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 http://www.python.org/). It also gives an overview of the directory structure of the CPython source code.
CPython is developed using Mercurial. The Mercurial command line program is named hg; this is also used to refer to Mercurial itself. Mercurial is easily available for common Unix systems by way of the standard package manager; under Windows, you might want to use the TortoiseHg graphical client.
One should always work from a working copy of the CPython source code. While it may be tempting to work from the copy of Python you already have installed on your machine, it is very likely that you will be working from out-of-date code as the Python core developers are constantly updating and fixing things in their VCS. It also means you will have better tool support through the VCS as it will provide a diff tool, etc.
hg clone http://hg.python.org/cpython
If you want a working copy of an already-released version of Python, i.e., a version in maintenance mode, you can update your working copy. For instance, to update your working copy to Python 3.3, do:
hg update 3.3
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 Documenting Python.
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.
The core CPython interpreter only needs a C compiler to be built; if you get compile errors with a C89 or C99-compliant compiler, please open a bug report. 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.
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.
Fedora, Red Hat Enterprise Linux and other yum based systems:
$ sudo yum install yum-utils $ sudo yum-builddep python3
Debian, Ubuntu and other apt based systems:
$ sudo apt-get build-dep python3
There will sometimes be optional modules added for a new release which won’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 bug fixes for Python 2.7, use python in place of python3 in the above commands.
Explaining how to build optional dependencies on a UNIX based system without root access is beyond the scope of this guide.
While you need a C compiler to build CPython, you don’t need any knowledge of the C language to contribute! Vast areas of CPython are written completely in Python: as of this writing, CPython contains slightly more Python code than C.
The basic steps for building Python for development is to configure it and then compile it.
Configuration is typically:
More flags are available to configure, but this is the minimum you should do to get a pydebug build of CPython.
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.
Do take note of what modules were not built as stated at the end of your build. More than likely you are missing a dependency for the module(s) that were not built, and so you can install the dependencies and re-run both configure and make (if available for your OS). Otherwise the build failed and thus should be fixed (at least with a bug being filed on the issue tracker).
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 OS X 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.
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 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).
Python 3.3 and later use Microsoft Visual Studio 2010. You can download Microsoft Visual C++ 2010 Express from Microsoft’s site. To use it for more than 28 days, one must register through a Windows Live account.
Most Python versions prior to 3.3 use Microsoft Visual Studio 2008. You can download Microsoft Visual C++ 2008 Express Edition with SP1 from a new location yet to be determined.
Regardless of Visual Studio version, the PCbuild directory of a source checkout contains the build files for the Python version you are building. The full version of Visual Studio is not necessary for common tasks with 32-bit builds; the gratis C++ Express versions linked above are sufficient. Their limitations are given here (2008) and here (2010).
To build from the Visual Studio GUI, open the pcbuild.sln solution file with Visual Studio. Choose the Build Solution option under the Build or Debug menu (depending on your version of Visual Studio). Be sure that “Debug” was chosen as the active solution configuration (e.g. under Build ‣ Configuration Manager...).
When building you may see a number of build errors related to missing files or directories. These do not necessarily mean that Python failed to build. If you prefer, you can exclude the offending projects from the build process by unchecking them inside the Build ‣ Configuration Manager... settings.
Once built you might want to set Python as a startup project. Pressing F5 in Visual Studio, or choosing Start Debugging from the Debug menu, will launch the interpreter.
If you want to launch the compiled interpreter from the command-line, the path varies according to the build. For a 32-bit build in debug mode, you have to invoke PCBuild\python_d.exe, for a 64-bit build in debug mode, PCBuild\amd64\python_d.exe. If you are compiling in release mode (which you shouldn’t, in general), replace python_d.exe with python.exe.
Python is used widely enough that practically all code editors have some form of support for writing Python code. Various coding tools also include Python support.
For editors and tools which the core developers have felt some special comment is needed for coding in Python, see Additional Resources.
There are several top-level directories in the CPython source tree. Knowing what each one is meant to hold will help you find where a certain piece of functionality is implemented. Do realize, though, there are always exceptions to every rule.