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cpython/Lib/dataclasses.py

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import sys
import types
from copy import deepcopy
import inspect
__all__ = ['dataclass',
'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 have already __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.
_FIELD = object() # An actual field.
_FIELD_CLASSVAR = object() # Not a field, but a ClassVar.
_FIELD_INITVAR = object() # Not a field, but an 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.
_MARKER = '__dataclass_fields__'
# The name of the function, that if it exists, is called at the end of
# __init__.
_POST_INIT_NAME = '__post_init__'
class _InitVarMeta(type):
def __getitem__(self, params):
return self
class InitVar(metaclass=_InitVarMeta):
pass
# 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._MARKER 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 or len(metadata) == 0 else
types.MappingProxyType(metadata))
self._field_type = None
def __repr__(self):
return ('Field('
f'name={self.name!r},'
f'type={self.type},'
f'default={self.default},'
f'default_factory={self.default_factory},'
f'init={self.init},'
f'repr={self.repr},'
f'hash={self.hash},'
f'compare={self.compare},'
f'metadata={self.metadata}'
')')
# 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])},)'
def _create_fn(name, args, body, *, globals=None, locals=None,
return_type=MISSING):
# Note that we mutate locals when exec() is called. Caller beware!
if locals is None:
locals = {}
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)
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'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 == _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:
# Do not initialize the pseudo-fields, only the real ones.
line = _field_init(f, frozen, globals, self_name)
if line is not None:
# line is None means that this field doesn't require
# initialization. Just skip it.
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 += [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_setattr(self, name, value):
raise FrozenInstanceError(f'cannot assign to field {name!r}')
def _frozen_delattr(self, name):
raise FrozenInstanceError(f'cannot delete field {name!r}')
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 _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:
f = field(default=default)
# Assume it's a normal field until proven otherwise.
f._field_type = _FIELD
# Only at this point do we know the name and the type. Set them.
f.name = a_name
f.type = a_type
# 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.
typing = sys.modules.get('typing')
if typing is not None:
# This test uses a typing internal class, but it's the best
# way to test if this is a ClassVar.
if (type(a_type) is typing._GenericAlias and
a_type.__origin__ is typing.ClassVar):
# This field is a ClassVar, so it's not a field.
f._field_type = _FIELD_CLASSVAR
if f._field_type is _FIELD:
# Check if this is an InitVar.
if a_type is InitVar:
# InitVars are not fields, either.
f._field_type = _FIELD_INITVAR
# Validations for fields. This is delayed until now, instead of
# in the Field() constructor, since only here do we know the field
# name, which allows 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 _find_fields(cls):
# Return a list of Field objects, in order, for this class (and no
# base classes). Fields are found from __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.
annotations = getattr(cls, '__annotations__', {})
return [_get_field(cls, a_name, a_type)
for a_name, a_type in annotations.items()]
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.
# Actions:
# '': Do nothing.
# 'none': Set __hash__ to None.
# 'add': Always add a generated __hash__function.
# 'exception': Raise an exception.
#
# +-------------------------------------- unsafe_hash?
# | +------------------------------- eq?
# | | +------------------------ frozen?
# | | | +---------------- has-explicit-hash?
# | | | |
# | | | | +------- action
# | | | | |
# v v v v v
_hash_action = {(False, False, False, False): (''),
(False, False, False, True ): (''),
(False, False, True, False): (''),
(False, False, True, True ): (''),
(False, True, False, False): ('none'),
(False, True, False, True ): (''),
(False, True, True, False): ('add'),
(False, True, True, True ): (''),
(True, False, False, False): ('add'),
(True, False, False, True ): ('exception'),
(True, False, True, False): ('add'),
(True, False, True, True ): ('exception'),
(True, True, False, False): ('add'),
(True, True, False, True ): ('exception'),
(True, True, True, False): ('add'),
(True, True, True, True ): ('exception'),
}
# See https://bugs.python.org/issue32929#msg312829 for an if-statement
# version of this table.
def _process_class(cls, repr, eq, order, unsafe_hash, init, 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 = {}
# 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.
for b in cls.__mro__[-1:0:-1]:
# Only process classes that have been processed by our
# decorator. That is, they have a _MARKER attribute.
base_fields = getattr(b, _MARKER, None)
if base_fields:
for f in base_fields.values():
fields[f.name] = f
# Now find fields in our class. While doing so, validate some
# things, and set the default values (as class attributes)
# where we can.
for f in _find_fields(cls):
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)
# We're inheriting from a frozen dataclass, but we're not frozen.
if cls.__setattr__ is _frozen_setattr and not frozen:
raise TypeError('cannot inherit non-frozen dataclass from a '
'frozen one')
# We're inheriting from a non-frozen dataclass, but we're frozen.
if (hasattr(cls, _MARKER) and cls.__setattr__ is not _frozen_setattr
and frozen):
raise TypeError('cannot inherit frozen dataclass from a '
'non-frozen one')
# Remember all of the fields on our class (including bases). This
# marks this class as being a dataclass.
setattr(cls, _MARKER, 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 name, fn in [('__setattr__', _frozen_setattr),
('__delattr__', _frozen_delattr)]:
if _set_new_attribute(cls, name, fn):
raise TypeError(f'Cannot overwrite attribute {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]
# No need to call _set_new_attribute here, since we already know if
# we're overwriting a __hash__ or not.
if hash_action == '':
# Do nothing.
pass
elif hash_action == 'none':
cls.__hash__ = None
elif hash_action == 'add':
flds = [f for f in field_list if (f.compare if f.hash is None else f.hash)]
cls.__hash__ = _hash_fn(flds)
elif hash_action == 'exception':
# Raise an exception.
raise TypeError(f'Cannot overwrite attribute __hash__ '
f'in class {cls.__name__}')
else:
assert False, f"can't get here: {hash_action}"
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=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 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, repr, eq, order, unsafe_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, unsafe_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, 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()
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,
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, _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)
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