Best practices
==============

- enumerate
- generators
- genexps 
- iteators
- with et contextlib

enumerate
=========

Sous-utilisé !

::

    >>> liste = ('un', 'deux', 'trois')
    >>> for index, val in enumerate(liste):
    ...     print '%d: %s' % (index, val)
    ... 
    0: un
    1: deux
    2: trois

Generators 
==========

- yield est devenu une expression (2.5) ::

    >>> def foo():
    ...     answer = (yield)
    ...     while True:
    ...         answer = yield answer + 1
    ... 
    >>> gen = foo()
    >>> gen.next()
    >>> gen.send(1)
    2
    >>> gen.send(45)
    46
    >>> gen.send(89)
    90


Generators 
==========

- possibilité d'écrire des co-routines

- extension `multitask` sous PyPI

- greenlet (dispo sans les expr. yield)

Genexps
=======

::

    >>> iter = (x**2 for x in range(10) if x % 2 == 0)
    >>> for el in iter:
    ...     print el
    ... 
    0
    4
    16
    36
    64


Iterators
=========

utilisez itertools : compilé en C

- islice
- tee
- groupby

islice
======

- islice, iterator fenêtre

::

    >>> import itertools
    >>> def starting_at_five():
    ...     value = raw_input().strip()
    ...     while value != '':
    ...         for el in itertools.islice(value.split(), 
    ...                                    4, None):
    ...             yield el
    ...         value = raw_input().strip()
    ... 
    >>> iter = starting_at_five()
    >>> iter.next()
    one two three four five six
    'five'
    >>> iter.next()
    'six'
    >>> iter.next()
    one two
    one two three four five six
    'five'
    >>> iter.next()
    'six'

Tee
===

- tee: multi-iterator::

    >>> import itertools
    >>> seq = range(1000)
    >>> def with_head(iterable, headsize=1):
    ...     a, b = itertools.tee(iterable)
    ...     return list(itertools.islice(a, headsize)), b
    ... 
    >>> with_head(seq)
    ([1], <itertools.tee object at 0x100c698>)
    >>> with_head(seq, 4)
    ([1, 2, 3, 4], <itertools.tee object at 0x100c670>)


groupby
=======

- semblable à uniq::

    >>> from itertools import groupby
    >>> def compress(data):
    ...     return ((len(list(group)), name)
    ...             for name, group in groupby(data))
    ... 
    >>> def decompress(data):
    ...     return (car * size for size, car in data)
    ... 
    >>> list(compress('get uuuuuuuuuuuuuuuuuup'))
    [(1, 'g'), (1, 'e'), (1, 't'), (1, ' '), 
     (18, 'u'), (1, 'p')]
    >>> compressed = compress('get uuuuuuuuuuuuuuuuuup')
    >>> ''.join(decompress(compressed))
    'get uuuuuuuuuuuuuuuuuup'


with et contextlib
==================

Introduit dans 2.6 mais dispo dans 2.5 avec __future__.
Sans with::

    >>> f = open(my_file, 'w')
    >>> try:
    ...     f.write('pycon fr, ca roxor')
    ... finally:
    ...     f.close()


with et contextlib
==================

Avec with::

    >>> from __future__ import with_statement
    >>> with open(my_file, 'w') as f:
    ...      f.write('pycon fr, ca roxor')

contextlib
==========

Création de ses propres contextes:

- implementer __enter__ et __exit__