| import re |
| import sys |
| import copy |
| import types |
| import inspect |
| import keyword |
| import builtins |
| import functools |
| import _thread |
| |
| |
| __all__ = ['dataclass', |
| 'field', |
| 'Field', |
| 'FrozenInstanceError', |
| 'InitVar', |
| 'MISSING', |
| |
| # Helper functions. |
| 'fields', |
| 'asdict', |
| 'astuple', |
| 'make_dataclass', |
| 'replace', |
| 'is_dataclass', |
| ] |
| |
| # Conditions for adding methods. The boxes indicate what action the |
| # dataclass decorator takes. For all of these tables, when I talk |
| # about init=, repr=, eq=, order=, unsafe_hash=, or frozen=, I'm |
| # referring to the arguments to the @dataclass decorator. When |
| # checking if a dunder method already exists, I mean check for an |
| # entry in the class's __dict__. I never check to see if an attribute |
| # is defined in a base class. |
| |
| # Key: |
| # +=========+=========================================+ |
| # + Value | Meaning | |
| # +=========+=========================================+ |
| # | <blank> | No action: no method is added. | |
| # +---------+-----------------------------------------+ |
| # | add | Generated method is added. | |
| # +---------+-----------------------------------------+ |
| # | raise | TypeError is raised. | |
| # +---------+-----------------------------------------+ |
| # | None | Attribute is set to None. | |
| # +=========+=========================================+ |
| |
| # __init__ |
| # |
| # +--- init= parameter |
| # | |
| # v | | | |
| # | no | yes | <--- class has __init__ in __dict__? |
| # +=======+=======+=======+ |
| # | False | | | |
| # +-------+-------+-------+ |
| # | True | add | | <- the default |
| # +=======+=======+=======+ |
| |
| # __repr__ |
| # |
| # +--- repr= parameter |
| # | |
| # v | | | |
| # | no | yes | <--- class has __repr__ in __dict__? |
| # +=======+=======+=======+ |
| # | False | | | |
| # +-------+-------+-------+ |
| # | True | add | | <- the default |
| # +=======+=======+=======+ |
| |
| |
| # __setattr__ |
| # __delattr__ |
| # |
| # +--- frozen= parameter |
| # | |
| # v | | | |
| # | no | yes | <--- class has __setattr__ or __delattr__ in __dict__? |
| # +=======+=======+=======+ |
| # | False | | | <- the default |
| # +-------+-------+-------+ |
| # | True | add | raise | |
| # +=======+=======+=======+ |
| # Raise because not adding these methods would break the "frozen-ness" |
| # of the class. |
| |
| # __eq__ |
| # |
| # +--- eq= parameter |
| # | |
| # v | | | |
| # | no | yes | <--- class has __eq__ in __dict__? |
| # +=======+=======+=======+ |
| # | False | | | |
| # +-------+-------+-------+ |
| # | True | add | | <- the default |
| # +=======+=======+=======+ |
| |
| # __lt__ |
| # __le__ |
| # __gt__ |
| # __ge__ |
| # |
| # +--- order= parameter |
| # | |
| # v | | | |
| # | no | yes | <--- class has any comparison method in __dict__? |
| # +=======+=======+=======+ |
| # | False | | | <- the default |
| # +-------+-------+-------+ |
| # | True | add | raise | |
| # +=======+=======+=======+ |
| # Raise because to allow this case would interfere with using |
| # functools.total_ordering. |
| |
| # __hash__ |
| |
| # +------------------- unsafe_hash= parameter |
| # | +----------- eq= parameter |
| # | | +--- frozen= parameter |
| # | | | |
| # v v v | | | |
| # | no | yes | <--- class has explicitly defined __hash__ |
| # +=======+=======+=======+========+========+ |
| # | False | False | False | | | No __eq__, use the base class __hash__ |
| # +-------+-------+-------+--------+--------+ |
| # | False | False | True | | | No __eq__, use the base class __hash__ |
| # +-------+-------+-------+--------+--------+ |
| # | False | True | False | None | | <-- the default, not hashable |
| # +-------+-------+-------+--------+--------+ |
| # | False | True | True | add | | Frozen, so hashable, allows override |
| # +-------+-------+-------+--------+--------+ |
| # | True | False | False | add | raise | Has no __eq__, but hashable |
| # +-------+-------+-------+--------+--------+ |
| # | True | False | True | add | raise | Has no __eq__, but hashable |
| # +-------+-------+-------+--------+--------+ |
| # | True | True | False | add | raise | Not frozen, but hashable |
| # +-------+-------+-------+--------+--------+ |
| # | True | True | True | add | raise | Frozen, so hashable |
| # +=======+=======+=======+========+========+ |
| # For boxes that are blank, __hash__ is untouched and therefore |
| # inherited from the base class. If the base is object, then |
| # id-based hashing is used. |
| # |
| # Note that a class may already have __hash__=None if it specified an |
| # __eq__ method in the class body (not one that was created by |
| # @dataclass). |
| # |
| # See _hash_action (below) for a coded version of this table. |
| |
| |
| # Raised when an attempt is made to modify a frozen class. |
| class FrozenInstanceError(AttributeError): pass |
| |
| # A sentinel object for default values to signal that a default |
| # factory will be used. This is given a nice repr() which will appear |
| # in the function signature of dataclasses' constructors. |
| class _HAS_DEFAULT_FACTORY_CLASS: |
| def __repr__(self): |
| return '<factory>' |
| _HAS_DEFAULT_FACTORY = _HAS_DEFAULT_FACTORY_CLASS() |
| |
| # A sentinel object to detect if a parameter is supplied or not. Use |
| # a class to give it a better repr. |
| class _MISSING_TYPE: |
| pass |
| MISSING = _MISSING_TYPE() |
| |
| # Since most per-field metadata will be unused, create an empty |
| # read-only proxy that can be shared among all fields. |
| _EMPTY_METADATA = types.MappingProxyType({}) |
| |
| # Markers for the various kinds of fields and pseudo-fields. |
| class _FIELD_BASE: |
| def __init__(self, name): |
| self.name = name |
| def __repr__(self): |
| return self.name |
| _FIELD = _FIELD_BASE('_FIELD') |
| _FIELD_CLASSVAR = _FIELD_BASE('_FIELD_CLASSVAR') |
| _FIELD_INITVAR = _FIELD_BASE('_FIELD_INITVAR') |
| |
| # The name of an attribute on the class where we store the Field |
| # objects. Also used to check if a class is a Data Class. |
| _FIELDS = '__dataclass_fields__' |
| |
| # The name of an attribute on the class that stores the parameters to |
| # @dataclass. |
| _PARAMS = '__dataclass_params__' |
| |
| # The name of the function, that if it exists, is called at the end of |
| # __init__. |
| _POST_INIT_NAME = '__post_init__' |
| |
| # String regex that string annotations for ClassVar or InitVar must match. |
| # Allows "identifier.identifier[" or "identifier[". |
| # https://bugs.python.org/issue33453 for details. |
| _MODULE_IDENTIFIER_RE = re.compile(r'^(?:\s*(\w+)\s*\.)?\s*(\w+)') |
| |
| class InitVar: |
| __slots__ = ('type', ) |
| |
| def __init__(self, type): |
| self.type = type |
| |
| def __repr__(self): |
| return f'dataclasses.InitVar[{self.type.__name__}]' |
| |
| def __class_getitem__(cls, type): |
| return InitVar(type) |
| |
| |
| # Instances of Field are only ever created from within this module, |
| # and only from the field() function, although Field instances are |
| # exposed externally as (conceptually) read-only objects. |
| # |
| # name and type are filled in after the fact, not in __init__. |
| # They're not known at the time this class is instantiated, but it's |
| # convenient if they're available later. |
| # |
| # When cls._FIELDS is filled in with a list of Field objects, the name |
| # and type fields will have been populated. |
| class Field: |
| __slots__ = ('name', |
| 'type', |
| 'default', |
| 'default_factory', |
| 'repr', |
| 'hash', |
| 'init', |
| 'compare', |
| 'metadata', |
| '_field_type', # Private: not to be used by user code. |
| ) |
| |
| def __init__(self, default, default_factory, init, repr, hash, compare, |
| metadata): |
| self.name = None |
| self.type = None |
| self.default = default |
| self.default_factory = default_factory |
| self.init = init |
| self.repr = repr |
| self.hash = hash |
| self.compare = compare |
| self.metadata = (_EMPTY_METADATA |
| if metadata is None else |
| types.MappingProxyType(metadata)) |
| self._field_type = None |
| |
| def __repr__(self): |
| return ('Field(' |
| f'name={self.name!r},' |
| f'type={self.type!r},' |
| f'default={self.default!r},' |
| f'default_factory={self.default_factory!r},' |
| f'init={self.init!r},' |
| f'repr={self.repr!r},' |
| f'hash={self.hash!r},' |
| f'compare={self.compare!r},' |
| f'metadata={self.metadata!r},' |
| f'_field_type={self._field_type}' |
| ')') |
| |
| # This is used to support the PEP 487 __set_name__ protocol in the |
| # case where we're using a field that contains a descriptor as a |
| # default value. For details on __set_name__, see |
| # https://www.python.org/dev/peps/pep-0487/#implementation-details. |
| # |
| # Note that in _process_class, this Field object is overwritten |
| # with the default value, so the end result is a descriptor that |
| # had __set_name__ called on it at the right time. |
| def __set_name__(self, owner, name): |
| func = getattr(type(self.default), '__set_name__', None) |
| if func: |
| # There is a __set_name__ method on the descriptor, call |
| # it. |
| func(self.default, owner, name) |
| |
| |
| class _DataclassParams: |
| __slots__ = ('init', |
| 'repr', |
| 'eq', |
| 'order', |
| 'unsafe_hash', |
| 'frozen', |
| ) |
| |
| def __init__(self, init, repr, eq, order, unsafe_hash, frozen): |
| self.init = init |
| self.repr = repr |
| self.eq = eq |
| self.order = order |
| self.unsafe_hash = unsafe_hash |
| self.frozen = frozen |
| |
| def __repr__(self): |
| return ('_DataclassParams(' |
| f'init={self.init!r},' |
| f'repr={self.repr!r},' |
| f'eq={self.eq!r},' |
| f'order={self.order!r},' |
| f'unsafe_hash={self.unsafe_hash!r},' |
| f'frozen={self.frozen!r}' |
| ')') |
| |
| |
| # This function is used instead of exposing Field creation directly, |
| # so that a type checker can be told (via overloads) that this is a |
| # function whose type depends on its parameters. |
| def field(*, default=MISSING, default_factory=MISSING, init=True, repr=True, |
| hash=None, compare=True, metadata=None): |
| """Return an object to identify dataclass fields. |
| |
| default is the default value of the field. default_factory is a |
| 0-argument function called to initialize a field's value. If init |
| is True, the field will be a parameter to the class's __init__() |
| function. If repr is True, the field will be included in the |
| object's repr(). If hash is True, the field will be included in |
| the object's hash(). If compare is True, the field will be used |
| in comparison functions. metadata, if specified, must be a |
| mapping which is stored but not otherwise examined by dataclass. |
| |
| It is an error to specify both default and default_factory. |
| """ |
| |
| if default is not MISSING and default_factory is not MISSING: |
| raise ValueError('cannot specify both default and default_factory') |
| return Field(default, default_factory, init, repr, hash, compare, |
| metadata) |
| |
| |
| def _tuple_str(obj_name, fields): |
| # Return a string representing each field of obj_name as a tuple |
| # member. So, if fields is ['x', 'y'] and obj_name is "self", |
| # return "(self.x,self.y)". |
| |
| # Special case for the 0-tuple. |
| if not fields: |
| return '()' |
| # Note the trailing comma, needed if this turns out to be a 1-tuple. |
| return f'({",".join([f"{obj_name}.{f.name}" for f in fields])},)' |
| |
| |
| # This function's logic is copied from "recursive_repr" function in |
| # reprlib module to avoid dependency. |
| def _recursive_repr(user_function): |
| # Decorator to make a repr function return "..." for a recursive |
| # call. |
| repr_running = set() |
| |
| @functools.wraps(user_function) |
| def wrapper(self): |
| key = id(self), _thread.get_ident() |
| if key in repr_running: |
| return '...' |
| repr_running.add(key) |
| try: |
| result = user_function(self) |
| finally: |
| repr_running.discard(key) |
| return result |
| return wrapper |
| |
| |
| def _create_fn(name, args, body, *, globals=None, locals=None, |
| return_type=MISSING): |
| # Note that we mutate locals when exec() is called. Caller |
| # beware! The only callers are internal to this module, so no |
| # worries about external callers. |
| if locals is None: |
| locals = {} |
| # __builtins__ may be the "builtins" module or |
| # the value of its "__dict__", |
| # so make sure "__builtins__" is the module. |
| if globals is not None and '__builtins__' not in globals: |
| globals['__builtins__'] = builtins |
| return_annotation = '' |
| if return_type is not MISSING: |
| locals['_return_type'] = return_type |
| return_annotation = '->_return_type' |
| args = ','.join(args) |
| body = '\n'.join(f' {b}' for b in body) |
| |
| # Compute the text of the entire function. |
| txt = f'def {name}({args}){return_annotation}:\n{body}' |
| |
| exec(txt, globals, locals) |
| return locals[name] |
| |
| |
| def _field_assign(frozen, name, value, self_name): |
| # If we're a frozen class, then assign to our fields in __init__ |
| # via object.__setattr__. Otherwise, just use a simple |
| # assignment. |
| # |
| # self_name is what "self" is called in this function: don't |
| # hard-code "self", since that might be a field name. |
| if frozen: |
| return f'__builtins__.object.__setattr__({self_name},{name!r},{value})' |
| 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): |
| fn = _create_fn('__repr__', |
| ('self',), |
| ['return self.__class__.__qualname__ + f"(' + |
| ', '.join([f"{f.name}={{self.{f.name}!r}}" |
| for f in fields]) + |
| ')"']) |
| return _recursive_repr(fn) |
| |
| |
| 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 (a_type is typing.ClassVar |
| or (type(a_type) is typing._GenericAlias |
| and a_type.__origin__ is typing.ClassVar)) |
| |
| |
| def _is_initvar(a_type, dataclasses): |
| # The module we're checking against is the module we're |
| # currently in (dataclasses.py). |
| return (a_type is dataclasses.InitVar |
| or type(a_type) is dataclasses.InitVar) |
| |
| |
| def _is_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 |
| |
| |
| 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 hasattr(type(obj), _FIELDS) |
| |
| |
| def is_dataclass(obj): |
| """Returns True if obj is a dataclass or an instance of a |
| dataclass.""" |
| cls = obj if isinstance(obj, type) else type(obj) |
| return hasattr(cls, _FIELDS) |
| |
| |
| def asdict(obj, *, dict_factory=dict): |
| """Return the fields of a dataclass instance as a new dictionary mapping |
| field names to field values. |
| |
| Example usage: |
| |
| @dataclass |
| class C: |
| x: int |
| y: int |
| |
| c = C(1, 2) |
| assert asdict(c) == {'x': 1, 'y': 2} |
| |
| If given, 'dict_factory' will be used instead of built-in dict. |
| The function applies recursively to field values that are |
| dataclass instances. This will also look into built-in containers: |
| tuples, lists, and dicts. |
| """ |
| 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, tuple) and hasattr(obj, '_fields'): |
| # obj is a namedtuple. Recurse into it, but the returned |
| # object is another namedtuple of the same type. This is |
| # similar to how other list- or tuple-derived classes are |
| # treated (see below), but we just need to create them |
| # differently because a namedtuple's __init__ needs to be |
| # called differently (see bpo-34363). |
| |
| # I'm not using namedtuple's _asdict() |
| # method, because: |
| # - it does not recurse in to the namedtuple fields and |
| # convert them to dicts (using dict_factory). |
| # - I don't actually want to return a dict here. The the main |
| # use case here is json.dumps, and it handles converting |
| # namedtuples to lists. Admittedly we're losing some |
| # information here when we produce a json list instead of a |
| # dict. Note that if we returned dicts here instead of |
| # namedtuples, we could no longer call asdict() on a data |
| # structure where a namedtuple was used as a dict key. |
| |
| return type(obj)(*[_asdict_inner(v, dict_factory) for v in obj]) |
| elif isinstance(obj, (list, tuple)): |
| # Assume we can create an object of this type by passing in a |
| # generator (which is not true for namedtuples, handled |
| # above). |
| return type(obj)(_asdict_inner(v, dict_factory) for v in obj) |
| elif isinstance(obj, dict): |
| 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, tuple) and hasattr(obj, '_fields'): |
| # obj is a namedtuple. Recurse into it, but the returned |
| # object is another namedtuple of the same type. This is |
| # similar to how other list- or tuple-derived classes are |
| # treated (see below), but we just need to create them |
| # differently because a namedtuple's __init__ needs to be |
| # called differently (see bpo-34363). |
| return type(obj)(*[_astuple_inner(v, tuple_factory) for v in obj]) |
| elif isinstance(obj, (list, tuple)): |
| # Assume we can create an object of this type by passing in a |
| # generator (which is not true for namedtuples, handled |
| # above). |
| return type(obj)(_astuple_inner(v, tuple_factory) for v in obj) |
| elif isinstance(obj, dict): |
| 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 identifiers: {name!r}') |
| if keyword.iskeyword(name): |
| raise TypeError(f'Field names must not be keywords: {name!r}') |
| if name in seen: |
| raise TypeError(f'Field name duplicated: {name!r}') |
| |
| seen.add(name) |
| 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) |