1185 lines
44 KiB
Python
1185 lines
44 KiB
Python
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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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__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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'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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# 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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# 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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class _InitVarMeta(type):
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def __getitem__(self, params):
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return self
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class InitVar(metaclass=_InitVarMeta):
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pass
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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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'_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):
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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 or len(metadata) == 0 else
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types.MappingProxyType(metadata))
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self._field_type = None
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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'_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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# defaul value. For details on __set_name__, see
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# https://www.python.org/dev/peps/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 _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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)
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def __init__(self, init, repr, eq, order, unsafe_hash, frozen):
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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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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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')')
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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):
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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
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the object's hash(). If compare is True, the field will be used
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in comparison functions. metadata, if specified, must be a
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mapping which is stored but not otherwise examined by dataclass.
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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)
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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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def _create_fn(name, args, body, *, globals=None, locals=None,
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return_type=MISSING):
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# Note that we mutate locals when exec() is called. Caller
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# beware! The only callers are internal to this module, so no
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# worries about external callers.
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if locals is None:
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locals = {}
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return_annotation = ''
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if return_type is not MISSING:
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locals['_return_type'] = return_type
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return_annotation = '->_return_type'
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args = ','.join(args)
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body = '\n'.join(f' {b}' for b in body)
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# Compute the text of the entire function.
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txt = f'def {name}({args}){return_annotation}:\n{body}'
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exec(txt, globals, locals)
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return locals[name]
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def _field_assign(frozen, name, value, self_name):
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# If we're a frozen class, then assign to our fields in __init__
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# via object.__setattr__. Otherwise, just use a simple
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# assignment.
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#
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# self_name is what "self" is called in this function: don't
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||
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# hard-code "self", since that might be a field name.
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if frozen:
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return f'object.__setattr__({self_name},{name!r},{value})'
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|
return f'{self_name}.{name}={value}'
|
||
|
|
|
||
|
|
|
||
|
|
def _field_init(f, frozen, globals, self_name):
|
||
|
|
# Return the text of the line in the body of __init__ that will
|
||
|
|
# initialize this field.
|
||
|
|
|
||
|
|
default_name = f'_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 _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:
|
||
|
|
# This field does not need initialization. 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'=_dflt_{f.name}'
|
||
|
|
elif f.default_factory is not MISSING:
|
||
|
|
# There's a factory function. Set a marker.
|
||
|
|
default = '=_HAS_DEFAULT_FACTORY'
|
||
|
|
return f'{f.name}:_type_{f.name}{default}'
|
||
|
|
|
||
|
|
|
||
|
|
def _init_fn(fields, frozen, has_post_init, self_name):
|
||
|
|
# 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 fields:
|
||
|
|
# Only consider 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')
|
||
|
|
|
||
|
|
globals = {'MISSING': MISSING,
|
||
|
|
'_HAS_DEFAULT_FACTORY': _HAS_DEFAULT_FACTORY}
|
||
|
|
|
||
|
|
body_lines = []
|
||
|
|
for f in fields:
|
||
|
|
line = _field_init(f, frozen, globals, self_name)
|
||
|
|
# 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']
|
||
|
|
|
||
|
|
locals = {f'_type_{f.name}': f.type for f in fields}
|
||
|
|
return _create_fn('__init__',
|
||
|
|
[self_name] + [_init_param(f) for f in fields if f.init],
|
||
|
|
body_lines,
|
||
|
|
locals=locals,
|
||
|
|
globals=globals,
|
||
|
|
return_type=None)
|
||
|
|
|
||
|
|
|
||
|
|
def _repr_fn(fields):
|
||
|
|
return _create_fn('__repr__',
|
||
|
|
('self',),
|
||
|
|
['return self.__class__.__qualname__ + f"(' +
|
||
|
|
', '.join([f"{f.name}={{self.{f.name}!r}}"
|
||
|
|
for f in fields]) +
|
||
|
|
')"'])
|
||
|
|
|
||
|
|
|
||
|
|
def _frozen_get_del_attr(cls, fields):
|
||
|
|
# XXX: globals is modified on the first call to _create_fn, then
|
||
|
|
# the modified version is used in the second call. Is this okay?
|
||
|
|
globals = {'cls': cls,
|
||
|
|
'FrozenInstanceError': FrozenInstanceError}
|
||
|
|
if fields:
|
||
|
|
fields_str = '(' + ','.join(repr(f.name) for f in fields) + ',)'
|
||
|
|
else:
|
||
|
|
# Special case for the zero-length tuple.
|
||
|
|
fields_str = '()'
|
||
|
|
return (_create_fn('__setattr__',
|
||
|
|
('self', 'name', 'value'),
|
||
|
|
(f'if type(self) is cls or name in {fields_str}:',
|
||
|
|
' raise FrozenInstanceError(f"cannot assign to field {name!r}")',
|
||
|
|
f'super(cls, self).__setattr__(name, value)'),
|
||
|
|
globals=globals),
|
||
|
|
_create_fn('__delattr__',
|
||
|
|
('self', 'name'),
|
||
|
|
(f'if type(self) is cls or name in {fields_str}:',
|
||
|
|
' raise FrozenInstanceError(f"cannot delete field {name!r}")',
|
||
|
|
f'super(cls, self).__delattr__(name)'),
|
||
|
|
globals=globals),
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def _cmp_fn(name, op, self_tuple, other_tuple):
|
||
|
|
# 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'])
|
||
|
|
|
||
|
|
|
||
|
|
def _hash_fn(fields):
|
||
|
|
self_tuple = _tuple_str('self', fields)
|
||
|
|
return _create_fn('__hash__',
|
||
|
|
('self',),
|
||
|
|
[f'return hash({self_tuple})'])
|
||
|
|
|
||
|
|
|
||
|
|
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 type(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
|
||
|
|
|
||
|
|
|
||
|
|
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):
|
||
|
|
# Return a Field object for this field name and type. ClassVars
|
||
|
|
# and InitVars are also returned, but marked as such (see
|
||
|
|
# f._field_type).
|
||
|
|
|
||
|
|
# 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 stirng
|
||
|
|
# 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>.
|
||
|
|
|
||
|
|
# For real fields, disallow mutable defaults for known types.
|
||
|
|
if f._field_type is _FIELD and isinstance(f.default, (list, dict, set)):
|
||
|
|
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):
|
||
|
|
return None
|
||
|
|
|
||
|
|
def _hash_add(cls, fields):
|
||
|
|
flds = [f for f in fields if (f.compare if f.hash is None else f.hash)]
|
||
|
|
return _hash_fn(flds)
|
||
|
|
|
||
|
|
def _hash_exception(cls, fields):
|
||
|
|
# 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):
|
||
|
|
# 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 = {}
|
||
|
|
|
||
|
|
setattr(cls, _PARAMS, _DataclassParams(init, repr, eq, order,
|
||
|
|
unsafe_hash, frozen))
|
||
|
|
|
||
|
|
# 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:
|
||
|
|
has_dataclass_bases = True
|
||
|
|
for f in base_fields.values():
|
||
|
|
fields[f.name] = f
|
||
|
|
if getattr(b, _PARAMS).frozen:
|
||
|
|
any_frozen_base = True
|
||
|
|
|
||
|
|
# Annotations that are defined in this class (not in base
|
||
|
|
# classes). If __annotations__ isn't present, then this class
|
||
|
|
# adds no new annotations. We use this to compute fields that are
|
||
|
|
# added by this class.
|
||
|
|
#
|
||
|
|
# 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 = cls.__dict__.get('__annotations__', {})
|
||
|
|
|
||
|
|
# 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_field(cls, name, type)
|
||
|
|
for name, type in cls_annotations.items()]
|
||
|
|
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')
|
||
|
|
|
||
|
|
if init:
|
||
|
|
# Does this class have a post-init function?
|
||
|
|
has_post_init = hasattr(cls, _POST_INIT_NAME)
|
||
|
|
|
||
|
|
# Include InitVars and regular fields (so, not ClassVars).
|
||
|
|
flds = [f for f in fields.values()
|
||
|
|
if f._field_type in (_FIELD, _FIELD_INITVAR)]
|
||
|
|
_set_new_attribute(cls, '__init__',
|
||
|
|
_init_fn(flds,
|
||
|
|
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',
|
||
|
|
))
|
||
|
|
|
||
|
|
# 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))
|
||
|
|
|
||
|
|
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))
|
||
|
|
|
||
|
|
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)):
|
||
|
|
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):
|
||
|
|
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)
|
||
|
|
|
||
|
|
if not getattr(cls, '__doc__'):
|
||
|
|
# Create a class doc-string.
|
||
|
|
cls.__doc__ = (cls.__name__ +
|
||
|
|
str(inspect.signature(cls)).replace(' -> None', ''))
|
||
|
|
|
||
|
|
return cls
|
||
|
|
|
||
|
|
|
||
|
|
# _cls should never be specified by keyword, so start it with an
|
||
|
|
# underscore. The presence of _cls is used to detect if this
|
||
|
|
# decorator is being called with parameters or not.
|
||
|
|
def dataclass(_cls=None, *, init=True, repr=True, eq=True, order=False,
|
||
|
|
unsafe_hash=False, frozen=False):
|
||
|
|
"""Returns the same class as was passed in, with dunder methods
|
||
|
|
added 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 function is added. If frozen is true, fields may
|
||
|
|
not be assigned to after instance creation.
|
||
|
|
"""
|
||
|
|
|
||
|
|
def wrap(cls):
|
||
|
|
return _process_class(cls, init, repr, eq, order, unsafe_hash, frozen)
|
||
|
|
|
||
|
|
# 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')
|
||
|
|
|
||
|
|
# 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 not isinstance(obj, type) and hasattr(obj, _FIELDS)
|
||
|
|
|
||
|
|
|
||
|
|
def is_dataclass(obj):
|
||
|
|
"""Returns True if obj is a dataclass or an instance of a
|
||
|
|
dataclass."""
|
||
|
|
return hasattr(obj, _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.
|
||
|
|
"""
|
||
|
|
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 _is_dataclass_instance(obj):
|
||
|
|
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, (list, tuple)):
|
||
|
|
return type(obj)(_asdict_inner(v, dict_factory) for v in obj)
|
||
|
|
elif isinstance(obj, dict):
|
||
|
|
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.
|
||
|
|
"""
|
||
|
|
|
||
|
|
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 _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, (list, tuple)):
|
||
|
|
return type(obj)(_astuple_inner(v, tuple_factory) for v in obj)
|
||
|
|
elif isinstance(obj, dict):
|
||
|
|
return type(obj)((_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):
|
||
|
|
"""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, and frozen are passed to
|
||
|
|
dataclass().
|
||
|
|
"""
|
||
|
|
|
||
|
|
if namespace is None:
|
||
|
|
namespace = {}
|
||
|
|
else:
|
||
|
|
# Copy namespace since we're going to mutate it.
|
||
|
|
namespace = namespace.copy()
|
||
|
|
|
||
|
|
# While we're looking through the field names, validate that they
|
||
|
|
# are identifiers, are not keywords, and not duplicates.
|
||
|
|
seen = set()
|
||
|
|
anns = {}
|
||
|
|
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
|
||
|
|
namespace[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 identifers: {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)
|
||
|
|
anns[name] = tp
|
||
|
|
|
||
|
|
namespace['__annotations__'] = anns
|
||
|
|
# We use `types.new_class()` instead of simply `type()` to allow dynamic creation
|
||
|
|
# of generic dataclassses.
|
||
|
|
cls = types.new_class(cls_name, bases, {}, lambda ns: ns.update(namespace))
|
||
|
|
return dataclass(cls, init=init, repr=repr, eq=eq, order=order,
|
||
|
|
unsafe_hash=unsafe_hash, frozen=frozen)
|
||
|
|
|
||
|
|
|
||
|
|
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:
|
||
|
|
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)
|