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3e3a4d2315
This is to allow the `dataclasses.make_dataclass` infrastructure to be used with another decorator that's compliant with `typing.dataclass_transform`. The new `decorator` argument to `dataclasses.make_dataclass` is `dataclasses.dataclass`, which used to be hard coded.
1690 lines
65 KiB
Python
1690 lines
65 KiB
Python
import re
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import sys
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import copy
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import types
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import inspect
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import keyword
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import itertools
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import annotationlib
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import abc
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from reprlib import recursive_repr
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__all__ = ['dataclass',
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'field',
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'Field',
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'FrozenInstanceError',
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'InitVar',
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'KW_ONLY',
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'MISSING',
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# Helper functions.
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'fields',
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'asdict',
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'astuple',
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'make_dataclass',
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'replace',
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'is_dataclass',
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]
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# Conditions for adding methods. The boxes indicate what action the
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# dataclass decorator takes. For all of these tables, when I talk
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# about init=, repr=, eq=, order=, unsafe_hash=, or frozen=, I'm
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# referring to the arguments to the @dataclass decorator. When
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# checking if a dunder method already exists, I mean check for an
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# entry in the class's __dict__. I never check to see if an attribute
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# is defined in a base class.
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# Key:
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# +=========+=========================================+
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# + Value | Meaning |
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# +=========+=========================================+
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# | <blank> | No action: no method is added. |
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# +---------+-----------------------------------------+
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# | add | Generated method is added. |
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# +---------+-----------------------------------------+
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# | raise | TypeError is raised. |
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# +---------+-----------------------------------------+
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# | None | Attribute is set to None. |
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# +=========+=========================================+
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# __init__
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#
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# +--- init= parameter
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# |
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# v | | |
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# | no | yes | <--- class has __init__ in __dict__?
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# +=======+=======+=======+
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# | False | | |
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# +-------+-------+-------+
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# | True | add | | <- the default
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# +=======+=======+=======+
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# __repr__
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#
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# +--- repr= parameter
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# |
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# v | | |
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# | no | yes | <--- class has __repr__ in __dict__?
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# +=======+=======+=======+
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# | False | | |
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# +-------+-------+-------+
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# | True | add | | <- the default
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# +=======+=======+=======+
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# __setattr__
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# __delattr__
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#
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# +--- frozen= parameter
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# |
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# v | | |
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# | no | yes | <--- class has __setattr__ or __delattr__ in __dict__?
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# +=======+=======+=======+
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# | False | | | <- the default
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# +-------+-------+-------+
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# | True | add | raise |
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# +=======+=======+=======+
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# Raise because not adding these methods would break the "frozen-ness"
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# of the class.
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# __eq__
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#
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# +--- eq= parameter
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# |
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# v | | |
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# | no | yes | <--- class has __eq__ in __dict__?
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# +=======+=======+=======+
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# | False | | |
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# +-------+-------+-------+
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# | True | add | | <- the default
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# +=======+=======+=======+
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# __lt__
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# __le__
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# __gt__
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# __ge__
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#
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# +--- order= parameter
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# |
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# v | | |
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# | no | yes | <--- class has any comparison method in __dict__?
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# +=======+=======+=======+
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# | False | | | <- the default
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# +-------+-------+-------+
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# | True | add | raise |
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# +=======+=======+=======+
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# Raise because to allow this case would interfere with using
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# functools.total_ordering.
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# __hash__
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# +------------------- unsafe_hash= parameter
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# | +----------- eq= parameter
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# | | +--- frozen= parameter
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# | | |
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# v v v | | |
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# | no | yes | <--- class has explicitly defined __hash__
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# +=======+=======+=======+========+========+
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# | False | False | False | | | No __eq__, use the base class __hash__
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# +-------+-------+-------+--------+--------+
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# | False | False | True | | | No __eq__, use the base class __hash__
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# +-------+-------+-------+--------+--------+
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# | False | True | False | None | | <-- the default, not hashable
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# +-------+-------+-------+--------+--------+
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# | False | True | True | add | | Frozen, so hashable, allows override
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# +-------+-------+-------+--------+--------+
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# | True | False | False | add | raise | Has no __eq__, but hashable
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# +-------+-------+-------+--------+--------+
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# | True | False | True | add | raise | Has no __eq__, but hashable
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# +-------+-------+-------+--------+--------+
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# | True | True | False | add | raise | Not frozen, but hashable
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# +-------+-------+-------+--------+--------+
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# | True | True | True | add | raise | Frozen, so hashable
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# +=======+=======+=======+========+========+
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# For boxes that are blank, __hash__ is untouched and therefore
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# inherited from the base class. If the base is object, then
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# id-based hashing is used.
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#
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# Note that a class may already have __hash__=None if it specified an
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# __eq__ method in the class body (not one that was created by
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# @dataclass).
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#
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# See _hash_action (below) for a coded version of this table.
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# __match_args__
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#
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# +--- match_args= parameter
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# |
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# v | | |
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# | no | yes | <--- class has __match_args__ in __dict__?
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# +=======+=======+=======+
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# | False | | |
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# +-------+-------+-------+
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# | True | add | | <- the default
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# +=======+=======+=======+
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# __match_args__ is always added unless the class already defines it. It is a
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# tuple of __init__ parameter names; non-init fields must be matched by keyword.
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# Raised when an attempt is made to modify a frozen class.
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class FrozenInstanceError(AttributeError): pass
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# A sentinel object for default values to signal that a default
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# factory will be used. This is given a nice repr() which will appear
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# in the function signature of dataclasses' constructors.
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class _HAS_DEFAULT_FACTORY_CLASS:
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def __repr__(self):
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return '<factory>'
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_HAS_DEFAULT_FACTORY = _HAS_DEFAULT_FACTORY_CLASS()
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# A sentinel object to detect if a parameter is supplied or not. Use
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# a class to give it a better repr.
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class _MISSING_TYPE:
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pass
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MISSING = _MISSING_TYPE()
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# A sentinel object to indicate that following fields are keyword-only by
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# default. Use a class to give it a better repr.
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class _KW_ONLY_TYPE:
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pass
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KW_ONLY = _KW_ONLY_TYPE()
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# Since most per-field metadata will be unused, create an empty
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# read-only proxy that can be shared among all fields.
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_EMPTY_METADATA = types.MappingProxyType({})
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# Markers for the various kinds of fields and pseudo-fields.
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class _FIELD_BASE:
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def __init__(self, name):
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self.name = name
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def __repr__(self):
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return self.name
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_FIELD = _FIELD_BASE('_FIELD')
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_FIELD_CLASSVAR = _FIELD_BASE('_FIELD_CLASSVAR')
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_FIELD_INITVAR = _FIELD_BASE('_FIELD_INITVAR')
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# The name of an attribute on the class where we store the Field
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# objects. Also used to check if a class is a Data Class.
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_FIELDS = '__dataclass_fields__'
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# The name of an attribute on the class that stores the parameters to
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# @dataclass.
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_PARAMS = '__dataclass_params__'
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# The name of the function, that if it exists, is called at the end of
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# __init__.
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_POST_INIT_NAME = '__post_init__'
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# String regex that string annotations for ClassVar or InitVar must match.
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# Allows "identifier.identifier[" or "identifier[".
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# https://bugs.python.org/issue33453 for details.
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_MODULE_IDENTIFIER_RE = re.compile(r'^(?:\s*(\w+)\s*\.)?\s*(\w+)')
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# Atomic immutable types which don't require any recursive handling and for which deepcopy
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# returns the same object. We can provide a fast-path for these types in asdict and astuple.
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_ATOMIC_TYPES = frozenset({
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# Common JSON Serializable types
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types.NoneType,
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bool,
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int,
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float,
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str,
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# Other common types
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complex,
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bytes,
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# Other types that are also unaffected by deepcopy
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types.EllipsisType,
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types.NotImplementedType,
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types.CodeType,
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types.BuiltinFunctionType,
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types.FunctionType,
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type,
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range,
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property,
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})
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class InitVar:
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__slots__ = ('type', )
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def __init__(self, type):
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self.type = type
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def __repr__(self):
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if isinstance(self.type, type):
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type_name = self.type.__name__
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else:
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# typing objects, e.g. List[int]
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type_name = repr(self.type)
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return f'dataclasses.InitVar[{type_name}]'
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def __class_getitem__(cls, type):
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return InitVar(type)
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# Instances of Field are only ever created from within this module,
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# and only from the field() function, although Field instances are
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# exposed externally as (conceptually) read-only objects.
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#
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# name and type are filled in after the fact, not in __init__.
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# They're not known at the time this class is instantiated, but it's
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# convenient if they're available later.
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#
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# When cls._FIELDS is filled in with a list of Field objects, the name
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# and type fields will have been populated.
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class Field:
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__slots__ = ('name',
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'type',
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'default',
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'default_factory',
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'repr',
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'hash',
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'init',
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'compare',
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'metadata',
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'kw_only',
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'doc',
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'_field_type', # Private: not to be used by user code.
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)
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def __init__(self, default, default_factory, init, repr, hash, compare,
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metadata, kw_only, doc):
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self.name = None
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self.type = None
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self.default = default
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self.default_factory = default_factory
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self.init = init
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self.repr = repr
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self.hash = hash
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self.compare = compare
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self.metadata = (_EMPTY_METADATA
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if metadata is None else
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types.MappingProxyType(metadata))
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self.kw_only = kw_only
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self.doc = doc
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self._field_type = None
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@recursive_repr()
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def __repr__(self):
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return ('Field('
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f'name={self.name!r},'
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f'type={self.type!r},'
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f'default={self.default!r},'
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f'default_factory={self.default_factory!r},'
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f'init={self.init!r},'
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f'repr={self.repr!r},'
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f'hash={self.hash!r},'
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f'compare={self.compare!r},'
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f'metadata={self.metadata!r},'
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f'kw_only={self.kw_only!r},'
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f'doc={self.doc!r},'
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f'_field_type={self._field_type}'
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')')
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# This is used to support the PEP 487 __set_name__ protocol in the
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# case where we're using a field that contains a descriptor as a
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# default value. For details on __set_name__, see
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# https://peps.python.org/pep-0487/#implementation-details.
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#
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# Note that in _process_class, this Field object is overwritten
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# with the default value, so the end result is a descriptor that
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# had __set_name__ called on it at the right time.
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def __set_name__(self, owner, name):
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func = getattr(type(self.default), '__set_name__', None)
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if func:
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# There is a __set_name__ method on the descriptor, call
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# it.
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func(self.default, owner, name)
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__class_getitem__ = classmethod(types.GenericAlias)
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class _DataclassParams:
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__slots__ = ('init',
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'repr',
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'eq',
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'order',
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'unsafe_hash',
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'frozen',
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'match_args',
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'kw_only',
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'slots',
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'weakref_slot',
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)
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def __init__(self,
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init, repr, eq, order, unsafe_hash, frozen,
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match_args, kw_only, slots, weakref_slot):
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self.init = init
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self.repr = repr
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self.eq = eq
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self.order = order
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self.unsafe_hash = unsafe_hash
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self.frozen = frozen
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self.match_args = match_args
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self.kw_only = kw_only
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self.slots = slots
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self.weakref_slot = weakref_slot
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def __repr__(self):
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return ('_DataclassParams('
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f'init={self.init!r},'
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f'repr={self.repr!r},'
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f'eq={self.eq!r},'
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f'order={self.order!r},'
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f'unsafe_hash={self.unsafe_hash!r},'
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f'frozen={self.frozen!r},'
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f'match_args={self.match_args!r},'
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f'kw_only={self.kw_only!r},'
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f'slots={self.slots!r},'
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f'weakref_slot={self.weakref_slot!r}'
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')')
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# This function is used instead of exposing Field creation directly,
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# so that a type checker can be told (via overloads) that this is a
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# function whose type depends on its parameters.
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def field(*, default=MISSING, default_factory=MISSING, init=True, repr=True,
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hash=None, compare=True, metadata=None, kw_only=MISSING, doc=None):
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"""Return an object to identify dataclass fields.
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default is the default value of the field. default_factory is a
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0-argument function called to initialize a field's value. If init
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is true, the field will be a parameter to the class's __init__()
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function. If repr is true, the field will be included in the
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object's repr(). If hash is true, the field will be included in the
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object's hash(). If compare is true, the field will be used in
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comparison functions. metadata, if specified, must be a mapping
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which is stored but not otherwise examined by dataclass. If kw_only
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is true, the field will become a keyword-only parameter to
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__init__(). doc is an optional docstring for this field.
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It is an error to specify both default and default_factory.
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"""
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if default is not MISSING and default_factory is not MISSING:
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raise ValueError('cannot specify both default and default_factory')
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return Field(default, default_factory, init, repr, hash, compare,
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metadata, kw_only, doc)
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def _fields_in_init_order(fields):
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# Returns the fields as __init__ will output them. It returns 2 tuples:
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# the first for normal args, and the second for keyword args.
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return (tuple(f for f in fields if f.init and not f.kw_only),
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tuple(f for f in fields if f.init and f.kw_only)
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)
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def _tuple_str(obj_name, fields):
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# Return a string representing each field of obj_name as a tuple
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# member. So, if fields is ['x', 'y'] and obj_name is "self",
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# return "(self.x,self.y)".
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# Special case for the 0-tuple.
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if not fields:
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return '()'
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# Note the trailing comma, needed if this turns out to be a 1-tuple.
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return f'({",".join([f"{obj_name}.{f.name}" for f in fields])},)'
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class _FuncBuilder:
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def __init__(self, globals):
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self.names = []
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self.src = []
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self.globals = globals
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self.locals = {}
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self.overwrite_errors = {}
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self.unconditional_adds = {}
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def add_fn(self, name, args, body, *, locals=None, return_type=MISSING,
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overwrite_error=False, unconditional_add=False, decorator=None):
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if locals is not None:
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self.locals.update(locals)
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# Keep track if this method is allowed to be overwritten if it already
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# exists in the class. The error is method-specific, so keep it with
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# the name. We'll use this when we generate all of the functions in
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# the add_fns_to_class call. overwrite_error is either True, in which
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# case we'll raise an error, or it's a string, in which case we'll
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# raise an error and append this string.
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if overwrite_error:
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self.overwrite_errors[name] = overwrite_error
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# Should this function always overwrite anything that's already in the
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# class? The default is to not overwrite a function that already
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# exists.
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if unconditional_add:
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self.unconditional_adds[name] = True
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self.names.append(name)
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if return_type is not MISSING:
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self.locals[f'__dataclass_{name}_return_type__'] = return_type
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return_annotation = f'->__dataclass_{name}_return_type__'
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else:
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return_annotation = ''
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args = ','.join(args)
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body = '\n'.join(body)
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# Compute the text of the entire function, add it to the text we're generating.
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self.src.append(f'{f' {decorator}\n' if decorator else ''} def {name}({args}){return_annotation}:\n{body}')
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def add_fns_to_class(self, cls):
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# The source to all of the functions we're generating.
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fns_src = '\n'.join(self.src)
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# The locals they use.
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local_vars = ','.join(self.locals.keys())
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# The names of all of the functions, used for the return value of the
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# outer function. Need to handle the 0-tuple specially.
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if len(self.names) == 0:
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return_names = '()'
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else:
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return_names =f'({",".join(self.names)},)'
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# txt is the entire function we're going to execute, including the
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# bodies of the functions we're defining. Here's a greatly simplified
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# version:
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# def __create_fn__():
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# def __init__(self, x, y):
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# self.x = x
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# self.y = y
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# @recursive_repr
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# def __repr__(self):
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# return f"cls(x={self.x!r},y={self.y!r})"
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# return __init__,__repr__
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|
|
txt = f"def __create_fn__({local_vars}):\n{fns_src}\n return {return_names}"
|
|
ns = {}
|
|
exec(txt, self.globals, ns)
|
|
fns = ns['__create_fn__'](**self.locals)
|
|
|
|
# Now that we've generated the functions, assign them into cls.
|
|
for name, fn in zip(self.names, fns):
|
|
fn.__qualname__ = f"{cls.__qualname__}.{fn.__name__}"
|
|
if self.unconditional_adds.get(name, False):
|
|
setattr(cls, name, fn)
|
|
else:
|
|
already_exists = _set_new_attribute(cls, name, fn)
|
|
|
|
# See if it's an error to overwrite this particular function.
|
|
if already_exists and (msg_extra := self.overwrite_errors.get(name)):
|
|
error_msg = (f'Cannot overwrite attribute {fn.__name__} '
|
|
f'in class {cls.__name__}')
|
|
if not msg_extra is True:
|
|
error_msg = f'{error_msg} {msg_extra}'
|
|
|
|
raise TypeError(error_msg)
|
|
|
|
|
|
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, func_builder, 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 = None
|
|
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 = f
|
|
elif seen_default:
|
|
raise TypeError(f'non-default argument {f.name!r} '
|
|
f'follows default argument {seen_default.name!r}')
|
|
|
|
locals = {**{f'__dataclass_type_{f.name}__': f.type for f in fields},
|
|
**{'__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 concatenating the lists together).
|
|
_init_params += ['*']
|
|
_init_params += [_init_param(f) for f in kw_only_fields]
|
|
func_builder.add_fn('__init__',
|
|
[self_name] + _init_params,
|
|
body_lines,
|
|
locals=locals,
|
|
return_type=None)
|
|
|
|
|
|
def _frozen_get_del_attr(cls, fields, func_builder):
|
|
locals = {'cls': cls,
|
|
'FrozenInstanceError': FrozenInstanceError}
|
|
condition = 'type(self) is cls'
|
|
if fields:
|
|
condition += ' or name in {' + ', '.join(repr(f.name) for f in fields) + '}'
|
|
|
|
func_builder.add_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,
|
|
overwrite_error=True)
|
|
func_builder.add_fn('__delattr__',
|
|
('self', 'name'),
|
|
(f' if {condition}:',
|
|
' raise FrozenInstanceError(f"cannot delete field {name!r}")',
|
|
f' super(cls, self).__delattr__(name)'),
|
|
locals=locals,
|
|
overwrite_error=True)
|
|
|
|
|
|
def _is_classvar(a_type, typing):
|
|
return (a_type is typing.ClassVar
|
|
or (typing.get_origin(a_type) 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_new_attribute(cls, name, value):
|
|
# Never overwrites an existing attribute. Returns True if the
|
|
# attribute already exists.
|
|
if name in cls.__dict__:
|
|
return True
|
|
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, func_builder):
|
|
# It's sort of a hack that I'm setting this here, instead of at
|
|
# func_builder.add_fns_to_class time, but since this is an exceptional case
|
|
# (it's not setting an attribute to a function, but to a scalar value),
|
|
# just do it directly here. I might come to regret this.
|
|
cls.__hash__ = None
|
|
|
|
def _hash_add(cls, fields, func_builder):
|
|
flds = [f for f in fields if (f.compare if f.hash is None else f.hash)]
|
|
self_tuple = _tuple_str('self', flds)
|
|
func_builder.add_fn('__hash__',
|
|
('self',),
|
|
[f' return hash({self_tuple})'],
|
|
unconditional_add=True)
|
|
|
|
def _hash_exception(cls, fields, func_builder):
|
|
# 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 all or any of them are frozen.
|
|
any_frozen_base = False
|
|
# By default `all_frozen_bases` is `None` to represent a case,
|
|
# where some dataclasses does not have any bases with `_FIELDS`
|
|
all_frozen_bases = None
|
|
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 all_frozen_bases is None:
|
|
all_frozen_bases = True
|
|
current_frozen = getattr(b, _PARAMS).frozen
|
|
all_frozen_bases = all_frozen_bases and current_frozen
|
|
any_frozen_base = any_frozen_base or current_frozen
|
|
|
|
# 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 = annotationlib.get_annotations(
|
|
cls, format=annotationlib.Format.FORWARDREF)
|
|
|
|
# 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 all_frozen_bases is False 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's
|
|
# 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)
|
|
|
|
func_builder = _FuncBuilder(globals)
|
|
|
|
if init:
|
|
# Does this class have a post-init function?
|
|
has_post_init = hasattr(cls, _POST_INIT_NAME)
|
|
|
|
_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',
|
|
func_builder,
|
|
slots,
|
|
)
|
|
|
|
_set_new_attribute(cls, '__replace__', _replace)
|
|
|
|
# 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]
|
|
func_builder.add_fn('__repr__',
|
|
('self',),
|
|
[' return f"{self.__class__.__qualname__}(' +
|
|
', '.join([f"{f.name}={{self.{f.name}!r}}"
|
|
for f in flds]) + ')"'],
|
|
locals={'__dataclasses_recursive_repr': recursive_repr},
|
|
decorator="@__dataclasses_recursive_repr()")
|
|
|
|
if eq:
|
|
# Create __eq__ method. There's no need for a __ne__ method,
|
|
# since python will call __eq__ and negate it.
|
|
cmp_fields = (field for field in field_list if field.compare)
|
|
terms = [f'self.{field.name}==other.{field.name}' for field in cmp_fields]
|
|
field_comparisons = ' and '.join(terms) or 'True'
|
|
func_builder.add_fn('__eq__',
|
|
('self', 'other'),
|
|
[ ' if self is other:',
|
|
' return True',
|
|
' if other.__class__ is self.__class__:',
|
|
f' return {field_comparisons}',
|
|
' return NotImplemented'])
|
|
|
|
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__', '>='),
|
|
]:
|
|
# 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)'.
|
|
func_builder.add_fn(name,
|
|
('self', 'other'),
|
|
[ ' if other.__class__ is self.__class__:',
|
|
f' return {self_tuple}{op}{other_tuple}',
|
|
' return NotImplemented'],
|
|
overwrite_error='Consider using functools.total_ordering')
|
|
|
|
if frozen:
|
|
_frozen_get_del_attr(cls, field_list, func_builder)
|
|
|
|
# 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:
|
|
cls.__hash__ = hash_action(cls, field_list, func_builder)
|
|
|
|
# Generate the methods and add them to the class. This needs to be done
|
|
# before the __doc__ logic below, since inspect will look at the __init__
|
|
# signature.
|
|
func_builder.add_fns_to_class(cls)
|
|
|
|
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, fields)
|
|
|
|
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__'):
|
|
# `__dictoffset__` and `__weakrefoffset__` can tell us whether
|
|
# the base type has dict/weakref slots, in a way that works correctly
|
|
# for both Python classes and C extension types. Extension types
|
|
# don't use `__slots__` for slot creation
|
|
case None:
|
|
slots = []
|
|
if getattr(cls, '__weakrefoffset__', -1) != 0:
|
|
slots.append('__weakref__')
|
|
if getattr(cls, '__dictoffset__', -1) != 0:
|
|
slots.append('__dict__')
|
|
yield from slots
|
|
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 _update_func_cell_for__class__(f, oldcls, newcls):
|
|
# Returns True if we update a cell, else False.
|
|
if f is None:
|
|
# f will be None in the case of a property where not all of
|
|
# fget, fset, and fdel are used. Nothing to do in that case.
|
|
return False
|
|
try:
|
|
idx = f.__code__.co_freevars.index("__class__")
|
|
except ValueError:
|
|
# This function doesn't reference __class__, so nothing to do.
|
|
return False
|
|
# Fix the cell to point to the new class, if it's already pointing
|
|
# at the old class. I'm not convinced that the "is oldcls" test
|
|
# is needed, but other than performance can't hurt.
|
|
closure = f.__closure__[idx]
|
|
if closure.cell_contents is oldcls:
|
|
closure.cell_contents = newcls
|
|
return True
|
|
return False
|
|
|
|
|
|
def _create_slots(defined_fields, inherited_slots, field_names, weakref_slot):
|
|
# The slots for our class. Remove slots from our base classes. Add
|
|
# '__weakref__' if weakref_slot was given, unless it is already present.
|
|
seen_docs = False
|
|
slots = {}
|
|
for slot in 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 ()
|
|
)
|
|
):
|
|
doc = getattr(defined_fields.get(slot), 'doc', None)
|
|
if doc is not None:
|
|
seen_docs = True
|
|
slots.update({slot: doc})
|
|
|
|
# We only return dict if there's at least one doc member,
|
|
# otherwise we return tuple, which is the old default format.
|
|
if seen_docs:
|
|
return slots
|
|
return tuple(slots)
|
|
|
|
|
|
def _add_slots(cls, is_frozen, weakref_slot, defined_fields):
|
|
# Need to create a new class, since we can't set __slots__ after a
|
|
# class has been created, and the @dataclass decorator is called
|
|
# after the class is 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]))
|
|
)
|
|
|
|
cls_dict["__slots__"] = _create_slots(
|
|
defined_fields, inherited_slots, field_names, weakref_slot,
|
|
)
|
|
|
|
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)
|
|
newcls = type(cls)(cls.__name__, cls.__bases__, cls_dict)
|
|
if qualname is not None:
|
|
newcls.__qualname__ = qualname
|
|
|
|
if is_frozen:
|
|
# Need this for pickling frozen classes with slots.
|
|
if '__getstate__' not in cls_dict:
|
|
newcls.__getstate__ = _dataclass_getstate
|
|
if '__setstate__' not in cls_dict:
|
|
newcls.__setstate__ = _dataclass_setstate
|
|
|
|
# Fix up any closures which reference __class__. This is used to
|
|
# fix zero argument super so that it points to the correct class
|
|
# (the newly created one, which we're returning) and not the
|
|
# original class. We can break out of this loop as soon as we
|
|
# make an update, since all closures for a class will share a
|
|
# given cell.
|
|
for member in newcls.__dict__.values():
|
|
# If this is a wrapped function, unwrap it.
|
|
member = inspect.unwrap(member)
|
|
|
|
if isinstance(member, types.FunctionType):
|
|
if _update_func_cell_for__class__(member, cls, newcls):
|
|
break
|
|
elif isinstance(member, property):
|
|
if (_update_func_cell_for__class__(member.fget, cls, newcls)
|
|
or _update_func_cell_for__class__(member.fset, cls, newcls)
|
|
or _update_func_cell_for__class__(member.fdel, cls, newcls)):
|
|
break
|
|
|
|
return newcls
|
|
|
|
|
|
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):
|
|
obj_type = type(obj)
|
|
if obj_type in _ATOMIC_TYPES:
|
|
return obj
|
|
elif hasattr(obj_type, _FIELDS):
|
|
# dataclass instance: 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:
|
|
return dict_factory([
|
|
(f.name, _asdict_inner(getattr(obj, f.name), dict_factory))
|
|
for f in fields(obj)
|
|
])
|
|
# handle the builtin types first for speed; subclasses handled below
|
|
elif obj_type is list:
|
|
return [_asdict_inner(v, dict_factory) for v in obj]
|
|
elif obj_type is dict:
|
|
return {
|
|
_asdict_inner(k, dict_factory): _asdict_inner(v, dict_factory)
|
|
for k, v in obj.items()
|
|
}
|
|
elif obj_type is tuple:
|
|
return tuple([_asdict_inner(v, dict_factory) for v in obj])
|
|
elif issubclass(obj_type, tuple):
|
|
if 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 obj_type(*[_asdict_inner(v, dict_factory) for v in obj])
|
|
else:
|
|
return obj_type(_asdict_inner(v, dict_factory) for v in obj)
|
|
elif issubclass(obj_type, dict):
|
|
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(obj.default_factory)
|
|
for k, v in obj.items():
|
|
result[_asdict_inner(k, dict_factory)] = _asdict_inner(v, dict_factory)
|
|
return result
|
|
return obj_type((_asdict_inner(k, dict_factory),
|
|
_asdict_inner(v, dict_factory))
|
|
for k, v in obj.items())
|
|
elif issubclass(obj_type, list):
|
|
# Assume we can create an object of this type by passing in a
|
|
# generator
|
|
return obj_type(_asdict_inner(v, dict_factory) for v in obj)
|
|
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):
|
|
return tuple_factory([
|
|
_astuple_inner(getattr(obj, f.name), tuple_factory)
|
|
for f in fields(obj)
|
|
])
|
|
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, decorator=dataclass):
|
|
"""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 provided decorator.
|
|
return decorator(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
|
|
"""
|
|
if not _is_dataclass_instance(obj):
|
|
raise TypeError("replace() should be called on dataclass instances")
|
|
return _replace(obj, **changes)
|
|
|
|
|
|
def _replace(self, /, **changes):
|
|
# We're going to mutate 'changes', but that's okay because it's a
|
|
# new dict, even if called with 'replace(self, **my_changes)'.
|
|
|
|
# It's an error to have init=False fields in 'changes'.
|
|
# If a field is not in 'changes', read its value from the provided 'self'.
|
|
|
|
for f in getattr(self, _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 TypeError(f'field {f.name} is declared with '
|
|
f'init=False, it cannot be specified with '
|
|
f'replace()')
|
|
continue
|
|
|
|
if f.name not in changes:
|
|
if f._field_type is _FIELD_INITVAR and f.default is MISSING:
|
|
raise TypeError(f"InitVar {f.name!r} "
|
|
f'must be specified with replace()')
|
|
changes[f.name] = getattr(self, 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 self.__class__(**changes)
|