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Type stubs for SciPy

Project description

scipy-stubs

Type stubs for SciPy.

scipy-stubs - PyPI scipy-stubs - Python Versions scipy-stubs - dependencies scipy-stubs - license

scipy-stubs - CI scipy-stubs - basedmypy scipy-stubs - basedpyright scipy-stubs - ruff


[!NOTE] This project is in the alpha stage, so some annotations are missing, and some might be (slightly) incorrect. But either way, it's no problem to scipy-stubs at the moment: Type-checkers will (already) understand scipy a lot better with scipy-stubs, than without it.

Installation

The scipy-stubs package is available as on PyPI:

pip install scipy-stubs

Version Compatibility

Type-checkers

For validation and testing, scipy-stubs primarily uses basedmypy (a mypy fork) and basedpyright (a pyright fork). Because they are in generally stricter than mypy and pyright, they should be compatible as well. If you find that this is not the case, then don't hesitate to open an issue.

Required dependencies

The versioning scheme of scipy-stubs includes the compatible scipy version. Later versions might work too, but in case of API-changes, the stubs could be outdated.

Apart from scipy's own dependencies (e.g. numpy), the only other required dependency is optype.

The exact version requirements are specified in the pyproject.toml.

Development Progress

Package or module Stubs status
scipy.__init__ 3: ready
scipy._lib 2: partial
scipy.cluster.vq 4: done
scipy.cluster.hierarchy 4: done
scipy.constants 4: done
scipy.datasets 4: done
scipy.fft 2: partial
scipy.fftpack 2: partial
scipy.integrate 4: done
scipy.interpolate 2: partial
scipy.io 2: partial
scipy.io.arff 2: partial
scipy.io.matlab 2: partial
scipy.linalg 4: done
scipy.misc 4: done
scipy.ndimage 2: partial
scipy.odr 1: skeleton
scipy.optimize 2: partial
scipy.signal 2: partial
scipy.signal.windows 1: skeleton
scipy.sparse 2: partial
scipy.sparse.csgraph 2: partial
scipy.sparse.linalg 2: partial
scipy.spatial 2: partial
scipy.spatial.distance 3: ready
scipy.special 4: done
scipy.special.cython_special 4: done
scipy.stats 2: partial
scipy.stats.contingency 1: skeleton
scipy.stats.distributions 4: done
scipy.stats.mstats 1: skeleton
scipy.stats.qmc 2: partial
scipy.stats.sampling 1: skeleton
scipy.version 4: done

Status labels:

  • 0: missing (failed stubgen)
  • 1: skeleton (mostly succesful stubgen)
  • 2: partial (incomplete/broad annotations)
  • 3: ready (complete & valid annotations, untested)
  • 4: done (complete, valid, tested, and production-ready)

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