# numpy.testing.Tester.test

method

testing.Tester.test(label='fast', verbose=1, extra_argv=None, doctests=False, coverage=False, raise_warnings=None, timer=False)

  Run tests for module using nose.

  Parameters
    label{‘fast’, ‘full’, ‘’, attribute identifier}, optional

      Identifies the tests to run. This can be a string to pass to the nosetests executable with the ‘-A’ option, or one of several special values. Special values are:

      - ‘fast’ - the default - which corresponds to the `nosetests -A` option of ‘not slow’.

      - ‘full’ - fast (as above) and slow tests as in the ‘no -A’ option to nosetests - this is the same as ‘’.

      - None or ‘’ - run all tests.

      - attribute_identifier - string passed directly to nosetests as ‘-A’.

    verbose int, optional

      Verbosity value for test outputs, in the range 1-10. Default is 1.

    extra_argv list, optional

      List with any extra arguments to pass to nosetests.

    doctests bool, optional

      If True, run doctests in module. Default is False.

    coverage bool, optional

      If True, report coverage of NumPy code. Default is False. (This requires the coverage module).

    raise_warnings None, str or sequence of warnings, optional

      This specifies which warnings to configure as ‘raise’ instead of being shown once during the test execution. Valid strings are:

      - “develop” : equals `(Warning,)`

      - “release” : equals `()`, do not raise on any warnings.

    timer bool or int, optional

      Timing of individual tests with `nose-timer` (which needs to be installed). If True, time tests and report on all of them. If an integer (say `N`), report timing results for `N` slowest tests.

  Returns
    result object

      Returns the result of running the tests as a `nose.result.TextTestResult` object.

  Notes

  Each NumPy module exposes `test` in its namespace to run all tests for it. For example, to run all tests for numpy.lib:

      >>> np.lib.test()

  Examples

      >>> result = np.lib.test()
      Running unit tests for numpy.lib
      ...
      Ran 976 tests in 3.933s

  OK

      >>> result.errors
      []
      >>> result.knownfail
      []