biopython
Freely available tools for computational molecular biology.
Decision gist · record as of 2026-08-14
Yes, with a license review. Biopython is production-stable, actively maintained, and widely used in computational biology. Install friction is low thanks to pre-compiled wheels for multiple platforms. However, verify that the custom Biopython License Agreement aligns with your project's licensing requirements before committing to it in production or proprietary work.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires numpy, which is installed automatically.
- Python 3.10 or later required.
- Pre-compiled wheels available for Python 3.10, 3.11, 3.12, 3.13 on Linux, macOS, and Windows reduce install friction significantly.
License · maintenance · safety
LicenseRef-Biopython-License-Agreement (unclear) — License treatment is marked unclear; the package uses a custom Biopython License Agreement (LicenseRef-Biopython-License-Agreement) rather than a standard SPDX identifier. Review the LICENSE file on the repository before use in proprietary or restricted contexts.
last release 2026-08-06 (8 days) · last repo commit 2026-08-06 · 5,164 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 14,442,412 downloads/mo, #1,229 on PyPI
Alternatives
Verify before relying
pip install biopython
import biopython
# Biopython modules available for sequence analysis and database access- Exact scope and restrictions of the custom Biopython License Agreement—whether it permits commercial use or has attribution requirements beyond standard open-source terms.
- Whether all optional dependencies (ReportLab, matplotlib, networkx, rdflib, psycopg2, MySQL connectors) are truly optional or required for core functionality.
- Specific sequence formats and biological databases supported by the package.
What it is and what it does
Biopython is a mature, production-grade library for computational molecular biology written in Python. It provides modules for reading and writing biological sequence formats, analyzing sequences, accessing biological databases, parsing phylogenetic trees, and generating graphics for molecular data. The package is built on numpy and supports optional dependencies for specialized tasks like phylogenetic visualization and database connectivity.
Developers use Biopython to automate sequence analysis workflows, parse large biological datasets, perform comparative genomics, and integrate bioinformatics into larger Python applications. It is widely adopted in academic research and bioinformatics pipelines, with active community maintenance and support for Python 3.10, 3.11, 3.12, 3.13, 3.14.
Use it for
- Parse and manipulate biological sequences in standard formats for comparative analysis.
- Query and retrieve biological data from online databases and parse results programmatically.
- Analyze phylogenetic trees and generate visualizations with optional dependencies.
- Build automated bioinformatics pipelines combining sequence analysis and statistical methods.
- Access and query biological data stored in PostgreSQL or MySQL databases via BioSQL module.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with a license review.
Biopython is production-stable, actively maintained, and widely used in computational biology. Install friction is low thanks to pre-compiled wheels for multiple platforms. However, verify that the custom Biopython License Agreement aligns with your project's licensing requirements before committing to it in production or proprietary work.
Install
biopython on PyPI
Before you install
Pre-compiled wheels available for Python 3.10, 3.11, 3.12, 3.13 on Linux, macOS, and Windows reduce install friction significantly. Active maintenance with a release 8 days old and 5164 GitHub stars indicate a well-supported project.
Requires numpy, which is installed automatically. Python 3.10 or later required.
License in practice
License treatment is marked unclear; the package uses a custom Biopython License Agreement (LicenseRef-Biopython-License-Agreement) rather than a standard SPDX identifier. Review the LICENSE file on the repository before use in proprietary or restricted contexts.
Quickstart
pip install biopython
import biopython
# Biopython modules available for sequence analysis and database accessVerify before relying
- Exact scope and restrictions of the custom Biopython License Agreement—whether it permits commercial use or has attribution requirements beyond standard open-source terms.
- Whether all optional dependencies (ReportLab, matplotlib, networkx, rdflib, psycopg2, MySQL connectors) are truly optional or required for core functionality.
- Specific sequence formats and biological databases supported by the package.
Package facts
| License | LicenseRef-Biopython-License-Agreement unclear |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Actively maintained 8 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 14,442,412 / month, #1,229 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Bio-InformaticsTopic :: Software Development :: Libraries :: Python Modules |
Evidence: biopython-1.88-cp310-cp310-macosx_11_0_arm64.whl; biopython-1.88-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; biopython-1.88-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; biopython-1.88-cp310-cp310-win32.whl; biopython-1.88-cp310-cp310-win_amd64.whl; biopython-1.88-cp311-cp311-macosx_11_0_arm64.whl; biopython-1.88-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; biopython-1.88-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; biopython-1.88-cp311-cp311-win32.whl; biopython-1.88-cp311-cp311-win_amd64.whl; biopython-1.88-cp312-cp312-macosx_11_0_arm64.whl; biopython-1.88-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; biopython-1.88-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; biopython-1.88-cp312-cp312-win32.whl; biopython-1.88-cp312-cp312-win_amd64.whl; biopython-1.88-cp313-cp313-macosx_11_0_arm64.whl; biopython-1.88-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; biopython-1.88-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; biopython-1.88-cp313-cp313-win32.whl; biopython-1.88-cp313-cp313-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “molecular biology python tools”
- biopythonBiopython provides Python tools for computational molecular biology,…
- mmcif-pdbxProvides a pure Python interface to read, parse, and work with…
- gemmiGemmi is a C++ library with Python bindings for reading, writing, and…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also biotite · ete3 · bio · scikit-bio · python-libsbml · mmcif-pdbx · pysylph · pyhmmer · logomaker · gseapy