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Collaborative Github Workflow
=============================

For developers interested in expanding pymatgen for their own purposes, we
recommend forking pymatgen directly from the
`pymatgen GitHub repo`_. Here's a typical workflow (adapted from
http://www.eqqon.com/index.php/Collaborative_Github_Workflow):

.. note::

Ignore the Github fork queue. Let the maintainer of pymatgen worry about
the fork queue.

1. Create a free GitHub account (if you don't already have one) and perform the
necessary setup (e.g., install SSH keys etc.).
2. Fork the pymatgen GitHub repo, i.e., go to the main
`pymatgen GitHub repo`_ and click fork to create a copy of the pymatgen code
base on your own Github account.
3. Install git on your local machine (if you don't already have it).
4. Clone *your forked repo* to your local machine. You will work mostly with
your local repo and only publish changes when they are ready to be merged:

::

git clone git@github.com:YOURNAME/pymatgen.git

Note that the entire Github repo is fairly large because of the presence of
test files, but these are absolutely necessary for rigorous testing of the
code.
5. It is highly recommended you install all the optional dependencies as well.
6. Code (see `Coding Guidelines`_). Commit early and commit often. Keep your
code up to date. You need to add the main repository to the list of your
remotes. Let's name the upstream repo as mpmaster (materialsproject master).

::

git remote add mpmaster git://github.com/materialsproject/pymatgen.git

Make sure your repository is clean (no uncommitted changes) and is currently
on the master branch. If not, commit or stash any changes and switch to the
master.

::

git checkout master

Then you can pull all the new commits from the main line

::

git pull mpmaster master

Remember, pull is a combination of the commands fetch and merge, so there may
be merge conflicts to be manually resolved.

7. Publish your contributions. Assuming that you now have a couple of commits
that you would like to contribute to the main repository. Please follow the
following steps:

a. If your change is based on a relatively old state of the main repository,
then you should probably bring your repository up-to-date first to see if
the change is not creating any merge conflicts.
b. Check that everything compiles cleanly and passes all tests.
The pymatgen repo comes with a complete set of tests for all modules. If
you have written new modules or methods, you must write tests for the new
code as well (see `Coding Guidelines`_). Install and run nosetest in your
local repo directory and fix all errors before continuing further. There
must be **no errors** for the nosetest.
c. If everything is ok, publish the commits to your github repository.

::

git push origin master

8. Now that your commit is published, it doesn't mean that it has already been
merged into the main repository. You should issue a merge request to
pymatgen' maintainers. They will pull your commits and run their own tests
before releasing.

Coding Guidelines
=================

Given that pymatgen is intended to be long-term code base, we adopt very strict
quality control and coding guidelines for all contributions to pymatgen. The
following must be satisfied for your contributions to be accepted into pymatgen.

1. **Unittests** are required for all new modules and methods. The only way to
minimize code regression is to ensure that all code are well-tested. If the
maintainer cannot test your code, the contribution will be rejected.
2. **Python PEP 8** `code style <http://www.python.org/dev/peps/pep-0008/>`_.
We allow a few exceptions when they are well-justified (e.g., Element's
atomic number is given a variable name of capital Z, in line with accepted
scientific convention), but generally, PEP 8 must be observed. Code style
will be automatically checked, but to aid you, you can copy the example
pre-commit hook into your .git/hooks directly. This will automatically run
pycodestyle prior to any commits. At the very least, copy pre-commit to
.git/hooks/pre-push.
3. **Python 3**. We only support Python 3.5+.
4. **Documentation** required for all modules, classes and methods. In
particular, the method docstrings should make clear the arguments expected
and the return values. For complex algorithms (e.g., an Ewald summation), a
summary of the alogirthm should be provided, and preferably with a link to a
publication outlining the method in detail.
5. **IDE**. We highly recommend the use of Pycharm. You should also set up
pycodestyle and turn those on within the IDE setup. This will warn of any
issues with coding styles. Many code style errors can be done by simply
selecting the entire code and using the Code->Reformat Code within Pycharm.

For the above, if in doubt, please refer to the core classes in pymatgen for
examples of what is expected.

A word on coding for Python 3 compatibility
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

With effect from version 3.0, all pymatgen code must be both Python 2.7+ and 3
compatible. Specifically, we have adopted the following practices throughout
pymatgen.

1. **Unicode-always.** Unless you are absolutely sure you need byte literals
(rare for pymatgen), always use unicode. In particular, the following should
be the first line of all pymatgen modules::

from __future__ import division, print_function, unicode_literals

Future division means that 1/2 returns a float (0.5),
which is more intuitive scientifically, instead of 0 (default integer
division in Python 2). print_function ensures that print() is used instead
of the print statement. And unicode_literals makes it such that all
strings are treated as unicode by default. If you need to use bytes,
those should be marked up explicitly as b'byte literal'.
2. **Use of the six package**. Where necessary, use the six package to handle
interoperability between Python 2 and 3. Examples include the six.moves
functions (common ones are zip, filter, map), and six.stringtypes (testing
for string types, which should be rarely done).
3. **Python-modernize**. Use python-modernize to check your code for any
potential changes that need to be made.
4. **Unit testing**. The entire pymatgen code base is continuously being
tested in both Python 2.7 and >=3.3. If your code fails either of the
tests, you need to fix it.

.. _`pymatgen's Google Groups page`: https://groups.google.com/forum/?fromgroups#!forum/pymatgen/
.. _`pymatgen GitHub repo`: https://github.com/materialsproject/pymatgen
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