.. doctest-skip-all .. include:: workflow/known_projects.inc .. _testing-guidelines: ================== Testing Guidelines ================== This section describes the testing framework and format standards for tests in Astropy core packages (this also serves as recommendations for affiliated packages). Testing Framework ================= The testing framework used by Astropy is the `py.test`_ framework. .. _py.test: http://pytest.org/latest/ .. _pytest.main: http://pytest.org/latest/builtin.html#pytest.main .. _running-tests: Running Tests ============= There are currently three different ways to invoke Astropy tests. Each method invokes `py.test`_ to run the tests but offers different options when calling. In addition to running the Astropy tests, these methods can also be called so that they check Python source code for `PEP8 compliance `_. All of the PEP8 testing options require the `pytest-pep8 plugin `_, which must be installed separately. setup.py test ------------- The safest way to run the astropy test suite is via the setup command ``test``. This is invoked by running ``python setup.py test`` while in the astropy source code directory. Run ``python setup.py test --help`` to see the options to the test command. Turn on PEP8 checking by passing ``--pep8`` to the ``test`` command. This will turn off regular testing and enable PEP8 testing. .. note:: This method of running the tests defaults to the version of `py.test`_ that is bundled with Astropy. To use the locally-installed version, you can set the ``ASTROPY_USE_SYSTEM_PYTEST`` environment variable, eg.:: > ASTROPY_USE_SYSTEM_PYTEST=1 python setup.py test py.test ------- An alternative way to run tests from the command line is to switch to the source code directory of astropy and simply type:: py.test `py.test`_ will look for files that `look like tests `_ in the current directory and all recursive directories then run all the code that `looks like tests `_ within those files. .. note:: To test any compiled C/Cython extensions, you must run ``python setup.py develop`` prior to running the py.test command-line script. Otherwise, any tests that make use of these extensions will not succeed. Similarly, in python 3, these tests will not run correctly in the source code, because they need the `2to3 `_ tool to be run on them. You may specify a specific test file or directory at the command line:: py.test test_file.py To run a specific test within a file use the ``-k`` option:: py.test test_file.py -k "test_function" You may also use the ``-k`` option to not run tests py putting a ``-`` in front of the matching string:: py.test test_file.py -k "-test_function" py.test has a number of `command line usage options. `_ Turn on PEP8 testing by adding the ``--pep8`` flag to the `py.test`_ call. By default regular tests will also be run but these can be turned off by adding ``-k pep8``:: py.test some_dir --pep8 -k pep8 .. note:: This method of running the tests uses the locally-installed version of `py.test`_ rather than the bundled one, and hence will fail if the local version it is not up-to-date enough (`py.test`_ 2.2 as of this writing). .. _astropy.test(): astropy.test() -------------- AstroPy includes a standalone version of py.test that allows to tests to be run even if py.test is not installed. Tests can be run from within AstroPy with:: import astropy astropy.test() This will run all the default tests for AstroPy. Tests for a specific package can be run by specifying the package in the call to the ``test()`` function:: astropy.test('io.fits') This method works only with package names that can be mapped to Astropy directories. As an alternative you can test a specific directory or file with the ``test_path`` option:: astropy.test(test_path='wcs/tests/test_wcs.py') The ``test_path`` must be specified either relative to the working directory or absolutely. By default `astropy.test()`_ will skip tests which retrieve data from the internet. To turn these tests on use the ``remote_data`` flag:: astropy.test('io.fits', remote_data=True) In addition, the ``test`` function supports any of the options that can be passed to `pytest.main() `_, and convenience options ``verbose=`` and ``pastebin=``. Enable PEP8 compliance testing with ``pep8=True`` in the call to ``astropy.test``. This will enable PEP8 checking and disable regular tests. .. note:: This method of running the tests defaults to the version of `py.test`_ that is bundled with Astropy. To use the locally-installed version, you should set the ``ASTROPY_USE_SYSTEM_PYTEST`` environment variable (see :doc:`/config/index`) or the `py.test`_ method described above. Tox --- `Tox `_ is a sort of meta-test runner for Python. It installs a project into one or more virtualenvs (usually one for each Python version supported), build and installs the project into each virtualenv, and runs the projects tests (or any other build processes one might want to test). This is a good way to run the tests against multiple installed Python versions locally without pushing to a continuous integration system. Tox works by detecting the presence of a file called ``tox.ini`` in the root of a Python project and using that to configure the desired virtualenvs and start the tests. So to run the Astropy tests on multiple Python versions using tox, simply install Tox:: $ pip install tox and then from the root of an Astropy repository clone run:: $ tox The Astropy tox configuration currently tests against Python versions 2.6, 2.7, 3.2, and 3.3. Tox will automatically skip any Python versions you do not have installed, but best results are achieved if you first install all supported Python versions and make sure they are on your ``$PATH``. .. note:: Tox creates its virtualenvs in the root of your project under a ``.tox`` directory (which is automatically ignored by ``.gitignore``). It's worth making note of this, however, as it is common practice to sometimes clean up a git repository and delete any untracked files by running the ``git clean -dfx`` command. As it can take a long time to rebuild the tox virtualenvs you may want to exclude the ``.tox`` directory from any cleanup. This can be achieved by running ``git clean -dfx -e .tox``, though it is probably worth defining a `git alias `_ to do this. Test-running options -------------------- Running parts of the test suite ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ It is possible to run only the tests for a particular subpackage. For example, to run only the ``wcs`` tests from the commandline:: python setup.py test -P wcs Or from Python:: >>> import astropy >>> astropy.test(package="wcs") You can also specify a single file to test from the commandline:: python setup.py test -t astropy/wcs/tests/test_wcs.py When the ``-t`` option is given a relative path, it is relative to the installed root of astropy. When ``-t`` is given a relative path to a documentation ``.rst`` file to test, it is relative to the root of the documentation, i.e. the ``docs`` directory in the source tree. For example:: python setup.py test -t units/index.rst Testing for open files ^^^^^^^^^^^^^^^^^^^^^^ Astropy can test whether any of the unit tests inadvertently leave any files open. Since this greatly slows down the time it takes to run the tests, it is turned off by default. To use it from the commandline, do:: python setup.py test --open-files To use it from Python, do:: >>> import astropy >>> astropy.test(open_files=True) Test coverage reports ^^^^^^^^^^^^^^^^^^^^^ Astropy can use `coverage.py `_ to generate test coverage reports. To generate a test coverage report, use:: python setup.py test --coverage There is a `coveragerc `_ file that defines files to omit as well as lines to exclude. It is installed along with astropy so that the ``astropy`` testing framework can use it. In the source tree, it is at ``astropy/tests/coveragerc``. Running tests in parallel ^^^^^^^^^^^^^^^^^^^^^^^^^ It is possible to speed up astropy's tests using the `pytest-xdist `_ plugin. This plugin can be installed using `pip`_:: pip install pytest-xdist Once installed, tests can be run in parallel using the ``'--parallel'`` commandline option. For example, to use 4 processes:: python setup.py test --parallel=4 Pass a negative number to ``'--parallel'`` to create the same number of processes as cores on your machine. Similarly, this feature can be invoked from Python:: >>> import astropy >>> astropy.test(parallel=4) Writing tests ============= ``py.test`` has the following test discovery rules: * ``test_*.py`` or ``*_test.py`` files * ``Test`` prefixed classes (without an ``__init__`` method) * ``test_`` prefixed functions and methods Consult the `test discovery rules `_ for detailed information on how to name files and tests so that they are automatically discovered by `py.test`_. Simple example -------------- The following example shows a simple function and a test to test this function:: def func(x): """Add one to the argument.""" return x + 1 def test_answer(): """Check the return value of func() for an example argument.""" assert func(3) == 5 If we place this in a ``test.py`` file and then run:: py.test test.py The result is:: ============================= test session starts ============================== python: platform darwin -- Python 2.7.2 -- pytest-1.1.1 test object 1: /Users/tom/tmp/test.py test.py F =================================== FAILURES =================================== _________________________________ test_answer __________________________________ def test_answer(): > assert func(3) == 5 E assert 4 == 5 E + where 4 = func(3) test.py:5: AssertionError =========================== 1 failed in 0.07 seconds =========================== Where to put tests ------------------ Package-specific tests ^^^^^^^^^^^^^^^^^^^^^^ Each package should include a suite of unit tests, covering as many of the public methods/functions as possible. These tests should be included inside each sub-package, e.g:: astropy/io/fits/tests/ ``tests`` directories should contain an ``__init__.py`` file so that the tests can be imported and so that they can use relative imports. Interoperability tests ^^^^^^^^^^^^^^^^^^^^^^ Tests involving two or more sub-packages should be included in:: astropy/tests/ Regression tests ---------------- Any time a bug is fixed, and wherever possible, one or more regression tests should be added to ensure that the bug is not introduced in future. Regression tests should include the ticket URL where the bug was reported. Working with data files ----------------------- Tests that need to make use of a data file should use the `~astropy.utils.data.get_pkg_data_fileobj` or `~astropy.utils.data.get_pkg_data_filename` functions. These functions search locally first, and then on the astropy data server or an arbitrary URL, and return a file-like object or a local filename, respectively. They automatically cache the data locally if remote data is obtained, and from then on the local copy will be used transparently. They also support the use of an MD5 hash to get a specific version of a data file. This hash can be obtained prior to submitting a file to the astropy data server by using the `~astropy.utils.data.compute_hash` function on a local copy of the file. Tests that may retrieve remote data should be marked with the ``@remote_data`` decorator, or, if a doctest, flagged with the ``REMOTE_DATA`` flag. Tests marked in this way will be skipped by default by ``astropy.test()`` to prevent test runs from taking too long. These tests can be run by ``astropy.test()`` by adding the ``remote_data=True`` flag. Turn on the remote data tests at the command line with ``py.test --remote-data``. Examples ^^^^^^^^ .. code-block:: none from ...config import get_data_filename from ...tests.helper import remote_data def test_1(): """Test version using a local file.""" #if filename.fits is a local file in the source distribution datafile = get_data_filename('filename.fits') # do the test @remote_data def test_2(): """Test version using a remote file.""" #this is the hash for a particular version of a file stored on the #astropy data server. datafile = get_data_filename('hash/94935ac31d585f68041c08f87d1a19d4') # do the test def doctest_example(): """ >>> datafile = get_data_filename('hash/94935') # doctest: +REMOTE_DATA """ pass The ``get_remote_test_data`` will place the files in a temporary directory indicated by the ``tempfile`` module, so that the test files will eventually get removed by the system. In the long term, once test data files become too large, we will need to design a mechanism for removing test data immediately. Tests that create files ----------------------- Tests may often be run from directories where users do not have write permissions so tests which create files should always do so in temporary directories. This can be done with the `py.test tmpdir function argument `_ or with Python's built-in `tempfile module `_. Setting up/Tearing down tests ----------------------------- In some cases, it can be useful to run a series of tests requiring something to be set up first. There are four ways to do this: Module-level setup/teardown ^^^^^^^^^^^^^^^^^^^^^^^^^^^ If the ``setup_module`` and ``teardown_module`` functions are specified in a file, they are called before and after all the tests in the file respectively. These functions take one argument, which is the module itself, which makes it very easy to set module-wide variables:: def setup_module(module): """Initialize the value of NUM.""" module.NUM = 11 def add_num(x): """Add pre-defined NUM to the argument.""" return x + NUM def test_42(): """Ensure that add_num() adds the correct NUM to its argument.""" added = add_num(42) assert added == 53 We can use this for example to download a remote test data file and have all the functions in the file access it:: import os def setup_module(module): """Store a copy of the remote test file.""" module.DATAFILE = get_remote_test_data('94935ac31d585f68041c08f87d1a19d4') def test(): """Perform test using cached remote input file.""" f = open(DATAFILE, 'rb') # do the test def teardown_module(module): """Clean up remote test file copy.""" os.remove(DATAFILE) Class-level setup/teardown ^^^^^^^^^^^^^^^^^^^^^^^^^^ Tests can be organized into classes that have their own setup/teardown functions. In the following :: def add_nums(x, y): """Add two numbers.""" return x + y class TestAdd42(object): """Test for add_nums with y=42.""" def setup_class(self): self.NUM = 42 def test_1(self): """Test behaviour for a specific input value.""" added = add_nums(11, self.NUM) assert added == 53 def test_2(self): """Test behaviour for another input value.""" added = add_nums(13, self.NUM) assert added == 55 def teardown_class(self): pass In the above example, the ``setup_class`` method is called first, then all the tests in the class, and finally the ``teardown_class`` is called. Method-level setup/teardown ^^^^^^^^^^^^^^^^^^^^^^^^^^^ There are cases where one might want setup and teardown methods to be run before and after *each* test. For this, use the ``setup_method`` and ``teardown_method`` methods:: def add_nums(x, y): """Add two numbers.""" return x + y class TestAdd42(object): """Test for add_nums with y=42.""" def setup_method(self, method): self.NUM = 42 def test_1(self): """Test behaviour for a specific input value.""" added = add_nums(11, self.NUM) assert added == 53 def test_2(self): """Test behaviour for another input value.""" added = add_nums(13, self.NUM) assert added == 55 def teardown_method(self, method): pass Function-level setup/teardown ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Finally, one can use ``setup_function`` and ``teardown_function`` to define a setup/teardown mechanism to be run before and after each function in a module. These take one argument, which is the function being tested:: def setup_function(function): pass def test_1(self): """First test.""" # do test def test_2(self): """Second test.""" # do test def teardown_method(function): pass Parametrizing tests ------------------- If you want to run a test several times for slightly different values, then it can be advantageous to use the ``py.test`` option to parametrize tests. For example, instead of writing:: def test1(): assert type('a') == str def test2(): assert type('b') == str def test3(): assert type('c') == str You can use the ``parametrize`` decorator to loop over the different inputs:: @pytest.mark.parametrize(('letter'), ['a', 'b', 'c']) def test(letter): """Check that the input is a string.""" assert type(letter) == str Tests requiring optional dependencies ------------------------------------- For tests that test functions or methods that require optional dependencies (e.g. Scipy), pytest should be instructed to skip the test if the dependencies are not present. The following example shows how this should be done:: import pytest try: import scipy HAS_SCIPY = True except ImportError: HAS_SCIPY = False @pytest.mark.skipif('not HAS_SCIPY') def test_that_uses_scipy(): ... In this way, the test is run if Scipy is present, and skipped if not. No tests should fail simply because an optional dependency is not present. Using py.test helper functions ------------------------------ If your tests need to use `py.test helper functions `_, such as ``pytest.raises``, import ``pytest`` into your test module like so:: from ...tests.helper import pytest You may need to adjust the relative import to work for the depth of your module. ``tests.helper`` imports ``pytest`` either from the user's system or ``extern.pytest`` if the user does not have py.test installed. This is so that users need not install py.test to run AstroPy's tests. Testing warnings ---------------- In order to test that warnings are triggered as expected in certain situations, you can use the ``astropy.tests.helper.catch_warnings`` context manager. Unlike the `warnings.catch_warnings` context manager in the standard library, this one will reset all warning state before hand so one is assured to get the warnings reported, regardless of what errors may have been emitted by other tests previously. Here is a real-world example:: from astropy.tests.helper import catch_warnings with catch_warnings(MergeConflictWarning) as warning_lines: # Test code which triggers a MergeConflictWarning out = table.vstack([t1, t2, t4], join_type='outer') assert warning_lines[0].category == metadata.MergeConflictWarning assert ("In merged column 'a' the 'units' attribute does not match (cm != m)" in str(warning_lines[0].message)) .. note:: Within `py.test`_ there is also the option of using the ``recwarn`` function argument to test that warnings are triggered. This method has been found to be problematic in at least one case (`pull request 1174 `_) so the ``astropy.tests.helper.catch_warnings`` context manager is preferred. Testing with Unicode literals ----------------------------- Python 2 can run code in two modes: by default, string literals are 8-bit `bytes` objects. However, when ``from __future__ import unicode_literals`` is used, string literals are `unicode` objects. In order to ensure that astropy supports user code written in both styles, the testing framework has a special feature to run a module containing tests in both modes. Simply add the comment:: # TEST_UNICODE_LITERALS anywhere in the file, and all tests in that file will be tested twice: once in the default mode where string literals are `bytes`, and again where string literals are `unicode`. Marking blocks of code to exclude from coverage ----------------------------------------------- Blocks of code may be ignored by the coverage testing by adding a comment containing the phrase ``pragma: no cover`` to the start of the block:: if this_rarely_happens: # pragma: no cover this_call_is_ignored() Blocks of code that are intended to run only in Python 2.x or 3.x may also be marked so that they will be ignored when appropriate by ``coverage.py``:: if sys.version_info[0] >= 3: # pragma: py3 do_it_the_python3_way() else: # pragma: py2 do_it_the_python2_way() Using ``six.PY3`` and ``six.PY2`` will also automatically exclude blocks from coverage, without requiring the pragma comment:: if six.PY3: do_it_the_python3_way() elif six.PY2: do_it_the_python2_way() .. _doctests: Writing doctests ================ A doctest in Python is a special kind of test that is embedded in a function, class, or module's docstring, or in the narrative Sphinx documentation, and is formatted to look like a Python interactive session--that is, they show lines of Python code entered at a ``>>>`` prompt followed by the output that would be expected (if any) when running that code in an interactive session. The idea is to write usage examples in docstrings that users can enter verbatim and check their output against the expected output to confirm that they are using the interface properly. Furthermore, Python includes a :mod:`doctest` module that can detect these doctests and execute them as part of a project's automated test suite. This way we can automatically ensure that all doctest-like examples in our docstrings are correct. The Astropy test suite automatically detects and runs any doctests in the Astropy source code or documentation, or in affiliated packages using the Astropy test running framework. For example doctests and detailed documentation on how to write them, see the full :mod:`doctest` documentation. .. note:: Since the narrative Sphinx documentation is not installed alongside the astropy source code, it can only be tested by running ``python setup.py test``, not by ``import astropy; astropy.test()``. Skipping doctests ----------------- Sometimes it is necessary to write examples that look like doctests but that are not actually executable verbatim. An example may depend on some external conditions being fulfilled, for example. In these cases there are a few ways to skip a doctest: 1. Next to the example add a comment like: ``# doctest: +SKIP``. For example: .. code-block:: none >>> import os >>> os.listdir('.') # doctest: +SKIP In the above example we want to direct the user to run ``os.listdir('.')`` but we don't want that line to be executed as part of the doctest. To skip tests that require fetching remote data, use the ``REMOTE_DATA`` flag instead. This way they can be turned on using the ``--remote-data`` flag when running the tests: .. code-block:: none >>> datafile = get_data_filename('hash/94935') # doctest: +REMOTE_DATA 2. Astropy's test framework adds support for a special ``__doctest_skip__`` variable that can be placed at the module level of any module to list functions, classes, and methods in that module whose doctests should not be run. That is, if it doesn't make sense to run a function's example usage as a doctest, the entire function can be skipped in the doctest collection phase. The value of ``__doctest_skip__`` should be a list of wildcard patterns for all functions/classes whose doctests should be skipped. For example:: __doctest_skip__ = ['myfunction', 'MyClass', 'MyClass.*'] skips the doctests in a function called ``myfunction``, the doctest for a class called ``MyClass``, and all *methods* of ``MyClass``. Module docstrings may contain doctests as well. To skip the module-level doctests include the string ``'.'`` in ``__doctest_skip__``. To skip all doctests in a module:: __doctest_skip__ = ['*'] 3. In the Sphinx documentation, a doctest section can be skipped by making it part of a ``doctest-skip`` directive:: .. doctest-skip:: >>> # This is a doctest that will appear in the documentation, >>> # but will not be executed by the testing framework. >>> 1 / 0 # Divide by zero, ouch! It is also possible to skip all doctests below a certain line using a ``doctest-skip-all`` comment. Note the lack of ``::`` at the end of the line here:: .. doctest-skip-all All doctests below here are skipped... 4. ``__doctest_requires__`` is a way to list dependencies for specific doctests. It should be a dictionary mapping wildcard patterns (in the same format as ``__doctest_skip__``) to a list of one or more modules that should be *importable* in order for the tests to run. For example, if some tests require the scipy module to work they will be skipped unless ``import scipy`` is possible. It is also possible to use a tuple of wildcard patterns as a key in this dict:: __doctest_requires__ = {('func1', 'func2'): ['scipy']} Having this module-level variable will require ``scipy`` to be importable in order to run the doctests for functions ``func1`` and ``func2`` in that module. In the Sphinx documentation, a doctest requirement can be notated with the ``doctest-requires`` directive:: .. doctest-requires:: scipy >>> import scipy >>> scipy.hamming(...) Skipping output --------------- One of the important aspects of writing doctests is that the example output can be accurately compared to the actual output produced when running the test. The doctest system compares the actual output to the example output verbatim by default, but this not always feasible. For example the example output may contain the ``__repr__`` of an object which displays its id (which will change on each run), or a test that expects an exception may output a traceback. The simplest way to generalize the example output is to use the ellipses ``...``. For example:: >>> 1 / 0 Traceback (most recent call last): ... ZeroDivisionError: integer division or modulo by zero This doctest expects an exception with a traceback, but the text of the traceback is skipped in the example output--only the first and last lines of the output are checked. See the :mod:``doctest`` documentation for more examples of skipping output. Handling float output --------------------- Some doctests may produce output that contains string representations of floating point values. Floating point representations are often not exact and contain roundoffs in their least significant digits. Depending on the platform the tests are being run on (different Python versions, different OS, etc.) the exact number of digits shown can differ. Because doctests work by comparing strings this can cause such tests to fail. To address this issue Astropy's test framework includes support for a ``FLOAT_CMP`` flag that can be used with doctests. For example:: >>> 1.0 / 3.0 # doctest: +FLOAT_CMP 0.333333333333333311 When this flag is used, the expected and actual outputs are both parsed to find any floating point values in the strings. Those are then converted to actual Python `float` objects and compared numerically. This means that small differences in representation of roundoff digits will be ignored by the doctest. The values are otherwise compared exactly, so more significant (albeit possibly small) differences will still be caught by these tests.