Build Test codecov License PyPI Python Version Read the Docs pre-commit

Squidpy - Spatial Single Cell Analysis in Python

Squidpy is the scverse toolkit for scalable analysis and visualization of spatial molecular data. It builds on scanpy and anndata, providing streamlined APIs for feature extraction, spatial statistics, and interactive exploration of tissue sections together with microscopy images.

Squidpy overview

Documentation

Head over to the documentation for installation instructions, tutorials, how-to guides, and reference material.

Installation

We recommend running Squidpy on a recent Linux or macOS system with Python ≥3.11, but it also works on Windows via WSL.

Install from PyPI with:

pip install squidpy

or from conda-forge:

conda install -c conda-forge squidpy

Interactive visualization

To get optional dependencies required for the napari-based interactive plotting APIs, install the interactive extra:

pip install 'squidpy[interactive]'

Key capabilities

  • Build and analyze spatial neighbor graphs directly from Visium, Slide-seq, Xenium, and other spatial omics assays.
  • Compute spatial statistics for cell types and genes, including neighborhood enrichment, co-occurrence, and Moran's I.
  • Efficiently store, featurize, and visualize high-resolution tissue microscopy images via scikit-image.
  • Explore annotated datasets interactively with napari and scverse visualization tooling.

Contributing

Contributions are welcome! Please read the contributing guide for instructions on setting up your environment, running tests, and submitting pull requests.

Citation

If you use Squidpy in your research, cite the original publication:

@article{palla:22,
    author = {Palla, Giovanni and Spitzer, Hannah and Klein, Michal and Fischer, David and Schaar, Anna Christina
              and Kuemmerle, Louis Benedikt and Rybakov, Sergei and Ibarra, Ignacio L. and Holmberg, Olle
              and Virshup, Isaac and Lotfollahi, Mohammad and Richter, Sabrina and Theis, Fabian J.},
    title = {Squidpy: a scalable framework for spatial omics analysis},
    journal = {Nature Methods},
    year = {2022},
    month = {Feb},
    volume = {19},
    number = {2},
    pages = {171--178},
    issn = {1548-7105},
    doi = {10.1038/s41592-021-01358-2},
}

Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

Project links

Data verified by PyPI on Dec 2, 2025
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.8.3)

Owner

PyPI data
Data sourced directly from PyPI's database.

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for wmv1992 from gravatar.com wmv1992

Credits

Author: scverse

Maintainer: Tim Treis

GitHub Statistics

Data verified by PyPI on Dec 2, 2025
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

BSD-3-Clause
View SPDX License List

Requires

Python >=3.11

Provides Extra

dev docs test

Tags

bio-informatics image analysis single-cell spatial data analysis spatial transcriptomics

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

squidpy-1.6.6.tar.gz (6.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

squidpy-1.6.6-py3-none-any.whl (178.1 kB view details)

Uploaded Python 3

File details

Details for the file squidpy-1.6.6.tar.gz.

File metadata

  • Download URL: squidpy-1.6.6.tar.gz
  • Upload date:
  • Size: 6.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for squidpy-1.6.6.tar.gz
Algorithm Hash digest
SHA256 09aeda3112e4baa7998c515062288e2ac6b77a5bbbac0f8f3531e07e5cc5371b
MD5 7ca368c08f820aaac27ae65ddc2a310c
BLAKE2b-256 a9d4a2ac2ddc18fefa29ef60c97f6cf015815549469012c9f3cde0dd2242ce93

See more details on using hashes here.

Provenance

The following attestation bundles were made for squidpy-1.6.6.tar.gz:

Publisher: release.yaml on scverse/squidpy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file squidpy-1.6.6-py3-none-any.whl.

File metadata

  • Download URL: squidpy-1.6.6-py3-none-any.whl
  • Upload date:
  • Size: 178.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for squidpy-1.6.6-py3-none-any.whl
Algorithm Hash digest
SHA256 41a07407f27934ed6f7e851bd67e1b5155340fc5529c31938cf7730a8265f294
MD5 1727d62167bf00cffbee829b3bb974d8
BLAKE2b-256 48ebac164184208b7706793410ed6cb01316fb2995255e7129227efa54c161c0

See more details on using hashes here.

Provenance

The following attestation bundles were made for squidpy-1.6.6-py3-none-any.whl:

Publisher: release.yaml on scverse/squidpy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

1.8.3

2 files

1.8.2

2 files

1.8.1

2 files

1.8.0

2 files

1.7.0

2 files

This release

1.6.6 This release

2 files

1.6.5

2 files

1.6.4

2 files

1.6.3

2 files

1.6.2

2 files

1.6.1

2 files

1.6.0

2 files

1.5.0

2 files

1.4.1

2 files

1.4.0

2 files

1.3.1

2 files

1.3.0

2 files

1.2.3

2 files

1.2.2

2 files

1.2.1

2 files

1.2.0

2 files

1.1.2

2 files

1.1.1

2 files

1.1.0

2 files

1.0.1

2 files

1.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page