Metadata-Version: 1.1
Name: pychemy
Version: 0.4.5
Summary: Helpers for handling chemical formulas in Python
Home-page: https://github.com/ginkgobioworks/pychemy
Author: Benjie Chen, Ginkgo Bioworks, Christoph Gohlke
Author-email: benjie@ginkgobioworks.com, devs@ginkgobioworks.com, cgohlke@uci.edu
License: MIT
Description: PyChemy
        =======
        
        .. image:: https://travis-ci.org/ginkgobioworks/pychemy.svg?branch=master
            :target: https://travis-ci.org/ginkgobioworks/pychemy
        
        Helpers for handling chemical formulas in Python. Mostly adopted from work of
        `Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_. Added methods that are useful for mass spec
        data analysis.
        
        Depends on `Open Babel <http://openbabel.org/>`_ and its Python bindings for handling InChI strings.
        
        
        Development
        -----------
        
        Development requires Docker and Make on your host system. Everything else, including Open Babel, is
        taken care of inside the Docker containers.
        
        Spin up your container using the provided ``docker-compose.yml`` file and ``Makefile`` by running
        ``make image``. This creates an image with a correct git configuration for your user, which makes it
        easy to release. All of the commands you should need to run are defined the ``Makefile`` as targets.
        All of the targets except for ``image``, are meant to be run inside the Docker container, but can be
        run from the host machine by having ``-ext`` appended to them. For example, to run tests, you could
        either call ``make test`` from a shell inside the container, or ``make test-ext`` from the host.
        
        This project supports both Python 2 and Python 3. To test Python 3, make run the ``make
        test`` and ``make test-ext`` with the ``TOXENV`` environment set to ``py3``, e.g.:
        
        ::
        
            TOXENV=py3 ./make test-ext
        
        
        All pull requests are run through the Travis CI process specified in ``.travis.yml`` and must pass
        all unit and doc tests in Python 2 and Python 3 before being accepted.
        
        Deployment
        ----------
        
        Deployment of tagged commits happens to PyPI automatically via Travis CI. To bump and deploy a new
        version directly, you must have access to write to the master branch. Run ``make bump/[foo]-ext``,
        where ``[foo]`` is ``major``, ``minor``, or ``patch``. Then ``git push origin --tags master``. If
        you do not have access to the master branch, do the same thing, but in a separate branch, and make
        a pull request.
        
Keywords: chemistry mass spectrometry chemoinformatics analysis molecular
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Artificial Life
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
