How to use calc_is_empty method in hypothesis

Best Python code snippet using hypothesis

collections.py

Source:collections.py

...47    def do_draw(self, data):48        return self.newtuple(49            data.draw(e) for e in self.element_strategies50        )51    def calc_is_empty(self, recur):52        return any(recur(e) for e in self.element_strategies)53TERMINATOR = hbytes(b'\0')54class ListStrategy(SearchStrategy):55    """A strategy for lists which takes an intended average length and a56    strategy for each of its element types and generates lists containing any57    of those element types.58    The conditional distribution of the length is geometric, and the59    conditional distribution of each parameter is whatever their60    strategies define.61    """62    def __init__(63        self,64        strategies, average_length=50.0, min_size=0, max_size=float('inf')65    ):66        SearchStrategy.__init__(self)67        assert average_length > 068        self.average_length = average_length69        strategies = tuple(strategies)70        self.min_size = min_size or 071        self.max_size = max_size or float('inf')72        self.element_strategy = one_of_strategies(strategies)73    def do_validate(self):74        self.element_strategy.validate()75        if self.is_empty:76            raise InvalidArgument((77                'Cannot create non-empty lists with elements drawn from '78                'strategy %r because it has no values.') % (79                self.element_strategy,))80    def calc_is_empty(self, recur):81        if self.min_size == 0:82            return False83        else:84            return recur(self.element_strategy)85    def do_draw(self, data):86        if self.element_strategy.is_empty:87            assert self.min_size == 088            return []89        elements = cu.many(90            data,91            min_size=self.min_size, max_size=self.max_size,92            average_size=self.average_length93        )94        result = []95        while elements.more():96            result.append(data.draw(self.element_strategy))97        return result98    def __repr__(self):99        return (100            'ListStrategy(%r, min_size=%r, average_size=%r, max_size=%r)'101        ) % (102            self.element_strategy, self.min_size, self.average_length,103            self.max_size104        )105class UniqueListStrategy(SearchStrategy):106    def __init__(107        self,108        elements, min_size, max_size, average_size,109        key110    ):111        super(UniqueListStrategy, self).__init__()112        assert min_size <= average_size <= max_size113        self.min_size = min_size114        self.max_size = max_size115        self.average_size = average_size116        self.element_strategy = elements117        self.key = key118    def do_validate(self):119        self.element_strategy.validate()120        if self.is_empty:121            raise InvalidArgument((122                'Cannot create non-empty lists with elements drawn from '123                'strategy %r because it has no values.') % (124                self.element_strategy,))125    def calc_is_empty(self, recur):126        if self.min_size == 0:127            return False128        else:129            return recur(self.element_strategy)130    def do_draw(self, data):131        if self.element_strategy.is_empty:132            assert self.min_size == 0133            return []134        elements = cu.many(135            data,136            min_size=self.min_size, max_size=self.max_size,137            average_size=self.average_size138        )139        seen = set()140        result = []141        while elements.more():142            value = data.draw(self.element_strategy)143            k = self.key(value)144            if k in seen:145                elements.reject()146            else:147                seen.add(k)148                result.append(value)149        assert self.max_size >= len(result) >= self.min_size150        return result151class FixedKeysDictStrategy(MappedSearchStrategy):152    """A strategy which produces dicts with a fixed set of keys, given a153    strategy for each of their equivalent values.154    e.g. {'foo' : some_int_strategy} would155    generate dicts with the single key 'foo' mapping to some integer.156    """157    def __init__(self, strategy_dict):158        self.dict_type = type(strategy_dict)159        if isinstance(strategy_dict, OrderedDict):160            self.keys = tuple(strategy_dict.keys())161        else:162            try:163                self.keys = tuple(sorted(164                    strategy_dict.keys(),165                ))166            except TypeError:167                self.keys = tuple(sorted(168                    strategy_dict.keys(), key=repr,169                ))170        super(FixedKeysDictStrategy, self).__init__(171            strategy=TupleStrategy(172                (strategy_dict[k] for k in self.keys), tuple173            )174        )175    def calc_is_empty(self, recur):176        return recur(self.mapped_strategy)177    def __repr__(self):178        return 'FixedKeysDictStrategy(%r, %r)' % (179            self.keys, self.mapped_strategy)180    def pack(self, value):...

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