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``attrs`` by Example
====================
Basics
------
The simplest possible usage is:
.. doctest::
>>> import attr
>>> @attr.s
... class Empty(object):
... pass
>>> Empty()
Empty()
>>> Empty() == Empty()
True
>>> Empty() is Empty()
False
So in other words: ``attrs`` is useful even without actual attributes!
But you'll usually want some data on your classes, so let's add some:
.. doctest::
>>> @attr.s
... class Coordinates(object):
... x = attr.ib()
... y = attr.ib()
By default, all features are added, so you immediately have a fully functional data class with a nice ``repr`` string and comparison methods.
.. doctest::
>>> c1 = Coordinates(1, 2)
>>> c1
Coordinates(x=1, y=2)
>>> c2 = Coordinates(x=2, y=1)
>>> c2
Coordinates(x=2, y=1)
>>> c1 == c2
False
As shown, the generated ``__init__`` method allows for both positional and keyword arguments.
If playful naming turns you off, ``attrs`` comes with serious-business aliases:
.. doctest::
>>> from attr import attrs, attrib
>>> @attrs
... class SeriousCoordinates(object):
... x = attrib()
... y = attrib()
>>> SeriousCoordinates(1, 2)
SeriousCoordinates(x=1, y=2)
>>> attr.fields(Coordinates) == attr.fields(SeriousCoordinates)
True
For private attributes, ``attrs`` will strip the leading underscores for keyword arguments:
.. doctest::
>>> @attr.s
... class C(object):
... _x = attr.ib()
>>> C(x=1)
C(_x=1)
If you want to initialize your private attributes yourself, you can do that too:
.. doctest::
>>> @attr.s
... class C(object):
... _x = attr.ib(init=False, default=42)
>>> C()
C(_x=42)
>>> C(23)
Traceback (most recent call last):
...
TypeError: __init__() takes exactly 1 argument (2 given)
An additional way of defining attributes is supported too.
This is useful in times when you want to enhance classes that are not yours (nice ``__repr__`` for Django models anyone?):
.. doctest::
>>> class SomethingFromSomeoneElse(object):
... def __init__(self, x):
... self.x = x
>>> SomethingFromSomeoneElse = attr.s(
... these={
... "x": attr.ib()
... }, init=False)(SomethingFromSomeoneElse)
>>> SomethingFromSomeoneElse(1)
SomethingFromSomeoneElse(x=1)
`Subclassing is bad for you <https://www.youtube.com/watch?v=3MNVP9-hglc>`_, but ``attrs`` will still do what you'd hope for:
.. doctest::
>>> @attr.s
... class A(object):
... a = attr.ib()
... def get_a(self):
... return self.a
>>> @attr.s
... class B(object):
... b = attr.ib()
>>> @attr.s
... class C(A, B):
... c = attr.ib()
>>> i = C(1, 2, 3)
>>> i
C(a=1, b=2, c=3)
>>> i == C(1, 2, 3)
True
>>> i.get_a()
1
The order of the attributes is defined by the `MRO <https://www.python.org/download/releases/2.3/mro/>`_.
In Python 3, classes defined within other classes are `detected <https://www.python.org/dev/peps/pep-3155/>`_ and reflected in the ``__repr__``.
In Python 2 though, it's impossible.
Therefore ``@attr.s`` comes with the ``repr_ns`` option to set it manually:
.. doctest::
>>> @attr.s
... class C(object):
... @attr.s(repr_ns="C")
... class D(object):
... pass
>>> C.D()
C.D()
``repr_ns`` works on both Python 2 and 3.
On Python 3 it overrides the implicit detection.
Keyword-only Attributes
~~~~~~~~~~~~~~~~~~~~~~~
You can also add `keyword-only <https://docs.python.org/3/glossary.html#keyword-only-parameter>`_ attributes:
.. doctest::
>>> @attr.s
... class A:
... a = attr.ib(kw_only=True)
>>> A()
Traceback (most recent call last):
...
TypeError: A() missing 1 required keyword-only argument: 'a'
>>> A(a=1)
A(a=1)
``kw_only`` may also be specified at via ``attr.s``, and will apply to all attributes:
.. doctest::
>>> @attr.s(kw_only=True)
... class A:
... a = attr.ib()
... b = attr.ib()
>>> A(1, 2)
Traceback (most recent call last):
...
TypeError: __init__() takes 1 positional argument but 3 were given
>>> A(a=1, b=2)
A(a=1, b=2)
If you create an attribute with ``init=False``, the ``kw_only`` argument is ignored.
Keyword-only attributes allow subclasses to add attributes without default values, even if the base class defines attributes with default values:
.. doctest::
>>> @attr.s
... class A:
... a = attr.ib(default=0)
>>> @attr.s
... class B(A):
... b = attr.ib(kw_only=True)
>>> B(b=1)
B(a=0, b=1)
>>> B()
Traceback (most recent call last):
...
TypeError: B() missing 1 required keyword-only argument: 'b'
If you don't set ``kw_only=True``, then there's is no valid attribute ordering and you'll get an error:
.. doctest::
>>> @attr.s
... class A:
... a = attr.ib(default=0)
>>> @attr.s
... class B(A):
... b = attr.ib()
Traceback (most recent call last):
...
ValueError: No mandatory attributes allowed after an attribute with a default value or factory. Attribute in question: Attribute(name='b', default=NOTHING, validator=None, repr=True, cmp=True, hash=None, init=True, converter=None, metadata=mappingproxy({}), type=None, kw_only=False)
.. _asdict:
Converting to Collections Types
-------------------------------
When you have a class with data, it often is very convenient to transform that class into a `dict` (for example if you want to serialize it to JSON):
.. doctest::
>>> attr.asdict(Coordinates(x=1, y=2))
{'x': 1, 'y': 2}
Some fields cannot or should not be transformed.
For that, `attr.asdict` offers a callback that decides whether an attribute should be included:
.. doctest::
>>> @attr.s
... class UserList(object):
... users = attr.ib()
>>> @attr.s
... class User(object):
... email = attr.ib()
... password = attr.ib()
>>> attr.asdict(UserList([User("jane@doe.invalid", "s33kred"),
... User("joe@doe.invalid", "p4ssw0rd")]),
... filter=lambda attr, value: attr.name != "password")
{'users': [{'email': 'jane@doe.invalid'}, {'email': 'joe@doe.invalid'}]}
For the common case where you want to `include <attr.filters.include>` or `exclude <attr.filters.exclude>` certain types or attributes, ``attrs`` ships with a few helpers:
.. doctest::
>>> @attr.s
... class User(object):
... login = attr.ib()
... password = attr.ib()
... id = attr.ib()
>>> attr.asdict(
... User("jane", "s33kred", 42),
... filter=attr.filters.exclude(attr.fields(User).password, int))
{'login': 'jane'}
>>> @attr.s
... class C(object):
... x = attr.ib()
... y = attr.ib()
... z = attr.ib()
>>> attr.asdict(C("foo", "2", 3),
... filter=attr.filters.include(int, attr.fields(C).x))
{'x': 'foo', 'z': 3}
Other times, all you want is a tuple and ``attrs`` won't let you down:
.. doctest::
>>> import sqlite3
>>> import attr
>>> @attr.s
... class Foo:
... a = attr.ib()
... b = attr.ib()
>>> foo = Foo(2, 3)
>>> with sqlite3.connect(":memory:") as conn:
... c = conn.cursor()
... c.execute("CREATE TABLE foo (x INTEGER PRIMARY KEY ASC, y)") #doctest: +ELLIPSIS
... c.execute("INSERT INTO foo VALUES (?, ?)", attr.astuple(foo)) #doctest: +ELLIPSIS
... foo2 = Foo(*c.execute("SELECT x, y FROM foo").fetchone())
<sqlite3.Cursor object at ...>
<sqlite3.Cursor object at ...>
>>> foo == foo2
True
Defaults
--------
Sometimes you want to have default values for your initializer.
And sometimes you even want mutable objects as default values (ever used accidentally ``def f(arg=[])``?).
``attrs`` has you covered in both cases:
.. doctest::
>>> import collections
>>> @attr.s
... class Connection(object):
... socket = attr.ib()
... @classmethod
... def connect(cls, db_string):
... # ... connect somehow to db_string ...
... return cls(socket=42)
>>> @attr.s
... class ConnectionPool(object):
... db_string = attr.ib()
... pool = attr.ib(default=attr.Factory(collections.deque))
... debug = attr.ib(default=False)
... def get_connection(self):
... try:
... return self.pool.pop()
... except IndexError:
... if self.debug:
... print("New connection!")
... return Connection.connect(self.db_string)
... def free_connection(self, conn):
... if self.debug:
... print("Connection returned!")
... self.pool.appendleft(conn)
...
>>> cp = ConnectionPool("postgres://localhost")
>>> cp
ConnectionPool(db_string='postgres://localhost', pool=deque([]), debug=False)
>>> conn = cp.get_connection()
>>> conn
Connection(socket=42)
>>> cp.free_connection(conn)
>>> cp
ConnectionPool(db_string='postgres://localhost', pool=deque([Connection(socket=42)]), debug=False)
More information on why class methods for constructing objects are awesome can be found in this insightful `blog post <https://as.ynchrono.us/2014/12/asynchronous-object-initialization.html>`_.
Default factories can also be set using a decorator.
The method receives the partially initialized instance which enables you to base a default value on other attributes:
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(default=1)
... y = attr.ib()
... @y.default
... def _any_name_except_a_name_of_an_attribute(self):
... return self.x + 1
>>> C()
C(x=1, y=2)
And since the case of ``attr.ib(default=attr.Factory(f))`` is so common, ``attrs`` also comes with syntactic sugar for it:
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(factory=list)
>>> C()
C(x=[])
.. _examples_validators:
Validators
----------
Although your initializers should do as little as possible (ideally: just initialize your instance according to the arguments!), it can come in handy to do some kind of validation on the arguments.
``attrs`` offers two ways to define validators for each attribute and it's up to you to choose which one suits your style and project better.
You can use a decorator:
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib()
... @x.validator
... def check(self, attribute, value):
... if value > 42:
... raise ValueError("x must be smaller or equal to 42")
>>> C(42)
C(x=42)
>>> C(43)
Traceback (most recent call last):
...
ValueError: x must be smaller or equal to 42
...or a callable...
.. doctest::
>>> def x_smaller_than_y(instance, attribute, value):
... if value >= instance.y:
... raise ValueError("'x' has to be smaller than 'y'!")
>>> @attr.s
... class C(object):
... x = attr.ib(validator=[attr.validators.instance_of(int),
... x_smaller_than_y])
... y = attr.ib()
>>> C(x=3, y=4)
C(x=3, y=4)
>>> C(x=4, y=3)
Traceback (most recent call last):
...
ValueError: 'x' has to be smaller than 'y'!
...or both at once:
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(validator=attr.validators.instance_of(int))
... @x.validator
... def fits_byte(self, attribute, value):
... if not 0 <= value < 256:
... raise ValueError("value out of bounds")
>>> C(128)
C(x=128)
>>> C("128")
Traceback (most recent call last):
...
TypeError: ("'x' must be <class 'int'> (got '128' that is a <class 'str'>).", Attribute(name='x', default=NOTHING, validator=[<instance_of validator for type <class 'int'>>, <function fits_byte at 0x10fd7a0d0>], repr=True, cmp=True, hash=True, init=True, metadata=mappingproxy({}), type=None, converter=None, kw_only=False), <class 'int'>, '128')
>>> C(256)
Traceback (most recent call last):
...
ValueError: value out of bounds
Please note that the decorator approach only works if -- and only if! -- the attribute in question has an ``attr.ib`` assigned.
Therefore if you use ``@attr.s(auto_attribs=True)``, it is *not* enough to decorate said attribute with a type.
``attrs`` ships with a bunch of validators, make sure to `check them out <api_validators>` before writing your own:
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(validator=attr.validators.instance_of(int))
>>> C(42)
C(x=42)
>>> C("42")
Traceback (most recent call last):
...
TypeError: ("'x' must be <type 'int'> (got '42' that is a <type 'str'>).", Attribute(name='x', default=NOTHING, factory=NOTHING, validator=<instance_of validator for type <type 'int'>>, type=None, kw_only=False), <type 'int'>, '42')
Check out `validators` for more details.
Conversion
----------
Attributes can have a ``converter`` function specified, which will be called with the attribute's passed-in value to get a new value to use.
This can be useful for doing type-conversions on values that you don't want to force your callers to do.
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(converter=int)
>>> o = C("1")
>>> o.x
1
Check out `converters` for more details.
.. _metadata:
Metadata
--------
All ``attrs`` attributes may include arbitrary metadata in the form of a read-only dictionary.
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib(metadata={'my_metadata': 1})
>>> attr.fields(C).x.metadata
mappingproxy({'my_metadata': 1})
>>> attr.fields(C).x.metadata['my_metadata']
1
Metadata is not used by ``attrs``, and is meant to enable rich functionality in third-party libraries.
The metadata dictionary follows the normal dictionary rules: keys need to be hashable, and both keys and values are recommended to be immutable.
If you're the author of a third-party library with ``attrs`` integration, please see `Extending Metadata <extending_metadata>`.
Types
-----
``attrs`` also allows you to associate a type with an attribute using either the *type* argument to `attr.ib` or -- as of Python 3.6 -- using `PEP 526 <https://www.python.org/dev/peps/pep-0526/>`_-annotations:
.. doctest::
>>> @attr.s
... class C:
... x = attr.ib(type=int)
... y: int = attr.ib()
>>> attr.fields(C).x.type
<class 'int'>
>>> attr.fields(C).y.type
<class 'int'>
If you don't mind annotating *all* attributes, you can even drop the `attr.ib` and assign default values instead:
.. doctest::
>>> import typing
>>> @attr.s(auto_attribs=True)
... class AutoC:
... cls_var: typing.ClassVar[int] = 5 # this one is ignored
... l: typing.List[int] = attr.Factory(list)
... x: int = 1
... foo: str = attr.ib(
... default="every attrib needs a type if auto_attribs=True"
... )
... bar: typing.Any = None
>>> attr.fields(AutoC).l.type
typing.List[int]
>>> attr.fields(AutoC).x.type
<class 'int'>
>>> attr.fields(AutoC).foo.type
<class 'str'>
>>> attr.fields(AutoC).bar.type
typing.Any
>>> AutoC()
AutoC(l=[], x=1, foo='every attrib needs a type if auto_attribs=True', bar=None)
>>> AutoC.cls_var
5
The generated ``__init__`` method will have an attribute called ``__annotations__`` that contains this type information.
If your annotations contain strings (e.g. forward references),
you can resolve these after all references have been defined by using :func:`attr.resolve_types`.
This will replace the *type* attribute in the respective fields.
.. doctest::
>>> import typing
>>> @attr.s(auto_attribs=True)
... class A:
... a: typing.List['A']
... b: 'B'
...
>>> @attr.s(auto_attribs=True)
... class B:
... a: A
...
>>> attr.fields(A).a.type
typing.List[ForwardRef('A')]
>>> attr.fields(A).b.type
'B'
>>> attr.resolve_types(A, globals(), locals())
<class 'A'>
>>> attr.fields(A).a.type
typing.List[A]
>>> attr.fields(A).b.type
<class 'B'>
.. warning::
``attrs`` itself doesn't have any features that work on top of type metadata *yet*.
However it's useful for writing your own validators or serialization frameworks.
Slots
-----
:term:`Slotted classes <slotted classes>` have several advantages on CPython.
Defining ``__slots__`` by hand is tedious, in ``attrs`` it's just a matter of passing ``slots=True``:
.. doctest::
>>> @attr.s(slots=True)
... class Coordinates(object):
... x = attr.ib()
... y = attr.ib()
Immutability
------------
Sometimes you have instances that shouldn't be changed after instantiation.
Immutability is especially popular in functional programming and is generally a very good thing.
If you'd like to enforce it, ``attrs`` will try to help:
.. doctest::
>>> @attr.s(frozen=True)
... class C(object):
... x = attr.ib()
>>> i = C(1)
>>> i.x = 2
Traceback (most recent call last):
...
attr.exceptions.FrozenInstanceError: can't set attribute
>>> i.x
1
Please note that true immutability is impossible in Python but it will `get <how-frozen>` you 99% there.
By themselves, immutable classes are useful for long-lived objects that should never change; like configurations for example.
In order to use them in regular program flow, you'll need a way to easily create new instances with changed attributes.
In Clojure that function is called `assoc <https://clojuredocs.org/clojure.core/assoc>`_ and ``attrs`` shamelessly imitates it: `attr.evolve`:
.. doctest::
>>> @attr.s(frozen=True)
... class C(object):
... x = attr.ib()
... y = attr.ib()
>>> i1 = C(1, 2)
>>> i1
C(x=1, y=2)
>>> i2 = attr.evolve(i1, y=3)
>>> i2
C(x=1, y=3)
>>> i1 == i2
False
Other Goodies
-------------
Sometimes you may want to create a class programmatically.
``attrs`` won't let you down and gives you `attr.make_class` :
.. doctest::
>>> @attr.s
... class C1(object):
... x = attr.ib()
... y = attr.ib()
>>> C2 = attr.make_class("C2", ["x", "y"])
>>> attr.fields(C1) == attr.fields(C2)
True
You can still have power over the attributes if you pass a dictionary of name: ``attr.ib`` mappings and can pass arguments to ``@attr.s``:
.. doctest::
>>> C = attr.make_class("C", {"x": attr.ib(default=42),
... "y": attr.ib(default=attr.Factory(list))},
... repr=False)
>>> i = C()
>>> i # no repr added!
<__main__.C object at ...>
>>> i.x
42
>>> i.y
[]
If you need to dynamically make a class with `attr.make_class` and it needs to be a subclass of something else than ``object``, use the ``bases`` argument:
.. doctest::
>>> class D(object):
... def __eq__(self, other):
... return True # arbitrary example
>>> C = attr.make_class("C", {}, bases=(D,), cmp=False)
>>> isinstance(C(), D)
True
Sometimes, you want to have your class's ``__init__`` method do more than just
the initialization, validation, etc. that gets done for you automatically when
using ``@attr.s``.
To do this, just define a ``__attrs_post_init__`` method in your class.
It will get called at the end of the generated ``__init__`` method.
.. doctest::
>>> @attr.s
... class C(object):
... x = attr.ib()
... y = attr.ib()
... z = attr.ib(init=False)
...
... def __attrs_post_init__(self):
... self.z = self.x + self.y
>>> obj = C(x=1, y=2)
>>> obj
C(x=1, y=2, z=3)
You can exclude single attributes from certain methods:
.. doctest::
>>> @attr.s
... class C(object):
... user = attr.ib()
... password = attr.ib(repr=False)
>>> C("me", "s3kr3t")
C(user='me')
Alternatively, to influence how the generated ``__repr__()`` method formats a specific attribute, specify a custom callable to be used instead of the ``repr()`` built-in function:
.. doctest::
>>> @attr.s
... class C(object):
... user = attr.ib()
... password = attr.ib(repr=lambda value: '***')
>>> C("me", "s3kr3t")
C(user='me', password=***)
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