Library import 16 (#2433)

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1 files changed, 1579 insertions, 0 deletions

diff --git a/contrib/tools/python3/Lib/dataclasses.py b/contrib/tools/python3/Lib/dataclasses.py
new file mode 100644
index 0000000000..3eacba840d
--- /dev/null
+++ b/contrib/tools/python3/Lib/dataclasses.py
@@ -0,0 +1,1579 @@
+import re
+import sys
+import copy
+import types
+import inspect
+import keyword
+import functools
+import itertools
+import abc
+import _thread
+from types import FunctionType, GenericAlias
+
+
+__all__ = ['dataclass',
+           'field',
+           'Field',
+           'FrozenInstanceError',
+           'InitVar',
+           'KW_ONLY',
+           'MISSING',
+
+           # Helper functions.
+           'fields',
+           'asdict',
+           'astuple',
+           'make_dataclass',
+           'replace',
+           'is_dataclass',
+           ]
+
+# Conditions for adding methods.  The boxes indicate what action the
+# dataclass decorator takes.  For all of these tables, when I talk
+# about init=, repr=, eq=, order=, unsafe_hash=, or frozen=, I'm
+# referring to the arguments to the @dataclass decorator.  When
+# checking if a dunder method already exists, I mean check for an
+# entry in the class's __dict__.  I never check to see if an attribute
+# is defined in a base class.
+
+# Key:
+# +=========+=========================================+
+# + Value   | Meaning                                 |
+# +=========+=========================================+
+# | <blank> | No action: no method is added.          |
+# +---------+-----------------------------------------+
+# | add     | Generated method is added.              |
+# +---------+-----------------------------------------+
+# | raise   | TypeError is raised.                    |
+# +---------+-----------------------------------------+
+# | None    | Attribute is set to None.               |
+# +=========+=========================================+
+
+# __init__
+#
+#   +--- init= parameter
+#   |
+#   v     |       |       |
+#         |  no   |  yes  |  <--- class has __init__ in __dict__?
+# +=======+=======+=======+
+# | False |       |       |
+# +-------+-------+-------+
+# | True  | add   |       |  <- the default
+# +=======+=======+=======+
+
+# __repr__
+#
+#    +--- repr= parameter
+#    |
+#    v    |       |       |
+#         |  no   |  yes  |  <--- class has __repr__ in __dict__?
+# +=======+=======+=======+
+# | False |       |       |
+# +-------+-------+-------+
+# | True  | add   |       |  <- the default
+# +=======+=======+=======+
+
+
+# __setattr__
+# __delattr__
+#
+#    +--- frozen= parameter
+#    |
+#    v    |       |       |
+#         |  no   |  yes  |  <--- class has __setattr__ or __delattr__ in __dict__?
+# +=======+=======+=======+
+# | False |       |       |  <- the default
+# +-------+-------+-------+
+# | True  | add   | raise |
+# +=======+=======+=======+
+# Raise because not adding these methods would break the "frozen-ness"
+# of the class.
+
+# __eq__
+#
+#    +--- eq= parameter
+#    |
+#    v    |       |       |
+#         |  no   |  yes  |  <--- class has __eq__ in __dict__?
+# +=======+=======+=======+
+# | False |       |       |
+# +-------+-------+-------+
+# | True  | add   |       |  <- the default
+# +=======+=======+=======+
+
+# __lt__
+# __le__
+# __gt__
+# __ge__
+#
+#    +--- order= parameter
+#    |
+#    v    |       |       |
+#         |  no   |  yes  |  <--- class has any comparison method in __dict__?
+# +=======+=======+=======+
+# | False |       |       |  <- the default
+# +-------+-------+-------+
+# | True  | add   | raise |
+# +=======+=======+=======+
+# Raise because to allow this case would interfere with using
+# functools.total_ordering.
+
+# __hash__
+
+#    +------------------- unsafe_hash= parameter
+#    |       +----------- eq= parameter
+#    |       |       +--- frozen= parameter
+#    |       |       |
+#    v       v       v    |        |        |
+#                         |   no   |  yes   |  <--- class has explicitly defined __hash__
+# +=======+=======+=======+========+========+
+# | False | False | False |        |        | No __eq__, use the base class __hash__
+# +-------+-------+-------+--------+--------+
+# | False | False | True  |        |        | No __eq__, use the base class __hash__
+# +-------+-------+-------+--------+--------+
+# | False | True  | False | None   |        | <-- the default, not hashable
+# +-------+-------+-------+--------+--------+
+# | False | True  | True  | add    |        | Frozen, so hashable, allows override
+# +-------+-------+-------+--------+--------+
+# | True  | False | False | add    | raise  | Has no __eq__, but hashable
+# +-------+-------+-------+--------+--------+
+# | True  | False | True  | add    | raise  | Has no __eq__, but hashable
+# +-------+-------+-------+--------+--------+
+# | True  | True  | False | add    | raise  | Not frozen, but hashable
+# +-------+-------+-------+--------+--------+
+# | True  | True  | True  | add    | raise  | Frozen, so hashable
+# +=======+=======+=======+========+========+
+# For boxes that are blank, __hash__ is untouched and therefore
+# inherited from the base class.  If the base is object, then
+# id-based hashing is used.
+#
+# Note that a class may already have __hash__=None if it specified an
+# __eq__ method in the class body (not one that was created by
+# @dataclass).
+#
+# See _hash_action (below) for a coded version of this table.
+
+# __match_args__
+#
+#    +--- match_args= parameter
+#    |
+#    v    |       |       |
+#         |  no   |  yes  |  <--- class has __match_args__ in __dict__?
+# +=======+=======+=======+
+# | False |       |       |
+# +-------+-------+-------+
+# | True  | add   |       |  <- the default
+# +=======+=======+=======+
+# __match_args__ is always added unless the class already defines it. It is a
+# tuple of __init__ parameter names; non-init fields must be matched by keyword.
+
+
+# Raised when an attempt is made to modify a frozen class.
+class FrozenInstanceError(AttributeError): pass
+
+# A sentinel object for default values to signal that a default
+# factory will be used.  This is given a nice repr() which will appear
+# in the function signature of dataclasses' constructors.
+class _HAS_DEFAULT_FACTORY_CLASS:
+    def __repr__(self):
+        return '<factory>'
+_HAS_DEFAULT_FACTORY = _HAS_DEFAULT_FACTORY_CLASS()
+
+# A sentinel object to detect if a parameter is supplied or not.  Use
+# a class to give it a better repr.
+class _MISSING_TYPE:
+    pass
+MISSING = _MISSING_TYPE()
+
+# A sentinel object to indicate that following fields are keyword-only by
+# default.  Use a class to give it a better repr.
+class _KW_ONLY_TYPE:
+    pass
+KW_ONLY = _KW_ONLY_TYPE()
+
+# Since most per-field metadata will be unused, create an empty
+# read-only proxy that can be shared among all fields.
+_EMPTY_METADATA = types.MappingProxyType({})
+
+# Markers for the various kinds of fields and pseudo-fields.
+class _FIELD_BASE:
+    def __init__(self, name):
+        self.name = name
+    def __repr__(self):
+        return self.name
+_FIELD = _FIELD_BASE('_FIELD')
+_FIELD_CLASSVAR = _FIELD_BASE('_FIELD_CLASSVAR')
+_FIELD_INITVAR = _FIELD_BASE('_FIELD_INITVAR')
+
+# The name of an attribute on the class where we store the Field
+# objects.  Also used to check if a class is a Data Class.
+_FIELDS = '__dataclass_fields__'
+
+# The name of an attribute on the class that stores the parameters to
+# @dataclass.
+_PARAMS = '__dataclass_params__'
+
+# The name of the function, that if it exists, is called at the end of
+# __init__.
+_POST_INIT_NAME = '__post_init__'
+
+# String regex that string annotations for ClassVar or InitVar must match.
+# Allows "identifier.identifier[" or "identifier[".
+# https://bugs.python.org/issue33453 for details.
+_MODULE_IDENTIFIER_RE = re.compile(r'^(?:\s*(\w+)\s*\.)?\s*(\w+)')
+
+# Atomic immutable types which don't require any recursive handling and for which deepcopy
+# returns the same object. We can provide a fast-path for these types in asdict and astuple.
+_ATOMIC_TYPES = frozenset({
+    # Common JSON Serializable types
+    types.NoneType,
+    bool,
+    int,
+    float,
+    str,
+    # Other common types
+    complex,
+    bytes,
+    # Other types that are also unaffected by deepcopy
+    types.EllipsisType,
+    types.NotImplementedType,
+    types.CodeType,
+    types.BuiltinFunctionType,
+    types.FunctionType,
+    type,
+    range,
+    property,
+})
+
+# This function's logic is copied from "recursive_repr" function in
+# reprlib module to avoid dependency.
+def _recursive_repr(user_function):
+    # Decorator to make a repr function return "..." for a recursive
+    # call.
+    repr_running = set()
+
+    @functools.wraps(user_function)
+    def wrapper(self):
+        key = id(self), _thread.get_ident()
+        if key in repr_running:
+            return '...'
+        repr_running.add(key)
+        try:
+            result = user_function(self)
+        finally:
+            repr_running.discard(key)
+        return result
+    return wrapper
+
+class InitVar:
+    __slots__ = ('type', )
+
+    def __init__(self, type):
+        self.type = type
+
+    def __repr__(self):
+        if isinstance(self.type, type):
+            type_name = self.type.__name__
+        else:
+            # typing objects, e.g. List[int]
+            type_name = repr(self.type)
+        return f'dataclasses.InitVar[{type_name}]'
+
+    def __class_getitem__(cls, type):
+        return InitVar(type)
+
+# Instances of Field are only ever created from within this module,
+# and only from the field() function, although Field instances are
+# exposed externally as (conceptually) read-only objects.
+#
+# name and type are filled in after the fact, not in __init__.
+# They're not known at the time this class is instantiated, but it's
+# convenient if they're available later.
+#
+# When cls._FIELDS is filled in with a list of Field objects, the name
+# and type fields will have been populated.
+class Field:
+    __slots__ = ('name',
+                 'type',
+                 'default',
+                 'default_factory',
+                 'repr',
+                 'hash',
+                 'init',
+                 'compare',
+                 'metadata',
+                 'kw_only',
+                 '_field_type',  # Private: not to be used by user code.
+                 )
+
+    def __init__(self, default, default_factory, init, repr, hash, compare,
+                 metadata, kw_only):
+        self.name = None
+        self.type = None
+        self.default = default
+        self.default_factory = default_factory
+        self.init = init
+        self.repr = repr
+        self.hash = hash
+        self.compare = compare
+        self.metadata = (_EMPTY_METADATA
+                         if metadata is None else
+                         types.MappingProxyType(metadata))
+        self.kw_only = kw_only
+        self._field_type = None
+
+    @_recursive_repr
+    def __repr__(self):
+        return ('Field('
+                f'name={self.name!r},'
+                f'type={self.type!r},'
+                f'default={self.default!r},'
+                f'default_factory={self.default_factory!r},'
+                f'init={self.init!r},'
+                f'repr={self.repr!r},'
+                f'hash={self.hash!r},'
+                f'compare={self.compare!r},'
+                f'metadata={self.metadata!r},'
+                f'kw_only={self.kw_only!r},'
+                f'_field_type={self._field_type}'
+                ')')
+
+    # This is used to support the PEP 487 __set_name__ protocol in the
+    # case where we're using a field that contains a descriptor as a
+    # default value.  For details on __set_name__, see
+    # https://peps.python.org/pep-0487/#implementation-details.
+    #
+    # Note that in _process_class, this Field object is overwritten
+    # with the default value, so the end result is a descriptor that
+    # had __set_name__ called on it at the right time.
+    def __set_name__(self, owner, name):
+        func = getattr(type(self.default), '__set_name__', None)
+        if func:
+            # There is a __set_name__ method on the descriptor, call
+            # it.
+            func(self.default, owner, name)
+
+    __class_getitem__ = classmethod(GenericAlias)
+
+
+class _DataclassParams:
+    __slots__ = ('init',
+                 'repr',
+                 'eq',
+                 'order',
+                 'unsafe_hash',
+                 'frozen',
+                 'match_args',
+                 'kw_only',
+                 'slots',
+                 'weakref_slot',
+                 )
+
+    def __init__(self,
+                 init, repr, eq, order, unsafe_hash, frozen,
+                 match_args, kw_only, slots, weakref_slot):
+        self.init = init
+        self.repr = repr
+        self.eq = eq
+        self.order = order
+        self.unsafe_hash = unsafe_hash
+        self.frozen = frozen
+        self.match_args = match_args
+        self.kw_only = kw_only
+        self.slots = slots
+        self.weakref_slot = weakref_slot
+
+    def __repr__(self):
+        return ('_DataclassParams('
+                f'init={self.init!r},'
+                f'repr={self.repr!r},'
+                f'eq={self.eq!r},'
+                f'order={self.order!r},'
+                f'unsafe_hash={self.unsafe_hash!r},'
+                f'frozen={self.frozen!r},'
+                f'match_args={self.match_args!r},'
+                f'kw_only={self.kw_only!r},'
+                f'slots={self.slots!r},'
+                f'weakref_slot={self.weakref_slot!r}'
+                ')')
+
+
+# This function is used instead of exposing Field creation directly,
+# so that a type checker can be told (via overloads) that this is a
+# function whose type depends on its parameters.
+def field(*, default=MISSING, default_factory=MISSING, init=True, repr=True,
+          hash=None, compare=True, metadata=None, kw_only=MISSING):
+    """Return an object to identify dataclass fields.
+
+    default is the default value of the field.  default_factory is a
+    0-argument function called to initialize a field's value.  If init
+    is true, the field will be a parameter to the class's __init__()
+    function.  If repr is true, the field will be included in the
+    object's repr().  If hash is true, the field will be included in the
+    object's hash().  If compare is true, the field will be used in
+    comparison functions.  metadata, if specified, must be a mapping
+    which is stored but not otherwise examined by dataclass.  If kw_only
+    is true, the field will become a keyword-only parameter to
+    __init__().
+
+    It is an error to specify both default and default_factory.
+    """
+
+    if default is not MISSING and default_factory is not MISSING:
+        raise ValueError('cannot specify both default and default_factory')
+    return Field(default, default_factory, init, repr, hash, compare,
+                 metadata, kw_only)
+
+
+def _fields_in_init_order(fields):
+    # Returns the fields as __init__ will output them.  It returns 2 tuples:
+    # the first for normal args, and the second for keyword args.
+
+    return (tuple(f for f in fields if f.init and not f.kw_only),
+            tuple(f for f in fields if f.init and f.kw_only)
+            )
+
+
+def _tuple_str(obj_name, fields):
+    # Return a string representing each field of obj_name as a tuple
+    # member.  So, if fields is ['x', 'y'] and obj_name is "self",
+    # return "(self.x,self.y)".
+
+    # Special case for the 0-tuple.
+    if not fields:
+        return '()'
+    # Note the trailing comma, needed if this turns out to be a 1-tuple.
+    return f'({",".join([f"{obj_name}.{f.name}" for f in fields])},)'
+
+
+def _create_fn(name, args, body, *, globals=None, locals=None,
+               return_type=MISSING):
+    # Note that we may mutate locals. Callers beware!
+    # The only callers are internal to this module, so no
+    # worries about external callers.
+    if locals is None:
+        locals = {}
+    return_annotation = ''
+    if return_type is not MISSING:
+        locals['__dataclass_return_type__'] = return_type
+        return_annotation = '->__dataclass_return_type__'
+    args = ','.join(args)
+    body = '\n'.join(f'  {b}' for b in body)
+
+    # Compute the text of the entire function.
+    txt = f' def {name}({args}){return_annotation}:\n{body}'
+
+    # Free variables in exec are resolved in the global namespace.
+    # The global namespace we have is user-provided, so we can't modify it for
+    # our purposes. So we put the things we need into locals and introduce a
+    # scope to allow the function we're creating to close over them.
+    local_vars = ', '.join(locals.keys())
+    txt = f"def __create_fn__({local_vars}):\n{txt}\n return {name}"
+    ns = {}
+    exec(txt, globals, ns)
+    return ns['__create_fn__'](**locals)
+
+
+def _field_assign(frozen, name, value, self_name):
+    # If we're a frozen class, then assign to our fields in __init__
+    # via object.__setattr__.  Otherwise, just use a simple
+    # assignment.
+    #
+    # self_name is what "self" is called in this function: don't
+    # hard-code "self", since that might be a field name.
+    if frozen:
+        return f'__dataclass_builtins_object__.__setattr__({self_name},{name!r},{value})'
+    return f'{self_name}.{name}={value}'
+
+
+def _field_init(f, frozen, globals, self_name, slots):
+    # Return the text of the line in the body of __init__ that will
+    # initialize this field.
+
+    default_name = f'__dataclass_dflt_{f.name}__'
+    if f.default_factory is not MISSING:
+        if f.init:
+            # This field has a default factory.  If a parameter is
+            # given, use it.  If not, call the factory.
+            globals[default_name] = f.default_factory
+            value = (f'{default_name}() '
+                     f'if {f.name} is __dataclass_HAS_DEFAULT_FACTORY__ '
+                     f'else {f.name}')
+        else:
+            # This is a field that's not in the __init__ params, but
+            # has a default factory function.  It needs to be
+            # initialized here by calling the factory function,
+            # because there's no other way to initialize it.
+
+            # For a field initialized with a default=defaultvalue, the
+            # class dict just has the default value
+            # (cls.fieldname=defaultvalue).  But that won't work for a
+            # default factory, the factory must be called in __init__
+            # and we must assign that to self.fieldname.  We can't
+            # fall back to the class dict's value, both because it's
+            # not set, and because it might be different per-class
+            # (which, after all, is why we have a factory function!).
+
+            globals[default_name] = f.default_factory
+            value = f'{default_name}()'
+    else:
+        # No default factory.
+        if f.init:
+            if f.default is MISSING:
+                # There's no default, just do an assignment.
+                value = f.name
+            elif f.default is not MISSING:
+                globals[default_name] = f.default
+                value = f.name
+        else:
+            # If the class has slots, then initialize this field.
+            if slots and f.default is not MISSING:
+                globals[default_name] = f.default
+                value = default_name
+            else:
+                # This field does not need initialization: reading from it will
+                # just use the class attribute that contains the default.
+                # Signify that to the caller by returning None.
+                return None
+
+    # Only test this now, so that we can create variables for the
+    # default.  However, return None to signify that we're not going
+    # to actually do the assignment statement for InitVars.
+    if f._field_type is _FIELD_INITVAR:
+        return None
+
+    # Now, actually generate the field assignment.
+    return _field_assign(frozen, f.name, value, self_name)
+
+
+def _init_param(f):
+    # Return the __init__ parameter string for this field.  For
+    # example, the equivalent of 'x:int=3' (except instead of 'int',
+    # reference a variable set to int, and instead of '3', reference a
+    # variable set to 3).
+    if f.default is MISSING and f.default_factory is MISSING:
+        # There's no default, and no default_factory, just output the
+        # variable name and type.
+        default = ''
+    elif f.default is not MISSING:
+        # There's a default, this will be the name that's used to look
+        # it up.
+        default = f'=__dataclass_dflt_{f.name}__'
+    elif f.default_factory is not MISSING:
+        # There's a factory function.  Set a marker.
+        default = '=__dataclass_HAS_DEFAULT_FACTORY__'
+    return f'{f.name}:__dataclass_type_{f.name}__{default}'
+
+
+def _init_fn(fields, std_fields, kw_only_fields, frozen, has_post_init,
+             self_name, globals, slots):
+    # fields contains both real fields and InitVar pseudo-fields.
+
+    # Make sure we don't have fields without defaults following fields
+    # with defaults.  This actually would be caught when exec-ing the
+    # function source code, but catching it here gives a better error
+    # message, and future-proofs us in case we build up the function
+    # using ast.
+
+    seen_default = False
+    for f in std_fields:
+        # Only consider the non-kw-only fields in the __init__ call.
+        if f.init:
+            if not (f.default is MISSING and f.default_factory is MISSING):
+                seen_default = True
+            elif seen_default:
+                raise TypeError(f'non-default argument {f.name!r} '
+                                'follows default argument')
+
+    locals = {f'__dataclass_type_{f.name}__': f.type for f in fields}
+    locals.update({
+        '__dataclass_HAS_DEFAULT_FACTORY__': _HAS_DEFAULT_FACTORY,
+        '__dataclass_builtins_object__': object,
+    })
+
+    body_lines = []
+    for f in fields:
+        line = _field_init(f, frozen, locals, self_name, slots)
+        # line is None means that this field doesn't require
+        # initialization (it's a pseudo-field).  Just skip it.
+        if line:
+            body_lines.append(line)
+
+    # Does this class have a post-init function?
+    if has_post_init:
+        params_str = ','.join(f.name for f in fields
+                              if f._field_type is _FIELD_INITVAR)
+        body_lines.append(f'{self_name}.{_POST_INIT_NAME}({params_str})')
+
+    # If no body lines, use 'pass'.
+    if not body_lines:
+        body_lines = ['pass']
+
+    _init_params = [_init_param(f) for f in std_fields]
+    if kw_only_fields:
+        # Add the keyword-only args.  Because the * can only be added if
+        # there's at least one keyword-only arg, there needs to be a test here
+        # (instead of just concatenting the lists together).
+        _init_params += ['*']
+        _init_params += [_init_param(f) for f in kw_only_fields]
+    return _create_fn('__init__',
+                      [self_name] + _init_params,
+                      body_lines,
+                      locals=locals,
+                      globals=globals,
+                      return_type=None)
+
+
+def _repr_fn(fields, globals):
+    fn = _create_fn('__repr__',
+                    ('self',),
+                    ['return self.__class__.__qualname__ + f"(' +
+                     ', '.join([f"{f.name}={{self.{f.name}!r}}"
+                                for f in fields]) +
+                     ')"'],
+                     globals=globals)
+    return _recursive_repr(fn)
+
+
+def _frozen_get_del_attr(cls, fields, globals):
+    locals = {'cls': cls,
+              'FrozenInstanceError': FrozenInstanceError}
+    condition = 'type(self) is cls'
+    if fields:
+        condition += ' or name in {' + ', '.join(repr(f.name) for f in fields) + '}'
+    return (_create_fn('__setattr__',
+                      ('self', 'name', 'value'),
+                      (f'if {condition}:',
+                        ' raise FrozenInstanceError(f"cannot assign to field {name!r}")',
+                       f'super(cls, self).__setattr__(name, value)'),
+                       locals=locals,
+                       globals=globals),
+            _create_fn('__delattr__',
+                      ('self', 'name'),
+                      (f'if {condition}:',
+                        ' raise FrozenInstanceError(f"cannot delete field {name!r}")',
+                       f'super(cls, self).__delattr__(name)'),
+                       locals=locals,
+                       globals=globals),
+            )
+
+
+def _cmp_fn(name, op, self_tuple, other_tuple, globals):
+    # Create a comparison function.  If the fields in the object are
+    # named 'x' and 'y', then self_tuple is the string
+    # '(self.x,self.y)' and other_tuple is the string
+    # '(other.x,other.y)'.
+
+    return _create_fn(name,
+                      ('self', 'other'),
+                      [ 'if other.__class__ is self.__class__:',
+                       f' return {self_tuple}{op}{other_tuple}',
+                        'return NotImplemented'],
+                      globals=globals)
+
+
+def _hash_fn(fields, globals):
+    self_tuple = _tuple_str('self', fields)
+    return _create_fn('__hash__',
+                      ('self',),
+                      [f'return hash({self_tuple})'],
+                      globals=globals)
+
+
+def _is_classvar(a_type, typing):
+    # This test uses a typing internal class, but it's the best way to
+    # test if this is a ClassVar.
+    return (a_type is typing.ClassVar
+            or (type(a_type) is typing._GenericAlias
+                and a_type.__origin__ is typing.ClassVar))
+
+
+def _is_initvar(a_type, dataclasses):
+    # The module we're checking against is the module we're
+    # currently in (dataclasses.py).
+    return (a_type is dataclasses.InitVar
+            or type(a_type) is dataclasses.InitVar)
+
+def _is_kw_only(a_type, dataclasses):
+    return a_type is dataclasses.KW_ONLY
+
+
+def _is_type(annotation, cls, a_module, a_type, is_type_predicate):
+    # Given a type annotation string, does it refer to a_type in
+    # a_module?  For example, when checking that annotation denotes a
+    # ClassVar, then a_module is typing, and a_type is
+    # typing.ClassVar.
+
+    # It's possible to look up a_module given a_type, but it involves
+    # looking in sys.modules (again!), and seems like a waste since
+    # the caller already knows a_module.
+
+    # - annotation is a string type annotation
+    # - cls is the class that this annotation was found in
+    # - a_module is the module we want to match
+    # - a_type is the type in that module we want to match
+    # - is_type_predicate is a function called with (obj, a_module)
+    #   that determines if obj is of the desired type.
+
+    # Since this test does not do a local namespace lookup (and
+    # instead only a module (global) lookup), there are some things it
+    # gets wrong.
+
+    # With string annotations, cv0 will be detected as a ClassVar:
+    #   CV = ClassVar
+    #   @dataclass
+    #   class C0:
+    #     cv0: CV
+
+    # But in this example cv1 will not be detected as a ClassVar:
+    #   @dataclass
+    #   class C1:
+    #     CV = ClassVar
+    #     cv1: CV
+
+    # In C1, the code in this function (_is_type) will look up "CV" in
+    # the module and not find it, so it will not consider cv1 as a
+    # ClassVar.  This is a fairly obscure corner case, and the best
+    # way to fix it would be to eval() the string "CV" with the
+    # correct global and local namespaces.  However that would involve
+    # a eval() penalty for every single field of every dataclass
+    # that's defined.  It was judged not worth it.
+
+    match = _MODULE_IDENTIFIER_RE.match(annotation)
+    if match:
+        ns = None
+        module_name = match.group(1)
+        if not module_name:
+            # No module name, assume the class's module did
+            # "from dataclasses import InitVar".
+            ns = sys.modules.get(cls.__module__).__dict__
+        else:
+            # Look up module_name in the class's module.
+            module = sys.modules.get(cls.__module__)
+            if module and module.__dict__.get(module_name) is a_module:
+                ns = sys.modules.get(a_type.__module__).__dict__
+        if ns and is_type_predicate(ns.get(match.group(2)), a_module):
+            return True
+    return False
+
+
+def _get_field(cls, a_name, a_type, default_kw_only):
+    # Return a Field object for this field name and type.  ClassVars and
+    # InitVars are also returned, but marked as such (see f._field_type).
+    # default_kw_only is the value of kw_only to use if there isn't a field()
+    # that defines it.
+
+    # If the default value isn't derived from Field, then it's only a
+    # normal default value.  Convert it to a Field().
+    default = getattr(cls, a_name, MISSING)
+    if isinstance(default, Field):
+        f = default
+    else:
+        if isinstance(default, types.MemberDescriptorType):
+            # This is a field in __slots__, so it has no default value.
+            default = MISSING
+        f = field(default=default)
+
+    # Only at this point do we know the name and the type.  Set them.
+    f.name = a_name
+    f.type = a_type
+
+    # Assume it's a normal field until proven otherwise.  We're next
+    # going to decide if it's a ClassVar or InitVar, everything else
+    # is just a normal field.
+    f._field_type = _FIELD
+
+    # In addition to checking for actual types here, also check for
+    # string annotations.  get_type_hints() won't always work for us
+    # (see https://github.com/python/typing/issues/508 for example),
+    # plus it's expensive and would require an eval for every string
+    # annotation.  So, make a best effort to see if this is a ClassVar
+    # or InitVar using regex's and checking that the thing referenced
+    # is actually of the correct type.
+
+    # For the complete discussion, see https://bugs.python.org/issue33453
+
+    # If typing has not been imported, then it's impossible for any
+    # annotation to be a ClassVar.  So, only look for ClassVar if
+    # typing has been imported by any module (not necessarily cls's
+    # module).
+    typing = sys.modules.get('typing')
+    if typing:
+        if (_is_classvar(a_type, typing)
+            or (isinstance(f.type, str)
+                and _is_type(f.type, cls, typing, typing.ClassVar,
+                             _is_classvar))):
+            f._field_type = _FIELD_CLASSVAR
+
+    # If the type is InitVar, or if it's a matching string annotation,
+    # then it's an InitVar.
+    if f._field_type is _FIELD:
+        # The module we're checking against is the module we're
+        # currently in (dataclasses.py).
+        dataclasses = sys.modules[__name__]
+        if (_is_initvar(a_type, dataclasses)
+            or (isinstance(f.type, str)
+                and _is_type(f.type, cls, dataclasses, dataclasses.InitVar,
+                             _is_initvar))):
+            f._field_type = _FIELD_INITVAR
+
+    # Validations for individual fields.  This is delayed until now,
+    # instead of in the Field() constructor, since only here do we
+    # know the field name, which allows for better error reporting.
+
+    # Special restrictions for ClassVar and InitVar.
+    if f._field_type in (_FIELD_CLASSVAR, _FIELD_INITVAR):
+        if f.default_factory is not MISSING:
+            raise TypeError(f'field {f.name} cannot have a '
+                            'default factory')
+        # Should I check for other field settings? default_factory
+        # seems the most serious to check for.  Maybe add others.  For
+        # example, how about init=False (or really,
+        # init=<not-the-default-init-value>)?  It makes no sense for
+        # ClassVar and InitVar to specify init=<anything>.
+
+    # kw_only validation and assignment.
+    if f._field_type in (_FIELD, _FIELD_INITVAR):
+        # For real and InitVar fields, if kw_only wasn't specified use the
+        # default value.
+        if f.kw_only is MISSING:
+            f.kw_only = default_kw_only
+    else:
+        # Make sure kw_only isn't set for ClassVars
+        assert f._field_type is _FIELD_CLASSVAR
+        if f.kw_only is not MISSING:
+            raise TypeError(f'field {f.name} is a ClassVar but specifies '
+                            'kw_only')
+
+    # For real fields, disallow mutable defaults.  Use unhashable as a proxy
+    # indicator for mutability.  Read the __hash__ attribute from the class,
+    # not the instance.
+    if f._field_type is _FIELD and f.default.__class__.__hash__ is None:
+        raise ValueError(f'mutable default {type(f.default)} for field '
+                         f'{f.name} is not allowed: use default_factory')
+
+    return f
+
+def _set_qualname(cls, value):
+    # Ensure that the functions returned from _create_fn uses the proper
+    # __qualname__ (the class they belong to).
+    if isinstance(value, FunctionType):
+        value.__qualname__ = f"{cls.__qualname__}.{value.__name__}"
+    return value
+
+def _set_new_attribute(cls, name, value):
+    # Never overwrites an existing attribute.  Returns True if the
+    # attribute already exists.
+    if name in cls.__dict__:
+        return True
+    _set_qualname(cls, value)
+    setattr(cls, name, value)
+    return False
+
+
+# Decide if/how we're going to create a hash function.  Key is
+# (unsafe_hash, eq, frozen, does-hash-exist).  Value is the action to
+# take.  The common case is to do nothing, so instead of providing a
+# function that is a no-op, use None to signify that.
+
+def _hash_set_none(cls, fields, globals):
+    return None
+
+def _hash_add(cls, fields, globals):
+    flds = [f for f in fields if (f.compare if f.hash is None else f.hash)]
+    return _set_qualname(cls, _hash_fn(flds, globals))
+
+def _hash_exception(cls, fields, globals):
+    # Raise an exception.
+    raise TypeError(f'Cannot overwrite attribute __hash__ '
+                    f'in class {cls.__name__}')
+
+#
+#                +-------------------------------------- unsafe_hash?
+#                |      +------------------------------- eq?
+#                |      |      +------------------------ frozen?
+#                |      |      |      +----------------  has-explicit-hash?
+#                |      |      |      |
+#                |      |      |      |        +-------  action
+#                |      |      |      |        |
+#                v      v      v      v        v
+_hash_action = {(False, False, False, False): None,
+                (False, False, False, True ): None,
+                (False, False, True,  False): None,
+                (False, False, True,  True ): None,
+                (False, True,  False, False): _hash_set_none,
+                (False, True,  False, True ): None,
+                (False, True,  True,  False): _hash_add,
+                (False, True,  True,  True ): None,
+                (True,  False, False, False): _hash_add,
+                (True,  False, False, True ): _hash_exception,
+                (True,  False, True,  False): _hash_add,
+                (True,  False, True,  True ): _hash_exception,
+                (True,  True,  False, False): _hash_add,
+                (True,  True,  False, True ): _hash_exception,
+                (True,  True,  True,  False): _hash_add,
+                (True,  True,  True,  True ): _hash_exception,
+                }
+# See https://bugs.python.org/issue32929#msg312829 for an if-statement
+# version of this table.
+
+
+def _process_class(cls, init, repr, eq, order, unsafe_hash, frozen,
+                   match_args, kw_only, slots, weakref_slot):
+    # Now that dicts retain insertion order, there's no reason to use
+    # an ordered dict.  I am leveraging that ordering here, because
+    # derived class fields overwrite base class fields, but the order
+    # is defined by the base class, which is found first.
+    fields = {}
+
+    if cls.__module__ in sys.modules:
+        globals = sys.modules[cls.__module__].__dict__
+    else:
+        # Theoretically this can happen if someone writes
+        # a custom string to cls.__module__.  In which case
+        # such dataclass won't be fully introspectable
+        # (w.r.t. typing.get_type_hints) but will still function
+        # correctly.
+        globals = {}
+
+    setattr(cls, _PARAMS, _DataclassParams(init, repr, eq, order,
+                                           unsafe_hash, frozen,
+                                           match_args, kw_only,
+                                           slots, weakref_slot))
+
+    # Find our base classes in reverse MRO order, and exclude
+    # ourselves.  In reversed order so that more derived classes
+    # override earlier field definitions in base classes.  As long as
+    # we're iterating over them, see if any are frozen.
+    any_frozen_base = False
+    has_dataclass_bases = False
+    for b in cls.__mro__[-1:0:-1]:
+        # Only process classes that have been processed by our
+        # decorator.  That is, they have a _FIELDS attribute.
+        base_fields = getattr(b, _FIELDS, None)
+        if base_fields is not None:
+            has_dataclass_bases = True
+            for f in base_fields.values():
+                fields[f.name] = f
+            if getattr(b, _PARAMS).frozen:
+                any_frozen_base = True
+
+    # Annotations defined specifically in this class (not in base classes).
+    #
+    # Fields are found from cls_annotations, which is guaranteed to be
+    # ordered.  Default values are from class attributes, if a field
+    # has a default.  If the default value is a Field(), then it
+    # contains additional info beyond (and possibly including) the
+    # actual default value.  Pseudo-fields ClassVars and InitVars are
+    # included, despite the fact that they're not real fields.  That's
+    # dealt with later.
+    cls_annotations = inspect.get_annotations(cls)
+
+    # Now find fields in our class.  While doing so, validate some
+    # things, and set the default values (as class attributes) where
+    # we can.
+    cls_fields = []
+    # Get a reference to this module for the _is_kw_only() test.
+    KW_ONLY_seen = False
+    dataclasses = sys.modules[__name__]
+    for name, type in cls_annotations.items():
+        # See if this is a marker to change the value of kw_only.
+        if (_is_kw_only(type, dataclasses)
+            or (isinstance(type, str)
+                and _is_type(type, cls, dataclasses, dataclasses.KW_ONLY,
+                             _is_kw_only))):
+            # Switch the default to kw_only=True, and ignore this
+            # annotation: it's not a real field.
+            if KW_ONLY_seen:
+                raise TypeError(f'{name!r} is KW_ONLY, but KW_ONLY '
+                                'has already been specified')
+            KW_ONLY_seen = True
+            kw_only = True
+        else:
+            # Otherwise it's a field of some type.
+            cls_fields.append(_get_field(cls, name, type, kw_only))
+
+    for f in cls_fields:
+        fields[f.name] = f
+
+        # If the class attribute (which is the default value for this
+        # field) exists and is of type 'Field', replace it with the
+        # real default.  This is so that normal class introspection
+        # sees a real default value, not a Field.
+        if isinstance(getattr(cls, f.name, None), Field):
+            if f.default is MISSING:
+                # If there's no default, delete the class attribute.
+                # This happens if we specify field(repr=False), for
+                # example (that is, we specified a field object, but
+                # no default value).  Also if we're using a default
+                # factory.  The class attribute should not be set at
+                # all in the post-processed class.
+                delattr(cls, f.name)
+            else:
+                setattr(cls, f.name, f.default)
+
+    # Do we have any Field members that don't also have annotations?
+    for name, value in cls.__dict__.items():
+        if isinstance(value, Field) and not name in cls_annotations:
+            raise TypeError(f'{name!r} is a field but has no type annotation')
+
+    # Check rules that apply if we are derived from any dataclasses.
+    if has_dataclass_bases:
+        # Raise an exception if any of our bases are frozen, but we're not.
+        if any_frozen_base and not frozen:
+            raise TypeError('cannot inherit non-frozen dataclass from a '
+                            'frozen one')
+
+        # Raise an exception if we're frozen, but none of our bases are.
+        if not any_frozen_base and frozen:
+            raise TypeError('cannot inherit frozen dataclass from a '
+                            'non-frozen one')
+
+    # Remember all of the fields on our class (including bases).  This
+    # also marks this class as being a dataclass.
+    setattr(cls, _FIELDS, fields)
+
+    # Was this class defined with an explicit __hash__?  Note that if
+    # __eq__ is defined in this class, then python will automatically
+    # set __hash__ to None.  This is a heuristic, as it's possible
+    # that such a __hash__ == None was not auto-generated, but it
+    # close enough.
+    class_hash = cls.__dict__.get('__hash__', MISSING)
+    has_explicit_hash = not (class_hash is MISSING or
+                             (class_hash is None and '__eq__' in cls.__dict__))
+
+    # If we're generating ordering methods, we must be generating the
+    # eq methods.
+    if order and not eq:
+        raise ValueError('eq must be true if order is true')
+
+    # Include InitVars and regular fields (so, not ClassVars).  This is
+    # initialized here, outside of the "if init:" test, because std_init_fields
+    # is used with match_args, below.
+    all_init_fields = [f for f in fields.values()
+                       if f._field_type in (_FIELD, _FIELD_INITVAR)]
+    (std_init_fields,
+     kw_only_init_fields) = _fields_in_init_order(all_init_fields)
+
+    if init:
+        # Does this class have a post-init function?
+        has_post_init = hasattr(cls, _POST_INIT_NAME)
+
+        _set_new_attribute(cls, '__init__',
+                           _init_fn(all_init_fields,
+                                    std_init_fields,
+                                    kw_only_init_fields,
+                                    frozen,
+                                    has_post_init,
+                                    # The name to use for the "self"
+                                    # param in __init__.  Use "self"
+                                    # if possible.
+                                    '__dataclass_self__' if 'self' in fields
+                                            else 'self',
+                                    globals,
+                                    slots,
+                          ))
+
+    # Get the fields as a list, and include only real fields.  This is
+    # used in all of the following methods.
+    field_list = [f for f in fields.values() if f._field_type is _FIELD]
+
+    if repr:
+        flds = [f for f in field_list if f.repr]
+        _set_new_attribute(cls, '__repr__', _repr_fn(flds, globals))
+
+    if eq:
+        # Create __eq__ method.  There's no need for a __ne__ method,
+        # since python will call __eq__ and negate it.
+        flds = [f for f in field_list if f.compare]
+        self_tuple = _tuple_str('self', flds)
+        other_tuple = _tuple_str('other', flds)
+        _set_new_attribute(cls, '__eq__',
+                           _cmp_fn('__eq__', '==',
+                                   self_tuple, other_tuple,
+                                   globals=globals))
+
+    if order:
+        # Create and set the ordering methods.
+        flds = [f for f in field_list if f.compare]
+        self_tuple = _tuple_str('self', flds)
+        other_tuple = _tuple_str('other', flds)
+        for name, op in [('__lt__', '<'),
+                         ('__le__', '<='),
+                         ('__gt__', '>'),
+                         ('__ge__', '>='),
+                         ]:
+            if _set_new_attribute(cls, name,
+                                  _cmp_fn(name, op, self_tuple, other_tuple,
+                                          globals=globals)):
+                raise TypeError(f'Cannot overwrite attribute {name} '
+                                f'in class {cls.__name__}. Consider using '
+                                'functools.total_ordering')
+
+    if frozen:
+        for fn in _frozen_get_del_attr(cls, field_list, globals):
+            if _set_new_attribute(cls, fn.__name__, fn):
+                raise TypeError(f'Cannot overwrite attribute {fn.__name__} '
+                                f'in class {cls.__name__}')
+
+    # Decide if/how we're going to create a hash function.
+    hash_action = _hash_action[bool(unsafe_hash),
+                               bool(eq),
+                               bool(frozen),
+                               has_explicit_hash]
+    if hash_action:
+        # No need to call _set_new_attribute here, since by the time
+        # we're here the overwriting is unconditional.
+        cls.__hash__ = hash_action(cls, field_list, globals)
+
+    if not getattr(cls, '__doc__'):
+        # Create a class doc-string.
+        try:
+            # In some cases fetching a signature is not possible.
+            # But, we surely should not fail in this case.
+            text_sig = str(inspect.signature(cls)).replace(' -> None', '')
+        except (TypeError, ValueError):
+            text_sig = ''
+        cls.__doc__ = (cls.__name__ + text_sig)
+
+    if match_args:
+        # I could probably compute this once
+        _set_new_attribute(cls, '__match_args__',
+                           tuple(f.name for f in std_init_fields))
+
+    # It's an error to specify weakref_slot if slots is False.
+    if weakref_slot and not slots:
+        raise TypeError('weakref_slot is True but slots is False')
+    if slots:
+        cls = _add_slots(cls, frozen, weakref_slot)
+
+    abc.update_abstractmethods(cls)
+
+    return cls
+
+
+# _dataclass_getstate and _dataclass_setstate are needed for pickling frozen
+# classes with slots.  These could be slightly more performant if we generated
+# the code instead of iterating over fields.  But that can be a project for
+# another day, if performance becomes an issue.
+def _dataclass_getstate(self):
+    return [getattr(self, f.name) for f in fields(self)]
+
+
+def _dataclass_setstate(self, state):
+    for field, value in zip(fields(self), state):
+        # use setattr because dataclass may be frozen
+        object.__setattr__(self, field.name, value)
+
+
+def _get_slots(cls):
+    match cls.__dict__.get('__slots__'):
+        case None:
+            return
+        case str(slot):
+            yield slot
+        # Slots may be any iterable, but we cannot handle an iterator
+        # because it will already be (partially) consumed.
+        case iterable if not hasattr(iterable, '__next__'):
+            yield from iterable
+        case _:
+            raise TypeError(f"Slots of '{cls.__name__}' cannot be determined")
+
+
+def _add_slots(cls, is_frozen, weakref_slot):
+    # Need to create a new class, since we can't set __slots__
+    #  after a class has been created.
+
+    # Make sure __slots__ isn't already set.
+    if '__slots__' in cls.__dict__:
+        raise TypeError(f'{cls.__name__} already specifies __slots__')
+
+    # Create a new dict for our new class.
+    cls_dict = dict(cls.__dict__)
+    field_names = tuple(f.name for f in fields(cls))
+    # Make sure slots don't overlap with those in base classes.
+    inherited_slots = set(
+        itertools.chain.from_iterable(map(_get_slots, cls.__mro__[1:-1]))
+    )
+    # The slots for our class.  Remove slots from our base classes.  Add
+    # '__weakref__' if weakref_slot was given, unless it is already present.
+    cls_dict["__slots__"] = tuple(
+        itertools.filterfalse(
+            inherited_slots.__contains__,
+            itertools.chain(
+                # gh-93521: '__weakref__' also needs to be filtered out if
+                # already present in inherited_slots
+                field_names, ('__weakref__',) if weakref_slot else ()
+            )
+        ),
+    )
+
+    for field_name in field_names:
+        # Remove our attributes, if present. They'll still be
+        #  available in _MARKER.
+        cls_dict.pop(field_name, None)
+
+    # Remove __dict__ itself.
+    cls_dict.pop('__dict__', None)
+
+    # Clear existing `__weakref__` descriptor, it belongs to a previous type:
+    cls_dict.pop('__weakref__', None)  # gh-102069
+
+    # And finally create the class.
+    qualname = getattr(cls, '__qualname__', None)
+    cls = type(cls)(cls.__name__, cls.__bases__, cls_dict)
+    if qualname is not None:
+        cls.__qualname__ = qualname
+
+    if is_frozen:
+        # Need this for pickling frozen classes with slots.
+        if '__getstate__' not in cls_dict:
+            cls.__getstate__ = _dataclass_getstate
+        if '__setstate__' not in cls_dict:
+            cls.__setstate__ = _dataclass_setstate
+
+    return cls
+
+
+def dataclass(cls=None, /, *, init=True, repr=True, eq=True, order=False,
+              unsafe_hash=False, frozen=False, match_args=True,
+              kw_only=False, slots=False, weakref_slot=False):
+    """Add dunder methods based on the fields defined in the class.
+
+    Examines PEP 526 __annotations__ to determine fields.
+
+    If init is true, an __init__() method is added to the class. If repr
+    is true, a __repr__() method is added. If order is true, rich
+    comparison dunder methods are added. If unsafe_hash is true, a
+    __hash__() method is added. If frozen is true, fields may not be
+    assigned to after instance creation. If match_args is true, the
+    __match_args__ tuple is added. If kw_only is true, then by default
+    all fields are keyword-only. If slots is true, a new class with a
+    __slots__ attribute is returned.
+    """
+
+    def wrap(cls):
+        return _process_class(cls, init, repr, eq, order, unsafe_hash,
+                              frozen, match_args, kw_only, slots,
+                              weakref_slot)
+
+    # See if we're being called as @dataclass or @dataclass().
+    if cls is None:
+        # We're called with parens.
+        return wrap
+
+    # We're called as @dataclass without parens.
+    return wrap(cls)
+
+
+def fields(class_or_instance):
+    """Return a tuple describing the fields of this dataclass.
+
+    Accepts a dataclass or an instance of one. Tuple elements are of
+    type Field.
+    """
+
+    # Might it be worth caching this, per class?
+    try:
+        fields = getattr(class_or_instance, _FIELDS)
+    except AttributeError:
+        raise TypeError('must be called with a dataclass type or instance') from None
+
+    # Exclude pseudo-fields.  Note that fields is sorted by insertion
+    # order, so the order of the tuple is as the fields were defined.
+    return tuple(f for f in fields.values() if f._field_type is _FIELD)
+
+
+def _is_dataclass_instance(obj):
+    """Returns True if obj is an instance of a dataclass."""
+    return hasattr(type(obj), _FIELDS)
+
+
+def is_dataclass(obj):
+    """Returns True if obj is a dataclass or an instance of a
+    dataclass."""
+    cls = obj if isinstance(obj, type) else type(obj)
+    return hasattr(cls, _FIELDS)
+
+
+def asdict(obj, *, dict_factory=dict):
+    """Return the fields of a dataclass instance as a new dictionary mapping
+    field names to field values.
+
+    Example usage::
+
+      @dataclass
+      class C:
+          x: int
+          y: int
+
+      c = C(1, 2)
+      assert asdict(c) == {'x': 1, 'y': 2}
+
+    If given, 'dict_factory' will be used instead of built-in dict.
+    The function applies recursively to field values that are
+    dataclass instances. This will also look into built-in containers:
+    tuples, lists, and dicts. Other objects are copied with 'copy.deepcopy()'.
+    """
+    if not _is_dataclass_instance(obj):
+        raise TypeError("asdict() should be called on dataclass instances")
+    return _asdict_inner(obj, dict_factory)
+
+
+def _asdict_inner(obj, dict_factory):
+    if type(obj) in _ATOMIC_TYPES:
+        return obj
+    elif _is_dataclass_instance(obj):
+        # fast path for the common case
+        if dict_factory is dict:
+            return {
+                f.name: _asdict_inner(getattr(obj, f.name), dict)
+                for f in fields(obj)
+            }
+        else:
+            result = []
+            for f in fields(obj):
+                value = _asdict_inner(getattr(obj, f.name), dict_factory)
+                result.append((f.name, value))
+            return dict_factory(result)
+    elif isinstance(obj, tuple) and hasattr(obj, '_fields'):
+        # obj is a namedtuple.  Recurse into it, but the returned
+        # object is another namedtuple of the same type.  This is
+        # similar to how other list- or tuple-derived classes are
+        # treated (see below), but we just need to create them
+        # differently because a namedtuple's __init__ needs to be
+        # called differently (see bpo-34363).
+
+        # I'm not using namedtuple's _asdict()
+        # method, because:
+        # - it does not recurse in to the namedtuple fields and
+        #   convert them to dicts (using dict_factory).
+        # - I don't actually want to return a dict here.  The main
+        #   use case here is json.dumps, and it handles converting
+        #   namedtuples to lists.  Admittedly we're losing some
+        #   information here when we produce a json list instead of a
+        #   dict.  Note that if we returned dicts here instead of
+        #   namedtuples, we could no longer call asdict() on a data
+        #   structure where a namedtuple was used as a dict key.
+
+        return type(obj)(*[_asdict_inner(v, dict_factory) for v in obj])
+    elif isinstance(obj, (list, tuple)):
+        # Assume we can create an object of this type by passing in a
+        # generator (which is not true for namedtuples, handled
+        # above).
+        return type(obj)(_asdict_inner(v, dict_factory) for v in obj)
+    elif isinstance(obj, dict):
+        if hasattr(type(obj), 'default_factory'):
+            # obj is a defaultdict, which has a different constructor from
+            # dict as it requires the default_factory as its first arg.
+            result = type(obj)(getattr(obj, 'default_factory'))
+            for k, v in obj.items():
+                result[_asdict_inner(k, dict_factory)] = _asdict_inner(v, dict_factory)
+            return result
+        return type(obj)((_asdict_inner(k, dict_factory),
+                          _asdict_inner(v, dict_factory))
+                         for k, v in obj.items())
+    else:
+        return copy.deepcopy(obj)
+
+
+def astuple(obj, *, tuple_factory=tuple):
+    """Return the fields of a dataclass instance as a new tuple of field values.
+
+    Example usage::
+
+      @dataclass
+      class C:
+          x: int
+          y: int
+
+      c = C(1, 2)
+      assert astuple(c) == (1, 2)
+
+    If given, 'tuple_factory' will be used instead of built-in tuple.
+    The function applies recursively to field values that are
+    dataclass instances. This will also look into built-in containers:
+    tuples, lists, and dicts. Other objects are copied with 'copy.deepcopy()'.
+    """
+
+    if not _is_dataclass_instance(obj):
+        raise TypeError("astuple() should be called on dataclass instances")
+    return _astuple_inner(obj, tuple_factory)
+
+
+def _astuple_inner(obj, tuple_factory):
+    if type(obj) in _ATOMIC_TYPES:
+        return obj
+    elif _is_dataclass_instance(obj):
+        result = []
+        for f in fields(obj):
+            value = _astuple_inner(getattr(obj, f.name), tuple_factory)
+            result.append(value)
+        return tuple_factory(result)
+    elif isinstance(obj, tuple) and hasattr(obj, '_fields'):
+        # obj is a namedtuple.  Recurse into it, but the returned
+        # object is another namedtuple of the same type.  This is
+        # similar to how other list- or tuple-derived classes are
+        # treated (see below), but we just need to create them
+        # differently because a namedtuple's __init__ needs to be
+        # called differently (see bpo-34363).
+        return type(obj)(*[_astuple_inner(v, tuple_factory) for v in obj])
+    elif isinstance(obj, (list, tuple)):
+        # Assume we can create an object of this type by passing in a
+        # generator (which is not true for namedtuples, handled
+        # above).
+        return type(obj)(_astuple_inner(v, tuple_factory) for v in obj)
+    elif isinstance(obj, dict):
+        obj_type = type(obj)
+        if hasattr(obj_type, 'default_factory'):
+            # obj is a defaultdict, which has a different constructor from
+            # dict as it requires the default_factory as its first arg.
+            result = obj_type(getattr(obj, 'default_factory'))
+            for k, v in obj.items():
+                result[_astuple_inner(k, tuple_factory)] = _astuple_inner(v, tuple_factory)
+            return result
+        return obj_type((_astuple_inner(k, tuple_factory), _astuple_inner(v, tuple_factory))
+                          for k, v in obj.items())
+    else:
+        return copy.deepcopy(obj)
+
+
+def make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True,
+                   repr=True, eq=True, order=False, unsafe_hash=False,
+                   frozen=False, match_args=True, kw_only=False, slots=False,
+                   weakref_slot=False, module=None):
+    """Return a new dynamically created dataclass.
+
+    The dataclass name will be 'cls_name'.  'fields' is an iterable
+    of either (name), (name, type) or (name, type, Field) objects. If type is
+    omitted, use the string 'typing.Any'.  Field objects are created by
+    the equivalent of calling 'field(name, type [, Field-info])'.::
+
+      C = make_dataclass('C', ['x', ('y', int), ('z', int, field(init=False))], bases=(Base,))
+
+    is equivalent to::
+
+      @dataclass
+      class C(Base):
+          x: 'typing.Any'
+          y: int
+          z: int = field(init=False)
+
+    For the bases and namespace parameters, see the builtin type() function.
+
+    The parameters init, repr, eq, order, unsafe_hash, frozen, match_args, kw_only,
+    slots, and weakref_slot are passed to dataclass().
+
+    If module parameter is defined, the '__module__' attribute of the dataclass is
+    set to that value.
+    """
+
+    if namespace is None:
+        namespace = {}
+
+    # While we're looking through the field names, validate that they
+    # are identifiers, are not keywords, and not duplicates.
+    seen = set()
+    annotations = {}
+    defaults = {}
+    for item in fields:
+        if isinstance(item, str):
+            name = item
+            tp = 'typing.Any'
+        elif len(item) == 2:
+            name, tp, = item
+        elif len(item) == 3:
+            name, tp, spec = item
+            defaults[name] = spec
+        else:
+            raise TypeError(f'Invalid field: {item!r}')
+
+        if not isinstance(name, str) or not name.isidentifier():
+            raise TypeError(f'Field names must be valid identifiers: {name!r}')
+        if keyword.iskeyword(name):
+            raise TypeError(f'Field names must not be keywords: {name!r}')
+        if name in seen:
+            raise TypeError(f'Field name duplicated: {name!r}')
+
+        seen.add(name)
+        annotations[name] = tp
+
+    # Update 'ns' with the user-supplied namespace plus our calculated values.
+    def exec_body_callback(ns):
+        ns.update(namespace)
+        ns.update(defaults)
+        ns['__annotations__'] = annotations
+
+    # We use `types.new_class()` instead of simply `type()` to allow dynamic creation
+    # of generic dataclasses.
+    cls = types.new_class(cls_name, bases, {}, exec_body_callback)
+
+    # For pickling to work, the __module__ variable needs to be set to the frame
+    # where the dataclass is created.
+    if module is None:
+        try:
+            module = sys._getframemodulename(1) or '__main__'
+        except AttributeError:
+            try:
+                module = sys._getframe(1).f_globals.get('__name__', '__main__')
+            except (AttributeError, ValueError):
+                pass
+    if module is not None:
+        cls.__module__ = module
+
+    # Apply the normal decorator.
+    return dataclass(cls, init=init, repr=repr, eq=eq, order=order,
+                     unsafe_hash=unsafe_hash, frozen=frozen,
+                     match_args=match_args, kw_only=kw_only, slots=slots,
+                     weakref_slot=weakref_slot)
+
+
+def replace(obj, /, **changes):
+    """Return a new object replacing specified fields with new values.
+
+    This is especially useful for frozen classes.  Example usage::
+
+      @dataclass(frozen=True)
+      class C:
+          x: int
+          y: int
+
+      c = C(1, 2)
+      c1 = replace(c, x=3)
+      assert c1.x == 3 and c1.y == 2
+    """
+
+    # We're going to mutate 'changes', but that's okay because it's a
+    # new dict, even if called with 'replace(obj, **my_changes)'.
+
+    if not _is_dataclass_instance(obj):
+        raise TypeError("replace() should be called on dataclass instances")
+
+    # It's an error to have init=False fields in 'changes'.
+    # If a field is not in 'changes', read its value from the provided obj.
+
+    for f in getattr(obj, _FIELDS).values():
+        # Only consider normal fields or InitVars.
+        if f._field_type is _FIELD_CLASSVAR:
+            continue
+
+        if not f.init:
+            # Error if this field is specified in changes.
+            if f.name in changes:
+                raise ValueError(f'field {f.name} is declared with '
+                                 'init=False, it cannot be specified with '
+                                 'replace()')
+            continue
+
+        if f.name not in changes:
+            if f._field_type is _FIELD_INITVAR and f.default is MISSING:
+                raise ValueError(f"InitVar {f.name!r} "
+                                 'must be specified with replace()')
+            changes[f.name] = getattr(obj, f.name)
+
+    # Create the new object, which calls __init__() and
+    # __post_init__() (if defined), using all of the init fields we've
+    # added and/or left in 'changes'.  If there are values supplied in
+    # changes that aren't fields, this will correctly raise a
+    # TypeError.
+    return obj.__class__(**changes)