# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
from hypothesis.internal.reflection import get_pretty_function_description
from hypothesis.strategies._internal.strategies import (
SampledFromStrategy,
SearchStrategy,
T,
is_simple_data,
)
from hypothesis.strategies._internal.utils import cacheable, defines_strategy
class JustStrategy(SampledFromStrategy):
"""A strategy which always returns a single fixed value.
It's implemented as a length-one SampledFromStrategy so that all our
special-case logic for filtering and sets applies also to just(x).
The important difference from a SampledFromStrategy with only one
element to choose is that JustStrategy *never* touches the underlying
choice sequence, i.e. drawing neither reads from nor writes to `data`.
This is a reasonably important optimisation (or semantic distinction!)
for both JustStrategy and SampledFromStrategy.
"""
@property
def value(self):
return self.elements[0]
def __repr__(self):
suffix = "".join(
f".{name}({get_pretty_function_description(f)})"
for name, f in self._transformations
)
if self.value is None:
return "none()" + suffix
return f"just({get_pretty_function_description(self.value)}){suffix}"
def calc_is_cacheable(self, recur):
return is_simple_data(self.value)
def do_filtered_draw(self, data):
# The parent class's `do_draw` implementation delegates directly to
# `do_filtered_draw`, which we can greatly simplify in this case since
# we have exactly one value. (This also avoids drawing any data.)
return self._transform(self.value)
[docs]
@defines_strategy(never_lazy=True)
def just(value: T) -> SearchStrategy[T]:
"""Return a strategy which only generates ``value``.
Note: ``value`` is not copied. Be wary of using mutable values.
If ``value`` is the result of a callable, you can use
:func:`builds(callable) <hypothesis.strategies.builds>` instead
of ``just(callable())`` to get a fresh value each time.
Examples from this strategy do not shrink (because there is only one).
"""
return JustStrategy([value])
[docs]
@defines_strategy(force_reusable_values=True)
def none() -> SearchStrategy[None]:
"""Return a strategy which only generates None.
Examples from this strategy do not shrink (because there is only
one).
"""
return just(None)
class Nothing(SearchStrategy):
def calc_is_empty(self, recur):
return True
def do_draw(self, data):
# This method should never be called because draw() will mark the
# data as invalid immediately because is_empty is True.
raise NotImplementedError("This should never happen")
def calc_has_reusable_values(self, recur):
return True
def __repr__(self):
return "nothing()"
def map(self, f):
return self
def filter(self, f):
return self
def flatmap(self, f):
return self
NOTHING = Nothing()
[docs]
@cacheable
@defines_strategy(never_lazy=True)
def nothing() -> SearchStrategy:
"""This strategy never successfully draws a value and will always reject on
an attempt to draw.
Examples from this strategy do not shrink (because there are none).
"""
return NOTHING
class BooleansStrategy(SearchStrategy):
def do_draw(self, data):
return data.draw_boolean()
def __repr__(self):
return "booleans()"