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How to use element_strategies method in hypothesis

Best Python code snippet using hypothesis

collections.py

Source:collections.py

1# coding=utf-82#3# This file is part of Hypothesis, which may be found at4# https://github.com/HypothesisWorks/hypothesis/5#6# Most of this work is copyright (C) 2013-2019 David R. MacIver7# (david@drmaciver.com), but it contains contributions by others. See8# CONTRIBUTING.rst for a full list of people who may hold copyright, and9# consult the git log if you need to determine who owns an individual10# contribution.11#12# This Source Code Form is subject to the terms of the Mozilla Public License,13# v. 2.0. If a copy of the MPL was not distributed with this file, You can14# obtain one at https://mozilla.org/MPL/2.0/.15#16# END HEADER17from __future__ import absolute_import, division, print_function18import hypothesis.internal.conjecture.utils as cu19from hypothesis.errors import InvalidArgument20from hypothesis.internal.compat import OrderedDict21from hypothesis.internal.conjecture.utils import combine_labels22from hypothesis.searchstrategy.strategies import MappedSearchStrategy, SearchStrategy23class TupleStrategy(SearchStrategy):24    """A strategy responsible for fixed length tuples based on heterogenous25    strategies for each of their elements."""26    def __init__(self, strategies):27        SearchStrategy.__init__(self)28        self.element_strategies = tuple(strategies)29    def do_validate(self):30        for s in self.element_strategies:31            s.validate()32    def calc_label(self):33        return combine_labels(34            self.class_label, *[s.label for s in self.element_strategies]35        )36    def __repr__(self):37        if len(self.element_strategies) == 1:38            tuple_string = "%s," % (repr(self.element_strategies[0]),)39        else:40            tuple_string = ", ".join(map(repr, self.element_strategies))41        return "TupleStrategy((%s))" % (tuple_string,)42    def calc_has_reusable_values(self, recur):43        return all(recur(e) for e in self.element_strategies)44    def do_draw(self, data):45        return tuple(data.draw(e) for e in self.element_strategies)46    def calc_is_empty(self, recur):47        return any(recur(e) for e in self.element_strategies)48class ListStrategy(SearchStrategy):49    """A strategy for lists which takes a strategy for its elements and the50    allowed lengths, and generates lists with the correct size and contents."""51    def __init__(self, elements, min_size=0, max_size=float("inf")):52        SearchStrategy.__init__(self)53        self.min_size = min_size or 054        self.max_size = max_size if max_size is not None else float("inf")55        assert 0 <= self.min_size <= self.max_size56        self.average_size = min(57            max(self.min_size * 2, self.min_size + 5),58            0.5 * (self.min_size + self.max_size),59        )60        self.element_strategy = elements61    def calc_label(self):62        return combine_labels(self.class_label, self.element_strategy.label)63    def do_validate(self):64        self.element_strategy.validate()65        if self.is_empty:66            raise InvalidArgument(67                (68                    "Cannot create non-empty lists with elements drawn from "69                    "strategy %r because it has no values."70                )71                % (self.element_strategy,)72            )73        if self.element_strategy.is_empty and 0 < self.max_size < float("inf"):74            raise InvalidArgument(75                "Cannot create a collection of max_size=%r, because no "76                "elements can be drawn from the element strategy %r"77                % (self.max_size, self.element_strategy)78            )79    def calc_is_empty(self, recur):80        if self.min_size == 0:81            return False82        else:83            return recur(self.element_strategy)84    def do_draw(self, data):85        if self.element_strategy.is_empty:86            assert self.min_size == 087            return []88        elements = cu.many(89            data,90            min_size=self.min_size,91            max_size=self.max_size,92            average_size=self.average_size,93        )94        result = []95        while elements.more():96            result.append(data.draw(self.element_strategy))97        return result98    def __repr__(self):99        return "%s(%r, min_size=%r, max_size=%r)" % (100            self.__class__.__name__,101            self.element_strategy,102            self.min_size,103            self.max_size,104        )105class UniqueListStrategy(ListStrategy):106    def __init__(self, elements, min_size, max_size, key):107        super(UniqueListStrategy, self).__init__(elements, min_size, max_size)108        self.key = key109    def do_draw(self, data):110        if self.element_strategy.is_empty:111            assert self.min_size == 0112            return []113        elements = cu.many(114            data,115            min_size=self.min_size,116            max_size=self.max_size,117            average_size=self.average_size,118        )119        seen = set()120        result = []121        while elements.more():122            value = data.draw(self.element_strategy)123            k = self.key(value)124            if k in seen:125                elements.reject()126            else:127                seen.add(k)128                result.append(value)129        assert self.max_size >= len(result) >= self.min_size130        return result131class FixedKeysDictStrategy(MappedSearchStrategy):132    """A strategy which produces dicts with a fixed set of keys, given a133    strategy for each of their equivalent values.134    e.g. {'foo' : some_int_strategy} would generate dicts with the single135    key 'foo' mapping to some integer.136    """137    def __init__(self, strategy_dict):138        self.dict_type = type(strategy_dict)139        if isinstance(strategy_dict, OrderedDict):140            self.keys = tuple(strategy_dict.keys())141        else:142            try:143                self.keys = tuple(sorted(strategy_dict.keys()))144            except TypeError:145                self.keys = tuple(sorted(strategy_dict.keys(), key=repr))146        super(FixedKeysDictStrategy, self).__init__(147            strategy=TupleStrategy((strategy_dict[k] for k in self.keys))148        )149    def calc_is_empty(self, recur):150        return recur(self.mapped_strategy)151    def __repr__(self):152        return "FixedKeysDictStrategy(%r, %r)" % (self.keys, self.mapped_strategy)153    def pack(self, value):...

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