Notes about specific Features

This sections describes details about specific features. For a full list of features please refer to the website.

Ctypes Dependencies

Ctypes is a foreign function library for Python, that allows calling functions present in shared libraries. Those libraries are not imported as Python packages, because they are not picked up via Python imports: their path is passed to ctypes instead, which deals with the shared library directly; this caused <1.4 PyInstaller import detect machinery to miss those libraries, failing the goal to build self-contained PyInstaller executables:

from ctypes import *
# This will pass undetected under PyInstaller detect machinery,
# because it's not a direct import.
handle = CDLL("/usr/lib/")

Solution in PyInstaller

PyInstaller contains a pragmatic implementation of Ctypes dependencies: it will search for simple standard usages of ctypes and automatically track and bundle the referenced libraries. The following usages will be correctly detected:

cdll.library # Only valid under Windows - a limitation of ctypes, not PyInstaller's
windll.library # Only valid under Windows - a limitation of ctypes, not PyInstaller's

More in detail, the following restrictions apply:

  • only libraries referenced by bare filenames (e.g. no leading paths) will be handled; handling absolute paths would be impossible without modifying the bytecode as well (remember that while running frozen, ctypes would keep searching the library at that very absolute location, whose presence on the host system nobody can guarantee), and relative paths handling would require recreating in the frozen executable the same hierarchy of directories leading to the library, in addition of keeping track of which the current working directory is;

  • only library paths represented by a literal string will be detected and included in the final executable: PyInstaller import detection works by inspecting raw Python bytecode, and since you can pass the library path to ctypes using a string (that can be represented by a literal in the code, but also by a variable, by the return value of an arbitrarily complex function, etc…), it’s not reasonably possible to detect all ctypes dependencies;

  • only libraries referenced in the same context of ctypes’ invocation will be handled.

We feel that it should be enough to cover most ctypes’ usages, with little or no modification required in your code.

If PyInstaller does not detect a library, you can add it to your bundle by passing the respective information to --add-binary option or listing it in the .spec-file. If your frozen application will be able to pick up the library at run-time can not be guaranteed as it depends on the detailed implementation.


The ctypes detection system at Analysis time is based on ctypes.util.find_library(). This means that you have to make sure that while performing Analysis and running frozen, all the environment values find_library() uses to search libraries are aligned to those when running un-frozen. Examples include using LD_LIBRARY_PATH or DYLD_LIBRARY_PATH to widen find_library() scope.

SWIG support

PyInstaller tries to detect binary modules created by SWIG. This detection requires:

  • The Python wrapper module must be imported somewhere in your application (or by any of the modules it uses).

  • The wrapper module must be available as source-code and it’s first line must contain the text automatically generated by SWIG.

  • The C-module must have the same name as the wrapper module prefixed with an underscore (_). (This is a SWIG restriction already.)

  • The C-module must sit just beside the wrapper module (thus a relative import would work).

Also some restrictions apply, due to the way the SWIG wrapper is implemented:

  • The C-module will become a global module. As a consequence, you can not use two SWIG modules with the same basename (e.g. pkg1._cmod and pkg2._cmod), as one would overwrite the other.

Cython support

PyInstaller can follow import statements that refer to Cython C object modules and bundle them – like for any other module implemented in C.

But – again, as for any other module implemented in C – PyInstaller can not determine if the Cython C object module is importing some Python module. These will typically show up as in a traceback like this (mind the .pyx extension):

Traceback (most recent call last):
File "myapp\cython_module.pyx", line 3, in init myapp.cython_module
ModuleNotFoundError: No module named 'csv'

So if you are using a Cython C object module, which imports Python modules, you will have to list these as --hidden-import.

macOS multi-arch support

With the introduction of Apple Silicon M1, there are now several architecture options available for python:

  • single-arch x86_64 with thin binaries: older builds, Homebrew python running natively on Intel Macs or under rosetta2 on M1 Macs

  • single-arch arm64 with thin binaries: Homebrew python running natively on M1 macs

  • multi-arch universal2 with fat binaries (i.e., containing both x86_64 and arm64 slices): recent universal2 builds

PyInstaller aims to support all possible combinations stemming from the above options:

  • single-arch application created using corresponding single-arch python

  • universal2 application created using universal2 python

  • single-arch application created using universal2 python (i.e., reducing universal2 fat binaries into either x86_64 or arm64 thin binaries)

By default, PyInstaller targets the current running architecture and produces a single-arch binary (x86_64 when running on Intel Mac or under rosetta2 on M1 Mac, or arm64 when running on M1 Mac). The reason for that is that even with a universal2 python environment, some packages may end up providing only single-arch binaries, making it impossible to create a functional universal2 frozen application.

The alternative options, such as creating a universal2 version of frozen application, or creating a non-native single-arch version using universal2 environment, must therefore be explicitly enabled. This can be done either by specifying the target architecture in the .spec file via the target_arch= argument to EXE(), or on command-line via the --target-arch switch. Valid values are x86_64, arm64, and universal2.

Architecture validation during binary collection

To prevent run-time issues caused by missing or mismatched architecture slices in binaries, the binary collection process performs strict architecture validation. It checks whether collected binary files contain required arch slice(s), and if not, the build process is aborted with an error message about the problematic binary.

In such cases, creating frozen application for the selected target architecture will not be possible unless the problem of missing arch slices is manually addressed (for example, by downloading the wheel corresponding to the missing architecture, and stiching the offending binary files together using the lipo utility).

Trimming fat binaries for single-arch targets

When targeting a single architecture, the build process extracts the corresponding arch slice from any collected fat binaries, including the bootloader. This results in a completely thin build even when building in universal2 python environment.

macOS binary code signing

With Apple Silicon M1 architecture, macOS introduced mandatory code signing, even if ad-hoc (i.e., without actual code-signing identity). This means that arm64 arch slices (but possibly also x86_64 ones, especially in universal2 binaries) in collected binaries always come with signature.

The processing of binaries done by PyInstaller (e.g., library path rewriting in binaries’ headers) invalidates their signatures. Therefore, the signatures need to be re-generated, otherwise the OS refuses to load a binary.

By default, PyInstaller ad-hoc (re)signs all collected binaries and the generated executable itself. Instead of ad-hoc signing, it is also possible to use real code-signing identity. To do so, either specify your identity in the .spec file via codesign_identity= argument to EXE() , or on command-line via the --codesign-identity switch.

Being able to provide codesign identity allows user to ensure that all collected binaries in either onefile or onedir build are signed with their identity. This is useful because for onefile builds, signing of embedded binaries cannot be performed in a post-processing step.


When codesign identity is specified, PyInstaller also turns on hardened runtime by passing --options=runtime to the codesign command. This requires the codesign identity to be a valid Apple-issued code signing certificate, and will not work with self-signed certificates.

Trying to use self-signed certificate as a codesign identity will result in shared libraries failing to load, with the following reason reported:

[libname]: code signature in ([libname]) not valid for use in process using Library Validation: mapped file has no Team ID and is not a platform binary (signed with custom identity or adhoc?)

Furthermore, it is possible to specify entitlements file to be used when signing the collected binaries and the executable. This can be done in the .spec file via entitlements_file= argument to EXE(), or on command-line via the --osx-entitlements-file switch.

App bundles

PyInstaller also automatically attempts to sign .app bundles, either using ad-hoc identity or actual signing identity, if provided via --codesign-identity switch. In addition to passing same options as when signing collected binaries (identity, hardened runtime, entitlement), deep signing is also enabled via by passing --deep option to the codesign utility.

Should the signing of the bundle fail for whatever reason, the error message from the codesign utility will be printed to the console, along with a warning that manual intervention and manual signing of the bundle are required.