Metadata-Version: 1.1
Name: memote
Version: 0.5.1
Summary: the genome-scale metabolic model test suite
Home-page: https://github.com/opencobra/memote
Author: Moritz E. Beber
Author-email: morbeb@biosustain.dtu.dk
License: Apache Software License 2.0
Description-Content-Type: UNKNOWN
Description: ====================================================
        memote - the genome-scale metabolic model test suite
        ====================================================
        
        .. image:: https://img.shields.io/pypi/v/memote.svg
                :target: https://pypi.python.org/pypi/memote
        
        .. image:: https://img.shields.io/travis/opencobra/memote.svg
                :target: https://travis-ci.org/opencobra/memote
        
        .. image:: https://readthedocs.org/projects/memote/badge/?version=latest
                :target: https://memote.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        .. image:: https://codecov.io/gh/opencobra/memote/branch/master/graph/badge.svg
                :target: https://codecov.io/gh/opencobra/memote
                :alt: Coverage
        
        .. image:: https://badges.gitter.im/opencobra/memote.svg
                :target: https://gitter.im/opencobra/memote
                :alt: Gitter
        
        .. summary-start
        
        Our goal in promoting this tool is to achieve two major shifts in the metabolic
        model building community:
        
        1. Models should be version-controlled such that changes can be tracked and if
           necessary reverted. Ideally, they should be available through a public
           repository such as GitHub that will allow other researchers to inspect,
           share, and contribute to the model.
        2. Models should, for the benefit of the community and for research gain, live
           up to certain standards and minimal functionality.
        
        The `memote` tool therefore performs four subfunctions:
        
        1. Create a skeleton git repository for the model.
        2. Run the current model through a test suite that represents the community
           standard.
        3. Generate an informative report which details the results of the test suite in
           a visually appealing manner.
        4. (Re-)compute test statistics for an existing version controlled history of
           a metabolic model.
        
        And in order to make this process as easy as possible the generated repository
        can easily be integrated with continuous integration testing providers such as
        Travis CI, which means that anytime you push a model change to GitHub, the test
        suite will be run automatically and a report will be available for you to look
        at via GitHub pages for your repository.
        
        .. summary-end
        
        * Documentation: https://memote.readthedocs.io/.
        
        Installation
        ============
        
        We highly recommend creating a Python virtualenv for your model tesing purposes.
        
        To install memote, run this command in your terminal:
        
        .. code-block:: console
        
            $ pip install memote
        
        This is the preferred method to install memote, as it will always install the
        most recent stable release.
        
        .. who-start
        
        Contact
        =======
        
        For comments and questions get in touch via
        
        * our `gitter chatroom <https://gitter.im/opencobra/memote>`_
        * or our `mailing list <https://groups.google.com/forum/#!forum/memote>`_.
        
        Are you excited about this project? Consider `contributing
        <https://memote.readthedocs.io/en/latest/contributing.html>`_ by adding novel
        tests, reporting or fixing bugs, and generally help us make this a better
        software for everyone.
        
        Copyright
        =========
        
        * Copyright (c) 2017, Novo Nordisk Foundation Center for Biosustainability,
          Technical University of Denmark.
        * Free software: `Apache Software License 2.0 <LICENSE>`_
        
        .. who-end
        
        Credits
        =======
        
        This package was created with Cookiecutter_ and the
        `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
Keywords: memote
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
