mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 20:56:46 +08:00
François Boulogne
181 lines
5.8 KiB
Plaintext
181 lines
5.8 KiB
Plaintext
Development process
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-------------------
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Here's the long and short of it:
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1. If you are a first-time contributor:
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* Go to `https://github.com/scikit-image/scikit-image
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<http://github.com/scikit-image/scikit-image>`_ and click the
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"fork" button to create your own copy of the project.
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* Clone the project to your local computer::
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git clone git@github.com:your-username/scikit-image.git
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* Add upstream repository::
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git remote add upstream git@github.com:scikit-image/scikit-image.git
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* Now, you have remote repositories named:
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- ``upstream``, which refers to the ``scikit-image`` repository
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- ``origin``, which refers to your personal fork
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2. Develop your contribution:
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* Pull the latest changes from upstream::
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git checkout master
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git pull upstream master
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* Create a branch for the feature you want to work on. Since the
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branch name will appear in the merge message, use a sensible name
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such as 'transform-speedups'::
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git checkout -b transform-speedups
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* Commit locally as you progress (``git add`` and ``git commit``)
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3. To submit your contribution:
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* Push your changes back to your fork on GitHub::
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git push origin transform-speedups
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* Go to GitHub. The new branch will show up with a Pull Request button -
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click it.
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* If you want, post on the `mailing list
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<http://groups.google.com/group/scikit-image>`_ to explain your changes or
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to ask for review.
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For a more detailed discussion, read these :doc:`detailed documents
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<gitwash/index>` on how to use Git with ``scikit-image``
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(`<http://scikit-image.org/docs/dev/gitwash/index.html>`_).
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.. note::
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To reviewers: add a short explanation of what a branch did to the merge
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message and, if closing a bug, also add "Closes gh-123" where 123 is the
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bug number.
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Divergence between ``upstream master`` and your feature branch
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..............................................................
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Do *not* ever merge the main branch into yours. If GitHub indicates that the
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branch of your Pull Request can no longer be merged automatically, rebase
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onto master::
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git checkout master
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git pull upstream master
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git checkout transform-speedups
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git rebase master
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If any conflicts occur, fix the according files and continue::
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git add conflict-file1 conflict-file2
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git rebase --continue
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However, you should only rebase your own branches and must generally not
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rebase any branch which you collaborate on with someone else.
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Finally, you must push your rebased branch::
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git push --force origin transform-speedups
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(If you are curious, here's a further discussion on the
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`dangers of rebasing <http://tinyurl.com/lll385>`__.
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Also see this `LWN article <http://tinyurl.com/nqcbkj>`__.)
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Guidelines
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----------
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* All code should have tests (see `test coverage`_ below for more details).
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* All code should be documented, to the same
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`standard <http://projects.scipy.org/numpy/wiki/CodingStyleGuidelines>`_
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as NumPy and SciPy.
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* For new functionality, always add an example to the
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gallery.
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* No changes should be committed without review. Ask on the
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`mailing list <http://groups.google.com/group/scikit-image>`_ if
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you get no response to your pull request.
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**Never merge your own pull request.**
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* Examples in the gallery should have a maximum figure width of 8 inches.
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Stylistic Guidelines
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--------------------
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* Set up your editor to remove trailing whitespace. Follow `PEP08
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<www.python.org/dev/peps/pep-0008/>`__. Check code with pyflakes / flake8.
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* Use numpy data types instead of strings (``np.uint8`` instead of
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``"uint8"``).
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* Use the following import conventions::
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import numpy as np
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import matplotlib.pyplot as plt
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cimport numpy as cnp # in Cython code
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* When documenting array parameters, use ``image : (M, N) ndarray``
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and then refer to ``M`` and ``N`` in the docstring, if necessary.
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* Functions should support all input image dtypes. Use utility functions such
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as ``img_as_float`` to help convert to an appropriate type. The output
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format can be whatever is most efficient. This allows us to string together
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several functions into a pipeline, e.g.::
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hough(canny(my_image))
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* Use ``Py_ssize_t`` as data type for all indexing, shape and size variables
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in C/C++ and Cython code.
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Test coverage
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-------------
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Tests for a module should ideally cover all code in that module,
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i.e., statement coverage should be at 100%.
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To measure the test coverage, install
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`coverage.py <http://nedbatchelder.com/code/coverage/>`__
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(using ``easy_install coverage``) and then run::
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$ make coverage
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This will print a report with one line for each file in `skimage`,
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detailing the test coverage::
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Name Stmts Exec Cover Missing
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------------------------------------------------------------------------------
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skimage/color/colorconv 77 77 100%
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skimage/filter/__init__ 1 1 100%
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...
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Activate Travis-CI for your fork (optional)
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-------------------------------------------
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Travis-CI checks all unittests in the project to prevent breakage.
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Before sending a pull request, you may want to check that Travis-CI
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successfully passes all tests. To do so,
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* Go to `Travis-CI <http://travis-ci.org/>`__ and follow the Sign In link at the top
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* Go to your `profile page <https://travis-ci.org/profile>`__ and switch on your
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scikit-image fork
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It corresponds to steps one and two in
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`Travis-CI documentation <http://about.travis-ci.org/docs/user/getting-started/>`__
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(Step three is already done in scikit-image).
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Thus, as soon as you push your code to your fork, it will trigger Travis-CI,
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and you will receive an email notification when the process is done.
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Bugs
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----
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Please `report bugs on GitHub <https://github.com/scikit-image/scikit-image/issues>`_.
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