attrs/docs/examples.rst

.. _examples:

Examples
========

The simplest possible usage would be:

.. doctest::

   >>> import attr
   >>> @attr.s
   ... class Empty(object):
   ...     pass
   >>> Empty()
   Empty()
   >>> Empty() == Empty()
   True
   >>> Empty() is Empty()
   False

So in other words: ``attrs`` 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()

These by default, all features are added, so you have immediately 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 both for positional and keyword arguments.

If playful naming turns you off, ``attrs`` comes with no-nonsense aliases:

.. doctest::

   >>> @attr.attributes
   ... class SeriousCoordinates(object):
   ...     x = attr.attr()
   ...     y = attr.attr()
   >>> SeriousCoordinates(1, 2)
   SeriousCoordinates(x=1, y=2)
   >>> attr.ls(Coordinates) == attr.ls(SeriousCoordinates)
   True


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(cl, db_string):
   ...        # connect somehow to db_string
   ...        return cl(socket=42)
   >>> @attr.s
   ... class ConnectionPool(object):
   ...     db_string = attr.ib()
   ...     pool = attr.ib(default_factory=collections.deque)
   ...     debug = attr.ib(default_value=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 <http://as.ynchrono.us/2014/12/asynchronous-object-initialization.html>`_.


Although your initializers should be a dumb as possible, it can come handy to do some kind of validation on the arguments.
That's when :func:`attr.ib`\ ’s ``validator`` argument comes into play.
A validator is simply a callable that takes two arguments: the attribute that it's validating 

.. 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_value=NOTHING, default_factory=NOTHING, validator=<instance_of validator for type <type 'int'>>), <type 'int'>, '42')

``attrs`` ships with a bunch of validators, make sure to :ref:`check them out <api_validators>` before writing your own!