The host system must be 64-bit. A Python 3.5+ interpreter must be available. The execution environment must have access to a Docker daemon (all build operations are performed in Docker containers for isolation from the host system).

To build a Python distribution for Linux x64:

$ ./
# With profile-guided optimizations (generated code should be faster):
$ ./ --optimizations pgo
# Produce a debug build.
$ ./ --optimizations debug

You can also build another version of Python. e.g.:

$ ./ --python cpython-3.8

To build a Python distribution for Linux x64 using musl libc:

$ ./ --target x86_64-unknown-linux-musl

Building a 32-bit x86 Python distribution is also possible:

$ ./ --target i686-unknown-linux-gnu

As are various other targets:

$ ./ --target aarch64-unknown-linux-gnu
$ ./ --target armv7-unknown-linux-gnueabi
$ ./ --target armv7-unknown-linux-gnueabihf
$ ./ --target mips-unknown-linux-gnu
$ ./ --target mipsel-unknown-linux-gnu
$ ./ --target ppc64le-unknown-linux-gnu
$ ./ --target s390x-unknown-linux-gnu


The XCode command line tools must be installed. A Python 3 interpreter is required to execute the build. /usr/bin/clang must exist.

macOS SDK headers must be installed. Try running xcode-select --install to install them if you see errors about e.g. stdio.h not being found. Verify they are installed by running xcrun --show-sdk-path. It should print something like /Applications/ on modern versions of macOS.

To build a Python distribution for macOS:

$ ./

macOS uses the same build code as Linux, just without Docker. So similar build configuration options are available. accepts a --target-triple argument to support building for non-native targets (i.e. cross-compiling). By default, macOS builds target the currently running architecture. e.g. an Intel Mac will target x86_64-apple-darwin and an M1 (ARM) Mac will target aarch64-apple-darwin. It should be possible to build an ARM distribution on an Intel Mac and an Intel distribution on an ARM Mac.

The APPLE_SDK_PATH environment variable is recognized as the path to the Apple SDK to use. If not defined, the build will attempt to find an SDK by running xcrun --show-sdk-path.

aarch64-apple-darwin builds require a macOS 11.0+ SDK and building Python 3.9+. It should be possible to build for aarch64-apple-darwin from an Intel 10.15 machine (as long as the 11.0+ SDK is used).

Python 3.8 may not build properly with a macOS 11.0+ SDK: try using the macOS 10.15 SDK instead.


Visual Studio 2017 (or later) is required. A compatible Windows SDK is required (10.0.17763.0 as per CPython 3.7.2).

If building CPython 3.8+, there are the following additional requirements:

  • A git.exe on PATH (to clone libffi from source).

  • An installation of Cywgin with the autoconf, automake, libtool, and make packages installed. (libffi build dependency.)

To build a dynamically linked Python distribution for Windows x64:

$ py.exe --profile noopt

It’s also possible to build with optional PGO optimizations:

$ py.exe --profile pgo

If building CPython 3.8+, you will need to specify the path to a sh.exe installed from cygwin. e.g.

$ py.exe –python cpython-3.8 –sh c:cygwinbinsh.exe –profile noopt

To build a 32-bit x86 binary, simply use an x86 Native Tools Command Prompt instead of x64.

Using sccache to Speed up Builds

Builds can take a long time.

python-build-standalone can automatically detect and use the sccache compiler cache to speed up subsequent builds on UNIX-like platforms. sccache can shave dozens of minutes from fresh builds, even on a 16 core CPU!

If there is an executable sccache in the source directory, it will automatically be copied into the build environment and used. For non-container builds, an sccache executable is also searched for on PATH.

The ~/.python-build-standalone-env file is read if it exists (the format is key=value pairs) and variables are added to the build environment.

In addition, environment variables AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and any variable beginning with SCCACHE_ are automatically added to the build environment.

The environment variable support enables you to define remote build caches (such as S3 buckets) to provide a persistent, shared cache across builds and machines.

Keep in mind that when performing builds in containers in Linux (the default behavior), the local filesystem is local to the container and does not survive the build of a single package. So sccache is practically meaningless unless configured to use an external store (such as S3).

When using remote stores (such as S3), sccache can be constrained on network I/O. We recommend having at least a 100mbps network connection to a remote store and employing a network store with as little latency as possible for best results.