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Commit f0db54a0 authored by Eric V. Smith's avatar Eric V. Smith Committed by GitHub
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bpo-32214: Implement PEP 557: Data Classes (#4704)

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Lib/dataclasses.py 0 → 100644
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import sys
import types
from copy import deepcopy
import collections
import inspect
__all__ = ['dataclass',
'field',
'FrozenInstanceError',
'InitVar',
# Helper functions.
'fields',
'asdict',
'astuple',
'make_dataclass',
'replace',
]
# 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.
class _MISSING_FACTORY:
def __repr__(self):
return '<missing>'
_MISSING = _MISSING_FACTORY()
# 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 len(fields) == 0:
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 len(body_lines) == 0:
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 _set_eq_fns(cls, fields):
# Create and set the equality comparison methods on cls.
# Pre-compute self_tuple and other_tuple, then re-use them for
# each function.
self_tuple = _tuple_str('self', fields)
other_tuple = _tuple_str('other', fields)
for name, op in [('__eq__', '=='),
('__ne__', '!='),
]:
_set_attribute(cls, name, _cmp_fn(name, op, self_tuple, other_tuple))
def _set_order_fns(cls, fields):
# Create and set the ordering methods on cls.
# Pre-compute self_tuple and other_tuple, then re-use them for
# each function.
self_tuple = _tuple_str('self', fields)
other_tuple = _tuple_str('other', fields)
for name, op in [('__lt__', '<'),
('__le__', '<='),
('__gt__', '>'),
('__ge__', '>='),
]:
_set_attribute(cls, name, _cmp_fn(name, op, self_tuple, other_tuple))
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._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 deal with later.
annotations = getattr(cls, '__annotations__', {})
return [_get_field(cls, a_name, a_type)
for a_name, a_type in annotations.items()]
def _set_attribute(cls, name, value):
# Raise TypeError if an attribute by this name already exists.
if name in cls.__dict__:
raise TypeError(f'Cannot overwrite attribute {name} '
f'in {cls.__name__}')
setattr(cls, name, value)
def _process_class(cls, repr, eq, order, hash, init, frozen):
# Use an OrderedDict because:
# - Order matters!
# - Derived class fields overwrite base class fields, but the
# order is defined by the base class, which is found first.
fields = collections.OrderedDict()
# 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)
# 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 presense 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.
return tuple(f for f in fields.values() if f._field_type is _FIELD)
def _isdataclass(obj):
"""Returns True if obj is an instance of a dataclass."""
return not isinstance(obj, type) and 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 _isdataclass(obj):
raise TypeError("asdict() should be called on dataclass instances")
return _asdict_inner(obj, dict_factory)
def _asdict_inner(obj, dict_factory):
if _isdataclass(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 asdtuple(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 _isdataclass(obj):
raise TypeError("astuple() should be called on dataclass instances")
return _astuple_inner(obj, tuple_factory)
def _astuple_inner(obj, tuple_factory):
if _isdataclass(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):
"""Return a new dynamically created dataclass.
The dataclass name will be 'cls_name'. 'fields' is an interable
of either (name, type) or (name, type, Field) objects. Field
objects are created by calling 'field(name, type [, Field])'.
C = make_class('C', [('a', int', ('b', int, Field(init=False))], bases=Base)
is equivalent to:
@dataclass
class C(Base):
a: int
b: int = field(init=False)
For the bases and namespace paremeters, see the builtin type() function.
"""
if namespace is None:
namespace = {}
else:
# Copy namespace since we're going to mutate it.
namespace = namespace.copy()
anns = collections.OrderedDict((name, tp) for name, tp, *_ in fields)
namespace['__annotations__'] = anns
for item in fields:
if len(item) == 3:
name, tp, spec = item
namespace[name] = spec
cls = type(cls_name, bases, namespace)
return dataclass(cls)
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 _isdataclass(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)
Lib/test/test_dataclasses.py 0 → 100755
View file @ f0db54a0
from dataclasses import (
dataclass, field, FrozenInstanceError, fields, asdict, astuple,
make_dataclass, replace, InitVar, Field
)
import pickle
import inspect
import unittest
from unittest.mock import Mock
from typing import ClassVar, Any, List, Union, Tuple, Dict, Generic, TypeVar
from collections import deque, OrderedDict, namedtuple
# Just any custom exception we can catch.
class CustomError(Exception): pass
class TestCase(unittest.TestCase):
def test_no_fields(self):
@dataclass
class C:
pass
o = C()
self.assertEqual(len(fields(C)), 0)
def test_one_field_no_default(self):
@dataclass
class C:
x: int
o = C(42)
self.assertEqual(o.x, 42)
def test_named_init_params(self):
@dataclass
class C:
x: int
o = C(x=32)
self.assertEqual(o.x, 32)
def test_two_fields_one_default(self):
@dataclass
class C:
x: int
y: int = 0
o = C(3)
self.assertEqual((o.x, o.y), (3, 0))
# Non-defaults following defaults.
with self.assertRaisesRegex(TypeError,
"non-default argument 'y' follows "
"default argument"):
@dataclass
class C:
x: int = 0
y: int
# A derived class adds a non-default field after a default one.
with self.assertRaisesRegex(TypeError,
"non-default argument 'y' follows "
"default argument"):
@dataclass
class B:
x: int = 0
@dataclass
class C(B):
y: int
# Override a base class field and add a default to
# a field which didn't use to have a default.
with self.assertRaisesRegex(TypeError,
"non-default argument 'y' follows "
"default argument"):
@dataclass
class B:
x: int
y: int
@dataclass
class C(B):
x: int = 0
def test_overwriting_init(self):
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __init__ '
'in C'):
@dataclass
class C:
x: int
def __init__(self, x):
self.x = 2 * x
@dataclass(init=False)
class C:
x: int
def __init__(self, x):
self.x = 2 * x
self.assertEqual(C(5).x, 10)
def test_overwriting_repr(self):
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __repr__ '
'in C'):
@dataclass
class C:
x: int
def __repr__(self):
pass
@dataclass(repr=False)
class C:
x: int
def __repr__(self):
return 'x'
self.assertEqual(repr(C(0)), 'x')
def test_overwriting_cmp(self):
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __eq__ '
'in C'):
# This will generate the comparison functions, make sure we can't
# overwrite them.
@dataclass(hash=False, frozen=False)
class C:
x: int
def __eq__(self):
pass
@dataclass(order=False, eq=False)
class C:
x: int
def __eq__(self, other):
return True
self.assertEqual(C(0), 'x')
def test_overwriting_hash(self):
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __hash__ '
'in C'):
@dataclass(frozen=True)
class C:
x: int
def __hash__(self):
pass
@dataclass(frozen=True,hash=False)
class C:
x: int
def __hash__(self):
return 600
self.assertEqual(hash(C(0)), 600)
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __hash__ '
'in C'):
@dataclass(frozen=True)
class C:
x: int
def __hash__(self):
pass
@dataclass(frozen=True, hash=False)
class C:
x: int
def __hash__(self):
return 600
self.assertEqual(hash(C(0)), 600)
def test_overwriting_frozen(self):
# frozen uses __setattr__ and __delattr__
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __setattr__ '
'in C'):
@dataclass(frozen=True)
class C:
x: int
def __setattr__(self):
pass
with self.assertRaisesRegex(TypeError,
'Cannot overwrite attribute __delattr__ '
'in C'):
@dataclass(frozen=True)
class C:
x: int
def __delattr__(self):
pass
@dataclass(frozen=False)
class C:
x: int
def __setattr__(self, name, value):
self.__dict__['x'] = value * 2
self.assertEqual(C(10).x, 20)
def test_overwrite_fields_in_derived_class(self):
# Note that x from C1 replaces x in Base, but the order remains
# the same as defined in Base.
@dataclass
class Base:
x: Any = 15.0
y: int = 0
@dataclass
class C1(Base):
z: int = 10
x: int = 15
o = Base()
self.assertEqual(repr(o), 'TestCase.test_overwrite_fields_in_derived_class.<locals>.Base(x=15.0, y=0)')
o = C1()
self.assertEqual(repr(o), 'TestCase.test_overwrite_fields_in_derived_class.<locals>.C1(x=15, y=0, z=10)')
o = C1(x=5)
self.assertEqual(repr(o), 'TestCase.test_overwrite_fields_in_derived_class.<locals>.C1(x=5, y=0, z=10)')
def test_field_named_self(self):
@dataclass
class C:
self: str
c=C('foo')
self.assertEqual(c.self, 'foo')
# Make sure the first parameter is not named 'self'.
sig = inspect.signature(C.__init__)
first = next(iter(sig.parameters))
self.assertNotEqual('self', first)
# But we do use 'self' if no field named self.
@dataclass
class C:
selfx: str
# Make sure the first parameter is named 'self'.
sig = inspect.signature(C.__init__)
first = next(iter(sig.parameters))
self.assertEqual('self', first)
def test_repr(self):
@dataclass
class B:
x: int
@dataclass
class C(B):
y: int = 10
o = C(4)
self.assertEqual(repr(o), 'TestCase.test_repr.<locals>.C(x=4, y=10)')
@dataclass
class D(C):
x: int = 20
self.assertEqual(repr(D()), 'TestCase.test_repr.<locals>.D(x=20, y=10)')
@dataclass
class C:
@dataclass
class D:
i: int
@dataclass
class E:
pass
self.assertEqual(repr(C.D(0)), 'TestCase.test_repr.<locals>.C.D(i=0)')
self.assertEqual(repr(C.E()), 'TestCase.test_repr.<locals>.C.E()')
def test_0_field_compare(self):
# Ensure that order=False is the default.
@dataclass
class C0:
pass
@dataclass(order=False)
class C1:
pass
for cls in [C0, C1]:
with self.subTest(cls=cls):
self.assertEqual(cls(), cls())
for idx, fn in enumerate([lambda a, b: a < b,
lambda a, b: a <= b,
lambda a, b: a > b,
lambda a, b: a >= b]):
with self.subTest(idx=idx):
with self.assertRaisesRegex(TypeError,
f"not supported between instances of '{cls.__name__}' and '{cls.__name__}'"):
fn(cls(), cls())
@dataclass(order=True)
class C:
pass
self.assertLessEqual(C(), C())
self.assertGreaterEqual(C(), C())
def test_1_field_compare(self):
# Ensure that order=False is the default.
@dataclass
class C0:
x: int
@dataclass(order=False)
class C1:
x: int
for cls in [C0, C1]:
with self.subTest(cls=cls):
self.assertEqual(cls(1), cls(1))
self.assertNotEqual(cls(0), cls(1))
for idx, fn in enumerate([lambda a, b: a < b,
lambda a, b: a <= b,
lambda a, b: a > b,
lambda a, b: a >= b]):
with self.subTest(idx=idx):
with self.assertRaisesRegex(TypeError,
f"not supported between instances of '{cls.__name__}' and '{cls.__name__}'"):
fn(cls(0), cls(0))
@dataclass(order=True)
class C:
x: int
self.assertLess(C(0), C(1))
self.assertLessEqual(C(0), C(1))
self.assertLessEqual(C(1), C(1))
self.assertGreater(C(1), C(0))
self.assertGreaterEqual(C(1), C(0))
self.assertGreaterEqual(C(1), C(1))
def test_simple_compare(self):
# Ensure that order=False is the default.
@dataclass
class C0:
x: int
y: int
@dataclass(order=False)
class C1:
x: int
y: int
for cls in [C0, C1]:
with self.subTest(cls=cls):
self.assertEqual(cls(0, 0), cls(0, 0))
self.assertEqual(cls(1, 2), cls(1, 2))
self.assertNotEqual(cls(1, 0), cls(0, 0))
self.assertNotEqual(cls(1, 0), cls(1, 1))
for idx, fn in enumerate([lambda a, b: a < b,
lambda a, b: a <= b,
lambda a, b: a > b,
lambda a, b: a >= b]):
with self.subTest(idx=idx):
with self.assertRaisesRegex(TypeError,
f"not supported between instances of '{cls.__name__}' and '{cls.__name__}'"):
fn(cls(0, 0), cls(0, 0))
@dataclass(order=True)
class C:
x: int
y: int
for idx, fn in enumerate([lambda a, b: a == b,
lambda a, b: a <= b,
lambda a, b: a >= b]):
with self.subTest(idx=idx):
self.assertTrue(fn(C(0, 0), C(0, 0)))
for idx, fn in enumerate([lambda a, b: a < b,
lambda a, b: a <= b,
lambda a, b: a != b]):
with self.subTest(idx=idx):
self.assertTrue(fn(C(0, 0), C(0, 1)))
self.assertTrue(fn(C(0, 1), C(1, 0)))
self.assertTrue(fn(C(1, 0), C(1, 1)))
for idx, fn in enumerate([lambda a, b: a > b,
lambda a, b: a >= b,
lambda a, b: a != b]):
with self.subTest(idx=idx):
self.assertTrue(fn(C(0, 1), C(0, 0)))
self.assertTrue(fn(C(1, 0), C(0, 1)))
self.assertTrue(fn(C(1, 1), C(1, 0)))
def test_compare_subclasses(self):
# Comparisons fail for subclasses, even if no fields
# are added.
@dataclass
class B:
i: int
@dataclass
class C(B):
pass
for idx, (fn, expected) in enumerate([(lambda a, b: a == b, False),
(lambda a, b: a != b, True)]):
with self.subTest(idx=idx):
self.assertEqual(fn(B(0), C(0)), expected)
for idx, fn in enumerate([lambda a, b: a < b,
lambda a, b: a <= b,
lambda a, b: a > b,
lambda a, b: a >= b]):
with self.subTest(idx=idx):
with self.assertRaisesRegex(TypeError,
"not supported between instances of 'B' and 'C'"):
fn(B(0), C(0))
def test_0_field_hash(self):
@dataclass(hash=True)
class C:
pass
self.assertEqual(hash(C()), hash(()))
def test_1_field_hash(self):
@dataclass(hash=True)
class C:
x: int
self.assertEqual(hash(C(4)), hash((4,)))
self.assertEqual(hash(C(42)), hash((42,)))
def test_hash(self):
@dataclass(hash=True)
class C:
x: int
y: str
self.assertEqual(hash(C(1, 'foo')), hash((1, 'foo')))
def test_no_hash(self):
@dataclass(hash=None)
class C:
x: int
with self.assertRaisesRegex(TypeError,
"unhashable type: 'C'"):
hash(C(1))
def test_hash_rules(self):
# There are 24 cases of:
# hash=True/False/None
# eq=True/False
# order=True/False
# frozen=True/False
for (hash, eq, order, frozen, result ) in [
(False, False, False, False, 'absent'),
(False, False, False, True, 'absent'),
(False, False, True, False, 'exception'),
(False, False, True, True, 'exception'),
(False, True, False, False, 'absent'),
(False, True, False, True, 'absent'),
(False, True, True, False, 'absent'),
(False, True, True, True, 'absent'),
(True, False, False, False, 'fn'),
(True, False, False, True, 'fn'),
(True, False, True, False, 'exception'),
(True, False, True, True, 'exception'),
(True, True, False, False, 'fn'),
(True, True, False, True, 'fn'),
(True, True, True, False, 'fn'),
(True, True, True, True, 'fn'),
(None, False, False, False, 'absent'),
(None, False, False, True, 'absent'),
(None, False, True, False, 'exception'),
(None, False, True, True, 'exception'),
(None, True, False, False, 'none'),
(None, True, False, True, 'fn'),
(None, True, True, False, 'none'),
(None, True, True, True, 'fn'),
]:
with self.subTest(hash=hash, eq=eq, order=order, frozen=frozen):
if result == 'exception':
with self.assertRaisesRegex(ValueError, 'eq must be true if order is true'):
@dataclass(hash=hash, eq=eq, order=order, frozen=frozen)
class C:
pass
else:
@dataclass(hash=hash, eq=eq, order=order, frozen=frozen)
class C:
pass
# See if the result matches what's expected.
if result == 'fn':
# __hash__ contains the function we generated.
self.assertIn('__hash__', C.__dict__)
self.assertIsNotNone(C.__dict__['__hash__'])
elif result == 'absent':
# __hash__ is not present in our class.
self.assertNotIn('__hash__', C.__dict__)
elif result == 'none':
# __hash__ is set to None.
self.assertIn('__hash__', C.__dict__)
self.assertIsNone(C.__dict__['__hash__'])
else:
assert False, f'unknown result {result!r}'
def test_eq_order(self):
for (eq, order, result ) in [
(False, False, 'neither'),
(False, True, 'exception'),
(True, False, 'eq_only'),
(True, True, 'both'),
]:
with self.subTest(eq=eq, order=order):
if result == 'exception':
with self.assertRaisesRegex(ValueError, 'eq must be true if order is true'):
@dataclass(eq=eq, order=order)
class C:
pass
else:
@dataclass(eq=eq, order=order)
class C:
pass
if result == 'neither':
self.assertNotIn('__eq__', C.__dict__)
self.assertNotIn('__ne__', C.__dict__)
self.assertNotIn('__lt__', C.__dict__)
self.assertNotIn('__le__', C.__dict__)
self.assertNotIn('__gt__', C.__dict__)
self.assertNotIn('__ge__', C.__dict__)
elif result == 'both':
self.assertIn('__eq__', C.__dict__)
self.assertIn('__ne__', C.__dict__)
self.assertIn('__lt__', C.__dict__)
self.assertIn('__le__', C.__dict__)
self.assertIn('__gt__', C.__dict__)
self.assertIn('__ge__', C.__dict__)
elif result == 'eq_only':
self.assertIn('__eq__', C.__dict__)
self.assertIn('__ne__', C.__dict__)
self.assertNotIn('__lt__', C.__dict__)
self.assertNotIn('__le__', C.__dict__)
self.assertNotIn('__gt__', C.__dict__)
self.assertNotIn('__ge__', C.__dict__)
else:
assert False, f'unknown result {result!r}'
def test_field_no_default(self):
@dataclass
class C:
x: int = field()
self.assertEqual(C(5).x, 5)
with self.assertRaisesRegex(TypeError,
r"__init__\(\) missing 1 required "
"positional argument: 'x'"):
C()
def test_field_default(self):
default = object()
@dataclass
class C:
x: object = field(default=default)
self.assertIs(C.x, default)
c = C(10)
self.assertEqual(c.x, 10)
# If we delete the instance attribute, we should then see the
# class attribute.
del c.x
self.assertIs(c.x, default)
self.assertIs(C().x, default)
def test_not_in_repr(self):
@dataclass
class C:
x: int = field(repr=False)
with self.assertRaises(TypeError):
C()
c = C(10)
self.assertEqual(repr(c), 'TestCase.test_not_in_repr.<locals>.C()')
@dataclass
class C:
x: int = field(repr=False)
y: int
c = C(10, 20)
self.assertEqual(repr(c), 'TestCase.test_not_in_repr.<locals>.C(y=20)')
def test_not_in_compare(self):
@dataclass
class C:
x: int = 0
y: int = field(compare=False, default=4)
self.assertEqual(C(), C(0, 20))
self.assertEqual(C(1, 10), C(1, 20))
self.assertNotEqual(C(3), C(4, 10))
self.assertNotEqual(C(3, 10), C(4, 10))
def test_hash_field_rules(self):
# Test all 6 cases of:
# hash=True/False/None
# compare=True/False
for (hash_val, compare, result ) in [
(True, False, 'field' ),
(True, True, 'field' ),
(False, False, 'absent'),
(False, True, 'absent'),
(None, False, 'absent'),
(None, True, 'field' ),
]:
with self.subTest(hash_val=hash_val, compare=compare):
@dataclass(hash=True)
class C:
x: int = field(compare=compare, hash=hash_val, default=5)
if result == 'field':
# __hash__ contains the field.
self.assertEqual(C(5).__hash__(), hash((5,)))
elif result == 'absent':
# The field is not present in the hash.
self.assertEqual(C(5).__hash__(), hash(()))
else:
assert False, f'unknown result {result!r}'
def test_init_false_no_default(self):
# If init=False and no default value, then the field won't be
# present in the instance.
@dataclass
class C:
x: int = field(init=False)
self.assertNotIn('x', C().__dict__)
@dataclass
class C:
x: int
y: int = 0
z: int = field(init=False)
t: int = 10
self.assertNotIn('z', C(0).__dict__)
self.assertEqual(vars(C(5)), {'t': 10, 'x': 5, 'y': 0})
def test_class_marker(self):
@dataclass
class C:
x: int
y: str = field(init=False, default=None)
z: str = field(repr=False)
the_fields = fields(C)
# the_fields is a tuple of 3 items, each value
# is in __annotations__.
self.assertIsInstance(the_fields, tuple)
for f in the_fields:
self.assertIs(type(f), Field)
self.assertIn(f.name, C.__annotations__)
self.assertEqual(len(the_fields), 3)
self.assertEqual(the_fields[0].name, 'x')
self.assertEqual(the_fields[0].type, int)
self.assertFalse(hasattr(C, 'x'))
self.assertTrue (the_fields[0].init)
self.assertTrue (the_fields[0].repr)
self.assertEqual(the_fields[1].name, 'y')
self.assertEqual(the_fields[1].type, str)
self.assertIsNone(getattr(C, 'y'))
self.assertFalse(the_fields[1].init)
self.assertTrue (the_fields[1].repr)
self.assertEqual(the_fields[2].name, 'z')
self.assertEqual(the_fields[2].type, str)
self.assertFalse(hasattr(C, 'z'))
self.assertTrue (the_fields[2].init)
self.assertFalse(the_fields[2].repr)
def test_field_order(self):
@dataclass
class B:
a: str = 'B:a'
b: str = 'B:b'
c: str = 'B:c'
@dataclass
class C(B):
b: str = 'C:b'
self.assertEqual([(f.name, f.default) for f in fields(C)],
[('a', 'B:a'),
('b', 'C:b'),
('c', 'B:c')])
@dataclass
class D(B):
c: str = 'D:c'
self.assertEqual([(f.name, f.default) for f in fields(D)],
[('a', 'B:a'),
('b', 'B:b'),
('c', 'D:c')])
@dataclass
class E(D):
a: str = 'E:a'
d: str = 'E:d'
self.assertEqual([(f.name, f.default) for f in fields(E)],
[('a', 'E:a'),
('b', 'B:b'),
('c', 'D:c'),
('d', 'E:d')])
def test_class_attrs(self):
# We only have a class attribute if a default value is
# specified, either directly or via a field with a default.
default = object()
@dataclass
class C:
x: int
y: int = field(repr=False)
z: object = default
t: int = field(default=100)
self.assertFalse(hasattr(C, 'x'))
self.assertFalse(hasattr(C, 'y'))
self.assertIs (C.z, default)
self.assertEqual(C.t, 100)
def test_disallowed_mutable_defaults(self):
# For the known types, don't allow mutable default values.
for typ, empty, non_empty in [(list, [], [1]),
(dict, {}, {0:1}),
(set, set(), set([1])),
]:
with self.subTest(typ=typ):
# Can't use a zero-length value.
with self.assertRaisesRegex(ValueError,
f'mutable default {typ} for field '
'x is not allowed'):
@dataclass
class Point:
x: typ = empty
# Nor a non-zero-length value
with self.assertRaisesRegex(ValueError,
f'mutable default {typ} for field '
'y is not allowed'):
@dataclass
class Point:
y: typ = non_empty
# Check subtypes also fail.
class Subclass(typ): pass
with self.assertRaisesRegex(ValueError,
f"mutable default .*Subclass'>"
' for field z is not allowed'
):
@dataclass
class Point:
z: typ = Subclass()
# Because this is a ClassVar, it can be mutable.
@dataclass
class C:
z: ClassVar[typ] = typ()
# Because this is a ClassVar, it can be mutable.
@dataclass
class C:
x: ClassVar[typ] = Subclass()
def test_deliberately_mutable_defaults(self):
# If a mutable default isn't in the known list of
# (list, dict, set), then it's okay.
class Mutable:
def __init__(self):
self.l = []
@dataclass
class C:
x: Mutable
# These 2 instances will share this value of x.
lst = Mutable()
o1 = C(lst)
o2 = C(lst)
self.assertEqual(o1, o2)
o1.x.l.extend([1, 2])
self.assertEqual(o1, o2)
self.assertEqual(o1.x.l, [1, 2])
self.assertIs(o1.x, o2.x)
def test_no_options(self):
# call with dataclass()
@dataclass()
class C:
x: int
self.assertEqual(C(42).x, 42)
def test_not_tuple(self):
# Make sure we can't be compared to a tuple.
@dataclass
class Point:
x: int
y: int
self.assertNotEqual(Point(1, 2), (1, 2))
# And that we can't compare to another unrelated dataclass
@dataclass
class C:
x: int
y: int
self.assertNotEqual(Point(1, 3), C(1, 3))
def test_base_has_init(self):
class B:
def __init__(self):
pass
# Make sure that declaring this class doesn't raise an error.
# The issue is that we can't override __init__ in our class,
# but it should be okay to add __init__ to us if our base has
# an __init__.
@dataclass
class C(B):
x: int = 0
def test_frozen(self):
@dataclass(frozen=True)
class C:
i: int
c = C(10)
self.assertEqual(c.i, 10)
with self.assertRaises(FrozenInstanceError):
c.i = 5
self.assertEqual(c.i, 10)
# Check that a derived class is still frozen, even if not
# marked so.
@dataclass
class D(C):
pass
d = D(20)
self.assertEqual(d.i, 20)
with self.assertRaises(FrozenInstanceError):
d.i = 5
self.assertEqual(d.i, 20)
def test_not_tuple(self):
# Test that some of the problems with namedtuple don't happen
# here.
@dataclass
class Point3D:
x: int
y: int
z: int
@dataclass
class Date:
year: int
month: int
day: int
self.assertNotEqual(Point3D(2017, 6, 3), Date(2017, 6, 3))
self.assertNotEqual(Point3D(1, 2, 3), (1, 2, 3))
# Make sure we can't unpack
with self.assertRaisesRegex(TypeError, 'is not iterable'):
x, y, z = Point3D(4, 5, 6)
# Maka sure another class with the same field names isn't
# equal.
@dataclass
class Point3Dv1:
x: int = 0
y: int = 0
z: int = 0
self.assertNotEqual(Point3D(0, 0, 0), Point3Dv1())
def test_function_annotations(self):
# Some dummy class and instance to use as a default.
class F:
pass
f = F()
def validate_class(cls):
# First, check __annotations__, even though they're not
# function annotations.
self.assertEqual(cls.__annotations__['i'], int)
self.assertEqual(cls.__annotations__['j'], str)
self.assertEqual(cls.__annotations__['k'], F)
self.assertEqual(cls.__annotations__['l'], float)
self.assertEqual(cls.__annotations__['z'], complex)
# Verify __init__.
signature = inspect.signature(cls.__init__)
# Check the return type, should be None
self.assertIs(signature.return_annotation, None)
# Check each parameter.
params = iter(signature.parameters.values())
param = next(params)
# This is testing an internal name, and probably shouldn't be tested.
self.assertEqual(param.name, 'self')
param = next(params)
self.assertEqual(param.name, 'i')
self.assertIs (param.annotation, int)
self.assertEqual(param.default, inspect.Parameter.empty)
self.assertEqual(param.kind, inspect.Parameter.POSITIONAL_OR_KEYWORD)
param = next(params)
self.assertEqual(param.name, 'j')
self.assertIs (param.annotation, str)
self.assertEqual(param.default, inspect.Parameter.empty)
self.assertEqual(param.kind, inspect.Parameter.POSITIONAL_OR_KEYWORD)
param = next(params)
self.assertEqual(param.name, 'k')
self.assertIs (param.annotation, F)
# Don't test for the default, since it's set to _MISSING
self.assertEqual(param.kind, inspect.Parameter.POSITIONAL_OR_KEYWORD)
param = next(params)
self.assertEqual(param.name, 'l')
self.assertIs (param.annotation, float)
# Don't test for the default, since it's set to _MISSING
self.assertEqual(param.kind, inspect.Parameter.POSITIONAL_OR_KEYWORD)
self.assertRaises(StopIteration, next, params)
@dataclass
class C:
i: int
j: str
k: F = f
l: float=field(default=None)
z: complex=field(default=3+4j, init=False)
validate_class(C)
# Now repeat with __hash__.
@dataclass(frozen=True, hash=True)
class C:
i: int
j: str
k: F = f
l: float=field(default=None)
z: complex=field(default=3+4j, init=False)
validate_class(C)
def test_dont_include_other_annotations(self):
@dataclass
class C:
i: int
def foo(self) -> int:
return 4
@property
def bar(self) -> int:
return 5
self.assertEqual(list(C.__annotations__), ['i'])
self.assertEqual(C(10).foo(), 4)
self.assertEqual(C(10).bar, 5)
def test_post_init(self):
# Just make sure it gets called
@dataclass
class C:
def __post_init__(self):
raise CustomError()
with self.assertRaises(CustomError):
C()
@dataclass
class C:
i: int = 10
def __post_init__(self):
if self.i == 10:
raise CustomError()
with self.assertRaises(CustomError):
C()
# post-init gets called, but doesn't raise. This is just
# checking that self is used correctly.
C(5)
# If there's not an __init__, then post-init won't get called.
@dataclass(init=False)
class C:
def __post_init__(self):
raise CustomError()
# Creating the class won't raise
C()
@dataclass
class C:
x: int = 0
def __post_init__(self):
self.x *= 2
self.assertEqual(C().x, 0)
self.assertEqual(C(2).x, 4)
# Make sure that if we'r frozen, post-init can't set
# attributes.
@dataclass(frozen=True)
class C:
x: int = 0
def __post_init__(self):
self.x *= 2
with self.assertRaises(FrozenInstanceError):
C()
def test_post_init_super(self):
# Make sure super() post-init isn't called by default.
class B:
def __post_init__(self):
raise CustomError()
@dataclass
class C(B):
def __post_init__(self):
self.x = 5
self.assertEqual(C().x, 5)
# Now call super(), and it will raise
@dataclass
class C(B):
def __post_init__(self):
super().__post_init__()
with self.assertRaises(CustomError):
C()
# Make sure post-init is called, even if not defined in our
# class.
@dataclass
class C(B):
pass
with self.assertRaises(CustomError):
C()
def test_post_init_staticmethod(self):
flag = False
@dataclass
class C:
x: int
y: int
@staticmethod
def __post_init__():
nonlocal flag
flag = True
self.assertFalse(flag)
c = C(3, 4)
self.assertEqual((c.x, c.y), (3, 4))
self.assertTrue(flag)
def test_post_init_classmethod(self):
@dataclass
class C:
flag = False
x: int
y: int
@classmethod
def __post_init__(cls):
cls.flag = True
self.assertFalse(C.flag)
c = C(3, 4)
self.assertEqual((c.x, c.y), (3, 4))
self.assertTrue(C.flag)
def test_class_var(self):
# Make sure ClassVars are ignored in __init__, __repr__, etc.
@dataclass
class C:
x: int
y: int = 10
z: ClassVar[int] = 1000
w: ClassVar[int] = 2000
t: ClassVar[int] = 3000
c = C(5)
self.assertEqual(repr(c), 'TestCase.test_class_var.<locals>.C(x=5, y=10)')
self.assertEqual(len(fields(C)), 2) # We have 2 fields
self.assertEqual(len(C.__annotations__), 5) # And 3 ClassVars
self.assertEqual(c.z, 1000)
self.assertEqual(c.w, 2000)
self.assertEqual(c.t, 3000)
C.z += 1
self.assertEqual(c.z, 1001)
c = C(20)
self.assertEqual((c.x, c.y), (20, 10))
self.assertEqual(c.z, 1001)
self.assertEqual(c.w, 2000)
self.assertEqual(c.t, 3000)
def test_class_var_no_default(self):
# If a ClassVar has no default value, it should not be set on the class.
@dataclass
class C:
x: ClassVar[int]
self.assertNotIn('x', C.__dict__)
def test_class_var_default_factory(self):
# It makes no sense for a ClassVar to have a default factory. When
# would it be called? Call it yourself, since it's class-wide.
with self.assertRaisesRegex(TypeError,
'cannot have a default factory'):
@dataclass
class C:
x: ClassVar[int] = field(default_factory=int)
self.assertNotIn('x', C.__dict__)
def test_class_var_with_default(self):
# If a ClassVar has a default value, it should be set on the class.
@dataclass
class C:
x: ClassVar[int] = 10
self.assertEqual(C.x, 10)
@dataclass
class C:
x: ClassVar[int] = field(default=10)
self.assertEqual(C.x, 10)
def test_class_var_frozen(self):
# Make sure ClassVars work even if we're frozen.
@dataclass(frozen=True)
class C:
x: int
y: int = 10
z: ClassVar[int] = 1000
w: ClassVar[int] = 2000
t: ClassVar[int] = 3000
c = C(5)
self.assertEqual(repr(C(5)), 'TestCase.test_class_var_frozen.<locals>.C(x=5, y=10)')
self.assertEqual(len(fields(C)), 2) # We have 2 fields
self.assertEqual(len(C.__annotations__), 5) # And 3 ClassVars
self.assertEqual(c.z, 1000)
self.assertEqual(c.w, 2000)
self.assertEqual(c.t, 3000)
# We can still modify the ClassVar, it's only instances that are
# frozen.
C.z += 1
self.assertEqual(c.z, 1001)
c = C(20)
self.assertEqual((c.x, c.y), (20, 10))
self.assertEqual(c.z, 1001)
self.assertEqual(c.w, 2000)
self.assertEqual(c.t, 3000)
def test_init_var_no_default(self):
# If an InitVar has no default value, it should not be set on the class.
@dataclass
class C:
x: InitVar[int]
self.assertNotIn('x', C.__dict__)
def test_init_var_default_factory(self):
# It makes no sense for an InitVar to have a default factory. When
# would it be called? Call it yourself, since it's class-wide.
with self.assertRaisesRegex(TypeError,
'cannot have a default factory'):
@dataclass
class C:
x: InitVar[int] = field(default_factory=int)
self.assertNotIn('x', C.__dict__)
def test_init_var_with_default(self):
# If an InitVar has a default value, it should be set on the class.
@dataclass
class C:
x: InitVar[int] = 10
self.assertEqual(C.x, 10)
@dataclass
class C:
x: InitVar[int] = field(default=10)
self.assertEqual(C.x, 10)
def test_init_var(self):
@dataclass
class C:
x: int = None
init_param: InitVar[int] = None
def __post_init__(self, init_param):
if self.x is None:
self.x = init_param*2
c = C(init_param=10)
self.assertEqual(c.x, 20)
def test_init_var_inheritance(self):
# Note that this deliberately tests that a dataclass need not
# have a __post_init__ function if it has an InitVar field.
# It could just be used in a derived class, as shown here.
@dataclass
class Base:
x: int
init_base: InitVar[int]
# We can instantiate by passing the InitVar, even though
# it's not used.
b = Base(0, 10)
self.assertEqual(vars(b), {'x': 0})
@dataclass
class C(Base):
y: int
init_derived: InitVar[int]
def __post_init__(self, init_base, init_derived):
self.x = self.x + init_base
self.y = self.y + init_derived
c = C(10, 11, 50, 51)
self.assertEqual(vars(c), {'x': 21, 'y': 101})
def test_default_factory(self):
# Test a factory that returns a new list.
@dataclass
class C:
x: int
y: list = field(default_factory=list)
c0 = C(3)
c1 = C(3)
self.assertEqual(c0.x, 3)
self.assertEqual(c0.y, [])
self.assertEqual(c0, c1)
self.assertIsNot(c0.y, c1.y)
self.assertEqual(astuple(C(5, [1])), (5, [1]))
# Test a factory that returns a shared list.
l = []
@dataclass
class C:
x: int
y: list = field(default_factory=lambda: l)
c0 = C(3)
c1 = C(3)
self.assertEqual(c0.x, 3)
self.assertEqual(c0.y, [])
self.assertEqual(c0, c1)
self.assertIs(c0.y, c1.y)
self.assertEqual(astuple(C(5, [1])), (5, [1]))
# Test various other field flags.
# repr
@dataclass
class C:
x: list = field(default_factory=list, repr=False)
self.assertEqual(repr(C()), 'TestCase.test_default_factory.<locals>.C()')
self.assertEqual(C().x, [])
# hash
@dataclass(hash=True)
class C:
x: list = field(default_factory=list, hash=False)
self.assertEqual(astuple(C()), ([],))
self.assertEqual(hash(C()), hash(()))
# init (see also test_default_factory_with_no_init)
@dataclass
class C:
x: list = field(default_factory=list, init=False)
self.assertEqual(astuple(C()), ([],))
# compare
@dataclass
class C:
x: list = field(default_factory=list, compare=False)
self.assertEqual(C(), C([1]))
def test_default_factory_with_no_init(self):
# We need a factory with a side effect.
factory = Mock()
@dataclass
class C:
x: list = field(default_factory=factory, init=False)
# Make sure the default factory is called for each new instance.
C().x
self.assertEqual(factory.call_count, 1)
C().x
self.assertEqual(factory.call_count, 2)
def test_default_factory_not_called_if_value_given(self):
# We need a factory that we can test if it's been called.
factory = Mock()
@dataclass
class C:
x: int = field(default_factory=factory)
# Make sure that if a field has a default factory function,
# it's not called if a value is specified.
C().x
self.assertEqual(factory.call_count, 1)
self.assertEqual(C(10).x, 10)
self.assertEqual(factory.call_count, 1)
C().x
self.assertEqual(factory.call_count, 2)
def x_test_classvar_default_factory(self):
# XXX: it's an error for a ClassVar to have a factory function
@dataclass
class C:
x: ClassVar[int] = field(default_factory=int)
self.assertIs(C().x, int)
def test_isdataclass(self):
# There is no isdataclass() helper any more, but the PEP
# describes how to write it, so make sure that works. Note
# that this version returns True for both classes and
# instances.
def isdataclass(obj):
try:
fields(obj)
return True
except TypeError:
return False
self.assertFalse(isdataclass(0))
self.assertFalse(isdataclass(int))
@dataclass
class C:
x: int
self.assertTrue(isdataclass(C))
self.assertTrue(isdataclass(C(0)))
def test_helper_fields_with_class_instance(self):
# Check that we can call fields() on either a class or instance,
# and get back the same thing.
@dataclass
class C:
x: int
y: float
self.assertEqual(fields(C), fields(C(0, 0.0)))
def test_helper_fields_exception(self):
# Check that TypeError is raised if not passed a dataclass or
# instance.
with self.assertRaisesRegex(TypeError, 'dataclass type or instance'):
fields(0)
class C: pass
with self.assertRaisesRegex(TypeError, 'dataclass type or instance'):
fields(C)
with self.assertRaisesRegex(TypeError, 'dataclass type or instance'):
fields(C())
def test_helper_asdict(self):
# Basic tests for asdict(), it should return a new dictionary
@dataclass
class C:
x: int
y: int
c = C(1, 2)
self.assertEqual(asdict(c), {'x': 1, 'y': 2})
self.assertEqual(asdict(c), asdict(c))
self.assertIsNot(asdict(c), asdict(c))
c.x = 42
self.assertEqual(asdict(c), {'x': 42, 'y': 2})
self.assertIs(type(asdict(c)), dict)
def test_helper_asdict_raises_on_classes(self):
# asdict() should raise on a class object
@dataclass
class C:
x: int
y: int
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
asdict(C)
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
asdict(int)
def test_helper_asdict_copy_values(self):
@dataclass
class C:
x: int
y: List[int] = field(default_factory=list)
initial = []
c = C(1, initial)
d = asdict(c)
self.assertEqual(d['y'], initial)
self.assertIsNot(d['y'], initial)
c = C(1)
d = asdict(c)
d['y'].append(1)
self.assertEqual(c.y, [])
def test_helper_asdict_nested(self):
@dataclass
class UserId:
token: int
group: int
@dataclass
class User:
name: str
id: UserId
u = User('Joe', UserId(123, 1))
d = asdict(u)
self.assertEqual(d, {'name': 'Joe', 'id': {'token': 123, 'group': 1}})
self.assertIsNot(asdict(u), asdict(u))
u.id.group = 2
self.assertEqual(asdict(u), {'name': 'Joe',
'id': {'token': 123, 'group': 2}})
def test_helper_asdict_builtin_containers(self):
@dataclass
class User:
name: str
id: int
@dataclass
class GroupList:
id: int
users: List[User]
@dataclass
class GroupTuple:
id: int
users: Tuple[User, ...]
@dataclass
class GroupDict:
id: int
users: Dict[str, User]
a = User('Alice', 1)
b = User('Bob', 2)
gl = GroupList(0, [a, b])
gt = GroupTuple(0, (a, b))
gd = GroupDict(0, {'first': a, 'second': b})
self.assertEqual(asdict(gl), {'id': 0, 'users': [{'name': 'Alice', 'id': 1},
{'name': 'Bob', 'id': 2}]})
self.assertEqual(asdict(gt), {'id': 0, 'users': ({'name': 'Alice', 'id': 1},
{'name': 'Bob', 'id': 2})})
self.assertEqual(asdict(gd), {'id': 0, 'users': {'first': {'name': 'Alice', 'id': 1},
'second': {'name': 'Bob', 'id': 2}}})
def test_helper_asdict_builtin_containers(self):
@dataclass
class Child:
d: object
@dataclass
class Parent:
child: Child
self.assertEqual(asdict(Parent(Child([1]))), {'child': {'d': [1]}})
self.assertEqual(asdict(Parent(Child({1: 2}))), {'child': {'d': {1: 2}}})
def test_helper_asdict_factory(self):
@dataclass
class C:
x: int
y: int
c = C(1, 2)
d = asdict(c, dict_factory=OrderedDict)
self.assertEqual(d, OrderedDict([('x', 1), ('y', 2)]))
self.assertIsNot(d, asdict(c, dict_factory=OrderedDict))
c.x = 42
d = asdict(c, dict_factory=OrderedDict)
self.assertEqual(d, OrderedDict([('x', 42), ('y', 2)]))
self.assertIs(type(d), OrderedDict)
def test_helper_astuple(self):
# Basic tests for astuple(), it should return a new tuple
@dataclass
class C:
x: int
y: int = 0
c = C(1)
self.assertEqual(astuple(c), (1, 0))
self.assertEqual(astuple(c), astuple(c))
self.assertIsNot(astuple(c), astuple(c))
c.y = 42
self.assertEqual(astuple(c), (1, 42))
self.assertIs(type(astuple(c)), tuple)
def test_helper_astuple_raises_on_classes(self):
# astuple() should raise on a class object
@dataclass
class C:
x: int
y: int
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
astuple(C)
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
astuple(int)
def test_helper_astuple_copy_values(self):
@dataclass
class C:
x: int
y: List[int] = field(default_factory=list)
initial = []
c = C(1, initial)
t = astuple(c)
self.assertEqual(t[1], initial)
self.assertIsNot(t[1], initial)
c = C(1)
t = astuple(c)
t[1].append(1)
self.assertEqual(c.y, [])
def test_helper_astuple_nested(self):
@dataclass
class UserId:
token: int
group: int
@dataclass
class User:
name: str
id: UserId
u = User('Joe', UserId(123, 1))
t = astuple(u)
self.assertEqual(t, ('Joe', (123, 1)))
self.assertIsNot(astuple(u), astuple(u))
u.id.group = 2
self.assertEqual(astuple(u), ('Joe', (123, 2)))
def test_helper_astuple_builtin_containers(self):
@dataclass
class User:
name: str
id: int
@dataclass
class GroupList:
id: int
users: List[User]
@dataclass
class GroupTuple:
id: int
users: Tuple[User, ...]
@dataclass
class GroupDict:
id: int
users: Dict[str, User]
a = User('Alice', 1)
b = User('Bob', 2)
gl = GroupList(0, [a, b])
gt = GroupTuple(0, (a, b))
gd = GroupDict(0, {'first': a, 'second': b})
self.assertEqual(astuple(gl), (0, [('Alice', 1), ('Bob', 2)]))
self.assertEqual(astuple(gt), (0, (('Alice', 1), ('Bob', 2))))
self.assertEqual(astuple(gd), (0, {'first': ('Alice', 1), 'second': ('Bob', 2)}))
def test_helper_astuple_builtin_containers(self):
@dataclass
class Child:
d: object
@dataclass
class Parent:
child: Child
self.assertEqual(astuple(Parent(Child([1]))), (([1],),))
self.assertEqual(astuple(Parent(Child({1: 2}))), (({1: 2},),))
def test_helper_astuple_factory(self):
@dataclass
class C:
x: int
y: int
NT = namedtuple('NT', 'x y')
def nt(lst):
return NT(*lst)
c = C(1, 2)
t = astuple(c, tuple_factory=nt)
self.assertEqual(t, NT(1, 2))
self.assertIsNot(t, astuple(c, tuple_factory=nt))
c.x = 42
t = astuple(c, tuple_factory=nt)
self.assertEqual(t, NT(42, 2))
self.assertIs(type(t), NT)
def test_dynamic_class_creation(self):
cls_dict = {'__annotations__': OrderedDict(x=int, y=int),
}
# Create the class.
cls = type('C', (), cls_dict)
# Make it a dataclass.
cls1 = dataclass(cls)
self.assertEqual(cls1, cls)
self.assertEqual(asdict(cls(1, 2)), {'x': 1, 'y': 2})
def test_dynamic_class_creation_using_field(self):
cls_dict = {'__annotations__': OrderedDict(x=int, y=int),
'y': field(default=5),
}
# Create the class.
cls = type('C', (), cls_dict)
# Make it a dataclass.
cls1 = dataclass(cls)
self.assertEqual(cls1, cls)
self.assertEqual(asdict(cls1(1)), {'x': 1, 'y': 5})
def test_init_in_order(self):
@dataclass
class C:
a: int
b: int = field()
c: list = field(default_factory=list, init=False)
d: list = field(default_factory=list)
e: int = field(default=4, init=False)
f: int = 4
calls = []
def setattr(self, name, value):
calls.append((name, value))
C.__setattr__ = setattr
c = C(0, 1)
self.assertEqual(('a', 0), calls[0])
self.assertEqual(('b', 1), calls[1])
self.assertEqual(('c', []), calls[2])
self.assertEqual(('d', []), calls[3])
self.assertNotIn(('e', 4), calls)
self.assertEqual(('f', 4), calls[4])
def test_items_in_dicts(self):
@dataclass
class C:
a: int
b: list = field(default_factory=list, init=False)
c: list = field(default_factory=list)
d: int = field(default=4, init=False)
e: int = 0
c = C(0)
# Class dict
self.assertNotIn('a', C.__dict__)
self.assertNotIn('b', C.__dict__)
self.assertNotIn('c', C.__dict__)
self.assertIn('d', C.__dict__)
self.assertEqual(C.d, 4)
self.assertIn('e', C.__dict__)
self.assertEqual(C.e, 0)
# Instance dict
self.assertIn('a', c.__dict__)
self.assertEqual(c.a, 0)
self.assertIn('b', c.__dict__)
self.assertEqual(c.b, [])
self.assertIn('c', c.__dict__)
self.assertEqual(c.c, [])
self.assertNotIn('d', c.__dict__)
self.assertIn('e', c.__dict__)
self.assertEqual(c.e, 0)
def test_alternate_classmethod_constructor(self):
# Since __post_init__ can't take params, use a classmethod
# alternate constructor. This is mostly an example to show how
# to use this technique.
@dataclass
class C:
x: int
@classmethod
def from_file(cls, filename):
# In a real example, create a new instance
# and populate 'x' from contents of a file.
value_in_file = 20
return cls(value_in_file)
self.assertEqual(C.from_file('filename').x, 20)
def test_field_metadata_default(self):
# Make sure the default metadata is read-only and of
# zero length.
@dataclass
class C:
i: int
self.assertFalse(fields(C)[0].metadata)
self.assertEqual(len(fields(C)[0].metadata), 0)
with self.assertRaisesRegex(TypeError,
'does not support item assignment'):
fields(C)[0].metadata['test'] = 3
def test_field_metadata_mapping(self):
# Make sure only a mapping can be passed as metadata
# zero length.
with self.assertRaises(TypeError):
@dataclass
class C:
i: int = field(metadata=0)
# Make sure an empty dict works
@dataclass
class C:
i: int = field(metadata={})
self.assertFalse(fields(C)[0].metadata)
self.assertEqual(len(fields(C)[0].metadata), 0)
with self.assertRaisesRegex(TypeError,
'does not support item assignment'):
fields(C)[0].metadata['test'] = 3
# Make sure a non-empty dict works.
@dataclass
class C:
i: int = field(metadata={'test': 10, 'bar': '42', 3: 'three'})
self.assertEqual(len(fields(C)[0].metadata), 3)
self.assertEqual(fields(C)[0].metadata['test'], 10)
self.assertEqual(fields(C)[0].metadata['bar'], '42')
self.assertEqual(fields(C)[0].metadata[3], 'three')
with self.assertRaises(KeyError):
# Non-existent key.
fields(C)[0].metadata['baz']
with self.assertRaisesRegex(TypeError,
'does not support item assignment'):
fields(C)[0].metadata['test'] = 3
def test_field_metadata_custom_mapping(self):
# Try a custom mapping.
class SimpleNameSpace:
def __init__(self, **kw):
self.__dict__.update(kw)
def __getitem__(self, item):
if item == 'xyzzy':
return 'plugh'
return getattr(self, item)
def __len__(self):
return self.__dict__.__len__()
@dataclass
class C:
i: int = field(metadata=SimpleNameSpace(a=10))
self.assertEqual(len(fields(C)[0].metadata), 1)
self.assertEqual(fields(C)[0].metadata['a'], 10)
with self.assertRaises(AttributeError):
fields(C)[0].metadata['b']
# Make sure we're still talking to our custom mapping.
self.assertEqual(fields(C)[0].metadata['xyzzy'], 'plugh')
def test_generic_dataclasses(self):
T = TypeVar('T')
@dataclass
class LabeledBox(Generic[T]):
content: T
label: str = '<unknown>'
box = LabeledBox(42)
self.assertEqual(box.content, 42)
self.assertEqual(box.label, '<unknown>')
# subscripting the resulting class should work, etc.
Alias = List[LabeledBox[int]]
def test_generic_extending(self):
S = TypeVar('S')
T = TypeVar('T')
@dataclass
class Base(Generic[T, S]):
x: T
y: S
@dataclass
class DataDerived(Base[int, T]):
new_field: str
Alias = DataDerived[str]
c = Alias(0, 'test1', 'test2')
self.assertEqual(astuple(c), (0, 'test1', 'test2'))
class NonDataDerived(Base[int, T]):
def new_method(self):
return self.y
Alias = NonDataDerived[float]
c = Alias(10, 1.0)
self.assertEqual(c.new_method(), 1.0)
def test_helper_replace(self):
@dataclass(frozen=True)
class C:
x: int
y: int
c = C(1, 2)
c1 = replace(c, x=3)
self.assertEqual(c1.x, 3)
self.assertEqual(c1.y, 2)
def test_helper_replace_frozen(self):
@dataclass(frozen=True)
class C:
x: int
y: int
z: int = field(init=False, default=10)
t: int = field(init=False, default=100)
c = C(1, 2)
c1 = replace(c, x=3)
self.assertEqual((c.x, c.y, c.z, c.t), (1, 2, 10, 100))
self.assertEqual((c1.x, c1.y, c1.z, c1.t), (3, 2, 10, 100))
with self.assertRaisesRegex(ValueError, 'init=False'):
replace(c, x=3, z=20, t=50)
with self.assertRaisesRegex(ValueError, 'init=False'):
replace(c, z=20)
replace(c, x=3, z=20, t=50)
# Make sure the result is still frozen.
with self.assertRaisesRegex(FrozenInstanceError, "cannot assign to field 'x'"):
c1.x = 3
# Make sure we can't replace an attribute that doesn't exist,
# if we're also replacing one that does exist. Test this
# here, because setting attributes on frozen instances is
# handled slightly differently from non-frozen ones.
with self.assertRaisesRegex(TypeError, "__init__\(\) got an unexpected "
"keyword argument 'a'"):
c1 = replace(c, x=20, a=5)
def test_helper_replace_invalid_field_name(self):
@dataclass(frozen=True)
class C:
x: int
y: int
c = C(1, 2)
with self.assertRaisesRegex(TypeError, "__init__\(\) got an unexpected "
"keyword argument 'z'"):
c1 = replace(c, z=3)
def test_helper_replace_invalid_object(self):
@dataclass(frozen=True)
class C:
x: int
y: int
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
replace(C, x=3)
with self.assertRaisesRegex(TypeError, 'dataclass instance'):
replace(0, x=3)
def test_helper_replace_no_init(self):
@dataclass
class C:
x: int
y: int = field(init=False, default=10)
c = C(1)
c.y = 20
# Make sure y gets the default value.
c1 = replace(c, x=5)
self.assertEqual((c1.x, c1.y), (5, 10))
# Trying to replace y is an error.
with self.assertRaisesRegex(ValueError, 'init=False'):
replace(c, x=2, y=30)
with self.assertRaisesRegex(ValueError, 'init=False'):
replace(c, y=30)
def test_dataclassses_pickleable(self):
global P, Q, R
@dataclass
class P:
x: int
y: int = 0
@dataclass
class Q:
x: int
y: int = field(default=0, init=False)
@dataclass
class R:
x: int
y: List[int] = field(default_factory=list)
q = Q(1)
q.y = 2
samples = [P(1), P(1, 2), Q(1), q, R(1), R(1, [2, 3, 4])]
for sample in samples:
for proto in range(pickle.HIGHEST_PROTOCOL + 1):
with self.subTest(sample=sample, proto=proto):
new_sample = pickle.loads(pickle.dumps(sample, proto))
self.assertEqual(sample.x, new_sample.x)
self.assertEqual(sample.y, new_sample.y)
self.assertIsNot(sample, new_sample)
new_sample.x = 42
another_new_sample = pickle.loads(pickle.dumps(new_sample, proto))
self.assertEqual(new_sample.x, another_new_sample.x)
self.assertEqual(sample.y, another_new_sample.y)
def test_helper_make_dataclass(self):
C = make_dataclass('C',
[('x', int),
('y', int, field(default=5))],
namespace={'add_one': lambda self: self.x + 1})
c = C(10)
self.assertEqual((c.x, c.y), (10, 5))
self.assertEqual(c.add_one(), 11)
def test_helper_make_dataclass_no_mutate_namespace(self):
# Make sure a provided namespace isn't mutated.
ns = {}
C = make_dataclass('C',
[('x', int),
('y', int, field(default=5))],
namespace=ns)
self.assertEqual(ns, {})
def test_helper_make_dataclass_base(self):
class Base1:
pass
class Base2:
pass
C = make_dataclass('C',
[('x', int)],
bases=(Base1, Base2))
c = C(2)
self.assertIsInstance(c, C)
self.assertIsInstance(c, Base1)
self.assertIsInstance(c, Base2)
def test_helper_make_dataclass_base_dataclass(self):
@dataclass
class Base1:
x: int
class Base2:
pass
C = make_dataclass('C',
[('y', int)],
bases=(Base1, Base2))
with self.assertRaisesRegex(TypeError, 'required positional'):
c = C(2)
c = C(1, 2)
self.assertIsInstance(c, C)
self.assertIsInstance(c, Base1)
self.assertIsInstance(c, Base2)
self.assertEqual((c.x, c.y), (1, 2))
def test_helper_make_dataclass_init_var(self):
def post_init(self, y):
self.x *= y
C = make_dataclass('C',
[('x', int),
('y', InitVar[int]),
],
namespace={'__post_init__': post_init},
)
c = C(2, 3)
self.assertEqual(vars(c), {'x': 6})
self.assertEqual(len(fields(c)), 1)
def test_helper_make_dataclass_class_var(self):
C = make_dataclass('C',
[('x', int),
('y', ClassVar[int], 10),
('z', ClassVar[int], field(default=20)),
])
c = C(1)
self.assertEqual(vars(c), {'x': 1})
self.assertEqual(len(fields(c)), 1)
self.assertEqual(C.y, 10)
self.assertEqual(C.z, 20)
class TestDocString(unittest.TestCase):
def assertDocStrEqual(self, a, b):
# Because 3.6 and 3.7 differ in how inspect.signature work
# (see bpo #32108), for the time being just compare them with
# whitespace stripped.
self.assertEqual(a.replace(' ', ''), b.replace(' ', ''))
def test_existing_docstring_not_overridden(self):
@dataclass
class C:
"""Lorem ipsum"""
x: int
self.assertEqual(C.__doc__, "Lorem ipsum")
def test_docstring_no_fields(self):
@dataclass
class C:
pass
self.assertDocStrEqual(C.__doc__, "C()")
def test_docstring_one_field(self):
@dataclass
class C:
x: int
self.assertDocStrEqual(C.__doc__, "C(x:int)")
def test_docstring_two_fields(self):
@dataclass
class C:
x: int
y: int
self.assertDocStrEqual(C.__doc__, "C(x:int, y:int)")
def test_docstring_three_fields(self):
@dataclass
class C:
x: int
y: int
z: str
self.assertDocStrEqual(C.__doc__, "C(x:int, y:int, z:str)")
def test_docstring_one_field_with_default(self):
@dataclass
class C:
x: int = 3
self.assertDocStrEqual(C.__doc__, "C(x:int=3)")
def test_docstring_one_field_with_default_none(self):
@dataclass
class C:
x: Union[int, type(None)] = None
self.assertDocStrEqual(C.__doc__, "C(x:Union[int, NoneType]=None)")
def test_docstring_list_field(self):
@dataclass
class C:
x: List[int]
self.assertDocStrEqual(C.__doc__, "C(x:List[int])")
def test_docstring_list_field_with_default_factory(self):
@dataclass
class C:
x: List[int] = field(default_factory=list)
self.assertDocStrEqual(C.__doc__, "C(x:List[int]=<factory>)")
def test_docstring_deque_field(self):
@dataclass
class C:
x: deque
self.assertDocStrEqual(C.__doc__, "C(x:collections.deque)")
def test_docstring_deque_field_with_default_factory(self):
@dataclass
class C:
x: deque = field(default_factory=deque)
self.assertDocStrEqual(C.__doc__, "C(x:collections.deque=<factory>)")
if __name__ == '__main__':
unittest.main()
Misc/NEWS.d/next/Library/2017-12-04-15-51-57.bpo-32214.uozdNj.rst 0 → 100644
View file @ f0db54a0
PEP 557, Data Classes. Provides a decorator which adds boilerplate methods
to classes which use type annotations so specify fields.
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