Upload backend/venv/lib/python3.10/site-packages/mypy_extensions.py with huggingface_hub

backend/venv/lib/python3.10/site-packages/mypy_extensions.py

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+"""Defines experimental extensions to the standard "typing" module that are
+supported by the mypy typechecker.
+
+Example usage:
+    from mypy_extensions import TypedDict
+"""
+
+from typing import Any, Dict
+
+import sys
+# _type_check is NOT a part of public typing API, it is used here only to mimic
+# the (convenient) behavior of types provided by typing module.
+from typing import _type_check  # type: ignore
+
+
+def _check_fails(cls, other):
+    try:
+        if sys._getframe(1).f_globals['__name__'] not in ['abc', 'functools', 'typing']:
+            # Typed dicts are only for static structural subtyping.
+            raise TypeError('TypedDict does not support instance and class checks')
+    except (AttributeError, ValueError):
+        pass
+    return False
+
+
+def _dict_new(cls, *args, **kwargs):
+    return dict(*args, **kwargs)
+
+
+def _typeddict_new(cls, _typename, _fields=None, **kwargs):
+    total = kwargs.pop('total', True)
+    if _fields is None:
+        _fields = kwargs
+    elif kwargs:
+        raise TypeError("TypedDict takes either a dict or keyword arguments,"
+                        " but not both")
+
+    ns = {'__annotations__': dict(_fields), '__total__': total}
+    try:
+        # Setting correct module is necessary to make typed dict classes pickleable.
+        ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
+    except (AttributeError, ValueError):
+        pass
+
+    return _TypedDictMeta(_typename, (), ns, _from_functional_call=True)
+
+
+class _TypedDictMeta(type):
+    def __new__(cls, name, bases, ns, total=True, _from_functional_call=False):
+        # Create new typed dict class object.
+        # This method is called directly when TypedDict is subclassed,
+        # or via _typeddict_new when TypedDict is instantiated. This way
+        # TypedDict supports all three syntaxes described in its docstring.
+        # Subclasses and instances of TypedDict return actual dictionaries
+        # via _dict_new.
+
+        # We need the `if TypedDict in globals()` check,
+        # or we emit a DeprecationWarning when creating mypy_extensions.TypedDict itself
+        if 'TypedDict' in globals():
+            import warnings
+            warnings.warn(
+                (
+                    "mypy_extensions.TypedDict is deprecated, "
+                    "and will be removed in a future version. "
+                    "Use typing.TypedDict or typing_extensions.TypedDict instead."
+                ),
+                DeprecationWarning,
+                stacklevel=(3 if _from_functional_call else 2)
+            )
+
+        ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new
+        tp_dict = super(_TypedDictMeta, cls).__new__(cls, name, (dict,), ns)
+
+        anns = ns.get('__annotations__', {})
+        msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
+        anns = {n: _type_check(tp, msg) for n, tp in anns.items()}
+        for base in bases:
+            anns.update(base.__dict__.get('__annotations__', {}))
+        tp_dict.__annotations__ = anns
+        if not hasattr(tp_dict, '__total__'):
+            tp_dict.__total__ = total
+        return tp_dict
+
+    __instancecheck__ = __subclasscheck__ = _check_fails
+
+
+TypedDict = _TypedDictMeta('TypedDict', (dict,), {})
+TypedDict.__module__ = __name__
+TypedDict.__doc__ = \
+    """A simple typed name space. At runtime it is equivalent to a plain dict.
+
+    TypedDict creates a dictionary type that expects all of its
+    instances to have a certain set of keys, with each key
+    associated with a value of a consistent type. This expectation
+    is not checked at runtime but is only enforced by typecheckers.
+    Usage::
+
+        Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
+        a: Point2D = {'x': 1, 'y': 2, 'label': 'good'}  # OK
+        b: Point2D = {'z': 3, 'label': 'bad'}           # Fails type check
+        assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
+
+    The type info could be accessed via Point2D.__annotations__. TypedDict
+    supports two additional equivalent forms::
+
+        Point2D = TypedDict('Point2D', x=int, y=int, label=str)
+
+        class Point2D(TypedDict):
+            x: int
+            y: int
+            label: str
+
+    The latter syntax is only supported in Python 3.6+, while two other
+    syntax forms work for 3.2+
+    """
+
+# Argument constructors for making more-detailed Callables. These all just
+# return their type argument, to make them complete noops in terms of the
+# `typing` module.
+
+
+def Arg(type=Any, name=None):
+    """A normal positional argument"""
+    return type
+
+
+def DefaultArg(type=Any, name=None):
+    """A positional argument with a default value"""
+    return type
+
+
+def NamedArg(type=Any, name=None):
+    """A keyword-only argument"""
+    return type
+
+
+def DefaultNamedArg(type=Any, name=None):
+    """A keyword-only argument with a default value"""
+    return type
+
+
+def VarArg(type=Any):
+    """A *args-style variadic positional argument"""
+    return type
+
+
+def KwArg(type=Any):
+    """A **kwargs-style variadic keyword argument"""
+    return type
+
+
+# Return type that indicates a function does not return
+# Deprecated, use typing or typing_extensions variants instead
+class _DEPRECATED_NoReturn: pass
+
+
+def trait(cls):
+    return cls
+
+
+def mypyc_attr(*attrs, **kwattrs):
+    return lambda x: x
+
+
+# TODO: We may want to try to properly apply this to any type
+# variables left over...
+class _FlexibleAliasClsApplied:
+    def __init__(self, val):
+        self.val = val
+
+    def __getitem__(self, args):
+        return self.val
+
+
+class _FlexibleAliasCls:
+    def __getitem__(self, args):
+        return _FlexibleAliasClsApplied(args[-1])
+
+
+FlexibleAlias = _FlexibleAliasCls()
+
+
+class _NativeIntMeta(type):
+    def __instancecheck__(cls, inst):
+        return isinstance(inst, int)
+
+
+_sentinel = object()
+
+
+class i64(metaclass=_NativeIntMeta):
+    def __new__(cls, x=0, base=_sentinel):
+        if base is not _sentinel:
+            return int(x, base)
+        return int(x)
+
+
+class i32(metaclass=_NativeIntMeta):
+    def __new__(cls, x=0, base=_sentinel):
+        if base is not _sentinel:
+            return int(x, base)
+        return int(x)
+
+
+class i16(metaclass=_NativeIntMeta):
+    def __new__(cls, x=0, base=_sentinel):
+        if base is not _sentinel:
+            return int(x, base)
+        return int(x)
+
+
+class u8(metaclass=_NativeIntMeta):
+    def __new__(cls, x=0, base=_sentinel):
+        if base is not _sentinel:
+            return int(x, base)
+        return int(x)
+
+
+for _int_type in i64, i32, i16, u8:
+    _int_type.__doc__ = \
+        """A native fixed-width integer type when used with mypyc.
+
+        In code not compiled with mypyc, behaves like the 'int' type in these
+        runtime contexts:
+
+        * {name}(x[, base=n]) converts a number or string to 'int'
+        * isinstance(x, {name}) is the same as isinstance(x, int)
+        """.format(name=_int_type.__name__)
+del _int_type
+
+
+def _warn_deprecation(name: str, module_globals: Dict[str, Any]) -> Any:
+    if (val := module_globals.get(f"_DEPRECATED_{name}")) is None:
+        msg = f"module '{__name__}' has no attribute '{name}'"
+        raise AttributeError(msg)
+    module_globals[name] = val
+    if name in {"NoReturn"}:
+        msg = (
+            f"'mypy_extensions.{name}' is deprecated, "
+            "and will be removed in a future version. "
+            f"Use 'typing.{name}' or 'typing_extensions.{name}' instead"
+        )
+    else:
+        assert False, f"Add deprecation message for 'mypy_extensions.{name}'"
+    import warnings
+    warnings.warn(msg, DeprecationWarning, stacklevel=3)
+    return val
+
+
+def __getattr__(name: str) -> Any:
+    return _warn_deprecation(name, module_globals=globals())