mirror of https://github.com/python/cpython
799 lines
29 KiB
Python
799 lines
29 KiB
Python
import sys
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import types
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from copy import deepcopy
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import inspect
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__all__ = ['dataclass',
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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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# 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
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# default-factory will be used.
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# This is given a nice repr() which will appear in the function
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# 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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_FIELD = object() # An actual field.
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_FIELD_CLASSVAR = object() # Not a field, but a ClassVar.
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_FIELD_INITVAR = object() # Not a field, but an 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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_MARKER = '__dataclass_fields__'
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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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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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# name and type are filled in after the fact, not in __init__. They're
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# 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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# When cls._MARKER 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},'
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f'default={self.default},'
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f'default_factory={self.default_factory},'
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f'init={self.init},'
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f'repr={self.repr},'
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f'hash={self.hash},'
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f'compare={self.compare},'
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f'metadata={self.metadata}'
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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 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.
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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 len(fields) == 0:
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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 beware!
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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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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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# self_name is what "self" is called in this function: don't
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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}'
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def _field_init(f, frozen, globals, self_name):
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# Return the text of the line in the body of __init__ that will
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# initialize this field.
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default_name = f'_dflt_{f.name}'
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if f.default_factory is not MISSING:
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if f.init:
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# This field has a default factory. If a parameter is
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# given, use it. If not, call the factory.
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globals[default_name] = f.default_factory
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value = (f'{default_name}() '
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f'if {f.name} is _HAS_DEFAULT_FACTORY '
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f'else {f.name}')
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else:
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# This is a field that's not in the __init__ params, but
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# has a default factory function. It needs to be
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# initialized here by calling the factory function,
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# because there's no other way to initialize it.
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# For a field initialized with a default=defaultvalue, the
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# class dict just has the default value
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# (cls.fieldname=defaultvalue). But that won't work for a
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# default factory, the factory must be called in __init__
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# and we must assign that to self.fieldname. We can't
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# fall back to the class dict's value, both because it's
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# not set, and because it might be different per-class
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# (which, after all, is why we have a factory function!).
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globals[default_name] = f.default_factory
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value = f'{default_name}()'
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else:
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# No default factory.
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if f.init:
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if f.default is MISSING:
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# There's no default, just do an assignment.
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value = f.name
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elif f.default is not MISSING:
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globals[default_name] = f.default
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value = f.name
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else:
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# This field does not need initialization. Signify that to
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# the caller by returning None.
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return None
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# Only test this now, so that we can create variables for the
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# default. However, return None to signify that we're not going
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# to actually do the assignment statement for InitVars.
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if f._field_type == _FIELD_INITVAR:
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return None
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# Now, actually generate the field assignment.
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return _field_assign(frozen, f.name, value, self_name)
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def _init_param(f):
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# Return the __init__ parameter string for this field.
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# For example, the equivalent of 'x:int=3' (except instead of 'int',
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# reference a variable set to int, and instead of '3', reference a
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# variable set to 3).
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if f.default is MISSING and f.default_factory is MISSING:
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# There's no default, and no default_factory, just
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# output the variable name and type.
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default = ''
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elif f.default is not MISSING:
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# There's a default, this will be the name that's used to look it up.
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default = f'=_dflt_{f.name}'
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elif f.default_factory is not MISSING:
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# There's a factory function. Set a marker.
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default = '=_HAS_DEFAULT_FACTORY'
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return f'{f.name}:_type_{f.name}{default}'
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def _init_fn(fields, frozen, has_post_init, self_name):
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# fields contains both real fields and InitVar pseudo-fields.
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# Make sure we don't have fields without defaults following fields
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# with defaults. This actually would be caught when exec-ing the
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# function source code, but catching it here gives a better error
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# message, and future-proofs us in case we build up the function
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# using ast.
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seen_default = False
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for f in fields:
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# Only consider fields in the __init__ call.
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if f.init:
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if not (f.default is MISSING and f.default_factory is MISSING):
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seen_default = True
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elif seen_default:
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raise TypeError(f'non-default argument {f.name!r} '
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'follows default argument')
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globals = {'MISSING': MISSING,
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'_HAS_DEFAULT_FACTORY': _HAS_DEFAULT_FACTORY}
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body_lines = []
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for f in fields:
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# Do not initialize the pseudo-fields, only the real ones.
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line = _field_init(f, frozen, globals, self_name)
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if line is not None:
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# line is None means that this field doesn't require
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# initialization. Just skip it.
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body_lines.append(line)
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# Does this class have a post-init function?
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if has_post_init:
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params_str = ','.join(f.name for f in fields
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if f._field_type is _FIELD_INITVAR)
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body_lines += [f'{self_name}.{_POST_INIT_NAME}({params_str})']
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# If no body lines, use 'pass'.
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if len(body_lines) == 0:
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body_lines = ['pass']
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locals = {f'_type_{f.name}': f.type for f in fields}
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return _create_fn('__init__',
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[self_name] +[_init_param(f) for f in fields if f.init],
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body_lines,
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locals=locals,
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globals=globals,
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return_type=None)
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def _repr_fn(fields):
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return _create_fn('__repr__',
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['self'],
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['return self.__class__.__qualname__ + f"(' +
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', '.join([f"{f.name}={{self.{f.name}!r}}"
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for f in fields]) +
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')"'])
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def _frozen_setattr(self, name, value):
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raise FrozenInstanceError(f'cannot assign to field {name!r}')
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def _frozen_delattr(self, name):
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raise FrozenInstanceError(f'cannot delete field {name!r}')
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def _cmp_fn(name, op, self_tuple, other_tuple):
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# Create a comparison function. If the fields in the object are
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# named 'x' and 'y', then self_tuple is the string
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# '(self.x,self.y)' and other_tuple is the string
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# '(other.x,other.y)'.
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return _create_fn(name,
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['self', 'other'],
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[ 'if other.__class__ is self.__class__:',
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f' return {self_tuple}{op}{other_tuple}',
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'return NotImplemented'])
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def _set_eq_fns(cls, fields):
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# Create and set the equality comparison methods on cls.
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# Pre-compute self_tuple and other_tuple, then re-use them for
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# each function.
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self_tuple = _tuple_str('self', fields)
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other_tuple = _tuple_str('other', fields)
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for name, op in [('__eq__', '=='),
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('__ne__', '!='),
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]:
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_set_attribute(cls, name, _cmp_fn(name, op, self_tuple, other_tuple))
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def _set_order_fns(cls, fields):
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# Create and set the ordering methods on cls.
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# Pre-compute self_tuple and other_tuple, then re-use them for
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# each function.
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self_tuple = _tuple_str('self', fields)
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other_tuple = _tuple_str('other', fields)
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for name, op in [('__lt__', '<'),
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('__le__', '<='),
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('__gt__', '>'),
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('__ge__', '>='),
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]:
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_set_attribute(cls, name, _cmp_fn(name, op, self_tuple, other_tuple))
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def _hash_fn(fields):
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self_tuple = _tuple_str('self', fields)
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return _create_fn('__hash__',
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['self'],
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[f'return hash({self_tuple})'])
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def _get_field(cls, a_name, a_type):
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# Return a Field object, for this field name and type. ClassVars
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# and InitVars are also returned, but marked as such (see
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# f._field_type).
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# If the default value isn't derived from field, then it's
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# only a normal default value. Convert it to a Field().
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default = getattr(cls, a_name, MISSING)
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if isinstance(default, Field):
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f = default
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else:
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f = field(default=default)
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# Assume it's a normal field until proven otherwise.
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f._field_type = _FIELD
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# Only at this point do we know the name and the type. Set them.
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f.name = a_name
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f.type = a_type
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# If typing has not been imported, then it's impossible for
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# any annotation to be a ClassVar. So, only look for ClassVar
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# if typing has been imported.
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typing = sys.modules.get('typing')
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if typing is not None:
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# This test uses a typing internal class, but it's the best
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# way to test if this is a ClassVar.
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if (type(a_type) is typing._GenericAlias and
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a_type.__origin__ is typing.ClassVar):
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# This field is a ClassVar, so it's not a field.
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f._field_type = _FIELD_CLASSVAR
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if f._field_type is _FIELD:
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# Check if this is an InitVar.
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if a_type is InitVar:
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# InitVars are not fields, either.
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f._field_type = _FIELD_INITVAR
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# Validations for fields. This is delayed until now, instead of
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# in the Field() constructor, since only here do we know the field
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# name, which allows better error reporting.
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# Special restrictions for ClassVar and InitVar.
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if f._field_type in (_FIELD_CLASSVAR, _FIELD_INITVAR):
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if f.default_factory is not MISSING:
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raise TypeError(f'field {f.name} cannot have a '
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'default factory')
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# Should I check for other field settings? default_factory
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# seems the most serious to check for. Maybe add others. For
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# example, how about init=False (or really,
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# init=<not-the-default-init-value>)? It makes no sense for
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# ClassVar and InitVar to specify init=<anything>.
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# For real fields, disallow mutable defaults for known types.
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if f._field_type is _FIELD and isinstance(f.default, (list, dict, set)):
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raise ValueError(f'mutable default {type(f.default)} for field '
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f'{f.name} is not allowed: use default_factory')
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return f
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def _find_fields(cls):
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# Return a list of Field objects, in order, for this class (and no
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# base classes). Fields are found from __annotations__ (which is
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# guaranteed to be ordered). Default values are from class
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# attributes, if a field has a default. If the default value is
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# a Field(), then it contains additional info beyond (and
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# possibly including) the actual default value. Pseudo-fields
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# ClassVars and InitVars are included, despite the fact that
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# they're not real fields. That's deal with later.
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annotations = getattr(cls, '__annotations__', {})
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return [_get_field(cls, a_name, a_type)
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for a_name, a_type in annotations.items()]
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def _set_attribute(cls, name, value):
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# Raise TypeError if an attribute by this name already exists.
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if name in cls.__dict__:
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raise TypeError(f'Cannot overwrite attribute {name} '
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f'in {cls.__name__}')
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setattr(cls, name, value)
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def _process_class(cls, repr, eq, order, hash, init, frozen):
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# Now that dicts retain insertion order, there's no reason to use
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# an ordered dict. I am leveraging that ordering here, because
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# derived class fields overwrite base class fields, but the order
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# is defined by the base class, which is found first.
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fields = {}
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# Find our base classes in reverse MRO order, and exclude
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# ourselves. In reversed order so that more derived classes
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# override earlier field definitions in base classes.
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for b in cls.__mro__[-1:0:-1]:
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# Only process classes that have been processed by our
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# decorator. That is, they have a _MARKER attribute.
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base_fields = getattr(b, _MARKER, None)
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if base_fields:
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for f in base_fields.values():
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fields[f.name] = f
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# Now find fields in our class. While doing so, validate some
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# things, and set the default values (as class attributes)
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# where we can.
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for f in _find_fields(cls):
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fields[f.name] = f
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# If the class attribute (which is the default value for
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# this field) exists and is of type 'Field', replace it
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# with the real default. This is so that normal class
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# introspection sees a real default value, not a Field.
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if isinstance(getattr(cls, f.name, None), Field):
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if f.default is MISSING:
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# If there's no default, delete the class attribute.
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# This happens if we specify field(repr=False), for
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# example (that is, we specified a field object, but
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# no default value). Also if we're using a default
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# factory. The class attribute should not be set at
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# all in the post-processed class.
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delattr(cls, f.name)
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else:
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setattr(cls, f.name, f.default)
|
|
|
|
# Remember all of the fields on our class (including bases). This
|
|
# marks this class as being a dataclass.
|
|
setattr(cls, _MARKER, fields)
|
|
|
|
# We also need to check if a parent class is frozen: frozen has to
|
|
# be inherited down.
|
|
is_frozen = frozen or cls.__setattr__ is _frozen_setattr
|
|
|
|
# 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).
|
|
_set_attribute(cls, '__init__',
|
|
_init_fn(list(filter(lambda f: f._field_type
|
|
in (_FIELD, _FIELD_INITVAR),
|
|
fields.values())),
|
|
is_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 = list(filter(lambda f: f._field_type is _FIELD,
|
|
fields.values()))
|
|
|
|
if repr:
|
|
_set_attribute(cls, '__repr__',
|
|
_repr_fn(list(filter(lambda f: f.repr, field_list))))
|
|
|
|
if is_frozen:
|
|
_set_attribute(cls, '__setattr__', _frozen_setattr)
|
|
_set_attribute(cls, '__delattr__', _frozen_delattr)
|
|
|
|
generate_hash = False
|
|
if hash is None:
|
|
if eq and frozen:
|
|
# Generate a hash function.
|
|
generate_hash = True
|
|
elif eq and not frozen:
|
|
# Not hashable.
|
|
_set_attribute(cls, '__hash__', None)
|
|
elif not eq:
|
|
# Otherwise, use the base class definition of hash(). That is,
|
|
# don't set anything on this class.
|
|
pass
|
|
else:
|
|
assert "can't get here"
|
|
else:
|
|
generate_hash = hash
|
|
if generate_hash:
|
|
_set_attribute(cls, '__hash__',
|
|
_hash_fn(list(filter(lambda f: f.compare
|
|
if f.hash is None
|
|
else f.hash,
|
|
field_list))))
|
|
|
|
if eq:
|
|
# Create and __eq__ and __ne__ methods.
|
|
_set_eq_fns(cls, list(filter(lambda f: f.compare, field_list)))
|
|
|
|
if order:
|
|
# Create and __lt__, __le__, __gt__, and __ge__ methods.
|
|
# Create and set the comparison functions.
|
|
_set_order_fns(cls, list(filter(lambda f: f.compare, 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,
|
|
hash=None, 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 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, repr, eq, order, hash, init, 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, _MARKER)
|
|
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, _MARKER)
|
|
|
|
|
|
def is_dataclass(obj):
|
|
"""Returns True if obj is a dataclass or an instance of a
|
|
dataclass."""
|
|
return hasattr(obj, _MARKER)
|
|
|
|
|
|
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 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 deepcopy(obj)
|
|
|
|
|
|
def make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True,
|
|
repr=True, eq=True, order=False, hash=None, 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, 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()
|
|
|
|
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
|
|
anns[name] = tp
|
|
|
|
namespace['__annotations__'] = anns
|
|
cls = type(cls_name, bases, namespace)
|
|
return dataclass(cls, init=init, repr=repr, eq=eq, order=order,
|
|
hash=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, _MARKER).values():
|
|
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:
|
|
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)
|