Building PyPy from Source

For building PyPy, we recommend installing a pre-built PyPy first (see Downloading and Installing PyPy). It is possible to build PyPy with CPython, but it will take a lot longer to run – depending on your architecture, between two and three times as long.

Even when using PyPy to build PyPy, translation is time-consuming – 20 minutes on a fast machine – and RAM-hungry. You will need at least 3 GB of memory on a 32-bit machine and 6GB on a 64-bit machine.

Before you start

Our normal development workflow avoids a full translation by using test-driven development. You can read more about how to develop PyPy here, and latest translated (hopefully functional) binary packages are available on our buildbot’s nightly builds

You will need the build dependencies below to run the tests.

Clone the repository

If you prefer to compile your own PyPy, or if you want to modify it, you will need to obtain a copy of the sources. This can be done either by downloading them from the download page or by checking them out from the repository using git. We suggest using git if you want to access the current development.

You must issue the following command on your command line, DOS box, or terminal:

git clone

This will clone the repository and place it into a directory named pypy, and will get you the PyPy source in pypy/pypy and documentation files in pypy/pypy/doc. We try to ensure that the tip is always stable, but it might occasionally be broken. You may want to check out our nightly tests: find a revision (12-chars alphanumeric string, e.g. “963e808156b3”) that passed at least the {linux32} tests (corresponding to a + sign on the line success) and then, in your cloned repository, switch to this revision using:

hg up -r XXXXX

where XXXXX is the revision id.

Install build-time dependencies

(Note: for some hints on how to translate the Python interpreter under Windows, see the windows document .

The host Python needs to have CFFI installed. If translating on PyPy, CFFI is already installed. If translating on CPython, you need to install it, e.g. using python -mpip install cffi.

To build PyPy on Unix using the C translation backend, you need at least a C compiler and make installed. Further, some optional modules have additional dependencies:

cffi, ctypes
libffi, pkg-config
libunwind (optional, loaded dynamically at runtime)

Make sure to have these libraries (with development headers) installed before building PyPy, otherwise the resulting binary will not contain these modules. Furthermore, the following libraries should be present after building PyPy, otherwise the corresponding CFFI modules are not built (you can run or re-run lib_pypy/pypy_tools/ to build them; you don’t need to re-translate the whole PyPy):

_ssl, _hashlib
libncurses-dev (for PyPy2) libncursesw-dev (for PyPy3)
lzma (PyPy3 only)
liblzma or libxz, version 5 and up

To run untranslated tests, you need the Boehm garbage collector libgc, version 7.4 and up

On Debian and Ubuntu (16.04 onwards), this is the command to install all build-time dependencies:

apt-get install gcc make libffi-dev pkg-config zlib1g-dev libbz2-dev \
libsqlite3-dev libncurses5-dev libexpat1-dev libssl-dev libgdbm-dev \
tk-dev libgc-dev python-cffi \
liblzma-dev libncursesw5-dev     # these two only needed on PyPy3

On Fedora:

dnf install gcc make libffi-devel pkgconfig zlib-devel bzip2-devel \
sqlite-devel ncurses-devel expat-devel openssl-devel tk-devel \
gdbm-devel python-cffi gc-devel\
xz-devel  # For lzma on PyPy3.

On SLES11:

zypper install gcc make python-devel pkg-config \
zlib-devel libopenssl-devel libbz2-devel sqlite3-devel \
libexpat-devel libffi-devel python-curses python-cffi \
xz-devel # For lzma on PyPy3.
(XXX plus the SLES11 version of libgdbm-dev and tk-dev)

On Mac OS X:

Currently PyPy supports both building on both Apple Silicon (M1, Arm64) and X86_64. You must use an appropriate toolchain for building: either arm64 or x86_64. “Fat” universal2 builds are not supported.

Most of the build-time dependencies are installed alongside the Developer Tools. libx11 is needed for tkinter. openssl needs to be installed for tests, and a brew-provided pypy will speed up translation. Note that you must use the architecture-appropriate x86_64 or arm64 brew command:

xcode-select --install
    brew install openssl pypy pkg-config libx11

After setting this up, translation (described next) will find the libs as expected via pkg-config.

Set environment variables that will affect translation

The following environment variables can be used to tweak the result:

value result
CC compiler to use
PYPY_MULTIARCH pypy 3.7+: ends up in sys.platform._multiarch on posix, defaults to x86_64-linux-gnu
PYPY_USESSION_DIR base directory for temporary files, usually $TMP
PYPY_USESSION_BASENAME each call to from import udir will get a temporary directory $PYPY_USESSION_DIR/usession-$PYPY_USESSION_BASENAME-N where N increments on each call
PYPY_USESSION_KEEP how many old temporary directories to keep, any older ones will be deleted. Defaults to 3

Run the translation

We usually translate in the pypy/goal directory, so all the following commands assume your $pwd is there.

Translate with JIT:

pypy ../../rpython/bin/rpython --opt=jit

Translate without JIT:

pypy ../../rpython/bin/rpython --opt=2

Note this translates pypy via the file, so these are shorthand for:

pypy ../../rpython/bin/rpython <rpython options> <pypy options>

More help is availabe via --help at either option position, and more info can be found in the Configuration Options for PyPy section.

(You can use python instead of pypy here, which will take longer but works too.)

If everything works correctly this will:

  1. Run the rpython translation chain, producing a database of the entire pypy interpreter. This step is currently singe threaded, and RAM hungry. As part of this step, the chain creates a large number of C code files and a Makefile to compile them in a directory controlled by the PYPY_USESSION_DIR environment variable.
  2. Create an executable pypy-c by running the Makefile. This step can utilize all possible cores on the machine.
  3. Copy the needed binaries to the current directory.
  4. Generate c-extension modules for any cffi-based stdlib modules.

The resulting executable behaves mostly like a normal Python interpreter (see Differences between PyPy and CPython), and is ready for testing, for use as a base interpreter for a new virtualenv, or for packaging into a binary suitable for installation on another machine running the same OS as the build machine.

Note that step 4 is merely done as a convenience, any of the steps may be rerun without rerunning the previous steps.

Making a debug build of PyPy

Rerun the Makefile with the make lldebug or make lldebug0 target, which will build in a way that running under a debugger makes sense. Appropriate compilation flags are added to add debug info, and for lldebug0 compiler optimizations are fully disabled. If you stop in a debugger, you will see the very wordy machine-generated C code from the rpython translation step, which takes a little bit of reading to relate back to the rpython code.

Build cffi import libraries for the stdlib

Various stdlib modules require a separate build step to create the cffi import libraries in the out-of-line API mode. This is done by the following command:

cd pypy/goal
PYTHONPATH=../.. ./pypy-c ../../lib_pypy/pypy_tools/

Packaging (preparing for installation)

Packaging is required if you want to install PyPy system-wide, even to install on the same machine. The reason is that doing so prepares a number of extra features that cannot be done lazily on a root-installed PyPy, because the normal users don’t have write access. This concerns mostly libraries that would normally be compiled if and when they are imported the first time.

python pypy/tool/release/ --archive-name=pypy-VER-PLATFORM

This creates a clean and prepared hierarchy, as well as a .tar.bz2 with the same content; the directory to find these will be printed out. You can then either move the file hierarchy or unpack the .tar.bz2 at the correct place.

It is recommended to use because custom scripts will invariably become out-of-date. If you want to write custom scripts anyway, note an easy-to-miss point: some modules are written with CFFI, and require some compilation. If you install PyPy as root without pre-compiling them, normal users will get errors.


PyPy dynamically finds the location of its libraries depending on the location of the executable. The directory hierarchy of a typical PyPy2 installation looks like this:


A PyPy3.8+ installation will match the CPython layout:


The hierarchy shown above is relative to a PREFIX directory. PREFIX is computed by starting from the directory where the executable resides, and “walking up” the filesystem until we find a directory containing lib_pypy and lib-python/2.7 (on pypy2).

To install PyPy system wide on unix-like systems, it is recommended to put the whole hierarchy alone (e.g. in /opt/pypy) and put a symlink to the pypy executable into /usr/bin or /usr/local/bin.

If the executable fails to find suitable libraries, it will report debug: WARNING: library path not found, using compiled-in sys.path and then attempt to continue normally. If the default path is usable, most code will be fine. However, the sys.prefix will be unset and some existing libraries assume that this is never the case.