Examples

Basics

The simplest possible usage would be:

>>> 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:

>>> @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.

>>> 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:

>>> 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:

>>> @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:

>>> @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 (not unlike characteristic) 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?):

>>> 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)

Or if you want to use properties:

>>> @attr.s(these={"_x": attr.ib()})
... class ReadOnlyXSquared(object):
...    @property
...    def x(self):
...       return self._x ** 2
>>> rox = ReadOnlyXSquared(x=5)
>>> rox
ReadOnlyXSquared(_x=5)
>>> rox.x
25
>>> rox.x = 6
Traceback (most recent call last):
   ...
AttributeError: can't set attribute

Subclassing is bad for you, but attrs will still do what you’d hope for:

>>> @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(B, A):
...     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.

In Python 3, classes defined within other classes are detected 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:

>>> @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.

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):

>>> attr.asdict(Coordinates(x=1, y=2))
{'y': 2, 'x': 1}

Some fields cannot or should not be transformed. For that, attr.asdict() offers a callback that decides whether an attribute should be included:

>>> @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 or exclude certain types or attributes, attrs ships with a few helpers:

>>> @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))
{'z': 3, 'x': 'foo'}

Other times, all you want is a tuple and attrs won’t let you down:

>>> 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)") 
...    c.execute("INSERT INTO foo VALUES (?, ?)", attr.astuple(foo)) 
...    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:

>>> 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.

Validators

Although your initializers should be as dumb as possible, it can come in handy to do some kind of validation on the arguments. That’s when attr.ib()’s validator argument comes into play. A validator is simply a callable that takes three arguments:

1. the instance that’s being validated,
2. the attribute that it’s validating, and finally
3. the value that is passed for it.

If the value does not pass the validator’s standards, it just raises an appropriate exception. Since the validator runs after the instance is initialized, you can refer to other attributes while validating :

>>> 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=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'!

attrs won’t intercept your changes to those attributes but you can always call attr.validate() on any instance to verify that it’s still valid:

>>> i = C(4, 5)
>>> i.x = 5  # works, no magic here
>>> attr.validate(i)
Traceback (most recent call last):
   ...
ValueError: 'x' has to be smaller than 'y'!

attrs ships with a bunch of validators, make sure to check them out before writing your own:

>>> @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 'int'>, '42')

If you like zope.interface, attrs also comes with a attr.validators.provides() validator:

>>> import zope.interface
>>> class IFoo(zope.interface.Interface):
...     def f():
...         """A function called f."""
>>> @attr.s
... class C(object):
...     x = attr.ib(validator=attr.validators.provides(IFoo))
>>> C(x=object())
Traceback (most recent call last):
   ...
TypeError: ("'x' must provide <InterfaceClass __builtin__.IFoo> which <object object at 0x10bafaaf0> doesn't.", Attribute(name='x', default=NOTHING, factory=NOTHING, validator=<provides validator for interface <InterfaceClass __builtin__.IFoo>>), <InterfaceClass __builtin__.IFoo>, <object object at 0x10bafaaf0>)
>>> @zope.interface.implementer(IFoo)
... @attr.s
... class Foo(object):
...     def f(self):
...         print("hello, world")
>>> C(Foo())
C(x=Foo())

You can also disable them globally:

>>> attr.set_run_validators(False)
>>> C(42)
C(x=42)
>>> attr.set_run_validators(True)
>>> C(42)
Traceback (most recent call last):
   ...
TypeError: ("'x' must provide <InterfaceClass __builtin__.IFoo> which 42 doesn't.", Attribute(name='x', default=NOTHING, validator=<provides validator for interface <InterfaceClass __builtin__.IFoo>>, repr=True, cmp=True, hash=True, init=True), <InterfaceClass __builtin__.IFoo>, 42)

Conversion

Attributes can have a convert 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.

>>> @attr.s
... class C(object):
...     x = attr.ib(convert=int)
>>> o = C("1")
>>> o.x
1

Converters are run before validators, so you can use validators to check the final form of the value.

>>> def validate_x(instance, attribute, value):
...     if value < 0:
...         raise ValueError("x must be be at least 0.")
>>> @attr.s
... class C(object):
...     x = attr.ib(convert=int, validator=validate_x)
>>> o = C("0")
>>> o.x
0
>>> C("-1")
Traceback (most recent call last):
    ...
ValueError: x must be be at least 0.

Slots

By default, instances of classes have a dictionary for attribute storage. This wastes space for objects having very few data attributes. The space consumption can become significant when creating large numbers of instances.

Normal Python classes can avoid using a separate dictionary for each instance of a class by defining __slots__. For attrs classes it’s enough to set slots=True:

>>> @attr.s(slots=True)
... class Coordinates(object):
...     x = attr.ib()
...     y = attr.ib()

Note

attrs slot classes can inherit from other classes just like non-slot classes, but some of the benefits of slot classes are lost if you do that. If you must inherit from other classes, try to inherit only from other slot classes.

Slot classes are a little different than ordinary, dictionary-backed classes:

• Assigning to a non-existent attribute of an instance will result in an AttributeError being raised. Depending on your needs, this might be a good thing since it will let you catch typos early. This is not the case if your class inherits from any non-slot classes.

  >>> @attr.s(slots=True)
  ... class Coordinates(object):
  ...     x = attr.ib()
  ...     y = attr.ib()
  ...
  >>> c = Coordinates(x=1, y=2)
  >>> c.z = 3
  Traceback (most recent call last):
      ...
  AttributeError: 'Coordinates' object has no attribute 'z'
  

• Slot classes cannot share attribute names with their instances, while non-slot classes can. The following behaves differently if slot classes are used:

  >>> @attr.s
  ... class C(object):
  ...     x = attr.ib()
  >>> C.x
  Attribute(name='x', default=NOTHING, validator=None, repr=True, cmp=True, hash=True, init=True, convert=None)
  >>> @attr.s(slots=True)
  ... class C(object):
  ...     x = attr.ib()
  >>> C.x
  <member 'x' of 'C' objects>
  

• Since non-slot classes cannot be turned into slot classes after they have been created, attr.s(.., slots=True) will replace the class it is applied to with a copy. In almost all cases this isn’t a problem, but we mention it for the sake of completeness.

• Using pickle with slot classes requires pickle protocol 2 or greater. Python 2 uses protocol 0 by default so the protocol needs to be specified. Python 3 uses protocol 3 by default. You can support protocol 0 and 1 by implementing __getstate__ and __setstate__ methods yourself. Those methods are created for frozen slot classes because they won’t pickle otherwise. Think twice before using pickle though.

All in all, setting slots=True is usually a very good idea.

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:

>>> @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 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 and attrs shamelessly imitates it: attr.assoc():

>>> @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.assoc(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() :

>>> @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:

>>> 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!
<attr._make.C object at ...>
>>> i.x
42
>>> i.y
[]

Finally, you can exclude single attributes from certain methods:

>>> @attr.s
... class C(object):
...     user = attr.ib()
...     password = attr.ib(repr=False)
>>> C("me", "s3kr3t")
C(user='me')