docformatter wants the blank lines gone

Author: dchudz

examples/test_binary_search.py

@@ -23,7 +23,6 @@
 
 It also demonstrates the useful testing technique of testing how the answer
 should change (or not) in response to movements in the underlying data.
-
 """
 
 from __future__ import division, print_function, absolute_import
@@ -40,7 +39,6 @@ def binary_search(ls, v):
 
     1. ls.insert(i, v) is sorted
     2. ls.insert(j, v) is not sorted for j < i
-
     """
     # Without this check we will get an index error on the next line when the
     # list is empty.
@@ -134,7 +132,6 @@ def test_inserts_into_same_place_twice(ls, v):
 
     This is an instance of a good general category of test: Testing how the
     function moves in responses to changes in the underlying data.
-
     """
     i = binary_search(ls, v)
     ls.insert(i, v)

examples/test_rle.py

@@ -27,7 +27,6 @@
 
 It also has an example of testing invariants in response to changes in the
 underlying data.
-
 """
 
 from __future__ import division, print_function, absolute_import
@@ -79,7 +78,6 @@ def test_decodes_to_starting_sequence(ls):
     original sequence back.
 
     Otherwise we've done something very wrong.
-
     """
     assert run_length_decode(run_length_encode(ls)) == ls
 
@@ -92,7 +90,6 @@ def test_duplicating_an_element_does_not_increase_length(ls, data):
     In this test we deliberately introduce or extend a run and assert
     that this does not increase the length of our encoding, because they
     should be part of the same run in the final result.
-
     """
     # We use assume to get a valid index into the list. We could also have used
     # e.g. flatmap, but this is relatively straightforward and will tend to

scripts/hypothesistooling.py

@@ -162,7 +162,6 @@ def build_jobs():
     Note: This usage of Travis has been somewhat reverse engineered due
     to a certain dearth of documentation as to what values what takes
     when.
-
     """
     import requests
 

src/hypothesis/__init__.py

@@ -20,7 +20,6 @@
 
 It verifies your code against a wide range of input and minimizes any
 failing examples it finds.
-
 """
 
 

src/hypothesis/_settings.py

@@ -19,7 +19,6 @@
 
 Either an explicit settings object can be used or the default object on
 this module can be modified.
-
 """
 
 from __future__ import division, print_function, absolute_import
@@ -116,7 +115,6 @@ class settings(settingsMeta('settings', (object,), {})):
 
     Default values are picked up from the settings.default object and
     changes made there will be picked up in newly created settings.
-
     """
 
     _WHITELISTED_REAL_PROPERTIES = [
@@ -193,7 +191,6 @@ def define_setting(
         - default is the default value. This may be a zero argument
           function in which case it is evaluated and its result is stored
           the first time it is accessed on any given settings object.
-
         """
         if settings.__definitions_are_locked:
             from hypothesis.errors import InvalidState
@@ -265,7 +262,6 @@ def database(self):
         database_file setting is not None this will be lazily loaded as
         an ExampleDatabase, using that file the first time that this
         property is accessed on a particular thread.
-
         """
         if self._database is not_set and self.database_file is not None:
             from hypothesis.database import ExampleDatabase
@@ -294,7 +290,6 @@ def register_profile(name, settings):
         These settings can be loaded in by name. Enable different
         defaults for different settings.  ``settings`` must be a
         settings object.
-
         """
         settings._profiles[name] = settings
 
@@ -306,7 +301,6 @@ def get_profile(name):
          to load
         A InvalidArgument exception will be thrown if the
          profile does not exist
-
         """
         try:
             return settings._profiles[name]
@@ -324,7 +318,6 @@ def load_profile(name):
 
         Any setting not defined in the profile will be the library
         defined default for that setting
-
         """
         settings._current_profile = name
         settings._assign_default_internal(settings.get_profile(name))
@@ -482,7 +475,6 @@ class HealthCheck(Enum):
     """Arguments for :attr:`~hypothesis.settings.suppress_health_check`.
 
     Each member of this enum is a type of health check to suppress.
-
     """
 
     exception_in_generation = 0

src/hypothesis/control.py

@@ -35,7 +35,6 @@ def assume(condition):
 
     This allows you to specify properties that you *assume* will be
     true, and let Hypothesis try to avoid similar examples in future.
-
     """
     if not condition:
         raise UnsatisfiedAssumption()
@@ -95,7 +94,6 @@ def cleanup(teardown):
     Inside a test this isn't very interesting, because you can just use
     a finally block, but note that you can use this inside map, flatmap,
     etc. in order to e.g. insist that a value is closed at the end.
-
     """
     context = _current_build_context.value
     if context is None:
@@ -121,7 +119,6 @@ def event(value):
     statistics reporting mode.
 
     Events should be strings or convertible to them.
-
     """
     context = _current_build_context.value
     if context is None:

src/hypothesis/core.py

@@ -133,7 +133,6 @@ def reproduce_failure(version, blob):
     in the event that you don't have access to the test database. Because of
     this, *no* compatibility guarantees are made between different versions of
     Hypothesis - its API may change arbitrarily from version to version.
-
     """
     def accept(test):
         test._hypothesis_internal_use_reproduce_failure = (version, blob)
@@ -349,7 +348,6 @@ def skip_exceptions_to_reraise():
 
     This is intended to cover most common test runners; if you would
     like another to be added please open an issue or pull request.
-
     """
     import unittest
     # This is a set because nose may simply re-export unittest.SkipTest
@@ -885,7 +883,6 @@ def given(*given_arguments, **given_kwargs):
     randomized test.
 
     This is the main entry point to Hypothesis.
-
     """
     def run_test_with_generator(test):
         generator_arguments = tuple(given_arguments)

src/hypothesis/database.py

@@ -60,23 +60,20 @@ class ExampleDatabase(EDMeta('ExampleDatabase', (object,), {})):
     A key -> multiple distinct values mapping.
 
     Keys and values are binary data.
-
     """
 
     def save(self, key, value):
         """Save ``value`` under ``key``.
 
         If this value is already present for this key, silently do
         nothing
-
         """
         raise NotImplementedError('%s.save' % (type(self).__name__))
 
     def delete(self, key, value):
         """Remove this value from this key.
 
         If this value is not present, silently do nothing.
-
         """
         raise NotImplementedError('%s.delete' % (type(self).__name__))
 
@@ -87,7 +84,6 @@ def move(self, src, dest, value):
 
         Note that value will be inserted at dest regardless of whether
         it is currently present at src.
-
         """
         if src == dest:
             self.save(src, value)

src/hypothesis/errors.py

@@ -30,7 +30,6 @@ class UnsatisfiedAssumption(HypothesisException):
     """An internal error raised by assume.
 
     If you're seeing this error something has gone wrong.
-
     """
 
 
@@ -41,7 +40,6 @@ class BadTemplateDraw(HypothesisException):
 
     This is not an error condition internally, but if you ever see this
     in your code it's probably a Hypothesis bug
-
     """
 
 
@@ -50,7 +48,6 @@ class NoSuchExample(HypothesisException):
 
     This does not guarantee that no example exists, only that we were
     unable to find one.
-
     """
 
     def __init__(self, condition_string, extra=''):
@@ -66,7 +63,6 @@ class DefinitelyNoSuchExample(NoSuchExample):  # pragma: no cover
 
     This exception remains for compatibility reasons for now but can
     never actually be thrown.
-
     """
 
 
@@ -86,7 +82,6 @@ class Unsatisfiable(HypothesisException):
     strategy or using a better starting point (e.g if you are requiring
     a list has unique values you could instead filter out all duplicate
     values from the list)
-
     """
 
 
@@ -104,7 +99,6 @@ class Flaky(HypothesisException):
         3. The function is timing sensitive and can fail or pass depending on
            how long it takes. Try breaking it up into smaller functions which
            don't do that and testing those instead.
-
     """
 
 
@@ -134,7 +128,6 @@ class ResolutionFailed(InvalidArgument):
     Type inference is best-effort, so this only happens when an
     annotation exists but could not be resolved for a required argument
     to the target of ``builds()``, or where the user passed ``infer``.
-
     """
 
 

src/hypothesis/extra/datetime.py

@@ -19,7 +19,6 @@
 
 It depends on the ``pytz`` package, which is stable enough that almost any
 version should be compatible - most updates are for the timezone database.
-
 """
 
 from __future__ import division, print_function, absolute_import
@@ -74,7 +73,6 @@ def datetimes(allow_naive=None, timezones=None, min_year=None, max_year=None):
     available via pytz will be used.
 
     All generated datetimes will be between min_year and max_year, inclusive.
-
     """
     note_deprecation('Use hypothesis.strategies.datetimes, which supports '
                      'full-precision bounds and has a simpler API.')
@@ -92,7 +90,6 @@ def dates(min_year=None, max_year=None):
         use :py:func:`hypothesis.strategies.dates` instead.
 
     All generated dates will be between min_year and max_year, inclusive.
-
     """
     note_deprecation('Use hypothesis.strategies.dates, which supports bounds '
                      'given as date objects for single-day resolution.')
@@ -109,7 +106,6 @@ def times(allow_naive=None, timezones=None):
 
     The allow_naive and timezones arguments act the same as the datetimes
     strategy above.
-
     """
     note_deprecation('Use hypothesis.strategies.times, which supports '
                      'min_time and max_time arguments.')

src/hypothesis/extra/django/models.py

@@ -186,7 +186,6 @@ def models(model, **field_strategies):
     be generated with::
 
       shop_strategy = models(Shop, company=models(Company))
-
     """
     result = {k: v for k, v in field_strategies.items()
               if v is not default_value}

src/hypothesis/extra/numpy.py

@@ -298,7 +298,6 @@ def arrays(
     primarily designed around testing small examples. If you have arrays with
     hundreds or more elements, having a fill value is essential if you want
     your tests to run in reasonable time.
-
     """
     if isinstance(dtype, SearchStrategy):
         dtype = draw(dtype)
@@ -383,7 +382,6 @@ def unsigned_integer_dtypes(endianness='?', sizes=(8, 16, 32, 64)):
 
     sizes must be a collection of integer sizes in bits.  The default
     (8, 16, 32, 64) covers the full range of sizes.
-
     """
     return dtype_factory('u', sizes, (8, 16, 32, 64), endianness)
 
@@ -394,7 +392,6 @@ def integer_dtypes(endianness='?', sizes=(8, 16, 32, 64)):
 
     endianness and sizes are treated as for
     :func:`unsigned_integer_dtypes`.
-
     """
     return dtype_factory('i', sizes, (8, 16, 32, 64), endianness)
 
@@ -409,7 +406,6 @@ def floating_dtypes(endianness='?', sizes=(16, 32, 64)):
     Larger floats (96 and 128 bit real parts) are not supported on all
     platforms and therefore disabled by default.  To generate these dtypes,
     include these values in the sizes argument.
-
     """
     return dtype_factory('f', sizes, (16, 32, 64, 96, 128), endianness)
 
@@ -421,7 +417,6 @@ def complex_number_dtypes(endianness='?', sizes=(64, 128)):
     sizes is the total size in bits of a complex number, which consists
     of two floats.  Complex halfs (a 16-bit real part) are not supported
     by numpy and will not be generated by this strategy.
-
     """
     return dtype_factory('c', sizes, (64, 128, 192, 256), endianness)
 
@@ -503,7 +498,6 @@ def nested_dtypes(subtype_strategy=scalar_dtypes(),
     :func:`array_dtypes` with ``allow_subarrays=True``. Subdtypes in an
     array dtype may be nested to any depth, subject to the max_leaves
     argument.
-
     """
     return st.recursive(subtype_strategy,
                         lambda x: array_dtypes(x, allow_subarrays=True),

src/hypothesis/extra/pandas/impl.py

@@ -156,7 +156,6 @@ def range_indexes(min_size=0, max_size=None):
     * min_size is the smallest number of elements the index can have.
     * max_size is the largest number of elements the index can have. If None
       it will default to some suitable value based on min_size.
-
     """
     check_valid_size(min_size, 'min_size')
     check_valid_size(max_size, 'max_size')
@@ -189,7 +188,6 @@ def indexes(
       should pass a max_size explicitly.
     * unique specifies whether all of the elements in the resulting index
       should be distinct.
-
     """
     check_valid_size(min_size, 'min_size')
     check_valid_size(max_size, 'max_size')
@@ -238,7 +236,6 @@ def series(elements=None, dtype=None, index=None, fill=None, unique=False):
         >>> series(dtype=int).example()
         0   -2001747478
         1    1153062837
-
     """
     if index is None:
         index = range_indexes()
@@ -292,7 +289,6 @@ class column(object):
     * fill: A default value for elements of the column. See
       :func:`~hypothesis.extra.numpy.arrays` for a full explanation.
     * unique: If all values in this column should be distinct.
-
     """
 
     name = attr.ib(default=None)
@@ -313,7 +309,6 @@ def columns(
     objects, or a number, in which case that many unnamed columns will
     be created. All other arguments are passed through verbatim to
     create the columns.
-
     """
     try:
         names = list(names_or_number)
@@ -431,7 +426,6 @@ def data_frames(
       dicts are passed, if there are keys with no corresponding column name,
       if sequences are passed if there are too many items) will result in
       InvalidArgument being raised.
-
     """
     if index is None:
         index = range_indexes()