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Merge pull request #8026 from QuLogic/pytest-tweaks
Pytest documentation + build tweaks
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‎.travis.yml‎

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env: MOCK=mock NUMPY=numpy==1.7.1
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- python: 3.4
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env: PYTHON_ARGS=-OO
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- python: 3.5
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env: PANDAS=pandas DELETE_FONT_CACHE=1
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- python: 3.5
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env: BUILD_DOCS=true
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- python: 3.5

‎INSTALL‎

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If you want to try the many demos that come in the matplotlib source
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distribution, download the :file:`*.tar.gz` file and look in the
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:file:`examples` subdirectory.
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To run the test suite, copy the :file:`lib\\matplotlib\\tests` and
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:file:`lib\\mpl_toolkits\\tests` directories from the source
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distribution to :file:`sys.prefix\\Lib\\site-packages\\matplotlib` and
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:file:`sys.prefix\\Lib\\site-packages\\mpl_toolkits` respectively, and
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install `nose <https://pypi.python.org/pypi/nose>`_, `mock
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<https://pypi.python.org/pypi/mock>`_, Pillow, MiKTeX, GhostScript,
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ffmpeg, avconv, mencoder, ImageMagick, and `Inkscape
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<https://inkscape.org/>`_.
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To run the test suite:
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* extract the :file:`lib\\matplotlib\\tests` or
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:file:`lib\\mpl_toolkits\\tests` directories from the source distribution;
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* install test dependencies: `pytest <https://pypi.python.org/pypi/pytest>`_,
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`mock <https://pypi.python.org/pypi/mock>`_, Pillow, MiKTeX, GhostScript,
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ffmpeg, avconv, mencoder, ImageMagick, and `Inkscape
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<https://inkscape.org/>`_;
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* run ``py.test path\\to\\tests\\directory``.
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‎README.rst‎

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After installation, you can launch the test suite::
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python tests.py
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py.test
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Or from the Python interpreter::
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import matplotlib
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matplotlib.test()
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Consider reading http://matplotlib.org/devel/coding_guide.html#testing for
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more information. Note that the test suite requires nose and on Python 2.7 mock
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which are not installed by default. Please install with pip or your package
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manager of choice.
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more information. Note that the test suite requires pytest and, on Python 2.7,
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mock. Please install with pip or your package manager of choice.
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Contact
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=======

‎ci/conda_recipe/meta.yaml‎

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- freetype 2.6*
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- msinttypes # [win]
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- cycler >=0.10
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- nose
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- pytest >=3.0.0
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- pyparsing
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- pytz
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# - py2cairo # [linux and py2k]

‎doc/devel/contributing.rst‎

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python tests.py
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.. _nose: https://nose.readthedocs.io/en/latest/
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.. _pytest: http://doc.pytest.org/en/latest/
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.. _pep8: https://pep8.readthedocs.io/en/latest/
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.. _mock: https://docs.python.org/dev/library/unittest.mock.html
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.. _Ghostscript: https://www.ghostscript.com/
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.. _Inkscape: https://inkscape.org>
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.. note::
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**Additional dependencies for testing**: nose_ (version 1.0 or later), `mock
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<https://docs.python.org/dev/library/unittest.mock.html>`_ (if python < 3.3), `Ghostscript
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<https://www.ghostscript.com/>`_, `Inkscape <https://inkscape.org>`_
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**Additional dependencies for testing**: pytest_ (version 3.0 or later),
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mock_ (if python < 3.3), Ghostscript_, Inkscape_
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.. seealso::
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‎doc/devel/testing.rst‎

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Developer's tips for testing
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============================
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Matplotlib has a testing infrastructure based on nose_, making it easy
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to write new tests. The tests are in :mod:`matplotlib.tests`, and
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customizations to the nose testing infrastructure are in
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:mod:`matplotlib.testing`. (There is other old testing cruft around,
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please ignore it while we consolidate our testing to these locations.)
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.. _nose: https://nose.readthedocs.io/en/latest/
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Matplotlib's testing infrastructure depends on pytest_. The tests are in
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:file:`lib/matplotlib/tests`, and customizations to the pytest testing
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infrastructure are in :mod:`matplotlib.testing`.
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.. _pytest: http://doc.pytest.org/en/latest/
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.. _mock: https://docs.python.org/dev/library/unittest.mock.html>
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.. _Ghostscript: https://www.ghostscript.com/
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.. _Inkscape: https://inkscape.org
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.. _pytest-cov: https://pytest-cov.readthedocs.io/en/latest/
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.. _pytest-pep8: https://pypi.python.org/pypi/pytest-pep8
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.. _pytest-xdist: https://pypi.python.org/pypi/pytest-xdist
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.. _pytest-timeout: https://pypi.python.org/pypi/pytest-timeout
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Requirements
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------------
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The following software is required to run the tests:
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- nose_, version 1.0 or later
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- `mock <https://docs.python.org/dev/library/unittest.mock.html>`_, when running python
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versions < 3.3
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- `Ghostscript <https://www.ghostscript.com/>`_ (to render PDF
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files)
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- `Inkscape <https://inkscape.org>`_ (to render SVG files)
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- pytest_, version 3.0.0 or later
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- mock_, when running Python versions < 3.3
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- Ghostscript_ (to render PDF files)
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- Inkscape_ (to render SVG files)
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Optionally you can install:
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- `coverage <https://coverage.readthedocs.io/en/latest/>`_ to collect coverage
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information
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- `pep8 <http://pep8.readthedocs.io/en/latest>`_ to test coding standards
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- pytest-cov_ to collect coverage information
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- pytest-pep8_ to test coding standards
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- pytest-timeout_ to limit runtime in case of stuck tests
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- pytest-xdist_ to run tests in parallel
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Building matplotlib for image comparison tests
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----------------------------------------------
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Running the tests
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-----------------
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Running the tests is simple. Make sure you have nose installed and run::
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Running the tests is simple. Make sure you have pytest installed and run::
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py.test
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or::
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python tests.py
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in the root directory of the distribution. The script takes a set of
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commands, such as:
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======================== ===========
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``--pep8`` pep8 checks
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``--no-pep8`` Do not perform pep8 checks
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``--no-network`` Disable tests that require network access
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``--pep8`` Perform pep8 checks (requires pytest-pep8_)
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``-m "not network"`` Disable tests that require network access
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======================== ===========
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Additional arguments are passed on to nosetests. See the nose
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documentation for supported arguments. Some of the more important ones are given
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here:
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Additional arguments are passed on to pytest. See the pytest documentation for
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`supported arguments`_. Some of the more important ones are given here:
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============================= ===========
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``--verbose`` Be more verbose
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``--processes=NUM`` Run tests in parallel over NUM processes
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``--process-timeout=SECONDS`` Set timeout for results from test runner process
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``--nocapture`` Do not capture stdout
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``--n NUM`` Run tests in parallel over NUM
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processes (requires pytest-xdist_)
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``--timeout=SECONDS`` Set timeout for results from each test
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process (requires pytest-timeout_)
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``--capture=no`` or ``-s`` Do not capture stdout
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To run a single test from the command line, you can provide a
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dot-separated path to the module followed by the function separated by
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a colon, e.g., (this is assuming the test is installed)::
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To run a single test from the command line, you can provide a file path,
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optionally followed by the function separated by two colons, e.g., (tests do
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not need to be installed, but Matplotlib should be)::
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python tests.py matplotlib.tests.test_simplification:test_clipping
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py.test lib/matplotlib/tests/test_simplification.py::test_clipping
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or, if tests are installed, a dot-separated path to the module, optionally
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followed by the function separated by two colons, such as::
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running the tests in parallel::
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py.test --verbose -n 5
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Depending on your version of Python and pytest-xdist, you may need to set
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``PYTHONHASHSEED`` to a fixed value when running in parallel::
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An alternative implementation that does not look at command line
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arguments works from within Python is to run the tests from the
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matplotlib library function :func:`matplotlib.test`::
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PYTHONHASHSEED=0 py.test --verbose -n 5
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An alternative implementation that does not look at command line arguments
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and works from within Python is to run the tests from the Matplotlib library
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function :func:`matplotlib.test`::
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import matplotlib
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.. hint::
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To run the tests you need to install nose and mock if using python 2.7::
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pip install nose
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pip install mock
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.. _`nosetest arguments`: http://nose.readthedocs.io/en/latest/usage.html
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.. _supported arguments: http://doc.pytest.org/en/latest/usage.html
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Writing a simple test
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Many elements of Matplotlib can be tested using standard tests. For
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example, here is a test from :mod:`matplotlib.tests.test_basic`::
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def test_simple():
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"""
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very simple example test
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assert 1 + 1 == 2
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If the test has side effects that need to be cleaned up, such as
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creating figures using the pyplot interface, use the ``@cleanup``
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decorator::
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Pytest determines which functions are tests by searching for files whose names
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begin with ``"test_"`` and then within those files for functions beginning with
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``"test"`` or classes beginning with ``"Test"``.
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@cleanup
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def test_create_figure():
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"""
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very simple example test that creates a figure using pyplot.
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"""
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fig = figure()
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...
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Some tests have internal side effects that need to be cleaned up after their
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execution (such as created figures or modified rc params). The pytest fixture
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:func:`~matplotlib.testing.conftest.mpl_test_settings` will automatically clean
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Known failing tests
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If you're writing a test, you may mark it as a known failing test with
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the :func:`~matplotlib.testing.decorators.knownfailureif`
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decorator. This allows the test to be added to the test suite and run
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on the buildbots without causing undue alarm. For example, although
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the following test will fail, it is an expected failure::
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If you're writing a test, you may mark it as a known failing test with the
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:func:`pytest.mark.xfail` decorator. This allows the test to be added to the
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test suite and run on the buildbots without causing undue alarm. For example,
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although the following test will fail, it is an expected failure::
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from matplotlib.testing.decorators import knownfailureif
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import pytest
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@knownfailureif(True)
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@pytest.mark.xfail
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def test_simple_fail():
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assert_equal(1+1,3)
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assert 1 + 1 == 3
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Note that the first argument to the
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:func:`~matplotlib.testing.decorators.knownfailureif` decorator is a
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fail condition, which can be a value such as True, False, or
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'indeterminate', or may be a dynamically evaluated expression.
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Note that the first argument to the :func:`~pytest.mark.xfail` decorator is a
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fail condition, which can be a value such as True, False, or may be a
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dynamically evaluated expression. If a condition is supplied, then a reason
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must also be supplied with the ``reason='message'`` keyword argument.
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Creating a new module in matplotlib.tests
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testing. For example, the tests related to the ``mathtext.py`` module
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Let's say you've added a new module named ``whizbang.py`` and you want
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to add tests for it in ``matplotlib.tests.test_whizbang``. To add
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this module to the list of default tests, append its name to
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``default_test_modules`` in :file:`lib/matplotlib/__init__.py`.
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Using Travis CI
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---------------
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‎doc/users/event_handling.rst‎

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example that prints the location of the mouse click and which button
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fig = plt.figure()
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ax = fig.add_subplot(111)
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fig, ax = plt.subplots()
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ax.plot(np.random.rand(10))
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def onclick(event):
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print('button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %
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(event.button, event.x, event.y, event.xdata, event.ydata))
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print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %
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('double' if event.dblclick else 'single', event.button,
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event.x, event.y, event.xdata, event.ydata))
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cid = fig.canvas.mpl_connect('button_press_event', onclick)
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‎examples/event_handling/test_mouseclicks.py‎

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