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pyproject-indirect-import-detector: Indirect import detector

PyPI Project License Supported Python versions CircleCI Code style: black

Motivation

Indirect import is bad.

  • The biggest reason is requirements are not protected by semantic versioning.
  • Tests cannot check import-problem correctly.
  • Virtual environment is not strictly synced with pyproject.toml nor poetry.lock by poetry, so far. It is possible that you delete a dependency but it still remains in the virtual environment. This means, tests can accidentally pass.
  • FYI, indirect import is not allowed in rust/cargo.

We'll describe the first reason a little more. There are two examples here.

First, assume that

  • You are developping a library or application X.
  • X depends on a library A ^1 and indirectly depends on a library B ^1, meaning, X imports B but does not declare the dependency in pyproject.toml.
  • The latest A is version 1.0.0 and it depends on B 1.0.0.
      Indirect import; imported but no requirement in pyproject.toml
      |
  +--------> B
  |          ^
  |          |
  |          | ---+
  |          |    |
  X -------> A    Requirement in pyproject.toml
      |
      Requirement in pyproject.toml

Consider the case that the authers of A refactor A and publish A 1.1.0 and this does not depends on B anymore. Then,

  • If X is a library, user of library X can face ModuleNotFoundError.
  • If X is an application and you're using a "blessed" lockfile, you'll get no errors.
  • If X is an application and you're not lucky, you'll get ModuleNotFoundError.

The second example is almost the same to the first. Consider the case that the authers of A refactor A and publish A 1.1.0 and this depends on B ^2 and B has breaking chanegs. Then, you may not have an explicit errors but the behavior can differ from the expected.

It's horrible, isn't it? The most reliable and simple way is maintaining dependencies correctly. Because the resource of human brain is limited and most precious, this should be checked in CI. pyproject-indirect-import-detector is a tool for this purpose.

Limitation

Currently, this tool only suuport pyproject.toml using poetry. PEP 631 support is planed if python community agree this motivation and use this tool.

How to use

Install

poetry add --dev pyproject-indirect-import-detector

Note that this tool is intended to use in the virtual environment created by poetry install. See also: Why only works in venv?

Usage

poetry run pyproject-indirect-import-detector -v

See also CI config, especially the job check-indirect-import.

Configuration

You can configure by pyproject.toml as the following:

[tool.pyproject-indirect-import-detector]
exclude_projects = [
    "dataclasses",           # If you use compat trick like https://github.com/kenoss/pyproject-indirect-import-detector/tree/main/tests/integration_test/case/ok_exclude_projects
]
exclude_modules = [
    "dataclasses",           # Corresponding "dataclasses" in `exclude_projects`.
    "tests",                 # If your test suite make `tests` module importable and use it like https://github.com/andreoliwa/nitpick/blob/v0.26.0/tests/test_json.py#L6 .
    "dummy_module_for_test", # If you use dummy modules in tests like https://github.com/PyCQA/isort/blob/5.8.0/tests/unit/example_crlf_file.py#L1-L2 .
]
  • tool.pyproject-indirect-import-detector.exclude_projects

    Omit searching the distributions corresponding designated package names. Notice that this also prevent making "project to modules map". You should also specify exclude_modules manually. For example, see tests OK, NG.

  • tool.pyproject-indirect-import-detector.exclude_modules

    Omit checks for the designated modules. For example, see tests OK, NG.


You can find more examples in CI config, the jobs test-external-project-*.

FAQ

It failes with not reasonable errors.

Report an issue and let me know your case. The core logic is not yet well-tested with real packages. We need edge cases.

Why only works in venv?

This tool makes a correspondence from package names to module names. This use importlib and requires an environment that has all packages installed. This tool is designed to be used in CI. So, runnable under poetry run is enough.

Why installable with python >= 3.6 and runnable only in python >= 3.9?

See the comment in pyproject.toml. I tried to make it runnable in old pythons, but the cost is high. This tool is designed to be used in CI. So, this restriction is reasonable.

How to develop

How to release

  1. Bump version, PR and merge.
  2. git tag <version> then git push origin <version>.
  3. CI will pubish the package to PyPI: https://pypi.org/project/pyproject-indirect-import-detector/

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Indirct-import detector using pyproject.toml

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