def __init__(self, min_year, max_year): elements = self.nasty_dates if min_year is not None: elements = [d for d in elements if d.year >= min_year] if max_year is not None: elements = [d for d in elements if d.year <= max_year] SampledFromStrategy.__init__( self, elements=elements )
def __init__(self): SampledFromStrategy.__init__(self, elements=[ 0.0, sys.float_info.min, -sys.float_info.min, float('inf'), -float('inf'), float('nan'), ])
def __init__(self, allow_nan=True, allow_infinity=True): elements = [ 0.0, -0.0, sys.float_info.min, -sys.float_info.min, -sys.float_info.max, sys.float_info.max ] if allow_infinity: elements.extend([float('inf'), -float('inf')]) if allow_nan: elements.extend([float('nan')]) SampledFromStrategy.__init__(self, elements=elements)
def __init__(self): SampledFromStrategy.__init__( self, elements=[ 0.0, sys.float_info.min, -sys.float_info.min, float('inf'), -float('inf'), float('nan'), ] )
def __init__(self): SampledFromStrategy.__init__( self, elements=[ 0.0, -0.0, sys.float_info.min, -sys.float_info.min, -sys.float_info.max, sys.float_info.max, float("inf"), -float("inf"), float("nan"), ], )
def sampled_from(elements): """Returns a strategy which generates any value present in the iterable elements. Note that as with just, values will not be copied and thus you should be careful of using mutable data """ from hypothesis.searchstrategy.misc import SampledFromStrategy, \ JustStrategy elements = tuple(iter(elements)) if not elements: raise InvalidArgument( u'sampled_from requires at least one value' ) if len(elements) == 1: result = JustStrategy(elements[0]) else: result = SampledFromStrategy(elements) return ReprWrapperStrategy( result, u'sampled_from((%s))' % (u', '.join( map(unicode_safe_repr, elements) )) )
def __init__(self, allow_nan=True, allow_infinity=True): elements = [ 0.0, -0.0, sys.float_info.min, -sys.float_info.min, -sys.float_info.max, sys.float_info.max ] if allow_infinity: elements.extend([ float('inf'), -float('inf') ]) if allow_nan: elements.extend([ float('nan') ]) SampledFromStrategy.__init__(self, elements=elements)
def sampled_from(elements): """Returns a strategy which generates any value present in the iterable elements. Note that as with just, values will not be copied and thus you should be careful of using mutable data """ from hypothesis.searchstrategy.misc import SampledFromStrategy elements = tuple(iter(elements)) if not elements: raise InvalidArgument('sampled_from requires at least one value') if len(elements) == 1: return just(elements[0]) return SampledFromStrategy(elements)
def sampled_from(elements): """Returns a strategy which generates any value present in the iterable elements. Note that as with just, values will not be copied and thus you should be careful of using mutable data. """ from hypothesis.searchstrategy.misc import SampledFromStrategy, \ JustStrategy from hypothesis.internal.conjecture.utils import check_sample elements = check_sample(elements) if not elements: return nothing() if len(elements) == 1: return JustStrategy(elements[0]) return SampledFromStrategy(elements)
def sampled_from(elements): """Returns a strategy which generates any value present in the iterable elements. Note that as with just, values will not be copied and thus you should be careful of using mutable data """ from hypothesis.searchstrategy.misc import SampledFromStrategy, \ JustStrategy elements = tuple(iter(elements)) if not elements: return nothing() if len(elements) == 1: return JustStrategy(elements[0]) else: return SampledFromStrategy(elements)
def reify(self, value): return SampledFromStrategy.reify(self, value)