Pyskani |Stars|
================
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`PyO3 `_ *bindings and Python interface to* `skani `_,
*a method for fast fast genomic identity calculation using sparse chaining.*
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Overview
--------
``skani`` is a method developed by `Jim Shaw `_
and `Yun William Yu `_ for fast and robust
metagenomic sequence comparison through sparse chaining. It improves on
FastANI by being more accurate and much faster, while requiring less memory.
``pyskani`` is a Python module, implemented using the `PyO3 `_
framework, that provides bindings to ``skani``. It directly links to the
``skani`` code, which has the following advantages over CLI wrappers:
- **pre-built wheels**: ``pyskani`` is distributed on PyPI and features
pre-built wheels for common platforms, including x86-64 and Arm64 UNIX.
- **single dependency**: If your software or your analysis pipeline is
distributed as a Python package, you can add ``pyskani`` as a dependency to
your project, and stop worrying about the ``skani`` binary being present on
the end-user machine.
- **sans I/O**: Everything happens in memory, in Python objects you control,
making it easier to pass your sequences to ``skani`` without having to write
them to a temporary file.
Setup
-----
Run ``pip install pyskani`` in a shell to download the latest release and all
its dependencies from PyPi, or have a look at the
:doc:`Installation page ` to find other ways to install ``pyskani``.
Library
-------
.. toctree::
:maxdepth: 2
Installation
Contributing
API Reference
Changelog
License
-------
This library is provided under the `MIT License `_.
The ``skani`` code was written by `Jim Shaw `_
and is distributed under the terms of the
`MIT License `_ as well. Source
distributions of ``pyskani`` may vendors additional sources under their
own terms using the ``cargo vendor`` command.
*This project is in no way not affiliated, sponsored, or otherwise endorsed by
the original* ``skani`` *authors. It was developed by*
`Martin Larralde `_ *during his
PhD project at the* `European Molecular Biology Laboratory `_
*in the* `Zeller team `_.