Setup and building

These instructions cover how to get a working copy of the source code and a compiled version of the CPython interpreter (CPython is the version of Python available from https://www.python.org/). It also gives an overview of the directory structure of the CPython source code.

Alternatively, if you have Docker installed you might want to use our official images. These contain 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 from installing Git to submitting a pull request.

Install Git

CPython is developed using Git for version control. The Git command line program is named git; this is also used to refer to Git itself. Git is easily available for all common operating systems.

• Install

  As the CPython repo is hosted on GitHub, please refer to either the GitHub setup instructions or the Git project instructions for step-by-step installation directions. You may also want to consider a graphical client such as TortoiseGit or GitHub Desktop.

• Configure

  Configure your name and email and create an SSH key as this will allow you to interact with GitHub without typing a username and password each time you execute a command, such as git pull, git push, or git fetch. On Windows, you should also enable autocrlf.

Get the source code

The CPython repo is hosted on GitHub. To get a copy of the source code you should fork the Python repository on GitHub, create a local clone of your personal fork, and configure the remotes.

You will only need to execute these steps once per machine:

1. Go to https://github.com/python/cpython.

2. Press Fork on the top right.

3. When asked where to fork the repository, choose to fork it to your username.

4. Your fork will be created at https://github.com/<username>/cpython.

5. Clone your GitHub fork (replace <username> with your username):

   $ git clone git@github.com:<username>/cpython.git
   

   (You can use both SSH-based or HTTPS-based URLs.)

6. Add an upstream remote, then configure git to pull main from upstream and always push to origin:

   $ cd cpython
   $ git remote add upstream https://github.com/python/cpython
   $ git config --local branch.main.remote upstream
   $ git remote set-url --push upstream git@github.com:<your-username>/cpython.git
   

7. Verify that your setup is correct:

   $ git remote -v
   origin  git@github.com:<your-username>/cpython.git (fetch)
   origin  git@github.com:<your-username>/cpython.git (push)
   upstream        https://github.com/python/cpython (fetch)
   upstream        git@github.com:<your-username>/cpython.git (push)
   $ git config branch.main.remote
   upstream
   

For more information about these commands see Git Bootcamp and Cheat Sheet.

If you did everything correctly, you should now have a copy of the code in 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 checkout a release branch. For instance, to checkout a working copy of Python 3.8, do git switch 3.8.

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 immediate use and testing. (If you change C code, you will need to recompile the affected files as described below.)

Patches for the documentation can be made from the same repository; see Getting started.

Compile and build

CPython provides several compilation flags which help with debugging various things. While all of the known flags can be found in the Misc/SpecialBuilds.txt file, the most critical one is the Py_DEBUG flag which creates what is known as a “pydebug” build. This flag turns on various extra sanity checks which help catch common issues. The use of the flag is so common that turning on the flag is a basic compile option.

You should always develop under a pydebug build of CPython (the only instance of when you shouldn’t is if you are taking performance measurements). Even when working only on pure Python code the pydebug build provides several useful checks that one should not skip.

See also

The effects of various configure and build flags are documented in the Python configure docs.

Unix

The core CPython interpreter only needs a C compiler to be built, however, some of the extension modules will need development headers for additional libraries (such as the zlib library for compression). Depending on what you intend to work on, you might need to install these additional requirements so that the compiled interpreter supports the desired features.

If you want to install these optional dependencies, consult the Install dependencies section below.

If you don’t need to install them, the basic steps for building Python for development is to configure it and then compile it.

Configuration is typically:

$ ./configure --with-pydebug

More flags are available to configure, but this is the minimum you should do to get a pydebug build of CPython.

Note

You might need to run make clean before or after re-running configure in a particular build directory.

Once configure is done, you can then compile CPython with:

$ make -s -j2

This will build CPython with only warnings and errors being printed to stderr and utilize up to 2 CPU cores. If you are using a multi-core machine with more than 2 cores (or a single-core machine), you can adjust the number passed into the -j flag to match the number of cores you have (or if your version of Make supports it, you can use -j without a number and Make will not limit the number of steps that can run simultaneously.).

At the end of the build you should see a success message, followed by a list of extension modules that haven’t been built because their dependencies were missing:

The necessary bits to build these optional modules were not found:
_gdbm
To find the necessary bits, look in configure.ac and config.log.

Checked 106 modules (31 built-in, 74 shared, 0 n/a on macosx-13.4-arm64, 0 disabled, 1 missing, 0 failed on import)

If the build failed and you are using a C89 or C99-compliant compiler, please open a bug report on the issue tracker.

If you decide to Install dependencies, you will need to re-run both configure and make.

Once CPython is done building you will then have a working build that can be run in-place; ./python on most machines (and what is used in all examples), ./python.exe wherever a case-insensitive filesystem is used (e.g. on macOS by default), in order to avoid conflicts with the Python directory. There is normally no need to install your built copy of Python! The interpreter will realize where it is being run from and thus use the files found in the working copy. If you are worried you might accidentally install your working copy build, you can add --prefix=/tmp/python to the configuration step. When running from your working directory, it is best to avoid using the --enable-shared flag to configure; unless you are very careful, you may accidentally run with code from an older, installed shared Python library rather than from the interpreter you just built.

Clang

If you are using clang to build CPython, some flags you might want to set to quiet some standard warnings which are specifically superfluous to CPython are -Wno-unused-value -Wno-empty-body -Qunused-arguments. You can set your CFLAGS environment variable to these flags when running configure.

If you are using clang with ccache, turn off the noisy parentheses-equality warnings with the -Wno-parentheses-equality flag. These warnings are caused by clang not having enough information to detect that extraneous parentheses in expanded macros are valid, because the preprocessing is done separately by ccache.

If you are using LLVM 2.8, also use the -no-integrated-as flag in order to build the ctypes module (without the flag the rest of CPython will still build properly).

Optimization

If you are trying to improve CPython’s performance, you will probably want to use an optimized build of CPython. It can take a lot longer to build CPython with optimizations enabled, and it’s usually not necessary to do so. However, it’s essential if you want accurate benchmark results for a proposed performance optimization.

For an optimized build of Python, use configure --enable-optimizations --with-lto. This sets the default make targets up to enable Profile Guided Optimization (PGO) and may be used to auto-enable Link Time Optimization (LTO) on some platforms. See --enable-optimizations and --with-lto to learn more about these options.

$ ./configure --enable-optimizations --with-lto

Windows

Note

If you are using the Windows Subsystem for Linux (WSL), clone the repository from a native Windows shell program like PowerShell or the cmd.exe command prompt, and use a build of Git targeted for Windows, e.g. the Git for Windows download from the official Git website. Otherwise, Visual Studio will not be able to find all the project’s files and will fail the build.

For a concise step by step summary of building Python on Windows, you can read Victor Stinner’s guide.

All supported versions of Python can be built using Microsoft Visual Studio 2017 or later. You can download and use any of the free or paid versions of Visual Studio.

When installing it, select the Python development workload and the optional Python native development tools component to obtain all of the necessary build tools. You can find Git for Windows on the Individual components tab if you don’t already have it installed.

Note

If you want to build MSI installers, be aware that the build toolchain for them has a dependency on the Microsoft .NET Framework Version 3.5 (which may not be included on recent versions of Windows, such as Windows 10). If you are building on a recent Windows version, use the Control Panel (Programs ‣ Programs and Features ‣ Turn Windows Features on or off) and ensure that the entry .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 dependencies are downloaded:

PCbuild\build.bat -c Debug

The above command line build uses the -c Debug argument to build in the Debug configuration, which enables checks and assertions helpful for developing Python. By default, it builds in the Release configuration and for the 64-bit x64 platform rather than 32-bit Win32; use -c and -p to control build config and platform, respectively.

After this build succeeds, you can open the PCbuild\pcbuild.sln solution in the Visual Studio IDE to continue development, if you prefer. When building in Visual Studio, make sure to select build settings that match what you used with the script (the Debug configuration and the x64 platform) from the dropdown menus in the toolbar.

Note

If you need to change the build configuration or platform, build once with the build.bat script set to those options first before building with them in VS to ensure all files are rebuilt properly, or you may encounter errors when loading modules that were not rebuilt.

Avoid selecting the PGInstrument and PGUpdate configurations, as these are intended for PGO builds and not for normal development.

You can run the build of Python you’ve compiled with:

PCbuild\amd64\python_d.exe

See the PCBuild readme for more details on what other software is necessary and how to build.

Install dependencies

This section explains how to install additional extensions (e.g. zlib) on Linux and Install dependencies.

Linux

For Unix-based systems, we try to use system libraries whenever available. This means optional components will only build if the relevant system headers are available. The best way to obtain the appropriate headers will vary by distribution, but the appropriate commands for some popular distributions are below.

On Fedora, Red Hat Enterprise Linux and other yum based systems:

$ sudo yum install yum-utils
$ sudo yum-builddep python3