Tips and tricks¶

Tips¶

Building Linux wheels for non-native archs using emulation¶

cibuildwheel supports building non-native architectures on Linux, via emulation through the binfmt_misc kernel feature. The easiest way to use this is via the docker/setup-qemu-action on GitHub Actions or tonistiigi/binfmt.

Check out the following config for an example of how to set it up on GitHub Actions. Once QEMU is set up and registered, you just need to set the CIBW_ARCHS_LINUX environment variable (or use the --archs option on Linux), and the other architectures are emulated automatically.

.github/workflows/build.yml

name: Build

on: [push, pull_request]

jobs:
  build_wheels:
    name: Build wheels on ${{ matrix.os }}
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:
        # macos-13 is an intel runner, macos-14 is apple silicon
        os: [ubuntu-latest, ubuntu-24.04-arm, windows-latest, macos-13, macos-14]

    steps:
      - uses: actions/checkout@v4

      - name: Set up QEMU
        if: runner.os == 'Linux' && runner.arch == 'X64'
        uses: docker/setup-qemu-action@v3
        with:
          platforms: all

      - name: Build wheels
        uses: pypa/cibuildwheel@v3.0.0
        env:
          # configure cibuildwheel on Linux to build native archs ('auto'),
          # and to split the remaining architectures between the x86_64 and
          # ARM runners
          CIBW_ARCHS_LINUX: ${{ runner.arch == 'X64' && 'auto ppc64le s390x' || 'auto' }}

      - uses: actions/upload-artifact@v4
        with:
          name: cibw-wheels-${{ matrix.os }}-${{ strategy.job-index }}
          path: ./wheelhouse/*.whl

Building CPython ABI3 wheels (Limited API)¶

The CPython Limited API is a subset of the Python C Extension API that's declared to be forward-compatible, meaning you can compile wheels for one version of Python, and they'll be compatible with future versions. Wheels that use the Limited API are known as ABI3 wheels.

To create a package that builds ABI3 wheels, you'll need to configure your build backend to compile libraries correctly create wheels with the right tags. Check this repo for an example of how to do this with setuptools.

You could also consider running abi3audit against the produced wheels in order to check for abi3 violations or inconsistencies. You can run it alongside the default in your repair-wheel-command.

Packages with optional C extensions¶

cibuildwheel defines the environment variable CIBUILDWHEEL to the value 1 allowing projects for which the C extension is optional to make it mandatory when building wheels.

An easy way to do it in Python 3 is through the optional named argument of Extension constructor in your setup.py:

myextension = Extension(
    "myextension",
    ["myextension.c"],
    optional=os.environ.get('CIBUILDWHEEL', '0') != '1',
)

Building with NumPy¶

If using NumPy, there are a couple of things that can help.

First, if you require the numpy package at build-time (some binding tools, like pybind11 and nanobind, do not), then the backward compatibility for your build-backend.build-requires is a little complicated for Python <3.9:

• NumPy <1.25: You must build with the oldest version of NumPy you want to support at runtime.
• NumPy 1.25 and 1.26: Anything you build will be compatible with 1.19+ by default, and you can set the minimum target to, for example, 1.22 with #define NPY_TARGET_VERSION NPY_1_22_API_VERSION.
• NumPy 2.x: You must build with NumPy 2 to support NumPy 2; otherwise the same as 1.25+.

So the rule is:

• Python <3.8: Use the oldest supported NumPy (via helper oldest-supported-numpy if you want)
• Python 3.9+: Use latest supported NumPy (2+).

Second, there might be platforms you want to ship for that NumPy (or some other scientific Python libraries) are not shipping yet for. This is often true for beta candidates of new Python releases, for example. To work with this, you can use the Scientific Python Nightly wheels. Here's an example, depending on what frontend you use:

[tool.cibuildwheel]
environment.PIP_ONLY_BINARY = "numpy"
environment.PIP_PREFER_BINARY = "1"

[[tool.cibuildwheel.overrides]]
select = ["cp314*"]
inherit.environment = "append"
environment.PIP_EXTRA_INDEX_URL = "https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/"
environment.PIP_PRERELEASE = "allow"

[tool.cibuildwheel]
environment.UV_ONLY_BINARY = "numpy"
environment.UV_PREFER_BINARY = "1"

[[tool.cibuildwheel.overrides]]
select = ["cp314*"]
inherit.environment = "append"
environment.UV_INDEX = "https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/"
environment.UV_INDEX_STRATEGY = "unsafe-best-match"
environment.UV_PRERELEASE = "allow"

(Note the *_ONLY_BINARY variable also supports ":all:", and you don't need both that and *_PREFER_BINARY, you can use either one, depending on if you want a missing wheel to be a failure or an attempt to build in CI.)

Automatic updates using Dependabot¶

Selecting a moving target (like the latest release) is generally a bad idea in CI. If something breaks, you can't tell whether it was your code or an upstream update that caused the breakage, and in a worst-case scenario, it could occur during a release.

There are two suggested methods for keeping cibuildwheel up to date that instead involve scheduled pull requests using GitHub's Dependabot.

Option 1: GitHub Action¶

If you use GitHub Actions for builds, you can use cibuildwheel as an action:

uses: pypa/cibuildwheel@v3.0.0

This is a composite step that just runs cibuildwheel using pipx. You can set command-line options as with: parameters, and use env: as normal.

Then, your .github/dependabot.yml file could look like this:

version: 2
updates:
  - package-ecosystem: "github-actions"
    directory: "/"
    schedule:
      interval: "weekly"

Option 2: Requirement files¶

The second option, and the only one that supports other CI systems, is using a requirements-*.txt file. The file should have a distinct name and have only one entry:

# requirements-cibw.txt
cibuildwheel==3.0.0

Then your install step would have python -m pip install -r requirements-cibw.txt in it. Your .github/dependabot.yml file could look like this:

version: 2
updates:
  - package-ecosystem: "pip"
    directory: "/"
    schedule:
      interval: "daily"

This will also try to update other pins in all requirement files, so be sure you want to do that. The only control you have over the files used is via the directory option.

Alternatives to cibuildwheel options¶

cibuildwheel provides lots of opportunities to configure the build environment. However, you might consider adding this build configuration into the package itself - in general, this is preferred, because users of your package 'sdist' will also benefit.

Missing build dependencies¶

If your build needs Python dependencies, rather than using before-build, it's best to add these to the build-system.requires section of your pyproject.toml. For example, if your project requires Cython to build, your pyproject.toml might include a section like this:

[build-system]
requires = [
    "setuptools>=42",
    "Cython",
]

build-backend = "setuptools.build_meta"

Actions you need to perform before building¶

You might need to run some other commands before building, like running a script that performs codegen or downloading some data that's not stored in your source tree.

Rather than using before-all or before-build, you could incorporate these steps into your package's build process. For example, if you're using setuptools, you can add steps to your package's setup.py using a structure like this:

import subprocess
import setuptools
import setuptools.command.build_py


class BuildPyCommand(setuptools.command.build_py.build_py):
    """Custom build command."""

    def run(self):
        # your custom build steps here
        # e.g.
        #   subprocess.run(['python', 'scripts/my_custom_script.py'], check=True)
        setuptools.command.build_py.build_py.run(self)


setuptools.setup(
    cmdclass={
        'build_py': BuildPyCommand,
    },
    # Usual setup() args.
    # ...
)

Compiler flags¶

Your build might need some compiler flags to be set through environment variables. Consider incorporating these into your package, for example, in setup.py using extra_compile_args or extra_link_args.

Troubleshooting¶

If your wheel didn't compile, you might have a mistake in your config.

To quickly test your config without doing a git push and waiting for your code to build on CI, you can test the Linux build in a local Docker container.

Missing dependencies¶

Sometimes a build will fail due to a missing dependency.

If the build is missing a Python package, you should add it to pyproject.toml.

If you need a build tool (e.g. cmake, automake, ninja), you can install it through a package manager like apt/yum, brew or choco, using the before-all option.

If your build is linking into a native library dependency, you can build/install that in before-all. However, on Linux, Mac (and Windows if you're using delvewheel), the library that you install will be bundled into the wheel in the repair step. So take care to ensure that

• the bundled library doesn't accidentally increase the minimum system requirements (such as the minimum macOS version)
• the bundled library matches the architecture of the wheel you're building when cross-compiling

This is particularly an issue on macOS, where de facto package manager Homebrew will install libraries that are compiled for the specific version of macOS that the build machine is running, rendering the wheels useless for any previous version. And brew will not install the right arch for cross compilation of Apple Silicon wheels.

For these reasons, it's strongly recommended to not use brew for native library dependencies. Instead, we recommend compiling the library yourself. If you compile in the before-all step, cibuildwheel will have already set the appropriate MACOSX_DEPLOYMENT_TARGET env var, so the library will target the correct version of macOS.

Building Rust wheels¶

If you build Rust wheels, you need to download the Rust compilers in manylinux. If you support 32-bit Windows, you need to add this as a potential target. You can do this on GitHub Actions, for example, with:

CIBW_BEFORE_ALL_LINUX: curl -sSf https://sh.rustup.rs | sh -s -- -y
CIBW_BEFORE_ALL_WINDOWS: rustup target add i686-pc-windows-msvc
CIBW_ENVIRONMENT_LINUX: "PATH=$HOME/.cargo/bin:$PATH"

Rust's minimum macOS target is 10.12, while CPython supports 10.9 before Python 3.12, so you'll need to raise the minimum:

[tool.cibuildwheel.macos.environment]
MACOSX_DEPLOYMENT_TARGET = "10.12"

And Rust does not provide Cargo for musllinux 32-bit, so that needs to be skipped:

[tool.cibuildwheel]
skip = ["*-musllinux_i686"]

Also see maturin-action which is optimized for Rust wheels, builds the non-Python Rust modules once, and can cross-compile (and can build 32-bit musl, for example).

macOS: 'No module named XYZ' errors after running cibuildwheel¶

cibuildwheel on Mac installs the distributions from Python.org system-wide during its operation. This is necessary, but it can cause some confusing errors after cibuildwheel has finished.

Consider the build script:

python3 -m pip install twine cibuildwheel
python3 -m cibuildwheel --output-dir wheelhouse
python3 -m twine upload wheelhouse/*.whl
# error: no module named 'twine'

This doesn't work because while cibuildwheel was running, it installed a few new versions of 'python3', so the python3 run on line 3 isn't the same as the python3 that ran on line 1.

Solutions to this vary, but the simplest is to use pipx:

# most runners have pipx preinstalled, but in case you don't
python3 -m pip install pipx

pipx run cibuildwheel==3.0.0 --output-dir wheelhouse
pipx run twine upload wheelhouse/*.whl

macOS: Passing DYLD_LIBRARY_PATH to delocate¶

macOS has built-in System Integrity protections which limits the use of DYLD_LIBRARY_PATH and LD_LIBRARY_PATH so that it does not automatically pass to children processes. This means if you set DYLD_LIBRARY_PATH before running cibuildwheel, or even set it in environment, it will be stripped out of the environment before delocate is called.

To work around this, use a different environment variable such as REPAIR_LIBRARY_PATH to store the library path, and set DYLD_LIBRARY_PATH in macos.repair-wheel-command, like this:

CIBW_REPAIR_WHEEL_COMMAND_MACOS: >
    DYLD_LIBRARY_PATH=$REPAIR_LIBRARY_PATH delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel}

[tool.cibuildwheel.macos]
repair-wheel-command = """\
DYLD_LIBRARY_PATH=$REPAIR_LIBRARY_PATH delocate-wheel \
--require-archs {delocate_archs} -w {dest_dir} -v {wheel}\
"""

See #816, thanks to @phoerious for reporting.

macOS: Building CPython 3.8 wheels on arm64¶

If you're building on an arm64 runner, you might notice something strange about CPython 3.8 - unlike Python 3.9+, it's cross-compiled to arm64 from an x86_64 version of Python running under Rosetta emulation. This is because (despite the prevalence of arm64 versions of Python 3.8 from Apple and Homebrew) there is no officially supported Python.org installer of Python 3.8 for arm64.

This is fine for simple C extensions, but for more complicated builds on arm64 it becomes an issue.

So, if you want to build macOS arm64 wheels on an arm64 runner (e.g., macos-14) on Python 3.8, before invoking cibuildwheel, you should install a native arm64 Python 3.8 interpreter on the runner:

- uses: actions/setup-python@v5
  with:
    python-version: 3.8
  if: runner.os == 'macOS' && runner.arch == 'ARM64'

curl -o /tmp/Python38.pkg https://www.python.org/ftp/python/3.8.10/python-3.8.10-macos11.pkg
sudo installer -pkg /tmp/Python38.pkg -target /
sh "/Applications/Python 3.8/Install Certificates.command"

Then cibuildwheel will detect that it's installed and use it instead. However, you probably don't want to build x86_64 wheels on this Python, unless you're happy with them only supporting macOS 11+.

macOS: Library dependencies do not satisfy target MacOS¶

Since delocate 0.11.0 there is added verification that the library binary dependencies match the target macOS version. This is to prevent the situation where a wheel platform tag is lower than the actual minimum macOS version required by the library. To resolve this error you need to build the library to the same macOS version as the target wheel (for example using MACOSX_DEPLOYMENT_TARGET environment variable). Alternatively, you could set MACOSX_DEPLOYMENT_TARGET in environment to correctly label the wheel as incompatible with older macOS versions.

This error may happen when you install a library using a package manager like Homebrew, which compiles the library for the macOS version of the build machine. This is not suitable for wheels, as the library will only work on the same macOS version as the build machine. You should compile the library yourself, or use a precompiled binary that matches the target macOS version.

Windows: 'ImportError: DLL load failed: The specific module could not be found'¶

Visual Studio and MSVC link the compiled binary wheels to the Microsoft Visual C++ Runtime. Normally, the C parts of the runtime are included with Python, but the C++ components are not. When compiling modules using C++, it is possible users will run into problems on systems that do not have the full set of runtime libraries installed. The solution is to ask users to download the corresponding Visual C++ Redistributable from the Microsoft website and install it.

Additionally, Visual Studio 2019 started linking to an even newer DLL, VCRUNTIME140_1.dll, besides the VCRUNTIME140.dll that is included with recent Python versions (starting from Python 3.5; see here for more details on the corresponding Visual Studio & MSVC versions used to compile the different Python versions). To avoid this extra dependency on VCRUNTIME140_1.dll, the /d2FH4- flag can be added to the MSVC invocations (check out this issue for details and references). CPython 3.8.3 and all versions after it have this extra DLL, so it is only needed for 3.8 and earlier.

To add the /d2FH4- flag to a standard setup.py using setuptools, the extra_compile_args option can be used:

    ext_modules=[
        Extension(
            'c_module',
            sources=['extension.c'],
            extra_compile_args=['/d2FH4-'] if sys.platform == 'win32' else []
        )
    ],

To investigate the dependencies of a C extension (i.e., the .pyd file, a DLL in disguise) on Windows, Dependency Walker is a great tool. For diagnosing a failing import, the dlltracer tool may also provide additional details.