Skip to main content

COBRApy is a package for constraint-based modeling of metabolic networks.

Project description

COBRApy - Constraint-Based Reconstruction and Analysis in Python

Current PyPI Version Supported Python Versions GNU Lesser General Public License 2 or later Code of Conduct GitHub Actions CI/CD Status Codecov Documentation Status Gitter Chat Room Black

What is COBRApy?

COBRA methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. COBRApy is a constraint-based modeling package that is designed to accommodate the biological complexity of the next generation of COBRA models and provides access to commonly used COBRA methods, such as flux balance analysis, flux variability analysis, and gene deletion analyses.

Our aim with COBRApy is to provide useful, efficient infrastructure for:

  • creating and managing metabolic models

  • accessing popular solvers

  • analyzing models with methods such as FVA, FBA, pFBA, MOMA etc.

  • inspecting models and drawing conclusions on gene essentiality, testing consequences of knock-outs etc.

Our goal with COBRApy is for it to be useful on its own, and for it to be the natural choice of infrastructure for developers that want to build new COBRA related python packages for e.g. visualization, strain-design and data driven analysis. By re-using the same classes and design principles, we can make new methods both easier to implement and easier to use, thereby bringing the power of COBRA to more researchers.

The documentation is browseable online at readthedocs and can also be downloaded.

Please use the Google Group for help. By writing a well formulated question, with sufficient detail, you are much more likely to quickly receive a good answer! Please refer to these StackOverflow guidelines on how to ask questions. Alternatively, you can use gitter.im for quick questions and discussions about COBRApy (faster response times). Please keep in mind that answers are provided on a volunteer basis.

More information about opencobra is available at the website.

If you use COBRApy in a scientific publication, please cite doi:10.1186/1752-0509-7-74

Installation

Use pip to install COBRApy from PyPI (we recommend doing this inside a virtual environment):

pip install cobra

If you want to load MATLAB models, you will need additional dependencies. Please install:

pip install cobra[array]

For further information, please follow the detailed installation instructions.

Contributing

Contributions are always welcome! Please read the contributing guidelines to get started.

License

The COBRApy source is released under both the GPL and LGPL licenses version 2 or later. You may choose which license you choose to use the software under.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License or the GNU Lesser General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Installation of COBRApy

For installation help, please use the Google Group. For usage instructions, please see the documentation.

We only test against Python 3.6+, however, Python 3.4 or higher and even 2.7 should work mostly. For Windows users and possibly also Mac OS users, we recommend using the Anaconda Python distribution.

Stable version installation

COBRApy can be installed with any recent installation of pip. Instructions for several operating systems are below:

Mac OS X or Linux

  1. We highly recommend that you create a Python virtual environment.

  2. Install COBRApy when an environment is active by running pip install cobra in the terminal.

Microsoft Windows

If you heed our recommendation to use Anaconda, you can open an Anaconda shell and install COBRApy from the bioconda channel. Soon it should also be available from the conda-forge channel.

conda install -c bioconda cobra

Installation for development

Get the detailed contribution instructions for contributing to COBRApy.

Solvers

COBRApy uses optlang to interface the mathematical solvers used to optimize the created COBRA models. At the time of writing the supported solvers are:

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

cobra-0.21.0.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

cobra-0.21.0-py2.py3-none-any.whl (2.4 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file cobra-0.21.0.tar.gz.

File metadata

  • Download URL: cobra-0.21.0.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.8.7

File hashes

Hashes for cobra-0.21.0.tar.gz
Algorithm Hash digest
SHA256 4a0a95012bf97f5b196c1155d4db666006718f31f82be552ddb62d0721ae0182
MD5 6f06cff0fbefd496834bbbc0d02df267
BLAKE2b-256 e0ec34609362bc14bf8cf7c5d57e2061fcc01d839ee7fe41436a38126aaa4755

See more details on using hashes here.

File details

Details for the file cobra-0.21.0-py2.py3-none-any.whl.

File metadata

  • Download URL: cobra-0.21.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.8.7

File hashes

Hashes for cobra-0.21.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 dd8cfa1f6df99e91e99820d213d496014730025abce142246dddf61a3b080bf8
MD5 a6bf050b01252275d9e3f293a380e908
BLAKE2b-256 9cc0bea19dbbe6e4907a591272100717f491b82ff8a485b4ff1528182532bbcf

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page