adding partipy

[psl-schaefer]

Mandatory

Name of the tool: ParTIpy (partipy)

Short description: Implements Pareto task inference and archetypal analysis for analyzing functional trade-offs in single-cell and spatial omics data.

How does the package use scverse data structures (please describe in a few sentences): Uses anndata as primary data structure.

• The code is publicly available under an OSI-approved license
• The package provides versioned releases
• The package can be installed from a standard registry (e.g. PyPI, conda-forge, bioconda)
• Automated tests cover essential functions of the package and a reasonable range of inputs and conditions ¹
• Continuous integration (CI) automatically executes these tests on each push or pull request ²
• The package provides API documentation via a website or README³
• The package uses scverse datastructures where appropriate (i.e. AnnData, MuData or SpatialData and their modality-specific extensions)
• I am an author or maintainer of the tool and agree on listing the package on the scverse website

Recommended

• Please announce this package on scverse communication channels (zulip, discourse, twitter)

• Please tag the author(s) these announcements. Handles (e.g. @scverse_team) to include are:

  • Zulip: Philipp (937099)
  • Discourse:
  • Mastodon:
  • Bluesky: psl-schaefer
  • Twitter: psl_schaefer

• The package provides tutorials (or "vignettes") that help getting users started quickly

• The package uses the scverse cookiecutter template.

Footnotes

1. We recommend thtat tests cover at least all user facing (public) functions. Minimal tests ensure that the function does not fail on an example data set. Ideally, tests also ensure the correctness of the results, e.g. by comparing against a snapshot. ↩

2. Continuous integration means that software tests are automatically executed on every push to the git repository. This guarantees they are always run and that they are run in a clean environment. Scverse ecosystem packages most commonly use GitHub Actions for CI. For an example, check out our cookiecutter template. ↩

3. By API documentation, we mean an overview of all public functions provided a package, with documentation of their parameters. For an example, see the Scanpy documentation. In simple cases, this can be done manually in a README file. For anything more complex, we recommend the Sphinx Autodoc plugin ↩

[mikkelnrasmussen]

Hi @psl-schaefer,

Thanks for submitting this awesome package! Everything looks good to me - great API documentation, great tutorials, great test coverage!

Best,
Mikkel

[psl-schaefer]

Thanks a lot @mikkelnrasmussen!