Commit 713a9367 authored by Barry Warsaw's avatar Barry Warsaw Committed by GitHub

bpo-32216: Update dataclasses documentation (#6913)

parent 6d2cd903
...@@ -117,50 +117,46 @@ Module-level decorators, classes, and functions ...@@ -117,50 +117,46 @@ Module-level decorators, classes, and functions
:meth:`__le__`, :meth:`__gt__`, or :meth:`__ge__`, then :meth:`__le__`, :meth:`__gt__`, or :meth:`__ge__`, then
:exc:`ValueError` is raised. :exc:`ValueError` is raised.
- ``unsafe_hash``: If ``False`` (the default), the :meth:`__hash__` method - ``unsafe_hash``: If ``False`` (the default), a :meth:`__hash__` method
is generated according to how ``eq`` and ``frozen`` are set. is generated according to how ``eq`` and ``frozen`` are set.
If ``eq`` and ``frozen`` are both true, :func:`dataclass` will :meth:`__hash__` is used by built-in :meth:`hash()`, and when objects are
generate a :meth:`__hash__` method for you. If ``eq`` is true added to hashed collections such as dictionaries and sets. Having a
and ``frozen`` is false, :meth:`__hash__` will be set to :meth:`__hash__` implies that instances of the class are immutable.
``None``, marking it unhashable (which it is, since it is Mutability is a complicated property that depends on the programmer's
mutable). If ``eq`` is false, :meth:`__hash__` will be left intent, the existence and behavior of :meth:`__eq__`, and the values of
untouched meaning the :meth:`__hash__` method of the superclass the ``eq`` and ``frozen`` flags in the :func:`dataclass` decorator.
will be used (if the superclass is :class:`object`, this means it will
fall back to id-based hashing). By default, :func:`dataclass` will not implicitly add a :meth:`__hash__`
method unless it is safe to do so. Neither will it add or change an
Although not recommended, you can force :func:`dataclass` to existing explicitly defined :meth:`__hash__` method. Setting the class
create a :meth:`__hash__` method with ``unsafe_hash=True``. This attribute ``__hash__ = None`` has a specific meaning to Python, as
might be the case if your class is logically immutable but can described in the :meth:`__hash__` documentation.
nonetheless be mutated. This is a specialized use case and should
be considered carefully. If :meth:`__hash__` is not explicit defined, or if it is set to ``None``,
then :func:`dataclass` *may* add an implicit :meth:`__hash__` method.
If a class already has an explicitely defined :meth:`__hash__` Although not recommended, you can force :func:`dataclass` to create a
the behavior when adding :meth:`__hash__` is modified. An :meth:`__hash__` method with ``unsafe_hash=True``. This might be the case
expicitely defined :meth:`__hash__` is defined when: if your class is logically immutable but can nonetheless be mutated.
This is a specialized use case and should be considered carefully.
- :meth:`__eq__` is defined in the class and :meth:`__hash__` is defined
with any value other than ``None``. Here are the rules governing implicit creation of a :meth:`__hash__`
method. Note that you cannot both have an explicit :meth:`__hash__`
- :meth:`__eq__` is defined in the class and any non-``None`` method in your dataclass and set ``unsafe_hash=True``; this will result
:meth:`__hash__` is defined. in a :exc:`TypeError`.
- :meth:`__eq__` is not defined on the class, and any :meth:`__hash__` is If ``eq`` and ``frozen`` are both true, by default :func:`dataclass` will
defined. generate a :meth:`__hash__` method for you. If ``eq`` is true and
``frozen`` is false, :meth:`__hash__` will be set to ``None``, marking it
If ``unsafe_hash`` is true and an explicitely defined :meth:`__hash__` unhashable (which it is, since it is mutable). If ``eq`` is false,
is present, then :exc:`ValueError` is raised. :meth:`__hash__` will be left untouched meaning the :meth:`__hash__`
method of the superclass will be used (if the superclass is
If ``unsafe_hash`` is false and an explicitely defined :meth:`__hash__` :class:`object`, this means it will fall back to id-based hashing).
is present, then no :meth:`__hash__` is added.
See the Python documentation for more information.
- ``frozen``: If true (the default is False), assigning to fields will - ``frozen``: If true (the default is False), assigning to fields will
generate an exception. This emulates read-only frozen instances. generate an exception. This emulates read-only frozen instances. If
If either :meth:`__getattr__` or :meth:`__setattr__` is defined in :meth:`__setattr__` or :meth:`__delattr__` is defined in the class, then
the class, then :exc:`ValueError` is raised. See the discussion :exc:`TypeError` is raised. See the discussion below.
below.
``field``\s may optionally specify a default value, using normal ``field``\s may optionally specify a default value, using normal
Python syntax:: Python syntax::
...@@ -182,17 +178,17 @@ Module-level decorators, classes, and functions ...@@ -182,17 +178,17 @@ Module-level decorators, classes, and functions
.. function:: field(*, default=MISSING, default_factory=MISSING, repr=True, hash=None, init=True, compare=True, metadata=None) .. function:: field(*, default=MISSING, default_factory=MISSING, repr=True, hash=None, init=True, compare=True, metadata=None)
For common and simple use cases, no other functionality is For common and simple use cases, no other functionality is
required. There are, however, some Data Class features that required. There are, however, some dataclass features that
require additional per-field information. To satisfy this need for require additional per-field information. To satisfy this need for
additional information, you can replace the default field value additional information, you can replace the default field value
with a call to the provided :func:`field` function. For example:: with a call to the provided :func:`field` function. For example::
@dataclass @dataclass
class C: class C:
l: List[int] = field(default_factory=list) mylist: List[int] = field(default_factory=list)
c = C() c = C()
c.l += [1, 2, 3] c.mylist += [1, 2, 3]
As shown above, the ``MISSING`` value is a sentinel object used to As shown above, the ``MISSING`` value is a sentinel object used to
detect if the ``default`` and ``default_factory`` parameters are detect if the ``default`` and ``default_factory`` parameters are
...@@ -222,7 +218,7 @@ Module-level decorators, classes, and functions ...@@ -222,7 +218,7 @@ Module-level decorators, classes, and functions
generated equality and comparison methods (:meth:`__eq__`, generated equality and comparison methods (:meth:`__eq__`,
:meth:`__gt__`, et al.). :meth:`__gt__`, et al.).
- ``hash``: This can be a bool or ``None``. If True, this field is - ``hash``: This can be a bool or ``None``. If true, this field is
included in the generated :meth:`__hash__` method. If ``None`` (the included in the generated :meth:`__hash__` method. If ``None`` (the
default), use the value of ``compare``: this would normally be default), use the value of ``compare``: this would normally be
the expected behavior. A field should be considered in the hash the expected behavior. A field should be considered in the hash
...@@ -283,17 +279,16 @@ Module-level decorators, classes, and functions ...@@ -283,17 +279,16 @@ Module-level decorators, classes, and functions
.. function:: fields(class_or_instance) .. function:: fields(class_or_instance)
Returns a tuple of :class:`Field` objects Returns a tuple of :class:`Field` objects that define the fields for this
that define the fields for this Data Class. Accepts either a Data dataclass. Accepts either a dataclass, or an instance of a dataclass.
Class, or an instance of a Data Class. Raises :exc:`ValueError` if Raises :exc:`TypeError` if not passed a dataclass or instance of one.
not passed a Data Class or instance of one. Does not return Does not return pseudo-fields which are ``ClassVar`` or ``InitVar``.
pseudo-fields which are ``ClassVar`` or ``InitVar``.
.. function:: asdict(instance, *, dict_factory=dict) .. function:: asdict(instance, *, dict_factory=dict)
Converts the Data Class ``instance`` to a dict (by using the Converts the dataclass ``instance`` to a dict (by using the
factory function ``dict_factory``). Each Data Class is converted factory function ``dict_factory``). Each dataclass is converted
to a dict of its fields, as ``name: value`` pairs. Data Classes, dicts, to a dict of its fields, as ``name: value`` pairs. dataclasses, dicts,
lists, and tuples are recursed into. For example:: lists, and tuples are recursed into. For example::
@dataclass @dataclass
...@@ -303,21 +298,21 @@ Module-level decorators, classes, and functions ...@@ -303,21 +298,21 @@ Module-level decorators, classes, and functions
@dataclass @dataclass
class C: class C:
l: List[Point] mylist: List[Point]
p = Point(10, 20) p = Point(10, 20)
assert asdict(p) == {'x': 10, 'y': 20} assert asdict(p) == {'x': 10, 'y': 20}
c = C([Point(0, 0), Point(10, 4)]) c = C([Point(0, 0), Point(10, 4)])
assert asdict(c) == {'l': [{'x': 0, 'y': 0}, {'x': 10, 'y': 4}]} assert asdict(c) == {'mylist': [{'x': 0, 'y': 0}, {'x': 10, 'y': 4}]}
Raises :exc:`TypeError` if ``instance`` is not a Data Class instance. Raises :exc:`TypeError` if ``instance`` is not a dataclass instance.
.. function:: astuple(*, tuple_factory=tuple) .. function:: astuple(*, tuple_factory=tuple)
Converts the Data Class ``instance`` to a tuple (by using the Converts the dataclass ``instance`` to a tuple (by using the
factory function ``tuple_factory``). Each Data Class is converted factory function ``tuple_factory``). Each dataclass is converted
to a tuple of its field values. Data Classes, dicts, lists, and to a tuple of its field values. dataclasses, dicts, lists, and
tuples are recursed into. tuples are recursed into.
Continuing from the previous example:: Continuing from the previous example::
...@@ -325,11 +320,11 @@ Module-level decorators, classes, and functions ...@@ -325,11 +320,11 @@ Module-level decorators, classes, and functions
assert astuple(p) == (10, 20) assert astuple(p) == (10, 20)
assert astuple(c) == ([(0, 0), (10, 4)],) assert astuple(c) == ([(0, 0), (10, 4)],)
Raises :exc:`TypeError` if ``instance`` is not a Data Class instance. Raises :exc:`TypeError` if ``instance`` is not a dataclass instance.
.. function:: make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False) .. function:: make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False)
Creates a new Data Class with name ``cls_name``, fields as defined Creates a new dataclass with name ``cls_name``, fields as defined
in ``fields``, base classes as given in ``bases``, and initialized in ``fields``, base classes as given in ``bases``, and initialized
with a namespace as given in ``namespace``. ``fields`` is an with a namespace as given in ``namespace``. ``fields`` is an
iterable whose elements are each either ``name``, ``(name, type)``, iterable whose elements are each either ``name``, ``(name, type)``,
...@@ -341,7 +336,7 @@ Module-level decorators, classes, and functions ...@@ -341,7 +336,7 @@ Module-level decorators, classes, and functions
This function is not strictly required, because any Python This function is not strictly required, because any Python
mechanism for creating a new class with ``__annotations__`` can mechanism for creating a new class with ``__annotations__`` can
then apply the :func:`dataclass` function to convert that class to then apply the :func:`dataclass` function to convert that class to
a Data Class. This function is provided as a convenience. For a dataclass. This function is provided as a convenience. For
example:: example::
C = make_dataclass('C', C = make_dataclass('C',
...@@ -369,14 +364,14 @@ Module-level decorators, classes, and functions ...@@ -369,14 +364,14 @@ Module-level decorators, classes, and functions
specify fields, raises :exc:`TypeError`. specify fields, raises :exc:`TypeError`.
The newly returned object is created by calling the :meth:`__init__` The newly returned object is created by calling the :meth:`__init__`
method of the Data Class. This ensures that method of the dataclass. This ensures that
:meth:`__post_init__`, if present, is also called. :meth:`__post_init__`, if present, is also called.
Init-only variables without default values, if any exist, must be Init-only variables without default values, if any exist, must be
specified on the call to :func:`replace` so that they can be passed to specified on the call to :func:`replace` so that they can be passed to
:meth:`__init__` and :meth:`__post_init__`. :meth:`__init__` and :meth:`__post_init__`.
It is an error for :func:`changes` to contain any fields that are It is an error for ``changes`` to contain any fields that are
defined as having ``init=False``. A :exc:`ValueError` will be raised defined as having ``init=False``. A :exc:`ValueError` will be raised
in this case. in this case.
...@@ -408,7 +403,7 @@ The generated :meth:`__init__` code will call a method named ...@@ -408,7 +403,7 @@ The generated :meth:`__init__` code will call a method named
:meth:`__post_init__`, if :meth:`__post_init__` is defined on the :meth:`__post_init__`, if :meth:`__post_init__` is defined on the
class. It will normally be called as ``self.__post_init__()``. class. It will normally be called as ``self.__post_init__()``.
However, if any ``InitVar`` fields are defined, they will also be However, if any ``InitVar`` fields are defined, they will also be
passed to :meth:`__post_init` in the order they were defined in the passed to :meth:`__post_init__` in the order they were defined in the
class. If no :meth:`__init__` method is generated, then class. If no :meth:`__init__` method is generated, then
:meth:`__post_init__` will not automatically be called. :meth:`__post_init__` will not automatically be called.
...@@ -435,7 +430,7 @@ One of two places where :func:`dataclass` actually inspects the type ...@@ -435,7 +430,7 @@ One of two places where :func:`dataclass` actually inspects the type
of a field is to determine if a field is a class variable as defined of a field is to determine if a field is a class variable as defined
in :pep:`526`. It does this by checking if the type of the field is in :pep:`526`. It does this by checking if the type of the field is
``typing.ClassVar``. If a field is a ``ClassVar``, it is excluded ``typing.ClassVar``. If a field is a ``ClassVar``, it is excluded
from consideration as a field and is ignored by the Data Class from consideration as a field and is ignored by the dataclass
mechanisms. Such ``ClassVar`` pseudo-fields are not returned by the mechanisms. Such ``ClassVar`` pseudo-fields are not returned by the
module-level :func:`fields` function. module-level :func:`fields` function.
...@@ -450,7 +445,7 @@ field. As it is not a true field, it is not returned by the ...@@ -450,7 +445,7 @@ field. As it is not a true field, it is not returned by the
module-level :func:`fields` function. Init-only fields are added as module-level :func:`fields` function. Init-only fields are added as
parameters to the generated :meth:`__init__` method, and are passed to parameters to the generated :meth:`__init__` method, and are passed to
the optional :meth:`__post_init__` method. They are not otherwise used the optional :meth:`__post_init__` method. They are not otherwise used
by Data Classes. by dataclasses.
For example, suppose a field will be initialzed from a database, if a For example, suppose a field will be initialzed from a database, if a
value is not provided when creating the class:: value is not provided when creating the class::
...@@ -475,7 +470,7 @@ Frozen instances ...@@ -475,7 +470,7 @@ Frozen instances
It is not possible to create truly immutable Python objects. However, It is not possible to create truly immutable Python objects. However,
by passing ``frozen=True`` to the :meth:`dataclass` decorator you can by passing ``frozen=True`` to the :meth:`dataclass` decorator you can
emulate immutability. In that case, Data Classes will add emulate immutability. In that case, dataclasses will add
:meth:`__setattr__` and :meth:`__delattr__` methods to the class. These :meth:`__setattr__` and :meth:`__delattr__` methods to the class. These
methods will raise a :exc:`FrozenInstanceError` when invoked. methods will raise a :exc:`FrozenInstanceError` when invoked.
...@@ -486,9 +481,9 @@ must use :meth:`object.__setattr__`. ...@@ -486,9 +481,9 @@ must use :meth:`object.__setattr__`.
Inheritance Inheritance
----------- -----------
When the Data Class is being created by the :meth:`dataclass` decorator, When the dataclass is being created by the :meth:`dataclass` decorator,
it looks through all of the class's base classes in reverse MRO (that it looks through all of the class's base classes in reverse MRO (that
is, starting at :class:`object`) and, for each Data Class that it finds, is, starting at :class:`object`) and, for each dataclass that it finds,
adds the fields from that base class to an ordered mapping of fields. adds the fields from that base class to an ordered mapping of fields.
After all of the base class fields are added, it adds its own fields After all of the base class fields are added, it adds its own fields
to the ordered mapping. All of the generated methods will use this to the ordered mapping. All of the generated methods will use this
...@@ -520,7 +515,7 @@ Default factory functions ...@@ -520,7 +515,7 @@ Default factory functions
zero arguments when a default value for the field is needed. For zero arguments when a default value for the field is needed. For
example, to create a new instance of a list, use:: example, to create a new instance of a list, use::
l: list = field(default_factory=list) mylist: list = field(default_factory=list)
If a field is excluded from :meth:`__init__` (using ``init=False``) If a field is excluded from :meth:`__init__` (using ``init=False``)
and the field also specifies ``default_factory``, then the default and the field also specifies ``default_factory``, then the default
...@@ -532,7 +527,7 @@ Mutable default values ...@@ -532,7 +527,7 @@ Mutable default values
---------------------- ----------------------
Python stores default member variable values in class attributes. Python stores default member variable values in class attributes.
Consider this example, not using Data Classes:: Consider this example, not using dataclasses::
class C: class C:
x = [] x = []
...@@ -549,7 +544,7 @@ Mutable default values ...@@ -549,7 +544,7 @@ Mutable default values
Note that the two instances of class ``C`` share the same class Note that the two instances of class ``C`` share the same class
variable ``x``, as expected. variable ``x``, as expected.
Using Data Classes, *if* this code was valid:: Using dataclasses, *if* this code was valid::
@dataclass @dataclass
class D: class D:
...@@ -571,9 +566,9 @@ Mutable default values ...@@ -571,9 +566,9 @@ Mutable default values
This has the same issue as the original example using class ``C``. This has the same issue as the original example using class ``C``.
That is, two instances of class ``D`` that do not specify a value for That is, two instances of class ``D`` that do not specify a value for
``x`` when creating a class instance will share the same copy of ``x`` when creating a class instance will share the same copy of
``x``. Because Data Classes just use normal Python class creation ``x``. Because dataclasses just use normal Python class creation
they also share this problem. There is no general way for Data they also share this behavior. There is no general way for Data
Classes to detect this condition. Instead, Data Classes will raise a Classes to detect this condition. Instead, dataclasses will raise a
:exc:`TypeError` if it detects a default parameter of type ``list``, :exc:`TypeError` if it detects a default parameter of type ``list``,
``dict``, or ``set``. This is a partial solution, but it does protect ``dict``, or ``set``. This is a partial solution, but it does protect
against many common errors. against many common errors.
...@@ -586,3 +581,12 @@ Mutable default values ...@@ -586,3 +581,12 @@ Mutable default values
x: list = field(default_factory=list) x: list = field(default_factory=list)
assert D().x is not D().x assert D().x is not D().x
Exceptions
----------
.. exception:: FrozenInstanceError
Raised when an implicitly defined :meth:`__setattr__` or
:meth:`__delattr__` is called on a dataclass which was defined with
``frozen=True``.
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