729 lines
28 KiB
ReStructuredText
729 lines
28 KiB
ReStructuredText
:mod:`dataclasses` --- Data Classes
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===================================
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.. module:: dataclasses
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:synopsis: Generate special methods on user-defined classes.
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.. moduleauthor:: Eric V. Smith <eric@trueblade.com>
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.. sectionauthor:: Eric V. Smith <eric@trueblade.com>
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**Source code:** :source:`Lib/dataclasses.py`
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--------------
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This module provides a decorator and functions for automatically
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adding generated :term:`special method`\s such as :meth:`__init__` and
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:meth:`__repr__` to user-defined classes. It was originally described
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in :pep:`557`.
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The member variables to use in these generated methods are defined
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using :pep:`526` type annotations. For example, this code::
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from dataclasses import dataclass
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@dataclass
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class InventoryItem:
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"""Class for keeping track of an item in inventory."""
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name: str
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unit_price: float
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quantity_on_hand: int = 0
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def total_cost(self) -> float:
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return self.unit_price * self.quantity_on_hand
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will add, among other things, a :meth:`__init__` that looks like::
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def __init__(self, name: str, unit_price: float, quantity_on_hand: int = 0):
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self.name = name
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self.unit_price = unit_price
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self.quantity_on_hand = quantity_on_hand
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Note that this method is automatically added to the class: it is not
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directly specified in the ``InventoryItem`` definition shown above.
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.. versionadded:: 3.7
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Module contents
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---------------
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.. decorator:: dataclass(*, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False, match_args=True, kw_only=False, slots=False)
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This function is a :term:`decorator` that is used to add generated
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:term:`special method`\s to classes, as described below.
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The :func:`dataclass` decorator examines the class to find
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``field``\s. A ``field`` is defined as a class variable that has a
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:term:`type annotation <variable annotation>`. With two
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exceptions described below, nothing in :func:`dataclass`
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examines the type specified in the variable annotation.
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The order of the fields in all of the generated methods is the
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order in which they appear in the class definition.
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The :func:`dataclass` decorator will add various "dunder" methods to
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the class, described below. If any of the added methods already
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exist in the class, the behavior depends on the parameter, as documented
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below. The decorator returns the same class that it is called on; no new
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class is created.
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If :func:`dataclass` is used just as a simple decorator with no parameters,
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it acts as if it has the default values documented in this
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signature. That is, these three uses of :func:`dataclass` are
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equivalent::
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@dataclass
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class C:
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...
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@dataclass()
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class C:
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...
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@dataclass(init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False, match_args=True, kw_only=False, slots=False)
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class C:
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...
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The parameters to :func:`dataclass` are:
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- ``init``: If true (the default), a :meth:`__init__` method will be
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generated.
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If the class already defines :meth:`__init__`, this parameter is
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ignored.
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- ``repr``: If true (the default), a :meth:`__repr__` method will be
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generated. The generated repr string will have the class name and
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the name and repr of each field, in the order they are defined in
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the class. Fields that are marked as being excluded from the repr
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are not included. For example:
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``InventoryItem(name='widget', unit_price=3.0, quantity_on_hand=10)``.
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If the class already defines :meth:`__repr__`, this parameter is
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ignored.
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- ``eq``: If true (the default), an :meth:`__eq__` method will be
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generated. This method compares the class as if it were a tuple
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of its fields, in order. Both instances in the comparison must
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be of the identical type.
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If the class already defines :meth:`__eq__`, this parameter is
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ignored.
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- ``order``: If true (the default is ``False``), :meth:`__lt__`,
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:meth:`__le__`, :meth:`__gt__`, and :meth:`__ge__` methods will be
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generated. These compare the class as if it were a tuple of its
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fields, in order. Both instances in the comparison must be of the
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identical type. If ``order`` is true and ``eq`` is false, a
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:exc:`ValueError` is raised.
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If the class already defines any of :meth:`__lt__`,
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:meth:`__le__`, :meth:`__gt__`, or :meth:`__ge__`, then
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:exc:`TypeError` is raised.
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- ``unsafe_hash``: If ``False`` (the default), a :meth:`__hash__` method
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is generated according to how ``eq`` and ``frozen`` are set.
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:meth:`__hash__` is used by built-in :meth:`hash()`, and when objects are
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added to hashed collections such as dictionaries and sets. Having a
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:meth:`__hash__` implies that instances of the class are immutable.
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Mutability is a complicated property that depends on the programmer's
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intent, the existence and behavior of :meth:`__eq__`, and the values of
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the ``eq`` and ``frozen`` flags in the :func:`dataclass` decorator.
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By default, :func:`dataclass` will not implicitly add a :meth:`__hash__`
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method unless it is safe to do so. Neither will it add or change an
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existing explicitly defined :meth:`__hash__` method. Setting the class
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attribute ``__hash__ = None`` has a specific meaning to Python, as
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described in the :meth:`__hash__` documentation.
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If :meth:`__hash__` is not explicitly defined, or if it is set to ``None``,
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then :func:`dataclass` *may* add an implicit :meth:`__hash__` method.
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Although not recommended, you can force :func:`dataclass` to create a
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:meth:`__hash__` method with ``unsafe_hash=True``. This might be the case
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if your class is logically immutable but can nonetheless be mutated.
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This is a specialized use case and should be considered carefully.
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Here are the rules governing implicit creation of a :meth:`__hash__`
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method. Note that you cannot both have an explicit :meth:`__hash__`
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method in your dataclass and set ``unsafe_hash=True``; this will result
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in a :exc:`TypeError`.
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If ``eq`` and ``frozen`` are both true, by default :func:`dataclass` will
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generate a :meth:`__hash__` method for you. If ``eq`` is true and
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``frozen`` is false, :meth:`__hash__` will be set to ``None``, marking it
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unhashable (which it is, since it is mutable). If ``eq`` is false,
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:meth:`__hash__` will be left untouched meaning the :meth:`__hash__`
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method of the superclass will be used (if the superclass is
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:class:`object`, this means it will fall back to id-based hashing).
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- ``frozen``: If true (the default is ``False``), assigning to fields will
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generate an exception. This emulates read-only frozen instances. If
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:meth:`__setattr__` or :meth:`__delattr__` is defined in the class, then
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:exc:`TypeError` is raised. See the discussion below.
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- ``match_args``: If true (the default is ``True``), the
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``__match_args__`` tuple will be created from the list of
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parameters to the generated :meth:`__init__` method (even if
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:meth:`__init__` is not generated, see above). If false, or if
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``__match_args__`` is already defined in the class, then
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``__match_args__`` will not be generated.
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.. versionadded:: 3.10
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- ``kw_only``: If true (the default value is ``False``), then all
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fields will be marked as keyword-only. If a field is marked as
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keyword-only, then the only affect is that the :meth:`__init__`
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parameter generated from a keyword-only field must be specified
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with a keyword when :meth:`__init__` is called. There is no
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effect on any other aspect of dataclasses. See the
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:term:`parameter` glossary entry for details. Also see the
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:const:`KW_ONLY` section.
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.. versionadded:: 3.10
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- ``slots``: If true (the default is ``False``), :attr:`__slots__` attribute
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will be generated and new class will be returned instead of the original one.
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If :attr:`__slots__` is already defined in the class, then :exc:`TypeError`
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is raised.
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.. versionadded:: 3.10
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``field``\s may optionally specify a default value, using normal
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Python syntax::
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@dataclass
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class C:
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a: int # 'a' has no default value
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b: int = 0 # assign a default value for 'b'
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In this example, both ``a`` and ``b`` will be included in the added
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:meth:`__init__` method, which will be defined as::
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def __init__(self, a: int, b: int = 0):
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:exc:`TypeError` will be raised if a field without a default value
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follows a field with a default value. This is true whether this
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occurs in a single class, or as a result of class inheritance.
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.. function:: field(*, default=MISSING, default_factory=MISSING, init=True, repr=True, hash=None, compare=True, metadata=None, kw_only=MISSING)
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For common and simple use cases, no other functionality is
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required. There are, however, some dataclass features that
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require additional per-field information. To satisfy this need for
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additional information, you can replace the default field value
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with a call to the provided :func:`field` function. For example::
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@dataclass
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class C:
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mylist: list[int] = field(default_factory=list)
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c = C()
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c.mylist += [1, 2, 3]
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As shown above, the :const:`MISSING` value is a sentinel object used to
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detect if some parameters are provided by the user. This sentinel is
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used because ``None`` is a valid value for some parameters with
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a distinct meaning. No code should directly use the :const:`MISSING` value.
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The parameters to :func:`field` are:
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- ``default``: If provided, this will be the default value for this
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field. This is needed because the :meth:`field` call itself
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replaces the normal position of the default value.
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- ``default_factory``: If provided, it must be a zero-argument
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callable that will be called when a default value is needed for
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this field. Among other purposes, this can be used to specify
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fields with mutable default values, as discussed below. It is an
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error to specify both ``default`` and ``default_factory``.
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- ``init``: If true (the default), this field is included as a
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parameter to the generated :meth:`__init__` method.
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- ``repr``: If true (the default), this field is included in the
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string returned by the generated :meth:`__repr__` method.
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- ``hash``: This can be a bool or ``None``. If true, this field is
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included in the generated :meth:`__hash__` method. If ``None`` (the
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default), use the value of ``compare``: this would normally be
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the expected behavior. A field should be considered in the hash
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if it's used for comparisons. Setting this value to anything
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other than ``None`` is discouraged.
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One possible reason to set ``hash=False`` but ``compare=True``
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would be if a field is expensive to compute a hash value for,
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that field is needed for equality testing, and there are other
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fields that contribute to the type's hash value. Even if a field
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is excluded from the hash, it will still be used for comparisons.
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- ``compare``: If true (the default), this field is included in the
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generated equality and comparison methods (:meth:`__eq__`,
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:meth:`__gt__`, et al.).
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- ``metadata``: This can be a mapping or None. None is treated as
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an empty dict. This value is wrapped in
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:func:`~types.MappingProxyType` to make it read-only, and exposed
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on the :class:`Field` object. It is not used at all by Data
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Classes, and is provided as a third-party extension mechanism.
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Multiple third-parties can each have their own key, to use as a
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namespace in the metadata.
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- ``kw_only``: If true, this field will be marked as keyword-only.
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This is used when the generated :meth:`__init__` method's
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parameters are computed.
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.. versionadded:: 3.10
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If the default value of a field is specified by a call to
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:func:`field()`, then the class attribute for this field will be
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replaced by the specified ``default`` value. If no ``default`` is
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provided, then the class attribute will be deleted. The intent is
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that after the :func:`dataclass` decorator runs, the class
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attributes will all contain the default values for the fields, just
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as if the default value itself were specified. For example,
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after::
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@dataclass
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class C:
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x: int
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y: int = field(repr=False)
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z: int = field(repr=False, default=10)
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t: int = 20
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The class attribute ``C.z`` will be ``10``, the class attribute
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``C.t`` will be ``20``, and the class attributes ``C.x`` and
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``C.y`` will not be set.
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.. class:: Field
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:class:`Field` objects describe each defined field. These objects
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are created internally, and are returned by the :func:`fields`
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module-level method (see below). Users should never instantiate a
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:class:`Field` object directly. Its documented attributes are:
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- ``name``: The name of the field.
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- ``type``: The type of the field.
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- ``default``, ``default_factory``, ``init``, ``repr``, ``hash``,
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``compare``, ``metadata``, and ``kw_only`` have the identical
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meaning and values as they do in the :func:`field` function.
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Other attributes may exist, but they are private and must not be
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inspected or relied on.
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.. function:: fields(class_or_instance)
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Returns a tuple of :class:`Field` objects that define the fields for this
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dataclass. Accepts either a dataclass, or an instance of a dataclass.
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Raises :exc:`TypeError` if not passed a dataclass or instance of one.
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Does not return pseudo-fields which are ``ClassVar`` or ``InitVar``.
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.. function:: asdict(obj, *, dict_factory=dict)
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Converts the dataclass ``obj`` to a dict (by using the
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factory function ``dict_factory``). Each dataclass is converted
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to a dict of its fields, as ``name: value`` pairs. dataclasses, dicts,
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lists, and tuples are recursed into. Other objects are copied with
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:func:`copy.deepcopy`.
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Example of using :func:`asdict` on nested dataclasses::
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@dataclass
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class Point:
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x: int
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y: int
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@dataclass
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class C:
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mylist: list[Point]
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p = Point(10, 20)
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assert asdict(p) == {'x': 10, 'y': 20}
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c = C([Point(0, 0), Point(10, 4)])
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assert asdict(c) == {'mylist': [{'x': 0, 'y': 0}, {'x': 10, 'y': 4}]}
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To create a shallow copy, the following workaround may be used::
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dict((field.name, getattr(obj, field.name)) for field in fields(obj))
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:func:`asdict` raises :exc:`TypeError` if ``obj`` is not a dataclass
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instance.
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.. function:: astuple(obj, *, tuple_factory=tuple)
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Converts the dataclass ``obj`` to a tuple (by using the
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factory function ``tuple_factory``). Each dataclass is converted
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to a tuple of its field values. dataclasses, dicts, lists, and
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tuples are recursed into. Other objects are copied with
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:func:`copy.deepcopy`.
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Continuing from the previous example::
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assert astuple(p) == (10, 20)
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assert astuple(c) == ([(0, 0), (10, 4)],)
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To create a shallow copy, the following workaround may be used::
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tuple(getattr(obj, field.name) for field in dataclasses.fields(obj))
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:func:`astuple` raises :exc:`TypeError` if ``obj`` is not a dataclass
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instance.
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.. function:: make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False, match_args=True, kw_only=False, slots=False)
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Creates a new dataclass with name ``cls_name``, fields as defined
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in ``fields``, base classes as given in ``bases``, and initialized
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with a namespace as given in ``namespace``. ``fields`` is an
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iterable whose elements are each either ``name``, ``(name, type)``,
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or ``(name, type, Field)``. If just ``name`` is supplied,
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``typing.Any`` is used for ``type``. The values of ``init``,
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``repr``, ``eq``, ``order``, ``unsafe_hash``, ``frozen``,
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``match_args``, ``kw_only``, and ``slots`` have the same meaning as
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they do in :func:`dataclass`.
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This function is not strictly required, because any Python
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mechanism for creating a new class with ``__annotations__`` can
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then apply the :func:`dataclass` function to convert that class to
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a dataclass. This function is provided as a convenience. For
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example::
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C = make_dataclass('C',
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[('x', int),
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'y',
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('z', int, field(default=5))],
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namespace={'add_one': lambda self: self.x + 1})
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Is equivalent to::
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@dataclass
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class C:
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x: int
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y: 'typing.Any'
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z: int = 5
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def add_one(self):
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return self.x + 1
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.. function:: replace(obj, /, **changes)
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Creates a new object of the same type as ``obj``, replacing
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fields with values from ``changes``. If ``obj`` is not a Data
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Class, raises :exc:`TypeError`. If values in ``changes`` do not
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specify fields, raises :exc:`TypeError`.
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The newly returned object is created by calling the :meth:`__init__`
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method of the dataclass. This ensures that
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:meth:`__post_init__`, if present, is also called.
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Init-only variables without default values, if any exist, must be
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specified on the call to :func:`replace` so that they can be passed to
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:meth:`__init__` and :meth:`__post_init__`.
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It is an error for ``changes`` to contain any fields that are
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defined as having ``init=False``. A :exc:`ValueError` will be raised
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in this case.
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Be forewarned about how ``init=False`` fields work during a call to
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:func:`replace`. They are not copied from the source object, but
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rather are initialized in :meth:`__post_init__`, if they're
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initialized at all. It is expected that ``init=False`` fields will
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be rarely and judiciously used. If they are used, it might be wise
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to have alternate class constructors, or perhaps a custom
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``replace()`` (or similarly named) method which handles instance
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copying.
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.. function:: is_dataclass(obj)
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Return ``True`` if its parameter is a dataclass or an instance of one,
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otherwise return ``False``.
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If you need to know if a class is an instance of a dataclass (and
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not a dataclass itself), then add a further check for ``not
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isinstance(obj, type)``::
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def is_dataclass_instance(obj):
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return is_dataclass(obj) and not isinstance(obj, type)
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.. data:: MISSING
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A sentinel value signifying a missing default or default_factory.
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.. data:: KW_ONLY
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A sentinel value used as a type annotation. Any fields after a
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pseudo-field with the type of :const:`KW_ONLY` are marked as
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keyword-only fields. Note that a pseudo-field of type
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:const:`KW_ONLY` is otherwise completely ignored. This includes the
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name of such a field. By convention, a name of ``_`` is used for a
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:const:`KW_ONLY` field. Keyword-only fields signify
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:meth:`__init__` parameters that must be specified as keywords when
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the class is instantiated.
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In this example, the fields ``y`` and ``z`` will be marked as keyword-only fields::
|
|
|
|
@dataclass
|
|
class Point:
|
|
x: float
|
|
_: KW_ONLY
|
|
y: float
|
|
z: float
|
|
|
|
p = Point(0, y=1.5, z=2.0)
|
|
|
|
In a single dataclass, it is an error to specify more than one
|
|
field whose type is :const:`KW_ONLY`.
|
|
|
|
.. versionadded:: 3.10
|
|
|
|
.. exception:: FrozenInstanceError
|
|
|
|
Raised when an implicitly defined :meth:`__setattr__` or
|
|
:meth:`__delattr__` is called on a dataclass which was defined with
|
|
``frozen=True``. It is a subclass of :exc:`AttributeError`.
|
|
|
|
Post-init processing
|
|
--------------------
|
|
|
|
The generated :meth:`__init__` code will call a method named
|
|
:meth:`__post_init__`, if :meth:`__post_init__` is defined on the
|
|
class. It will normally be called as ``self.__post_init__()``.
|
|
However, if any ``InitVar`` fields are defined, they will also be
|
|
passed to :meth:`__post_init__` in the order they were defined in the
|
|
class. If no :meth:`__init__` method is generated, then
|
|
:meth:`__post_init__` will not automatically be called.
|
|
|
|
Among other uses, this allows for initializing field values that
|
|
depend on one or more other fields. For example::
|
|
|
|
@dataclass
|
|
class C:
|
|
a: float
|
|
b: float
|
|
c: float = field(init=False)
|
|
|
|
def __post_init__(self):
|
|
self.c = self.a + self.b
|
|
|
|
The :meth:`__init__` method generated by :func:`dataclass` does not call base
|
|
class :meth:`__init__` methods. If the base class has an :meth:`__init__` method
|
|
that has to be called, it is common to call this method in a
|
|
:meth:`__post_init__` method::
|
|
|
|
@dataclass
|
|
class Rectangle:
|
|
height: float
|
|
width: float
|
|
|
|
@dataclass
|
|
class Square(Rectangle):
|
|
side: float
|
|
|
|
def __post_init__(self):
|
|
super().__init__(self.side, self.side)
|
|
|
|
Note, however, that in general the dataclass-generated :meth:`__init__` methods
|
|
don't need to be called, since the derived dataclass will take care of
|
|
initializing all fields of any base class that is a dataclass itself.
|
|
|
|
See the section below on init-only variables for ways to pass
|
|
parameters to :meth:`__post_init__`. Also see the warning about how
|
|
:func:`replace` handles ``init=False`` fields.
|
|
|
|
Class variables
|
|
---------------
|
|
|
|
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
|
|
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
|
|
from consideration as a field and is ignored by the dataclass
|
|
mechanisms. Such ``ClassVar`` pseudo-fields are not returned by the
|
|
module-level :func:`fields` function.
|
|
|
|
Init-only variables
|
|
-------------------
|
|
|
|
The other place where :func:`dataclass` inspects a type annotation is to
|
|
determine if a field is an init-only variable. It does this by seeing
|
|
if the type of a field is of type ``dataclasses.InitVar``. If a field
|
|
is an ``InitVar``, it is considered a pseudo-field called an init-only
|
|
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
|
|
parameters to the generated :meth:`__init__` method, and are passed to
|
|
the optional :meth:`__post_init__` method. They are not otherwise used
|
|
by dataclasses.
|
|
|
|
For example, suppose a field will be initialized from a database, if a
|
|
value is not provided when creating the class::
|
|
|
|
@dataclass
|
|
class C:
|
|
i: int
|
|
j: int = None
|
|
database: InitVar[DatabaseType] = None
|
|
|
|
def __post_init__(self, database):
|
|
if self.j is None and database is not None:
|
|
self.j = database.lookup('j')
|
|
|
|
c = C(10, database=my_database)
|
|
|
|
In this case, :func:`fields` will return :class:`Field` objects for ``i`` and
|
|
``j``, but not for ``database``.
|
|
|
|
Frozen instances
|
|
----------------
|
|
|
|
It is not possible to create truly immutable Python objects. However,
|
|
by passing ``frozen=True`` to the :meth:`dataclass` decorator you can
|
|
emulate immutability. In that case, dataclasses will add
|
|
:meth:`__setattr__` and :meth:`__delattr__` methods to the class. These
|
|
methods will raise a :exc:`FrozenInstanceError` when invoked.
|
|
|
|
There is a tiny performance penalty when using ``frozen=True``:
|
|
:meth:`__init__` cannot use simple assignment to initialize fields, and
|
|
must use :meth:`object.__setattr__`.
|
|
|
|
Inheritance
|
|
-----------
|
|
|
|
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
|
|
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.
|
|
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
|
|
combined, calculated ordered mapping of fields. Because the fields
|
|
are in insertion order, derived classes override base classes. An
|
|
example::
|
|
|
|
@dataclass
|
|
class Base:
|
|
x: Any = 15.0
|
|
y: int = 0
|
|
|
|
@dataclass
|
|
class C(Base):
|
|
z: int = 10
|
|
x: int = 15
|
|
|
|
The final list of fields is, in order, ``x``, ``y``, ``z``. The final
|
|
type of ``x`` is ``int``, as specified in class ``C``.
|
|
|
|
The generated :meth:`__init__` method for ``C`` will look like::
|
|
|
|
def __init__(self, x: int = 15, y: int = 0, z: int = 10):
|
|
|
|
Re-ordering of keyword-only parameters in :meth:`__init__`
|
|
----------------------------------------------------------
|
|
|
|
After the parameters needed for :meth:`__init__` are computed, any
|
|
keyword-only parameters are moved to come after all regular
|
|
(non-keyword-only) parameters. This is a requirement of how
|
|
keyword-only parameters are implemented in Python: they must come
|
|
after non-keyword-only parameters.
|
|
|
|
In this example, ``Base.y``, ``Base.w``, and ``D.t`` are keyword-only
|
|
fields, and ``Base.x`` and ``D.z`` are regular fields::
|
|
|
|
@dataclass
|
|
class Base:
|
|
x: Any = 15.0
|
|
_: KW_ONLY
|
|
y: int = 0
|
|
w: int = 1
|
|
|
|
@dataclass
|
|
class D(Base):
|
|
z: int = 10
|
|
t: int = field(kw_only=True, default=0)
|
|
|
|
The generated :meth:`__init__` method for ``D`` will look like::
|
|
|
|
def __init__(self, x: Any = 15.0, z: int = 10, *, y: int = 0, w: int = 1, t: int = 0):
|
|
|
|
Note that the parameters have been re-ordered from how they appear in
|
|
the list of fields: parameters derived from regular fields are
|
|
followed by parameters derived from keyword-only fields.
|
|
|
|
The relative ordering of keyword-only parameters is maintained in the
|
|
re-ordered :meth:`__init__` parameter list.
|
|
|
|
|
|
Default factory functions
|
|
-------------------------
|
|
|
|
If a :func:`field` specifies a ``default_factory``, it is called with
|
|
zero arguments when a default value for the field is needed. For
|
|
example, to create a new instance of a list, use::
|
|
|
|
mylist: list = field(default_factory=list)
|
|
|
|
If a field is excluded from :meth:`__init__` (using ``init=False``)
|
|
and the field also specifies ``default_factory``, then the default
|
|
factory function will always be called from the generated
|
|
:meth:`__init__` function. This happens because there is no other
|
|
way to give the field an initial value.
|
|
|
|
Mutable default values
|
|
----------------------
|
|
|
|
Python stores default member variable values in class attributes.
|
|
Consider this example, not using dataclasses::
|
|
|
|
class C:
|
|
x = []
|
|
def add(self, element):
|
|
self.x.append(element)
|
|
|
|
o1 = C()
|
|
o2 = C()
|
|
o1.add(1)
|
|
o2.add(2)
|
|
assert o1.x == [1, 2]
|
|
assert o1.x is o2.x
|
|
|
|
Note that the two instances of class ``C`` share the same class
|
|
variable ``x``, as expected.
|
|
|
|
Using dataclasses, *if* this code was valid::
|
|
|
|
@dataclass
|
|
class D:
|
|
x: List = []
|
|
def add(self, element):
|
|
self.x += element
|
|
|
|
it would generate code similar to::
|
|
|
|
class D:
|
|
x = []
|
|
def __init__(self, x=x):
|
|
self.x = x
|
|
def add(self, element):
|
|
self.x += element
|
|
|
|
assert D().x is D().x
|
|
|
|
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 ``x`` when creating a class instance will share the same copy
|
|
of ``x``. Because dataclasses just use normal Python class
|
|
creation they also share this behavior. There is no general way
|
|
for Data Classes to detect this condition. Instead, the
|
|
:func:`dataclass` decorator will raise a :exc:`TypeError` if it
|
|
detects a default parameter of type ``list``, ``dict``, or ``set``.
|
|
This is a partial solution, but it does protect against many common
|
|
errors.
|
|
|
|
Using default factory functions is a way to create new instances of
|
|
mutable types as default values for fields::
|
|
|
|
@dataclass
|
|
class D:
|
|
x: list = field(default_factory=list)
|
|
|
|
assert D().x is not D().x
|