# 🐍🌈🪨 PyOpal [](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.*
[](https://github.com/althonos/pyopal/actions)
[](https://codecov.io/gh/althonos/pyopal/)
[](https://choosealicense.com/licenses/mit/)
[](https://pypi.org/project/pyopal)
[](https://anaconda.org/bioconda/pyopal)
[](https://aur.archlinux.org/packages/python-pyopal)
[](https://pypi.org/project/pyopal/#files)
[](https://pypi.org/project/pyopal/#files)
[](https://pypi.org/project/pyopal/#files)
[](https://github.com/althonos/pyopal/)
[](https://git.embl.de/larralde/pyopal/)
[](https://github.com/althonos/pyopal/issues)
[](https://pyopal.readthedocs.io)
[](https://github.com/althonos/pyopal/blob/main/CHANGELOG.md)
[](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, using
the multi-sequence vectorization method described in SWIPE[\[2\]](#ref2)
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+), optionally depending on
the lightweight Python package [`archspec`](https://pypi.org/project/archspec)
for runtime CPU feature detection.
It can be installed directly from [PyPI](https://pypi.org/project/pyopal/),
which hosts some pre-built x86-64 wheels for Linux, MacOS, and Windows,
Aarch64 wheels for Linux and MacOS, 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/).
- <a id="ref2">\[2\]</a> Rognes Torbjørn. Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation. BMC Bioinformatics. 2011 Jun 1;12:221. [doi:10.1186/1471-2105-12-221](https://doi.org/10.1186/1471-2105-12-221). [PMID:21631914](https://pubmed.ncbi.nlm.nih.gov/21631914/).[PMC3120707](http://www.ncbi.nlm.nih.gov/pmc/articles/pmc3120707/).
Raw data
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"description": "# \ud83d\udc0d\ud83c\udf08\ud83e\udea8 PyOpal [](https://github.com/althonos/pyopal/stargazers)\n\n*[Cython](https://cython.org/) bindings and Python interface to [Opal](https://github.com/Martinsos/opal), a SIMD-accelerated database search aligner.*\n\n[](https://github.com/althonos/pyopal/actions)\n[](https://codecov.io/gh/althonos/pyopal/)\n[](https://choosealicense.com/licenses/mit/)\n[](https://pypi.org/project/pyopal)\n[](https://anaconda.org/bioconda/pyopal)\n[](https://aur.archlinux.org/packages/python-pyopal)\n[](https://pypi.org/project/pyopal/#files)\n[](https://pypi.org/project/pyopal/#files)\n[](https://pypi.org/project/pyopal/#files)\n[](https://github.com/althonos/pyopal/)\n[](https://git.embl.de/larralde/pyopal/)\n[](https://github.com/althonos/pyopal/issues)\n[](https://pyopal.readthedocs.io)\n[](https://github.com/althonos/pyopal/blob/main/CHANGELOG.md)\n[](https://pepy.tech/project/pyopal)\n\n\n## \ud83d\uddfa\ufe0f Overview\n\n[Opal](https://github.com/Martinsos/opal) is a sequence aligner enabling fast\nsequence similarity search using either of the Smith-Waterman, semi-global or\nNeedleman-Wunsch algorithms. It is used part of the SW#db method[\\[1\\]](#ref1)\nto align a query sequence to multiple database sequences on CPU, using \nthe multi-sequence vectorization method described in SWIPE[\\[2\\]](#ref2)\n\nPyOpal is a Python module that provides bindings to [Opal](https://github.com/Martinsos/opal)\nusing [Cython](https://cython.org/). It implements a user-friendly, Pythonic\ninterface to query a database of sequences and access the search results. It\ninteracts with the Opal interface rather than with the CLI, which has the\nfollowing advantages:\n\n- **no binary dependency**: PyOpal is distributed as a Python package, so\n you can add it as a dependency to your project, and stop worrying about the\n Opal binary being present on the end-user machine.\n- **no intermediate files**: Everything happens in memory, in a Python object\n you control, so you don't have to invoke the Opal CLI using a sub-process\n and temporary files.\n- **better portability**: Opal uses SIMD to accelerate alignment scoring, but\n doesn't support dynamic dispatch, so it has to be compiled on the local\n machine to be able to use the full capabilities of the local CPU. PyOpal\n ships several versions of Opal instead, each compiled with different target\n features, and selects the best one for the local platform at runtime.\n- **wider platform support**: The Opal code has been backported to work on SSE2\n rather than SSE4.1, allowing PyOpal to run on older x86 CPUs (all x86 CPUs\n support it since 2003). In addition, Armv7 and Aarch64 CPUs are also\n supported if they implement NEON extensions. Finally, the C++ code of Opal\n has been modified to compile on Windows.\n\n## \ud83d\udd27 Installing\n\nPyOpal is available for all modern versions (3.6+), optionally depending on\nthe lightweight Python package [`archspec`](https://pypi.org/project/archspec)\nfor runtime CPU feature detection.\n\nIt can be installed directly from [PyPI](https://pypi.org/project/pyopal/),\nwhich hosts some pre-built x86-64 wheels for Linux, MacOS, and Windows,\nAarch64 wheels for Linux and MacOS, as well as the code required to \ncompile from source with Cython:\n```console\n$ pip install pyopal\n```\n\nOtherwise, PyOpal is also available as a [Bioconda](https://bioconda.github.io/)\npackage:\n```console\n$ conda install -c bioconda pyopal\n```\n\nCheck the [*install* page](https://pyopal.readthedocs.io/en/stable/install.html)\nof the documentation for other ways to install PyOpal on your machine.\n\n## \ud83d\udca1 Example\n\nAll classes are imported in the main namespace `pyopal`:\n```python\nimport pyopal\n```\n\n`pyopal` can work with sequences passed as Python strings, \nas well as with ASCII strings in `bytes` objects:\n```python\nquery = \"MAGFLKVVQLLAKYGSKAVQWAWANKGKILDWLNAGQAIDWVVSKIKQILGIK\"\ndatabase = [\n \"MESILDLQELETSEEESALMAASTVSNNC\",\n \"MKKAVIVENKGCATCSIGAACLVDGPIPDFEIAGATGLFGLWG\",\n \"MAGFLKVVQILAKYGSKAVQWAWANKGKILDWINAGQAIDWVVEKIKQILGIK\",\n \"MTQIKVPTALIASVHGEGQHLFEPMAARCTCTTIISSSSTF\",\n]\n```\n\nIf you plan to reuse the database across several queries, you can store it in \na [`Database`](https://pyopal.readthedocs.io/en/stable/api/database.html#pyopal.Database), \nwhich will keep sequences encoded according to \nan [`Alphabet`](https://pyopal.readthedocs.io/en/stable/api/alphabet.html#pyopal.Alphabet):\n\n```python\ndatabase = pyopal.Database(database)\n```\n\nThe top-level function `pyopal.align` can be used to align a query\nsequence against a database, using multithreading to process chunks\nof the database in parallel:\n```python\nfor result in pyopal.align(query, database):\n print(result.score, result.target_index, database[result.target_index])\n```\n\nSee the [API documentation](https://pyopal.readthedocs.io/en/stable/api/index.html) \nfor more examples, including how to use the internal API, and detailed \nreference of the parameters and result types.\n\n## \ud83e\uddf6 Thread-safety\n\n`Database` objects are thread safe through a\n[C++17 read/write lock](https://en.cppreference.com/w/cpp/thread/shared_mutex)\nthat prevents modification while the database is searched. In addition, the\n`Aligner.align` method is re-entrant and can be safely used to query the\nsame database in parallel with different queries across different threads:\n\n```python\nimport multiprocessing.pool\nimport pyopal\nimport Bio.SeqIO\n\nqueries = [\n \"MEQQIELDVLEISDLIAGAGENDDLAQVMAASCTTSSVSTSSSSSSS\",\n \"MTQIKVPTALIASVHGEGQHLFEPMAARCTCTTIISSSSTF\",\n \"MGAIAKLVAKFGWPIVKKYYKQIMQFIGEGWAINKIIDWIKKHI\",\n \"MGPVVVFDCMTADFLNDDPNNAELSALEMEELESWGAWDGEATS\",\n]\n\ndatabase = pyopal.Database([\n str(record.seq)\n for record in Bio.SeqIO.parse(\"vendor/opal/test_data/db/uniprot_sprot12071.fasta\", \"fasta\")\n])\n\naligner = pyopal.Aligner()\nwith multiprocessing.pool.ThreadPool() as pool:\n hits = dict(pool.map(lambda q: (q, aligner.align(q, database)), queries))\n```\n\n<!-- ## \u23f1\ufe0f Benchmarks -->\n\n\n## \ud83d\udcad Feedback\n\n### \u26a0\ufe0f Issue Tracker\n\nFound a bug ? Have an enhancement request ? Head over to the [GitHub issue tracker](https://github.com/althonos/pyopal/issues)\nif you need to report or ask something. If you are filing in on a bug,\nplease include as much information as you can about the issue, and try to\nrecreate the same bug in a simple, easily reproducible situation.\n\n\n### \ud83c\udfd7\ufe0f Contributing\n\nContributions are more than welcome! See\n[`CONTRIBUTING.md`](https://github.com/althonos/pyopal/blob/main/CONTRIBUTING.md)\nfor more details.\n\n\n## \ud83d\udccb Changelog\n\nThis project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html)\nand provides a [changelog](https://github.com/althonos/pyopal/blob/main/CHANGELOG.md)\nin the [Keep a Changelog](http://keepachangelog.com/en/1.0.0/) format.\n\n\n## \u2696\ufe0f License\n\nThis library is provided under the [MIT License](https://choosealicense.com/licenses/mit/).\nOpal is developed by [Martin \u0160o\u0161i\u0107](https://github.com/Martinsos) and is distributed under the\nterms of the MIT License as well. See `vendor/opal/LICENSE` for more information.\n\n*This project is in no way not affiliated, sponsored, or otherwise endorsed\nby the [Opal authors](https://github.com/Martinsos). It was developed\nby [Martin Larralde](https://github.com/althonos/) during his PhD project\nat the [European Molecular Biology Laboratory](https://www.embl.de/) in\nthe [Zeller team](https://github.com/zellerlab).*\n\n\n## \ud83d\udcda References\n\n- <a id=\"ref1\">\\[1\\]</a> Korpar Matija, Martin \u0160o\u0161i\u0107, Dino Bla\u017eeka, Mile \u0160iki\u0107. SW#db: \u2018GPU-Accelerated Exact Sequence Similarity Database Search\u2019. 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/).\n- <a id=\"ref2\">\\[2\\]</a> Rognes Torbj\u00f8rn. Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation. BMC Bioinformatics. 2011 Jun 1;12:221. [doi:10.1186/1471-2105-12-221](https://doi.org/10.1186/1471-2105-12-221). [PMID:21631914](https://pubmed.ncbi.nlm.nih.gov/21631914/).[PMC3120707](http://www.ncbi.nlm.nih.gov/pmc/articles/pmc3120707/).\n",
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