Python hypothesis.strategies 模块，one_of() 实例源码

def pattern_to_statements(pattern):
    if isinstance(pattern, template):
        return lists(just(pattern), min_size=1, max_size=1)
    rule, value = pattern
    if rule == 'sequence':
        return tuples(*map(pattern_to_statements, value)).map(unpack_list).map(list)
    elif rule == 'alternates':
        return one_of(*map(pattern_to_statements, value))
    elif rule == 'zeroOrMore':
        return lists(pattern_to_statements(value)).map(unpack_list).map(list)
    elif rule == 'oneOrMore':
        return lists(pattern_to_statements(value), min_size=1).map(unpack_list).map(list)
    elif rule == 'optional':
        return lists(pattern_to_statements(value), min_size=0, max_size=1).map(unpack_list).map(list)
    else:
        raise Exception("impossible!", rule)



# this replicates the current scorm pattern, a realistic example of medium
# complexity. Note it has repeated elements, just not in ambiguous ways.

def optional(strategy):
    """Return an optional version of the supplied strategy."""
    return st.one_of(st.none(), strategy)

def enums_of_primitives(draw):
    """Generate enum classes with primitive values."""
    if is_py2:
        names = draw(st.sets(st.text(alphabet=string.ascii_letters,
                                     min_size=1),
                             min_size=1))
    else:
        names = draw(st.sets(st.text(min_size=1), min_size=1))
    n = len(names)
    vals = draw(st.one_of(st.sets(st.one_of(
            st.integers(),
            st.floats(allow_nan=False),
            st.text(min_size=1)),
        min_size=n, max_size=n)))
    return Enum('HypEnum', list(zip(names, vals)))

def create_generic_dict_type(type1, type2):
    """Create a strategy for generating parameterized dict types."""
    return st.one_of(dict_types,
                     dict_types.map(lambda t: t[type1, type2]),
                     dict_types.map(lambda t: t[Any, type2]),
                     dict_types.map(lambda t: t[type1, Any]))

def strategy(self):
        'Returns resulting strategy that generates configured char set'
        max_codepoint = None if self._unicode else 127

        strategies = []
        if self._negate:
            if self._categories or self._whitelist_chars:
                strategies.append(
                    hs.characters(
                        blacklist_categories=self._categories | set(['Cc', 'Cs']),
                        blacklist_characters=self._whitelist_chars,
                        max_codepoint=max_codepoint,
                    )
                )
            if self._blacklist_chars:
                strategies.append(
                    hs.sampled_from(
                        list(self._blacklist_chars - self._whitelist_chars)
                    )
                )
        else:
            if self._categories or self._blacklist_chars:
                strategies.append(
                    hs.characters(
                        whitelist_categories=self._categories,
                        blacklist_characters=self._blacklist_chars,
                        max_codepoint=max_codepoint,
                    )
                )
            if self._whitelist_chars:
                strategies.append(
                    hs.sampled_from(
                        list(self._whitelist_chars - self._blacklist_chars)
                    )
                )

        return hs.one_of(*strategies) if strategies else hs.just(u'')

def slice_node(draw):
    lower = draw(hs.one_of(const_node(hs.integers()), hs.none()))
    upper = draw(hs.one_of(const_node(hs.integers()), hs.none()))
    step = draw(hs.one_of(const_node(hs.integers()), hs.none()))
    node = astroid.Slice()
    node.postinit(lower, upper, step)
    return node

def unaryop_node(draw, op=hs.one_of(non_bool_unary_op, unary_bool_operator),
                 operand=const_node()):
    op = draw(op)
    operand = draw(operand)
    node = astroid.UnaryOp(op)
    node.postinit(operand)
    return node