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Python Enhancement Proposals

PEP 725 – Specifying external dependencies in pyproject.toml

Pradyun Gedam <pradyunsg at>, Ralf Gommers <ralf.gommers at>
Discourse thread
Standards Track

Table of Contents


This PEP specifies how to write a project’s external, or non-PyPI, build and runtime dependencies in a pyproject.toml file for packaging-related tools to consume.


Python packages may have dependencies on build tools, libraries, command-line tools, or other software that is not present on PyPI. Currently there is no way to express those dependencies in standardized metadata [1], [2]. Key motivators for this PEP are to:

  • Enable tools to automatically map external dependencies to packages in other packaging repositories,
  • Make it possible to include needed dependencies in error messages emitting by Python package installers and build frontends,
  • Provide a canonical place for package authors to record this dependency information.

Packaging ecosystems like Linux distros, Conda, Homebrew, Spack, and Nix need full sets of dependencies for Python packages, and have tools like pyp2rpm (Fedora), Grayskull (Conda), and dh_python (Debian) which attempt to automatically generate dependency metadata from the metadata in upstream Python packages. External dependencies are currently handled manually, because there is no metadata for this in pyproject.toml or any other standard location. Enabling automating this conversion is a key benefit of this PEP, making packaging Python easier and more reliable. In addition, the authors envision other types of tools making use of this information, e.g., dependency analysis tools like Repology, Dependabot and Software bill of materials (SBOM) generation tools may also be able to use this information, e.g. for flagging that external dependencies listed in pyproject.toml but not contained in wheel metadata are likely vendored within the wheel.

Packages with external dependencies are typically hard to build from source, and error messages from build failures tend to be hard to decipher for end users. Missing external dependencies on the end user’s system are the most likely cause of build failures. If installers can show the required external dependencies as part of their error message, this may save users a lot of time.

At the moment, information on external dependencies is only captured in installation documentation of individual packages. It is hard to maintain for package authors and tends to go out of date. It’s also hard for users and distro packagers to find it. Having a canonical place to record this dependency information will improve this situation.

This PEP is not trying to specify how the external dependencies should be used, nor a mechanism to implement a name mapping from names of individual packages that are canonical for Python projects published on PyPI to those of other packaging ecosystems. Those topics should be addressed in separate PEPs.


Types of external dependencies

Multiple types of external dependencies can be distinguished:

  • Concrete packages that can be identified by name and have a canonical location in another language-specific package repository. E.g., Rust packages on, R packages on CRAN, JavaScript packages on the npm registry.
  • Concrete packages that can be identified by name but do not have a clear canonical location. This is typically the case for libraries and tools written in C, C++, Fortran, CUDA and other low-level languages. E.g., Boost, OpenSSL, Protobuf, Intel MKL, GCC.
  • “Virtual” packages, which are names for concepts, types of tools or interfaces. These typically have multiple implementations, which are concrete packages. E.g., a C++ compiler, BLAS, LAPACK, OpenMP, MPI.

Concrete packages are straightforward to understand, and are a concept present in virtually every package management system. Virtual packages are a concept also present in a number of packaging systems – but not always, and the details of their implementation varies.

Cross compilation

Cross compilation is not yet (as of August 2023) well-supported by stdlib modules and pyproject.toml metadata. It is however important when translating external dependencies to those of other packaging systems (with tools like pyp2rpm). Introducing support for cross compilation immediately in this PEP is much easier than extending [external] in the future, hence the authors choose to include this now.


This PEP uses the following terminology:

  • build machine: the machine on which the package build process is being executed
  • host machine: the machine on which the produced artifact will be installed and run
  • build dependency: dependency for building the package that needs to be present at build time and itself was built for the build machine’s OS and architecture
  • host dependency: dependency for building the package that needs to be present at build time and itself was built for the host machine’s OS and architecture

Note that this terminology is not consistent across build and packaging tools, so care must be taken when comparing build/host dependencies in pyproject.toml to dependencies from other package managers.

Note that “target machine” or “target dependency” is not used in this PEP. That is typically only relevant for cross-compiling compilers or other such advanced scenarios [3], [4] - this is out of scope for this PEP.

Finally, note that while “dependency” is the term most widely used for packages needed at build time, the existing key in pyproject.toml for PyPI build-time dependencies is build-requires. Hence this PEP uses the keys build-requires and host-requires under [external] for consistency.

Build and host dependencies

Clear separation of metadata associated with the definition of build and target platforms, rather than assuming that build and target platform will always be the same, is important [5].

Build dependencies are typically run during the build process - they may be compilers, code generators, or other such tools. In case the use of a build dependency implies a runtime dependency, that runtime dependency does not have to be declared explicitly. For example, when compiling Fortran code with gfortran into a Python extension module, the package likely incurs a dependency on the libgfortran runtime library. The rationale for not explicitly listing such runtime dependencies is two-fold: (1) it may depend on compiler/linker flags or details of the build environment whether the dependency is present, and (2) these runtime dependencies can be detected and handled automatically by tools like auditwheel.

Host dependencies are typically not run during the build process, but only used for linking against. This is not a rule though – it may be possible or necessary to run a host dependency under an emulator, or through a custom tool like crossenv. When host dependencies imply a runtime dependency, that runtime dependency also does not have to be declared, just like for build dependencies.

When host dependencies are declared and a tool is not cross-compilation aware and has to do something with external dependencies, the tool MAY merge the host-requires list into build-requires. This may for example happen if an installer like pip starts reporting external dependencies as a likely cause of a build failure when a package fails to build from an sdist.

Specifying external dependencies

Concrete package specification through PURL

The two types of concrete packages are supported by PURL (Package URL), which implements a scheme for identifying packages that is meant to be portable across packaging ecosystems. Its design is:


The scheme component is a fixed string, pkg, and of the other components only type and name are required. As an example, a package URL for the requests package on PyPI would be:


Adopting PURL to specify external dependencies in pyproject.toml solves a number of problems at once - and there are already implementations of the specification in Python and multiple languages. PURL is also already supported by dependency-related tooling like SPDX (see External Repository Identifiers in the SPDX 2.3 spec), the Open Source Vulnerability format, and the Sonatype OSS Index; not having to wait years before support in such tooling arrives is valuable.

For concrete packages without a canonical package manager to refer to, either pkg:generic/pkg-name can be used, or a direct reference to the VCS system that the package is maintained in (e.g., pkg:github/user-or-org-name/pkg-name). Which of these is more appropriate is situation-dependent. This PEP recommends using pkg:generic when the package name is unambiguous and well-known (e.g., pkg:generic/git or pkg:generic/openblas), and using the VCS as the PURL type otherwise.

Virtual package specification

There is no ready-made support for virtual packages in PURL or another standard. There are a relatively limited number of such dependencies though, and adoption a scheme similar to PURL but with the virtual: rather than pkg: scheme seems like it will be understandable and map well to Linux distros with virtual packages and the likes of Conda and Spack.

The two known virtual package types are compiler and interface.


Support in PURL for version expressions and ranges beyond a fixed version is still pending, see the Open Issues section.

Dependency specifiers

Regular Python dependency specifiers (as originally defined in PEP 508) may be used behind PURLs. PURL qualifiers, which use ? followed by a package type-specific dependency specifier component, must not be used. The reason for this is pragmatic: dependency specifiers are already used for other metadata in pyproject.toml, any tooling that is used with pyproject.toml is likely to already have a robust implementation to parse it. And we do not expect to need the extra possibilities that PURL qualifiers provide (e.g. to specify a Conan or Conda channel, or a RubyGems platform).

Usage of core metadata fields

The core metadata specification contains one relevant field, namely Requires-External. This has no well-defined semantics in core metadata 2.1; this PEP chooses to reuse the field for external runtime dependencies. The core metadata specification does not contain fields for any metadata in pyproject.toml’s [build-system] table. Therefore the build-requires and host-requires content also does not need to be reflected in core metadata fields. The optional-dependencies content from [external] would need to either reuse Provides-Extra or require a new Provides-External-Extra field. Neither seems desirable.

Differences between sdist and wheel metadata

A wheel may vendor its external dependencies. This happens in particular when distributing wheels on PyPI or other Python package indexes - and tools like auditwheel, delvewheel and delocate automate this process. As a result, a Requires-External entry in an sdist may disappear from a wheel built from that sdist. It is also possible that a Requires-External entry remains in a wheel, either unchanged or with narrower constraints. auditwheel does not vendor certain allow-listed dependencies, such as OpenGL, by default. In addition, auditwheel and delvewheel allow a user to manually exclude dependencies via a --exclude or --no-dll command-line flag. This is used to avoid vendoring large shared libraries, for example those from CUDA.

Requires-External entries generated from external dependencies in pyproject.toml in a wheel are therefore allowed to be narrower than those for the corresponding sdist. They must not be wider, i.e. constraints must not allow a version of a dependency for a wheel that isn’t allowed for an sdist, nor contain new dependencies that are not listed in the sdist’s metadata at all.


If metadata is improperly specified then tools MUST raise an error to notify the user about their mistake.


Note that pyproject.toml content is in the same format as in PEP 621.

Table name

Tools MUST specify fields defined by this PEP in a table named [external]. No tools may add fields to this table which are not defined by this PEP or subsequent PEPs. The lack of an [external] table means the package either does not have any external dependencies, or the ones it does have are assumed to be present on the system already.


  • Format: Array of PURL strings (build-requires) and a table with values of arrays of PURL strings (optional-build-requires)
  • Core metadata: N/A

The (optional) external build requirements needed to build the project.

For build-requires, it is a key whose value is an array of strings. Each string represents a build requirement of the project and MUST be formatted as either a valid PURL string or a virtual: string.

For optional-build-requires, it is a table where each key specifies an extra set of build requirements and whose value is an array of strings. The strings of the arrays MUST be valid PURL strings.


  • Format: Array of PURL strings (host-requires) and a table with values of arrays of PURL strings (optional-host-requires)
  • Core metadata: N/A

The (optional) external host requirements needed to build the project.

For host-requires, it is a key whose value is an array of strings. Each string represents a host requirement of the project and MUST be formatted as either a valid PURL string or a virtual: string.

For optional-host-requires, it is a table where each key specifies an extra set of host requirements and whose value is an array of strings. The strings of the arrays MUST be valid PURL strings.


  • Format: Array of PURL strings (dependencies) and a table with values of arrays of PURL strings (optional-dependencies)
  • Core metadata: Requires-External, N/A

The (optional) dependencies of the project.

For dependencies, it is a key whose value is an array of strings. Each string represents a dependency of the project and MUST be formatted as either a valid PURL string or a virtual: string. Each string maps directly to a Requires-External entry in the core metadata.

For optional-dependencies, it is a table where each key specifies an extra and whose value is an array of strings. The strings of the arrays MUST be valid PURL strings. Optional dependencies do not map to a core metadata field.


These examples show what the [external] content for a number of packages is expected to be.

cryptography 39.0:

build-requires = [
host-requires = [

SciPy 1.10:

build-requires = [
host-requires = [
  "virtual:interface/lapack",  # >=3.7.1 (can't express version ranges with PURL yet)

dependency_detection = [

pygraphviz 1.10:

build-requires = [
host-requires = [

NAVis 1.4.0:

r = ["rpy2"]

build-requires = [
  "pkg:generic/XCB; platform_system=='Linux'",

nat = [

Spyder 6.0:

dependencies = [

jupyterlab-git 0.41.0:

dependencies = [

dev = [

PyEnchant 3.2.2:

dependencies = [
  # libenchant is needed on all platforms but only vendored into wheels on
  # Windows, so on Windows the build backend should remove this external
  # dependency from wheel metadata.

Backwards Compatibility

There is no impact on backwards compatibility, as this PEP only adds new, optional metadata. In the absence of such metadata, nothing changes for package authors or packaging tooling.

Security Implications

There are no direct security concerns as this PEP covers how to statically define metadata for external dependencies. Any security issues would stem from how tools consume the metadata and choose to act upon it.

How to Teach This

External dependencies and if and how those external dependencies are vendored are topics that are typically not understood in detail by Python package authors. We intend to start from how an external dependency is defined, the different ways it can be depended on—from runtime-only with ctypes or a subprocess call to it being a build dependency that’s linked against— before going into how to declare external dependencies in metadata. The documentation should make explicit what is relevant for package authors, and what for distro packagers.

Material on this topic will be added to the most relevant packaging tutorials, primarily the Python Packaging User Guide. In addition, we expect that any build backend that adds support for external dependencies metadata will include information about that in its documentation, as will tools like auditwheel.

Reference Implementation

There is no reference implementation at this time.

Rejected Ideas

Specific syntax for external dependencies which are also packaged on PyPI

There are non-Python packages which are packaged on PyPI, such as Ninja, patchelf and CMake. What is typically desired is to use the system version of those, and if it’s not present on the system then install the PyPI package for it. The authors believe that specific support for this scenario is not necessary (or too complex to justify such support); a dependency provider for external dependencies can treat PyPI as one possible source for obtaining the package.

Using library and header names as external dependencies

A previous draft PEP (“External dependencies” (2015)) proposed using specific library and header names as external dependencies. This is too granular; using package names is a well-established pattern across packaging ecosystems and should be preferred.

Open Issues

Version specifiers for PURLs

Support in PURL for version expressions and ranges is still pending. The pull request at vers implementation for PURL seems close to being merged, at which point this PEP could adopt it.

Syntax for virtual dependencies

The current syntax this PEP uses for virtual dependencies is virtual:type/name, which is analogous to but not part of the PURL spec. This open issue discusses supporting virtual dependencies within PURL: purl-spec#222.

Should a host-requires key be added under [build-system]?

Adding host-requires for host dependencies that are on PyPI in order to better support name mapping to other packaging systems with support for cross-compiling may make sense. This issue tracks this topic and has arguments in favor and against adding host-requires under [build-system] as part of this PEP.



Last modified: 2023-09-09 17:39:29 GMT