Add entries for wsidata and LazySlide

[Mr-Milk]

Checklist for adding packages

Mandatory

Name of the tool: wsidata

Short description: wsidata is a data-structure for efficient IO of Whole Slide Images based on spatialdata.

How does the package use scverse data structures (please describe in a few sentences): The wsidata extends SpatialData to tailor the usage for Whole Slide Imaging

• 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 README[^3]
• 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:
  • Twitter:
  • Zulip:
  • Discourse:
  • Mastodon:
• The package provides tutorials (or "vignettes") that help getting users started quickly
• The package uses the scverse cookiecutter template.

Mandatory

Name of the tool: LazySlide

Short description: LazySlide is a Python library for processing whole slide images (WSI) analysis. It provides a simple interface to perform robust preprocessing and advanced analysis for WSI.

How does the package use scverse data structures (please describe in a few sentences): LazySlide used previous described wsidata as data structures. Since wsidata is extended from SpatialData, many functions in LazySlide is also compatible with SpatialData.

• 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 README[^3]
• 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:
  • Twitter:
  • Zulip:
  • Discourse:
  • Mastodon:
• The package provides tutorials (or "vignettes") that help getting users started quickly
• The package uses the scverse cookiecutter template.