Python hypothesis.strategies.none() Examples

def from_schema(schema):
    """Returns a strategy for objects that match the given schema."""
    check_schema(schema)
    # TODO: actually handle constraints on number/string/array schemas
    return dict(
        null=st.none(),
        bool=st.booleans(),
        number=st.floats(allow_nan=False),
        string=st.text(),
        array=st.lists(st.nothing()),
    )[schema["type"]]


# `@st.composite` is one way to write this - another would be to define a
# bare function, and `return st.one_of(st.none(), st.booleans(), ...)` so
# each strategy can be defined individually.  Use whichever seems more
# natural to you - the important thing in tests is usually readability! 

def chromeResponseReceived (reqid, url):
    mimeTypeSt = st.one_of (st.none (), st.just ('text/html'))
    remoteIpAddressSt = st.one_of (st.none (), st.just ('127.0.0.1'))
    protocolSt = st.one_of (st.none (), st.just ('h2'))
    statusCodeSt = st.integers (min_value=100, max_value=999)
    typeSt = st.sampled_from (['Document', 'Stylesheet', 'Image', 'Media',
            'Font', 'Script', 'TextTrack', 'XHR', 'Fetch', 'EventSource',
            'WebSocket', 'Manifest', 'SignedExchange', 'Ping',
            'CSPViolationReport', 'Other'])
    return st.fixed_dictionaries ({
            'requestId': reqid,
            'timestamp': timestamp,
            'type': typeSt,
            'response': st.fixed_dictionaries ({
                'url': url,
                'requestHeaders': chromeHeaders (), # XXX: make this optional
                'headers': chromeHeaders (),
                'status': statusCodeSt,
                'statusText': asciiText,
                'mimeType': mimeTypeSt,
                'remoteIPAddress': remoteIpAddressSt,
                'protocol': protocolSt,
                })
            }) 

def requestResponsePair ():
    def f (creq, cresp, hasPostData, reqBody, respBody):
        i = RequestResponsePair ()
        i.fromRequestWillBeSent (creq)
        i.request.hasPostData = hasPostData
        if hasPostData:
            i.request.body = reqBody

        if cresp is not None:
            i.fromResponseReceived (cresp)
            if respBody is not None:
                i.response.body = respBody
        return i

    bodySt = st.one_of (
            st.none (),
            st.builds (UnicodeBody, st.text ()),
            st.builds (Base64Body.fromBytes, st.binary ())
            )
    return st.builds (lambda reqresp, hasPostData, reqBody, respBody:
            f (reqresp[0], reqresp[1], hasPostData, reqBody, respBody),
            chromeReqResp (), st.booleans (), bodySt, bodySt) 

def gen_string(draw: Any) -> Dict[str, Union[str, int]]:
    """Draw a string schema."""
    min_size = draw(st.none() | st.integers(0, 10))
    max_size = draw(st.none() | st.integers(0, 1000))
    if min_size is not None and max_size is not None and min_size > max_size:
        min_size, max_size = max_size, min_size
    pattern = draw(st.none() | REGEX_PATTERNS)
    format_ = draw(st.none() | st.sampled_from(sorted(STRING_FORMATS)))
    out: Dict[str, Union[str, int]] = {"type": "string"}
    if pattern is not None:
        out["pattern"] = pattern
    elif format_ is not None:
        out["format"] = format_
    if min_size is not None:
        out["minLength"] = min_size
    if max_size is not None:
        out["maxLength"] = max_size
    return out 

def gen_roll_args(draw, arr):
    shift = draw(st.integers() | st.tuples(*(st.integers() for i in arr.shape)))

    if arr.ndim:
        ax_strat = hnp.valid_tuple_axes(
            arr.ndim,
            **(
                dict(min_size=len(shift), max_size=len(shift))
                if isinstance(shift, tuple)
                else {}
            )
        )
        axis = draw(st.none() | st.integers(-arr.ndim, arr.ndim - 1) | ax_strat)
    else:
        axis = None
    return dict(shift=shift, axis=axis) 

def gen_tuple_repeat_args(draw: st.DataObject.draw, arr: Tensor):

    valid_axis = draw(
        st.none() | (st.integers(-arr.ndim, arr.ndim - 1) if arr.ndim else st.just(0))
    )

    num_repeats = (
        arr.shape[valid_axis] if valid_axis is not None and arr.ndim else arr.size
    )
    repeats = draw(st.tuples(*[st.integers(0, 5)] * num_repeats))
    return dict(repeats=repeats, axis=valid_axis,) 

def gen_array(draw: Any) -> Schema:
    """Draw an array schema."""
    min_size = draw(st.none() | st.integers(0, 5))
    max_size = draw(st.none() | st.integers(2, 5))
    if min_size is not None and max_size is not None and min_size > max_size:
        min_size, max_size = max_size, min_size
    items = draw(
        st.builds(dict)
        | _json_schemata(recur=False)
        | st.lists(_json_schemata(recur=False), min_size=1, max_size=10)
    )
    out = {"type": "array", "items": items}
    if isinstance(items, list):
        increment = len(items)
        additional = draw(st.none() | _json_schemata(recur=False))
        if additional is not None:
            out["additionalItems"] = additional
        elif draw(st.booleans()):
            out["contains"] = draw(_json_schemata(recur=False).filter(bool))
            increment += 1
        if min_size is not None:
            min_size += increment
        if max_size is not None:
            max_size += increment
    else:
        if draw(st.booleans()):
            out["uniqueItems"] = True
        if items == {}:
            out["contains"] = draw(_json_schemata(recur=False))
    if min_size is not None:
        out["minItems"] = min_size
    if max_size is not None:
        out["maxItems"] = max_size
    return out 

def gen_number(draw: Any, kind: str) -> Dict[str, Union[str, float]]:
    """Draw a numeric schema."""
    max_int_float = 2 ** 53
    lower = draw(st.none() | st.integers(-max_int_float, max_int_float))
    upper = draw(st.none() | st.integers(-max_int_float, max_int_float))
    if lower is not None and upper is not None and lower > upper:
        lower, upper = upper, lower
    multiple_of = draw(
        st.none() | st.integers(2, 100) | st.floats(1 / 1024, 100, exclude_min=True)
    )
    assume(None in (multiple_of, lower, upper) or multiple_of <= (upper - lower))
    assert kind in ("integer", "number")
    out: Dict[str, Union[str, float]] = {"type": kind}
    # Generate the latest draft supported by jsonschema.
    assert hasattr(jsonschema, "Draft7Validator")
    if lower is not None:
        if draw(st.booleans(), label="exclusiveMinimum"):
            out["exclusiveMinimum"] = lower - 1
        else:
            out["minimum"] = lower
    if upper is not None:
        if draw(st.booleans(), label="exclusiveMaximum"):
            out["exclusiveMaximum"] = upper + 1
        else:
            out["maximum"] = upper
    if multiple_of is not None:
        out["multipleOf"] = multiple_of
    return out 

def optional_attrs(draw, defaults=None):
    """
    Generate a tuple of an attribute and a strategy that yields values
    for that attribute. The strategy generates optional integers.
    """
    default = NOTHING
    val_strat = st.integers() | st.none()
    if defaults is True or (defaults is None and draw(st.booleans())):
        default = draw(val_strat)

    return (attr.ib(default=default), val_strat) 

def json(value_limit=5):
    """Hypothesis strategy for generating values that can be passed to
    `json.dumps` to produce valid JSON data.

    :param value_limit: A limit on the number of values in the JSON data -
                        setting this too high can cause value generation to
                        time out.
    :type value_limit: int
    """
    return hy_st.recursive(
        hy_st.floats() | hy_st.booleans() | hy_st.text() | hy_st.none(),
        lambda children: hy_st.dictionaries(hy_st.text(), children),
        max_leaves=value_limit) 

def primitives():
    return (
        st.integers() |
        st.floats(allow_nan=False) |
        st.text() |
        st.binary() |
        st.datetimes(timezones=timezones() | st.none()) |
        st.dates() |
        st.times(timezones=timezones() | st.none()) |
        st.timedeltas() |
        st.booleans() |
        st.none()
    ) 

def optionals(strategy):
    return one_of(strategy, none()) 

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 gen_int_repeat_args(arr: Tensor) -> st.SearchStrategy[dict]:
    valid_axis = st.none()
    valid_axis |= st.integers(-arr.ndim, arr.ndim - 1) if arr.ndim else st.just(0)
    return st.fixed_dictionaries(
        dict(repeats=st.integers(min_value=0, max_value=5), axis=valid_axis,)
    ) 

def test_sliding_window(data, x):
    """ Test variations of window-shape, step, and dilation for sliding window
        view of N-dimensional array."""

    win_dim = data.draw(st.integers(1, x.ndim), label="win_dim")
    win_shape = data.draw(
        st.tuples(*(st.integers(1, s) for s in x.shape[-win_dim:])), label="win_shape"
    )
    step = data.draw(
        st.tuples(*(st.integers(1, s) for s in x.shape[-win_dim:])), label="step"
    )

    max_dilation = np.array(x.shape[-win_dim:]) // win_shape
    dilation = data.draw(
        st.one_of(
            st.none()
            | st.integers(1, min(max_dilation))
            | st.tuples(*(st.integers(1, s) for s in max_dilation))
        ),
        label="dilation",
    )
    y = sliding_window_view(x, window_shape=win_shape, step=step, dilation=dilation)

    if dilation is None:
        dilation = np.ones((len(win_shape),), dtype=int)

    if isinstance(dilation, int):
        dilation = np.full((len(win_shape),), fill_value=dilation, dtype=int)

    for ind in np.ndindex(*y.shape[:win_dim]):
        slices = tuple(
            slice(i * s, i * s + w * d, d)
            for i, w, s, d in zip(ind, win_shape, step, dilation)
        )
        assert_allclose(actual=y[tuple([*ind])], desired=x[(..., *slices)]) 

def single_axis_arg(*arrs):
    """ Wrapper for passing valid-axis (single-value only)
    search strategy to test factory"""
    if arrs[0].ndim:
        return valid_axes(arrs[0].ndim, single_axis_only=True)
    else:
        return st.none() 

def field_to_strategy(field, env):
    """Generate strategy for field."""
    if SCALAR_MAPPINGS.get(field.type) is not None:
        return apply_modifier(
            strategy=SCALAR_MAPPINGS[field.type],
            field=field
        )

    if field.type is FieldDescriptor.TYPE_ENUM:
        return apply_modifier(
            strategy=find_strategy_in_env(field.enum_type, env),
            field=field
        )

    if field.type is FieldDescriptor.TYPE_MESSAGE:
        field_options = field.message_type.GetOptions()

        if field_options.deprecated:
            return st.none()

        if field_options.map_entry:
            k, v = field.message_type.fields
            return st.dictionaries(
                field_to_strategy(k, env).filter(non_null),
                field_to_strategy(v, env).filter(non_null)
            )

        return apply_modifier(
            strategy=find_strategy_in_env(field.message_type, env),
            field=field
        )

    raise Exception("Unhandled field {}.".format(field)) 

def urls ():
    """ Build http/https URL """
    scheme = st.sampled_from (['http', 'https'])
    # Path must start with a slash
    pathSt = st.builds (lambda x: '/' + x, st.text ())
    args = st.fixed_dictionaries ({
            'scheme': scheme,
            'host': domains (),
            'port': st.one_of (st.none (), st.integers (min_value=1, max_value=2**16-1)),
            'path': pathSt,
            'query_string': st.text (),
            'fragment': st.text (),
            })
    return st.builds (lambda x: URL.build (**x), args) 

def requirements(
    draw, requirement_selection=random_requirements(), markers=random_marker_strings()
):
    req = draw(requirement_selection)
    marker_selection = draw(markers)
    name, versions, extras, hashes = req
    line = "{0}".format(name)
    if extras is not None:
        extras_choice = draw(st.one_of(st.lists(st.sampled_from(extras)), st.none()))
    else:
        extras_choice = None
    if versions:
        version_choice = draw(st.one_of(st.sampled_from(versions), st.none()))
    else:
        version_choice = None
    hashes_option = None
    if hashes:
        hashes_option = next(iter(h for v, h in hashes if v == version_choice), [])
    spec_op = ""
    extras_list = sorted(set(extras_choice)) if extras_choice is not None else []
    extras_str = "[{0}]".format(",".join(extras_list)) if extras_list else ""
    if not version_choice:
        version_str = ""
    else:
        spec_op = draw(st.sampled_from(list(Specifier._operators.keys())))
        version_str = "{0}{1}".format(spec_op, version_choice)
    line = line_without_markers = "{0}{1}{2}".format(
        line.strip(), extras_str.strip(), version_str.strip()
    )
    as_list = ["{0}".format(line)]
    list_without_markers = as_list[:]
    marker_str = ""
    if marker_selection:
        marker_str = "; {0}".format(marker_selection)
        line = "{0}{1}".format(line, marker_str)
        as_list = ["{0}".format(line)]
    if hashes_option:
        hashes_list = sorted(set(hashes_option))
        hashes_line = " ".join(["--hash={0}".format(h) for h in hashes_list])
        line = "{0} {1}".format(line, hashes_line)
        line_without_markers = "{0} {1}".format(line_without_markers, hashes_line)
        as_list.extend(hashes_list)
        list_without_markers.extend(hashes_list)
    else:
        hashes_list = None
    return NormalRequirement(
        name=name,
        specifier=spec_op,
        version=version_choice,
        extras=extras_list,
        markers=marker_selection,
        hashes=hashes_list,
        line=line,
        line_without_markers=line_without_markers,
        as_list=as_list,
        list_without_markers=list_without_markers,
    ) 

def gen_object(draw: Any) -> Schema:
    """Draw an object schema."""
    out: Schema = {"type": "object"}
    names = draw(st.sampled_from([None, None, None, draw(gen_string())]))
    name_strat = st.text() if names is None else from_schema(names)
    required = draw(
        st.just(False) | st.lists(name_strat, min_size=1, max_size=5, unique=True)
    )

    # Trying to generate schemata that are consistent would mean dealing with
    # overlapping regex and names, and that would suck.  So instead we ensure that
    # there *are* no overlapping requirements, which is much easier.
    properties = draw(st.dictionaries(name_strat, _json_schemata(recur=False)))
    disjoint = REGEX_PATTERNS.filter(
        lambda r: all(re.search(r, string=name) is None for name in properties)
    )
    patterns = draw(st.dictionaries(disjoint, _json_schemata(recur=False), max_size=1))
    additional = draw(st.none() | _json_schemata(recur=False))

    min_size = draw(st.none() | st.integers(0, 5))
    max_size = draw(st.none() | st.integers(2, 5))
    if min_size is not None and max_size is not None and min_size > max_size:
        min_size, max_size = max_size, min_size

    if names is not None:
        out["propertyNames"] = names
    if required:
        out["required"] = required
        if min_size is not None:
            min_size += len(required)
        if max_size is not None:
            max_size += len(required)
    if min_size is not None:
        out["minProperties"] = min_size
    if max_size is not None:
        out["maxProperties"] = max_size
    if properties:
        out["properties"] = properties

        props = st.sampled_from(sorted(properties))
        if draw(st.integers(0, 3)) == 3:
            out["dependencies"] = draw(
                st.dictionaries(props, st.lists(props, unique=True))
            )
        elif draw(st.integers(0, 3)) == 3:
            out["dependencies"] = draw(st.dictionaries(props, json_schemata()))
    if patterns:
        out["patternProperties"] = patterns
    if additional is not None:
        out["additionalProperties"] = additional

    return out