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CONTRIBUTING.txt
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CONTRIBUTING.txt
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Development process
-------------------
Here's the long and short of it:
1. If you are a first-time contributor:
* Go to `https://github.com/scikit-image/scikit-image
<http://github.com/scikit-image/scikit-image>`_ and click the
"fork" button to create your own copy of the project.
* Clone the project to your local computer::
git clone git@github.com:your-username/scikit-image.git
* Add the upstream repository::
git remote add upstream git@github.com:scikit-image/scikit-image.git
* Now, you have remote repositories named:
- ``upstream``, which refers to the ``scikit-image`` repository
- ``origin``, which refers to your personal fork
2. Develop your contribution:
* Pull the latest changes from upstream::
git checkout master
git pull upstream master
* Create a branch for the feature you want to work on. Since the
branch name will appear in the merge message, use a sensible name
such as 'transform-speedups'::
git checkout -b transform-speedups
* Commit locally as you progress (``git add`` and ``git commit``)
3. To submit your contribution:
* Push your changes back to your fork on GitHub::
git push origin transform-speedups
* Go to GitHub. The new branch will show up with a green Pull Request
button - click it.
* If you want, post on the `mailing list
<http://groups.google.com/group/scikit-image>`_ to explain your changes or
to ask for review.
For a more detailed discussion, read these :doc:`detailed documents
<gitwash/index>` on how to use Git with ``scikit-image``
(`<http://scikit-image.org/docs/dev/gitwash/index.html>`_).
4. Review process:
* Reviewers (the other developers and interested community members) will
write inline and/or general comments on your Pull Request (PR) to help
you improve its implementation, documentation and style. Every single
developer working on the project has their code reviewed, and we've come
to see it as friendly conversation from which we all learn and the
overall code quality benefits. Therefore, please don't let the review
discourage you from contributing: its only aim is to improve the quality
of project, not to criticize (we are, after all, very grateful for the
time you're donating!).
* To update your pull request, make your changes on your local repository
and commit. As soon as those changes are pushed up (to the same branch as
before) the pull request will update automatically.
* `Travis-CI <http://travis-ci.org/>`__, a continuous integration service,
is triggered after each Pull Request update to build the code, run unit
tests, measure code coverage and check coding style (PEP8) of your
branch. The Travis tests must pass before your PR can be merged. If
Travis fails, you can find out why by clicking on the "failed" icon (red
cross) and inspecting the build and test log.
5. Document changes
If your change introduces any API modifications, please update
``doc/source/api_changes.txt``.
If your change introduces a deprecation, add a reminder to ``TODO.txt``
for the team to remove the deprecated functionality in the future.
.. note::
To reviewers: if it is not obvious from the PR description, add a short
explanation of what a branch did to the merge message and, if closing a
bug, also add "Closes #123" where 123 is the issue number.
Divergence between ``upstream master`` and your feature branch
--------------------------------------------------------------
Do *not* ever merge the main branch into yours. If GitHub indicates that the
branch of your Pull Request can no longer be merged automatically, rebase
onto master::
git checkout master
git pull upstream master
git checkout transform-speedups
git rebase master
If any conflicts occur, fix the according files and continue::
git add conflict-file1 conflict-file2
git rebase --continue
However, you should only rebase your own branches and must generally not
rebase any branch which you collaborate on with someone else.
Finally, you must push your rebased branch::
git push --force origin transform-speedups
(If you are curious, here's a further discussion on the
`dangers of rebasing <http://tinyurl.com/lll385>`__.
Also see this `LWN article <http://tinyurl.com/nqcbkj>`__.)
Guidelines
----------
* All code should have tests (see `test coverage`_ below for more details).
* All code should be documented, to the same
`standard <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt#docstring-standard>`_ as NumPy and SciPy.
* For new functionality, always add an example to the gallery.
* No changes are ever committed without review. Ask on the
`mailing list <http://groups.google.com/group/scikit-image>`_ if
you get no response to your pull request.
**Never merge your own pull request.**
* Examples in the gallery should have a maximum figure width of 8 inches.
Stylistic Guidelines
--------------------
* Set up your editor to remove trailing whitespace. Follow `PEP08
<www.python.org/dev/peps/pep-0008/>`__. Check code with pyflakes / flake8.
* Use numpy data types instead of strings (``np.uint8`` instead of
``"uint8"``).
* Use the following import conventions::
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage as ndi
cimport numpy as cnp # in Cython code
* When documenting array parameters, use ``image : (M, N) ndarray``
and then refer to ``M`` and ``N`` in the docstring, if necessary.
* Refer to array dimensions as (plane), row, column, not as x, y, z. See
:ref:`Coordinate conventions <numpy-images-coordinate-conventions>`
in the user guide for more information.
* Functions should support all input image dtypes. Use utility functions such
as ``img_as_float`` to help convert to an appropriate type. The output
format can be whatever is most efficient. This allows us to string together
several functions into a pipeline, e.g.::
hough(canny(my_image))
* Use ``Py_ssize_t`` as data type for all indexing, shape and size variables
in C/C++ and Cython code.
* Use relative module imports, i.e. ``from .._shared import xyz`` rather than
``from skimage._shared import xyz``.
* Wrap Cython code in a pure Python function, which defines the API. This
improves compatibility with code introspection tools, which are often not
aware of Cython code.
* For Cython functions, release the GIL whenever possible, using
``with nogil:``.
Test coverage
-------------
Tests for a module should ideally cover all code in that module,
i.e., statement coverage should be at 100%.
To measure the test coverage, install
`coverage.py <http://nedbatchelder.com/code/coverage/>`__
(using ``easy_install coverage``) and then run::
$ make coverage
This will print a report with one line for each file in `skimage`,
detailing the test coverage::
Name Stmts Exec Cover Missing
------------------------------------------------------------------------------
skimage/color/colorconv 77 77 100%
skimage/filter/__init__ 1 1 100%
...
Activate Travis-CI for your fork (optional)
-------------------------------------------
Travis-CI checks all unittests in the project to prevent breakage.
Before sending a pull request, you may want to check that Travis-CI
successfully passes all tests. To do so,
* Go to `Travis-CI <http://travis-ci.org/>`__ and follow the Sign In link at
the top
* Go to your `profile page <https://travis-ci.org/profile>`__ and switch on
your scikit-image fork
It corresponds to steps one and two in
`Travis-CI documentation <http://about.travis-ci.org/docs/user/getting-started/>`__
(Step three is already done in scikit-image).
Thus, as soon as you push your code to your fork, it will trigger Travis-CI,
and you will receive an email notification when the process is done.
Every time Travis is triggered, it also calls on `Coveralls
<http://coveralls.io>`_ to inspect the current test overage.
Bugs
----
Please `report bugs on GitHub <https://github.com/scikit-image/scikit-image/issues>`_.