refer to either theGitHub setup instructionsor the git project instructions for step-by-stepinstallation directions. You may also want to consider a graphical clientsuch as TortoiseGit orGitHub Desktop.
Configure
Configure your name and email and createan SSH keyas this will allow you to interact with GitHub without typing a usernameand password each time you execute a command, such as
gitpull
,gitpush
, orgitfetch
. On Windows, you should alsoenable autocrlf.
1.2. Get the source code¶
The CPython repo is hosted on GitHub. To get a copy of the source code you shouldfork the Python repository on GitHub, create a localclone of your personal fork, and configure the remotes.
You will only need to execute these steps once:
Go to https://github.com/python/cpython.
Press Fork on the top right.
When asked where to fork the repository, choose to fork it to your username.
Your fork will be created at
https://github.com/<username>/cpython
.Clone your GitHub fork (replace
<username>
with your username):(You can use both SSH-based or HTTPS-based URLs.)
Configure an
upstream
remote:Verify that your setup is correct:
If you did everything correctly, you should now have a copy of the codein the cpython
directory and two remotes that refer to your own GitHub fork(origin
) and the official CPython repository (upstream
).
If you want a working copy of an already-released version of Python,i.e., a version in maintenance mode, you can checkouta release branch. For instance, to checkout a working copy of Python 3.8,do gitcheckout3.8
.
You will need to re-compile CPython when you do such an update.
Do note that CPython will notice that it is being run from a working copy.This means that if you edit CPython’s source code in your working copy,changes to Python code will be picked up by the interpreter for immediateuse and testing. (If you change C code, you will need to recompile theaffected files as described below.)
Patches for the documentation can be made from the same repository; seeDocumenting Python.
1.3. Compile and build¶
CPython provides several compilation flags which help with debugging variousthings. While all of the known flags can be found in theMisc/SpecialBuilds.txt
file, the most critical one is the Py_DEBUG
flagwhich creates what is known as a “pydebug” build. This flag turns on variousextra sanity checks which help catch common issues. The use of the flag is socommon that turning on the flag is a basic compile option.
You should always develop under a pydebug build of CPython (the only instance ofwhen you shouldn’t is if you are taking performance measurements). Even whenworking only on pure Python code the pydebug build provides several usefulchecks that one should not skip.
1.3.1. UNIX¶
The core CPython interpreter only needs a C compiler to be built,however, some of the extension modules will need development headersfor additional libraries (such as the zlib
library for compression).Depending on what you intend to work on, you might need to install theseadditional requirements so that the compiled interpreter supports thedesired features.
If you want to install these optional dependencies, consult theInstall dependencies section below.
If you don’t need to install them, the basic steps for building Pythonfor development is to configure it and then compile it.
Configuration is typically:
More flags are available to configure
, but this is the minimum you shoulddo to get a pydebug build of CPython.
Note
You might need to run makeclean
before or after re-running configure
in a particular build directory.
Once configure
is done, you can then compile CPython with:
This will build CPython with only warnings and errors being printed tostderr and utilize up to 2 CPU cores. If you are using a multi-core machinewith more than 2 cores (or a single-core machine), you can adjust the numberpassed into the -j
flag to match the number of cores you have (or if yourversion of Make supports it, you can use -j
without a number and Makewill not limit the number of steps that can run simultaneously.).
At the end of the build you should see a success message, possibly followedby a list of extension modules that haven’t been built because theirdependencies were missing:
If the build failed and you are using a C89 or C99-compliant compiler,please open a bug report.
If you decide to Install dependencies, you will need to re-run bothconfigure
and make
.
Once CPython is done building you will then have a working buildthat can be run in-place; ./python
on most machines (and what is used inall examples), ./python.exe
wherever a case-insensitive filesystem is used(e.g. on OS X by default), in order to avoid conflicts with the Python
directory. There is normally no need to install your built copyof Python! The interpreter will realize where it is being run fromand thus use the files found in the working copy. If you are worriedyou might accidentally install your working copy build, you can add--prefix=/tmp/python
to the configuration step. When running from yourworking directory, it is best to avoid using the --enable-shared
flagto configure
; unless you are very careful, you may accidentally runwith code from an older, installed shared Python library rather than fromthe interpreter you just built.
1.3.1.1. Clang¶
If you are using clang to build CPython, some flags you might want to set toquiet some standard warnings which are specifically superfluous to CPython are-Wno-unused-value-Wno-empty-body-Qunused-arguments
. You can set yourCFLAGS
environment variable to these flags when running configure
.
If you are using clang with ccache, turn off the noisyparentheses-equality
warnings with the -Wno-parentheses-equality
flag.These warnings are caused by clang not having enough information to detectthat extraneous parentheses in expanded macros are valid, because thepreprocessing is done separately by ccache.
If you are using LLVM 2.8, also use the -no-integrated-as
flag in order tobuild the ctypes
module (without the flag the rest of CPython willstill build properly).
1.3.2. Windows¶
For a quick guide to building you can read this documentation from VictorStinner.
Python 3.6 and later can use Microsoft Visual Studio 2017. You can downloadand use any of the free or paid versions of Visual Studio 2017.
When installing Visual Studio 2017, select the Python development workloadand the optional Python native development tools component to obtain all ofthe necessary build tools. If you do not already have git installed, you canfind git for Windows on the Individual components tab of the installer.
Note
If you want to build MSI installers, be aware that the build toolchainfor them has a dependency on the Microsoft .NET Framework Version 3.5 (whichmay not be configured on recent versions of Windows, such as Windows 10). Ifyou are building on a recent Windows version, use the Control Panel (Programs| Programs and Features | Turn Windows Features on or off) and ensure that theentry “.NET Framework 3.5 (includes .NET 2.0 and 3.0)” is enabled.
Your first build should use the command line to ensure any external dependenciesare downloaded:
After this build succeeds, you can open the PCBuildpcbuild.sln
solution inVisual Studio to continue development.
See the readme for more details on what other software is necessary and howto build.
Note
Python 2.7 uses Microsoft Visual Studio 2008, which is most easilyobtained through an MSDN subscription. To use the build files in thePCbuild directory you will also need Visual Studio 2010, see the 2.7readme for more details. If you have VS 2008 but not 2010 you can use thebuild files in the PC/VS9.0 directory, see the VS9 readme for details.
Note
If you are using the Windows Subsystem for Linux (WSL), clone therepository from a native Windows terminal program like cmd.exe command promptor PowerShell as well as use a build of git targeted for Windows, e.g., theofficial one from https://git-scm.com. Otherwise, Visual Studio willnot be able to find all the project’s files and will fail the build.
1.4. Install dependencies¶
This section explains how to install additional extensions (e.g. zlib
)on Linux and macOs/OS X. On Windows,extensions are already included and built automatically.
1.4.1. Linux¶
For UNIX based systems, we try to use system libraries whenever available.This means optional components will only build if the relevant system headersare available. The best way to obtain the appropriate headers will vary bydistribution, but the appropriate commands for some popular distributionsare below.
On Fedora, Red Hat Enterprise Linux and other yum
based systems:
On Fedora and other DNF
based systems:
On Debian, Ubuntu, and other apt
based systems, try to get thedependencies for the Python you’re working on by using the apt
command.
First, make sure you have enabled the source packages in the sources list.You can do this by adding the location of the source packages, includingURL, distribution name and component name, to /etc/apt/sources.list
.Take Ubuntu Bionic for example:
For other distributions, like Debian, change the URL and names to correspondwith the specific distribution.
Then you should update the packages index:
Now you can install the build dependencies via apt
:
If that package is not available for your system, try reducing the minorversion until you find a package that is available.
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1.4.2. macOS and OS X¶
For macOS systems (versions 10.12+) and OS X 10.9 and later,the Developer Tools can be downloaded and installed automatically;you do not need to download the complete Xcode application.
If necessary, run the following:
This will also ensure that the system header files are installed into/usr/include
.
On Mac OS X systems (versions 10.0 - 10.7) and OS X 10.8, use the Ccompiler and other development utilities provided by Apple’s Xcode DeveloperTools. The Developer Tools are not shipped with Mac OS X.
For these older releases (versions 10.0 - 10.8), you will need to download either thecorrect version of the Command Line Tools, if available, or install them from thefull Xcode app or package for that OS X release. Older versions may beavailable either as a no-cost download through Apple’s App Store or fromthe Apple Developer web site.
Also note that OS X does not include several libraries used by the Pythonstandard library, including libzma
, so expect to see some extension modulebuild failures unless you install local copies of them. As of OS X 10.11,Apple no longer provides header files for the deprecated system version ofOpenSSL which means that you will not be able to build the _ssl
extension.One solution is to install these libraries from a third-party packagemanager, like Homebrew or MacPorts, and then add the appropriate pathsfor the header and library files to your configure
command. For example,
with Homebrew:
and configure
Python versions >= 3.7:
or configure
Python versions < 3.7:
and make
:
or MacPorts:
and configure
:
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and make
:
There will sometimes be optional modules added for a new release whichwon’t yet be identified in the OS level build dependencies. In those cases,just ask for assistance on the core-mentorship list. If working on bugfixes for Python 2.7, use python
in place of python3
in the abovecommands.
Explaining how to build optional dependencies on a UNIX based system withoutroot access is beyond the scope of this guide.
Note
While you need a C compiler to build CPython, you don’t need anyknowledge of the C language to contribute! Vast areas of CPython arewritten completely in Python: as of this writing, CPython contains slightlymore Python code than C.
1.5. Regenerate configure
¶
If a change is made to Python which relies on some POSIX system-specificfunctionality (such as using a new system call), it is necessary to update theconfigure
script to test for availability of the functionality.
Python’s configure
script is generated from configure.ac
using Autoconf.Instead of editing configure
, edit configure.ac
and then runautoreconf
to regenerate configure
and a number of other files (such aspyconfig.h
).
When submitting a patch with changes made to configure.ac
, you should alsoinclude the generated files.
Note that running autoreconf
is not the same as running autoconf
. Forexample, autoconf
by itself will not regenerate pyconfig.h.in
.autoreconf
runs autoconf
and a number of other tools repeatedly as isappropriate.
Python’s configure.ac
script typically requires a specific version ofAutoconf. At the moment, this reads: AC_PREREQ(2.69)
.
If the system copy of Autoconf does not match this version, you will need toinstall your own copy of Autoconf.
1.6. Troubleshoot the build¶
This section lists some of the common problems that may arise during thecompilation of Python, with proposed solutions.
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1.6.1. Avoid recreating auto-generated files¶
Under some circumstances you may encounter Python errors in scripts likeParser/asdl_c.py
or Python/makeopcodetargets.py
while running make
.Python auto-generates some of its own code, and a full build from scratch needsto run the auto-generation scripts. However, this makes the Python build requirean already installed Python interpreter; this can also cause version mismatcheswhen trying to build an old (2.x) Python with a new (3.x) Python installed, orvice versa.
To overcome this problem, auto-generated files are also checked into theGit repository. So if you don’t touch the auto-generation scripts, there’sno real need to auto-generate anything.
1.7. Editors and Tools¶
Python is used widely enough that practically all code editors have some formof support for writing Python code. Various coding tools also include Pythonsupport.
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For editors and tools which the core developers have felt some special commentis needed for coding in Python, see Additional Resources.
1.8. Directory structure¶
There are several top-level directories in the CPython source tree. Knowing whateach one is meant to hold will help you find where a certain piece offunctionality is implemented. Do realize, though, there are always exceptions toevery rule.
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Doc
- The official documentation. This is what https://docs.python.org/ uses.See also Building the documentation.
Grammar
- Contains the EBNF grammar file forPython.
Include
- Contains all interpreter-wide header files.
Lib
- The part of the standard library implemented in pure Python.
Mac
- Mac-specific code (e.g., using IDLE as an OS X application).
Misc
- Things that do not belong elsewhere. Typically this is varying kinds ofdeveloper-specific documentation.
Modules
- The part of the standard library (plus some other code) that is implementedin C.
Objects
- Code for all built-in types.
PC
- Windows-specific code.
PCbuild
- Build files for the version of MSVC currently used for the Windowsinstallers provided on python.org.
Parser
- Code related to the parser. The definition of the AST nodes is also kepthere.
Programs
- Source code for C executables, including the main function for theCPython interpreter (in versions prior to Python 3.5, these files arein the Modules directory).
Python
- The code that makes up the core CPython runtime. This includes thecompiler, eval loop and various built-in modules.
Tools
- Various tools that are (or have been) used to maintain Python.