Metadata-Version: 2.1
Name: pyopal
Version: 0.5.0a5
Summary: Cython bindings and Python interface to Opal, a SIMD-accelerated pairwise aligner.
Home-page: https://github.com/althonos/pyopal
Author: Martin Larralde
Author-email: martin.larralde@embl.de
License: MIT
Project-URL: Documentation, https://pyopal.readthedocs.io/en/stable/
Project-URL: Bug Tracker, https://github.com/althonos/pyopal/issues
Project-URL: Changelog, https://github.com/althonos/pyopal/blob/main/CHANGELOG.md
Project-URL: Coverage, https://codecov.io/gh/althonos/pyopal/
Project-URL: Builds, https://github.com/althonos/pyopal/actions
Project-URL: PyPI, https://pypi.org/project/pyopal
Keywords: bioinformatics,pairwise,sequence,alignment,opal
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: C
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Typing :: Typed
Requires-Python: >=3.5
Description-Content-Type: text/markdown
License-File: COPYING
Requires-Dist: archspec ~=0.2 ; os_name != "nt"
Requires-Dist: py-cpuinfo ~=9.0 ; os_name == "nt"

# 🐍🌈🪨 PyOpal [![Stars](https://img.shields.io/github/stars/althonos/pyopal.svg?style=social&maxAge=3600&label=Star)](https://github.com/althonos/pyopal/stargazers)

*[Cython](https://cython.org/) bindings and Python interface to [Opal](https://github.com/Martinsos/opal), a SIMD-accelerated database search aligner.*

[![Actions](https://img.shields.io/github/actions/workflow/status/althonos/pyopal/test.yml?branch=main&logo=github&style=flat-square&maxAge=300)](https://github.com/althonos/pyopal/actions)
[![Coverage](https://img.shields.io/codecov/c/gh/althonos/pyopal?style=flat-square&maxAge=3600&logo=codecov)](https://codecov.io/gh/althonos/pyopal/)
[![License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat-square&maxAge=2678400)](https://choosealicense.com/licenses/mit/)
[![PyPI](https://img.shields.io/pypi/v/pyopal.svg?style=flat-square&maxAge=3600&logo=PyPI)](https://pypi.org/project/pyopal)
[![Bioconda](https://img.shields.io/conda/vn/bioconda/pyopal?style=flat-square&maxAge=3600&logo=anaconda)](https://anaconda.org/bioconda/pyopal)
[![AUR](https://img.shields.io/aur/version/python-pyopal?logo=archlinux&style=flat-square&maxAge=3600)](https://aur.archlinux.org/packages/python-pyopal)
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[![Downloads](https://img.shields.io/pypi/dm/pyopal?style=flat-square&color=303f9f&maxAge=86400&label=downloads)](https://pepy.tech/project/pyopal)


## 🗺️ Overview

[Opal](https://github.com/Martinsos/opal) is a sequence aligner enabling fast
sequence similarity search using either of the Smith-Waterman, semi-global or
Needleman-Wunsch algorithms. It is used part of the SW#db method[\[1\]](#ref1)
to align a query sequence to multiple database sequences on CPU.

PyOpal is a Python module that provides bindings to [Opal](https://github.com/Martinsos/opal)
using [Cython](https://cython.org/). It implements a user-friendly, Pythonic
interface to query a database of sequences and access the search results. It
interacts with the Opal interface rather than with the CLI, which has the
following advantages:

- **no binary dependency**: PyOpal is distributed as a Python package, so
  you can add it as a dependency to your project, and stop worrying about the
  Opal binary being present on the end-user machine.
- **no intermediate files**: Everything happens in memory, in a Python object
  you control, so you don't have to invoke the Opal CLI using a sub-process
  and temporary files.
- **better portability**: Opal uses SIMD to accelerate alignment scoring, but
  doesn't support dynamic dispatch, so it has to be compiled on the local
  machine to be able to use the full capabilities of the local CPU. PyOpal
  ships several versions of Opal instead, each compiled with different target
  features, and selects the best one for the local platform at runtime.
- **wider platform support**: The Opal code has been backported to work on SSE2
  rather than SSE4.1, allowing PyOpal to run on older x86 CPUs (all x86 CPUs
  support it since 2003). In addition, Armv7 and Aarch64 CPUs are also
  supported if they implement NEON extensions. Finally, the C++ code of Opal
  has been modified to compile on Windows.

## 🔧 Installing

PyOpal is available for all modern versions (3.6+), depending either
on the lightweight Python package [`archspec`](https://pypi.org/project/archspec)
or on [`py-cpuinfo`](https://pypi.org/project/archspec) for runtime CPU
feature detection, depending on the operating system.

It can be installed directly from [PyPI](https://pypi.org/project/pyopal/),
which hosts some pre-built x86-64 and Aarch64 wheels for Linux, MacOS, and
Windows, as well as the code required to compile from source with Cython:
```console
$ pip install pyopal
```

Otherwise, PyOpal is also available as a [Bioconda](https://bioconda.github.io/)
package:
```console
$ conda install -c bioconda pyopal
```

Check the [*install* page](https://pyopal.readthedocs.io/en/stable/install.html)
of the documentation for other ways to install PyOpal on your machine.

## 💡 Example

All classes are imported in the main namespace `pyopal`:
```python
import pyopal
```

`pyopal` can work with sequences passed as Python strings, 
as well as with ASCII strings in `bytes` objects:
```python
query = "MAGFLKVVQLLAKYGSKAVQWAWANKGKILDWLNAGQAIDWVVSKIKQILGIK"
database = [
    "MESILDLQELETSEEESALMAASTVSNNC",
    "MKKAVIVENKGCATCSIGAACLVDGPIPDFEIAGATGLFGLWG",
    "MAGFLKVVQILAKYGSKAVQWAWANKGKILDWINAGQAIDWVVEKIKQILGIK",
    "MTQIKVPTALIASVHGEGQHLFEPMAARCTCTTIISSSSTF",
]
```

If you plan to reuse the database across several queries, you can store it in 
a [`Database`](https://pyopal.readthedocs.io/en/stable/api/database.html#pyopal.Database), 
which will keep sequences encoded according to 
an [`Alphabet`](https://pyopal.readthedocs.io/en/stable/api/alphabet.html#pyopal.Alphabet):

```python
database = pyopal.Database(database)
```

The top-level function `pyopal.align` can be used to align a query
sequence against a database, using multithreading to process chunks
of the database in parallel:
```python
for result in pyopal.align(query, database):
    print(result.score, result.target_index, database[result.target_index])
```

See the [API documentation](https://pyopal.readthedocs.io/en/stable/api/index.html) 
for more examples, including how to use the internal API, and detailed 
reference of the parameters and result types.

## 🧶 Thread-safety

`Database` objects are thread safe through a
[C++17 read/write lock](https://en.cppreference.com/w/cpp/thread/shared_mutex)
that prevents modification while the database is searched. In addition, the
`Aligner.align`  method is re-entrant and can be safely used to query the
same database in parallel with different queries across different threads:

```python
import multiprocessing.pool
import pyopal
import Bio.SeqIO

queries = [
    "MEQQIELDVLEISDLIAGAGENDDLAQVMAASCTTSSVSTSSSSSSS",
    "MTQIKVPTALIASVHGEGQHLFEPMAARCTCTTIISSSSTF",
    "MGAIAKLVAKFGWPIVKKYYKQIMQFIGEGWAINKIIDWIKKHI",
    "MGPVVVFDCMTADFLNDDPNNAELSALEMEELESWGAWDGEATS",
]

database = pyopal.Database([
    str(record.seq)
    for record in Bio.SeqIO.parse("vendor/opal/test_data/db/uniprot_sprot12071.fasta", "fasta")
])

aligner = pyopal.Aligner()
with multiprocessing.pool.ThreadPool() as pool:
    hits = dict(pool.map(lambda q: (q, aligner.align(q, database)), queries))
```

<!-- ## ⏱️ Benchmarks -->


## 💭 Feedback

### ⚠️ Issue Tracker

Found a bug ? Have an enhancement request ? Head over to the [GitHub issue tracker](https://github.com/althonos/pyopal/issues)
if you need to report or ask something. If you are filing in on a bug,
please include as much information as you can about the issue, and try to
recreate the same bug in a simple, easily reproducible situation.


### 🏗️ Contributing

Contributions are more than welcome! See
[`CONTRIBUTING.md`](https://github.com/althonos/pyopal/blob/main/CONTRIBUTING.md)
for more details.


## 📋 Changelog

This project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html)
and provides a [changelog](https://github.com/althonos/pyopal/blob/main/CHANGELOG.md)
in the [Keep a Changelog](http://keepachangelog.com/en/1.0.0/) format.


## ⚖️ License

This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/).
Opal is developed by [Martin Šošić](https://github.com/Martinsos) and is distributed under the
terms of the MIT License as well. See `vendor/opal/LICENSE` for more information.

*This project is in no way not affiliated, sponsored, or otherwise endorsed
by the [Opal authors](https://github.com/Martinsos). It was developed
by [Martin Larralde](https://github.com/althonos/) during his PhD project
at the [European Molecular Biology Laboratory](https://www.embl.de/) in
the [Zeller team](https://github.com/zellerlab).*


## 📚 References

- <a id="ref1">\[1\]</a> Korpar Matija, Martin Šošić, Dino Blažeka, Mile Šikić. SW#db: ‘GPU-Accelerated Exact Sequence Similarity Database Search’. PLoS One. 2015 Dec 31;10(12):e0145857. [doi:10.1371/journal.pone.0145857](https://doi.org/10.1371/journal.pone.0145857). [PMID:26719890](https://pubmed.ncbi.nlm.nih.gov/26719890). [PMC4699916](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699916/).
