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Update cherrypy==18.9.0
This commit is contained in:
parent
2fc618c01f
commit
51196a7fb1
137 changed files with 44442 additions and 11582 deletions
396
lib/annotated_types/__init__.py
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396
lib/annotated_types/__init__.py
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import math
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import sys
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from dataclasses import dataclass
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from datetime import timezone
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from typing import TYPE_CHECKING, Any, Callable, Iterator, Optional, SupportsFloat, SupportsIndex, TypeVar, Union
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if sys.version_info < (3, 8):
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from typing_extensions import Protocol, runtime_checkable
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else:
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from typing import Protocol, runtime_checkable
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if sys.version_info < (3, 9):
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from typing_extensions import Annotated, Literal
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else:
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from typing import Annotated, Literal
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if sys.version_info < (3, 10):
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EllipsisType = type(Ellipsis)
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KW_ONLY = {}
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SLOTS = {}
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else:
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from types import EllipsisType
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KW_ONLY = {"kw_only": True}
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SLOTS = {"slots": True}
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__all__ = (
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'BaseMetadata',
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'GroupedMetadata',
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'Gt',
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'Ge',
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'Lt',
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'Le',
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'Interval',
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'MultipleOf',
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'MinLen',
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'MaxLen',
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'Len',
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'Timezone',
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'Predicate',
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'LowerCase',
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'UpperCase',
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'IsDigits',
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'IsFinite',
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'IsNotFinite',
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'IsNan',
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'IsNotNan',
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'IsInfinite',
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'IsNotInfinite',
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'doc',
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'DocInfo',
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'__version__',
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)
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__version__ = '0.6.0'
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T = TypeVar('T')
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# arguments that start with __ are considered
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# positional only
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# see https://peps.python.org/pep-0484/#positional-only-arguments
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class SupportsGt(Protocol):
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def __gt__(self: T, __other: T) -> bool:
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...
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class SupportsGe(Protocol):
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def __ge__(self: T, __other: T) -> bool:
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...
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class SupportsLt(Protocol):
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def __lt__(self: T, __other: T) -> bool:
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...
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class SupportsLe(Protocol):
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def __le__(self: T, __other: T) -> bool:
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...
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class SupportsMod(Protocol):
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def __mod__(self: T, __other: T) -> T:
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...
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class SupportsDiv(Protocol):
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def __div__(self: T, __other: T) -> T:
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...
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class BaseMetadata:
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"""Base class for all metadata.
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This exists mainly so that implementers
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can do `isinstance(..., BaseMetadata)` while traversing field annotations.
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"""
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__slots__ = ()
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@dataclass(frozen=True, **SLOTS)
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class Gt(BaseMetadata):
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"""Gt(gt=x) implies that the value must be greater than x.
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It can be used with any type that supports the ``>`` operator,
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including numbers, dates and times, strings, sets, and so on.
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"""
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gt: SupportsGt
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@dataclass(frozen=True, **SLOTS)
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class Ge(BaseMetadata):
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"""Ge(ge=x) implies that the value must be greater than or equal to x.
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It can be used with any type that supports the ``>=`` operator,
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including numbers, dates and times, strings, sets, and so on.
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"""
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ge: SupportsGe
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@dataclass(frozen=True, **SLOTS)
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class Lt(BaseMetadata):
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"""Lt(lt=x) implies that the value must be less than x.
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It can be used with any type that supports the ``<`` operator,
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including numbers, dates and times, strings, sets, and so on.
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"""
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lt: SupportsLt
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@dataclass(frozen=True, **SLOTS)
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class Le(BaseMetadata):
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"""Le(le=x) implies that the value must be less than or equal to x.
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It can be used with any type that supports the ``<=`` operator,
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including numbers, dates and times, strings, sets, and so on.
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"""
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le: SupportsLe
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@runtime_checkable
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class GroupedMetadata(Protocol):
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"""A grouping of multiple BaseMetadata objects.
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`GroupedMetadata` on its own is not metadata and has no meaning.
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All it the the constraint and metadata should be fully expressable
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in terms of the `BaseMetadata`'s returned by `GroupedMetadata.__iter__()`.
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Concrete implementations should override `GroupedMetadata.__iter__()`
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to add their own metadata.
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For example:
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>>> @dataclass
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>>> class Field(GroupedMetadata):
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>>> gt: float | None = None
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>>> description: str | None = None
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...
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>>> def __iter__(self) -> Iterable[BaseMetadata]:
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>>> if self.gt is not None:
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>>> yield Gt(self.gt)
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>>> if self.description is not None:
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>>> yield Description(self.gt)
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Also see the implementation of `Interval` below for an example.
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Parsers should recognize this and unpack it so that it can be used
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both with and without unpacking:
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- `Annotated[int, Field(...)]` (parser must unpack Field)
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- `Annotated[int, *Field(...)]` (PEP-646)
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""" # noqa: trailing-whitespace
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@property
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def __is_annotated_types_grouped_metadata__(self) -> Literal[True]:
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return True
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def __iter__(self) -> Iterator[BaseMetadata]:
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...
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if not TYPE_CHECKING:
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__slots__ = () # allow subclasses to use slots
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def __init_subclass__(cls, *args: Any, **kwargs: Any) -> None:
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# Basic ABC like functionality without the complexity of an ABC
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super().__init_subclass__(*args, **kwargs)
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if cls.__iter__ is GroupedMetadata.__iter__:
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raise TypeError("Can't subclass GroupedMetadata without implementing __iter__")
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def __iter__(self) -> Iterator[BaseMetadata]: # noqa: F811
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raise NotImplementedError # more helpful than "None has no attribute..." type errors
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@dataclass(frozen=True, **KW_ONLY, **SLOTS)
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class Interval(GroupedMetadata):
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"""Interval can express inclusive or exclusive bounds with a single object.
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It accepts keyword arguments ``gt``, ``ge``, ``lt``, and/or ``le``, which
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are interpreted the same way as the single-bound constraints.
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"""
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gt: Union[SupportsGt, None] = None
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ge: Union[SupportsGe, None] = None
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lt: Union[SupportsLt, None] = None
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le: Union[SupportsLe, None] = None
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def __iter__(self) -> Iterator[BaseMetadata]:
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"""Unpack an Interval into zero or more single-bounds."""
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if self.gt is not None:
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yield Gt(self.gt)
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if self.ge is not None:
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yield Ge(self.ge)
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if self.lt is not None:
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yield Lt(self.lt)
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if self.le is not None:
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yield Le(self.le)
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@dataclass(frozen=True, **SLOTS)
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class MultipleOf(BaseMetadata):
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"""MultipleOf(multiple_of=x) might be interpreted in two ways:
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1. Python semantics, implying ``value % multiple_of == 0``, or
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2. JSONschema semantics, where ``int(value / multiple_of) == value / multiple_of``
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We encourage users to be aware of these two common interpretations,
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and libraries to carefully document which they implement.
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"""
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multiple_of: Union[SupportsDiv, SupportsMod]
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@dataclass(frozen=True, **SLOTS)
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class MinLen(BaseMetadata):
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"""
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MinLen() implies minimum inclusive length,
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e.g. ``len(value) >= min_length``.
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"""
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min_length: Annotated[int, Ge(0)]
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@dataclass(frozen=True, **SLOTS)
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class MaxLen(BaseMetadata):
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"""
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MaxLen() implies maximum inclusive length,
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e.g. ``len(value) <= max_length``.
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"""
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max_length: Annotated[int, Ge(0)]
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@dataclass(frozen=True, **SLOTS)
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class Len(GroupedMetadata):
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"""
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Len() implies that ``min_length <= len(value) <= max_length``.
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Upper bound may be omitted or ``None`` to indicate no upper length bound.
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"""
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min_length: Annotated[int, Ge(0)] = 0
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max_length: Optional[Annotated[int, Ge(0)]] = None
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def __iter__(self) -> Iterator[BaseMetadata]:
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"""Unpack a Len into zone or more single-bounds."""
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if self.min_length > 0:
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yield MinLen(self.min_length)
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if self.max_length is not None:
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yield MaxLen(self.max_length)
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@dataclass(frozen=True, **SLOTS)
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class Timezone(BaseMetadata):
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"""Timezone(tz=...) requires a datetime to be aware (or ``tz=None``, naive).
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``Annotated[datetime, Timezone(None)]`` must be a naive datetime.
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``Timezone[...]`` (the ellipsis literal) expresses that the datetime must be
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tz-aware but any timezone is allowed.
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You may also pass a specific timezone string or timezone object such as
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``Timezone(timezone.utc)`` or ``Timezone("Africa/Abidjan")`` to express that
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you only allow a specific timezone, though we note that this is often
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a symptom of poor design.
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"""
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tz: Union[str, timezone, EllipsisType, None]
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@dataclass(frozen=True, **SLOTS)
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class Predicate(BaseMetadata):
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"""``Predicate(func: Callable)`` implies `func(value)` is truthy for valid values.
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Users should prefer statically inspectable metadata, but if you need the full
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power and flexibility of arbitrary runtime predicates... here it is.
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We provide a few predefined predicates for common string constraints:
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``IsLower = Predicate(str.islower)``, ``IsUpper = Predicate(str.isupper)``, and
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``IsDigit = Predicate(str.isdigit)``. Users are encouraged to use methods which
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can be given special handling, and avoid indirection like ``lambda s: s.lower()``.
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Some libraries might have special logic to handle certain predicates, e.g. by
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checking for `str.isdigit` and using its presence to both call custom logic to
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enforce digit-only strings, and customise some generated external schema.
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We do not specify what behaviour should be expected for predicates that raise
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an exception. For example `Annotated[int, Predicate(str.isdigit)]` might silently
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skip invalid constraints, or statically raise an error; or it might try calling it
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and then propogate or discard the resulting exception.
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"""
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func: Callable[[Any], bool]
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@dataclass
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class Not:
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func: Callable[[Any], bool]
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def __call__(self, __v: Any) -> bool:
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return not self.func(__v)
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_StrType = TypeVar("_StrType", bound=str)
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LowerCase = Annotated[_StrType, Predicate(str.islower)]
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"""
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Return True if the string is a lowercase string, False otherwise.
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A string is lowercase if all cased characters in the string are lowercase and there is at least one cased character in the string.
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""" # noqa: E501
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UpperCase = Annotated[_StrType, Predicate(str.isupper)]
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"""
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Return True if the string is an uppercase string, False otherwise.
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A string is uppercase if all cased characters in the string are uppercase and there is at least one cased character in the string.
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""" # noqa: E501
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IsDigits = Annotated[_StrType, Predicate(str.isdigit)]
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"""
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Return True if the string is a digit string, False otherwise.
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A string is a digit string if all characters in the string are digits and there is at least one character in the string.
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""" # noqa: E501
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IsAscii = Annotated[_StrType, Predicate(str.isascii)]
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"""
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Return True if all characters in the string are ASCII, False otherwise.
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ASCII characters have code points in the range U+0000-U+007F. Empty string is ASCII too.
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"""
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_NumericType = TypeVar('_NumericType', bound=Union[SupportsFloat, SupportsIndex])
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IsFinite = Annotated[_NumericType, Predicate(math.isfinite)]
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"""Return True if x is neither an infinity nor a NaN, and False otherwise."""
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IsNotFinite = Annotated[_NumericType, Predicate(Not(math.isfinite))]
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"""Return True if x is one of infinity or NaN, and False otherwise"""
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IsNan = Annotated[_NumericType, Predicate(math.isnan)]
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"""Return True if x is a NaN (not a number), and False otherwise."""
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IsNotNan = Annotated[_NumericType, Predicate(Not(math.isnan))]
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"""Return True if x is anything but NaN (not a number), and False otherwise."""
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IsInfinite = Annotated[_NumericType, Predicate(math.isinf)]
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"""Return True if x is a positive or negative infinity, and False otherwise."""
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IsNotInfinite = Annotated[_NumericType, Predicate(Not(math.isinf))]
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"""Return True if x is neither a positive or negative infinity, and False otherwise."""
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try:
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from typing_extensions import DocInfo, doc # type: ignore [attr-defined]
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except ImportError:
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@dataclass(frozen=True, **SLOTS)
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class DocInfo: # type: ignore [no-redef]
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""" "
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The return value of doc(), mainly to be used by tools that want to extract the
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Annotated documentation at runtime.
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"""
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documentation: str
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"""The documentation string passed to doc()."""
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def doc(
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documentation: str,
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) -> DocInfo:
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"""
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Add documentation to a type annotation inside of Annotated.
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For example:
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>>> def hi(name: Annotated[int, doc("The name of the user")]) -> None: ...
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"""
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return DocInfo(documentation)
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0
lib/annotated_types/py.typed
Normal file
0
lib/annotated_types/py.typed
Normal file
147
lib/annotated_types/test_cases.py
Normal file
147
lib/annotated_types/test_cases.py
Normal file
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import math
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import sys
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from datetime import date, datetime, timedelta, timezone
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from decimal import Decimal
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from typing import Any, Dict, Iterable, Iterator, List, NamedTuple, Set, Tuple
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if sys.version_info < (3, 9):
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from typing_extensions import Annotated
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else:
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from typing import Annotated
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import annotated_types as at
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class Case(NamedTuple):
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"""
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A test case for `annotated_types`.
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"""
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annotation: Any
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valid_cases: Iterable[Any]
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invalid_cases: Iterable[Any]
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def cases() -> Iterable[Case]:
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# Gt, Ge, Lt, Le
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yield Case(Annotated[int, at.Gt(4)], (5, 6, 1000), (4, 0, -1))
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yield Case(Annotated[float, at.Gt(0.5)], (0.6, 0.7, 0.8, 0.9), (0.5, 0.0, -0.1))
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yield Case(
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Annotated[datetime, at.Gt(datetime(2000, 1, 1))],
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[datetime(2000, 1, 2), datetime(2000, 1, 3)],
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[datetime(2000, 1, 1), datetime(1999, 12, 31)],
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||||
)
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yield Case(
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Annotated[datetime, at.Gt(date(2000, 1, 1))],
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[date(2000, 1, 2), date(2000, 1, 3)],
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[date(2000, 1, 1), date(1999, 12, 31)],
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)
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yield Case(
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Annotated[datetime, at.Gt(Decimal('1.123'))],
|
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[Decimal('1.1231'), Decimal('123')],
|
||||
[Decimal('1.123'), Decimal('0')],
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||||
)
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||||
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yield Case(Annotated[int, at.Ge(4)], (4, 5, 6, 1000, 4), (0, -1))
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yield Case(Annotated[float, at.Ge(0.5)], (0.5, 0.6, 0.7, 0.8, 0.9), (0.4, 0.0, -0.1))
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yield Case(
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Annotated[datetime, at.Ge(datetime(2000, 1, 1))],
|
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[datetime(2000, 1, 2), datetime(2000, 1, 3)],
|
||||
[datetime(1998, 1, 1), datetime(1999, 12, 31)],
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||||
)
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|
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yield Case(Annotated[int, at.Lt(4)], (0, -1), (4, 5, 6, 1000, 4))
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yield Case(Annotated[float, at.Lt(0.5)], (0.4, 0.0, -0.1), (0.5, 0.6, 0.7, 0.8, 0.9))
|
||||
yield Case(
|
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Annotated[datetime, at.Lt(datetime(2000, 1, 1))],
|
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[datetime(1999, 12, 31), datetime(1999, 12, 31)],
|
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[datetime(2000, 1, 2), datetime(2000, 1, 3)],
|
||||
)
|
||||
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yield Case(Annotated[int, at.Le(4)], (4, 0, -1), (5, 6, 1000))
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yield Case(Annotated[float, at.Le(0.5)], (0.5, 0.0, -0.1), (0.6, 0.7, 0.8, 0.9))
|
||||
yield Case(
|
||||
Annotated[datetime, at.Le(datetime(2000, 1, 1))],
|
||||
[datetime(2000, 1, 1), datetime(1999, 12, 31)],
|
||||
[datetime(2000, 1, 2), datetime(2000, 1, 3)],
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)
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||||
|
||||
# Interval
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||||
yield Case(Annotated[int, at.Interval(gt=4)], (5, 6, 1000), (4, 0, -1))
|
||||
yield Case(Annotated[int, at.Interval(gt=4, lt=10)], (5, 6), (4, 10, 1000, 0, -1))
|
||||
yield Case(Annotated[float, at.Interval(ge=0.5, le=1)], (0.5, 0.9, 1), (0.49, 1.1))
|
||||
yield Case(
|
||||
Annotated[datetime, at.Interval(gt=datetime(2000, 1, 1), le=datetime(2000, 1, 3))],
|
||||
[datetime(2000, 1, 2), datetime(2000, 1, 3)],
|
||||
[datetime(2000, 1, 1), datetime(2000, 1, 4)],
|
||||
)
|
||||
|
||||
yield Case(Annotated[int, at.MultipleOf(multiple_of=3)], (0, 3, 9), (1, 2, 4))
|
||||
yield Case(Annotated[float, at.MultipleOf(multiple_of=0.5)], (0, 0.5, 1, 1.5), (0.4, 1.1))
|
||||
|
||||
# lengths
|
||||
|
||||
yield Case(Annotated[str, at.MinLen(3)], ('123', '1234', 'x' * 10), ('', '1', '12'))
|
||||
yield Case(Annotated[str, at.Len(3)], ('123', '1234', 'x' * 10), ('', '1', '12'))
|
||||
yield Case(Annotated[List[int], at.MinLen(3)], ([1, 2, 3], [1, 2, 3, 4], [1] * 10), ([], [1], [1, 2]))
|
||||
yield Case(Annotated[List[int], at.Len(3)], ([1, 2, 3], [1, 2, 3, 4], [1] * 10), ([], [1], [1, 2]))
|
||||
|
||||
yield Case(Annotated[str, at.MaxLen(4)], ('', '1234'), ('12345', 'x' * 10))
|
||||
yield Case(Annotated[str, at.Len(0, 4)], ('', '1234'), ('12345', 'x' * 10))
|
||||
yield Case(Annotated[List[str], at.MaxLen(4)], ([], ['a', 'bcdef'], ['a', 'b', 'c']), (['a'] * 5, ['b'] * 10))
|
||||
yield Case(Annotated[List[str], at.Len(0, 4)], ([], ['a', 'bcdef'], ['a', 'b', 'c']), (['a'] * 5, ['b'] * 10))
|
||||
|
||||
yield Case(Annotated[str, at.Len(3, 5)], ('123', '12345'), ('', '1', '12', '123456', 'x' * 10))
|
||||
yield Case(Annotated[str, at.Len(3, 3)], ('123',), ('12', '1234'))
|
||||
|
||||
yield Case(Annotated[Dict[int, int], at.Len(2, 3)], [{1: 1, 2: 2}], [{}, {1: 1}, {1: 1, 2: 2, 3: 3, 4: 4}])
|
||||
yield Case(Annotated[Set[int], at.Len(2, 3)], ({1, 2}, {1, 2, 3}), (set(), {1}, {1, 2, 3, 4}))
|
||||
yield Case(Annotated[Tuple[int, ...], at.Len(2, 3)], ((1, 2), (1, 2, 3)), ((), (1,), (1, 2, 3, 4)))
|
||||
|
||||
# Timezone
|
||||
|
||||
yield Case(
|
||||
Annotated[datetime, at.Timezone(None)], [datetime(2000, 1, 1)], [datetime(2000, 1, 1, tzinfo=timezone.utc)]
|
||||
)
|
||||
yield Case(
|
||||
Annotated[datetime, at.Timezone(...)], [datetime(2000, 1, 1, tzinfo=timezone.utc)], [datetime(2000, 1, 1)]
|
||||
)
|
||||
yield Case(
|
||||
Annotated[datetime, at.Timezone(timezone.utc)],
|
||||
[datetime(2000, 1, 1, tzinfo=timezone.utc)],
|
||||
[datetime(2000, 1, 1), datetime(2000, 1, 1, tzinfo=timezone(timedelta(hours=6)))],
|
||||
)
|
||||
yield Case(
|
||||
Annotated[datetime, at.Timezone('Europe/London')],
|
||||
[datetime(2000, 1, 1, tzinfo=timezone(timedelta(0), name='Europe/London'))],
|
||||
[datetime(2000, 1, 1), datetime(2000, 1, 1, tzinfo=timezone(timedelta(hours=6)))],
|
||||
)
|
||||
|
||||
# predicate types
|
||||
|
||||
yield Case(at.LowerCase[str], ['abc', 'foobar'], ['', 'A', 'Boom'])
|
||||
yield Case(at.UpperCase[str], ['ABC', 'DEFO'], ['', 'a', 'abc', 'AbC'])
|
||||
yield Case(at.IsDigits[str], ['123'], ['', 'ab', 'a1b2'])
|
||||
yield Case(at.IsAscii[str], ['123', 'foo bar'], ['£100', '😊', 'whatever 👀'])
|
||||
|
||||
yield Case(Annotated[int, at.Predicate(lambda x: x % 2 == 0)], [0, 2, 4], [1, 3, 5])
|
||||
|
||||
yield Case(at.IsFinite[float], [1.23], [math.nan, math.inf, -math.inf])
|
||||
yield Case(at.IsNotFinite[float], [math.nan, math.inf], [1.23])
|
||||
yield Case(at.IsNan[float], [math.nan], [1.23, math.inf])
|
||||
yield Case(at.IsNotNan[float], [1.23, math.inf], [math.nan])
|
||||
yield Case(at.IsInfinite[float], [math.inf], [math.nan, 1.23])
|
||||
yield Case(at.IsNotInfinite[float], [math.nan, 1.23], [math.inf])
|
||||
|
||||
# check stacked predicates
|
||||
yield Case(at.IsInfinite[Annotated[float, at.Predicate(lambda x: x > 0)]], [math.inf], [-math.inf, 1.23, math.nan])
|
||||
|
||||
# doc
|
||||
yield Case(Annotated[int, at.doc("A number")], [1, 2], [])
|
||||
|
||||
# custom GroupedMetadata
|
||||
class MyCustomGroupedMetadata(at.GroupedMetadata):
|
||||
def __iter__(self) -> Iterator[at.Predicate]:
|
||||
yield at.Predicate(lambda x: float(x).is_integer())
|
||||
|
||||
yield Case(Annotated[float, MyCustomGroupedMetadata()], [0, 2.0], [0.01, 1.5])
|
Loading…
Add table
Add a link
Reference in a new issue