A few things to remember while coding in Python.

- 17 May 2012 -

UPDATE: There has been much discussion in Hacker News about this article. A few corrections from it.

Learning the culture that surrounds a language brings you one step closer to being a better programmer. If you haven't read the Zen of Python yet open a Python prompt and type `import this`. For each of the item on the list you can find examples here  [http://artifex.org/~hblanks/talks/2011/pep20_by_example.html](http://artifex.org/~hblanks/talks/2011/pep20_by_example.html)

One caught my attention:  

**Beautiful is better than ugly**  

Give me a function that takes a list of numbers and returns only the
    even ones, divided by two.
    halve_evens_only = lambda nums: map(lambda i: i/2, filter(lambda i: not i%2, nums))
    def halve_evens_only(nums):
        return [i/2 for i in nums if not i % 2]
- Swaping two variables:

        a, b = b, a

- The step argument in slice operators. For example:

        a = [1,2,3,4,5]
        >>> a[::2]  # iterate over the whole list in 2-increments
    The special case `x[::-1]` is a useful idiom for 'x reversed'.

        >>> a[::-1]

UPDATE: Do keep in mind `x.reverse()` reverses the list in place and slices gives you the ability to do this:

        >>> x[::-1]
        [5, 4, 3, 2, 1]

        >>> x[::-2]
        [5, 3, 1]
    def function(x, l=[]):          # Don't do this

    def function(x, l=None):        # Way better
        if l is None:
            l = []

UPDATE: I realise I haven't explained why. I would recommend reading the [article by Fredrik Lundh](http://effbot.org/zone/default-values.htm).
In short it is by design that this happens. "Default parameter values are always evaluated when, and only when, the “def” statement they belong to is executed;"
`iteritems` uses `generators` and thus are better while iterating through very large lists.

    d = {1: "1", 2: "2", 3: "3"}

    for key, val in d.items()       # builds complete list when called.

    for key, val in d.iteritems()   # calls values only when requested.

This is similar with `range` and `xrange` where `xrange` only calls values when requested.

UPDATE: Do note that the `iteritems`, `iterkeys`, `itervalues` are removed from Python 3.x. The `dict.keys()`, `dict.items()` and `dict.values()` return views instead of `lists`. [http://docs.python.org/release/3.1.5/whatsnew/3.0.html#views-and-iterators-instead-of-lists](http://docs.python.org/release/3.1.5/whatsnew/3.0.html#views-and-iterators-instead-of-lists)
Don't do 

    if type(s) == type(""): ...
    if type(seq) == list or \
       type(seq) == tuple: ...

    if isinstance(s, basestring): ...
    if isinstance(seq, (list, tuple)): ...

For why not to do so: [http://stackoverflow.com/a/1549854/504262](http://stackoverflow.com/a/1549854/504262)  

Notice I used `basestring` and not `str` as you might be trying to check if a unicode object is a string. For example:

    >>> a=u'aaaa'
    >>> print isinstance(a, basestring)
    >>> print isinstance(a, str)

This is because in Python versions below 3.0 there are two string types `str` and `unicode`:

            / \
           /   \
         str  unicode
Python has various container datatypes which are better alternative to the built-in containers like `list` and `dict` for specific cases. 

<s>Generally most use this:</s>
UPDATE: I'm sure most do not use this. Carelessness from my side. A few may consider writing it this way:

    freqs = {}
    for c in "abracadabra":
            freqs[c] += 1
            freqs[c] = 1

Some may say a better solution would be:

    freqs = {}
    for c in "abracadabra":
        freqs[c] = freqs.get(c, 0) + 1

Rather go for the `collection` type `defaultdict`

    from collections import defaultdict
    freqs = defaultdict(int)
    for c in "abracadabra":
        freqs[c] += 1

**Other collections**
    namedtuple()	# factory function for creating tuple subclasses with named fields	
    deque	        # list-like container with fast appends and pops on either end	
    Counter	        # dict subclass for counting hashable objects	
    OrderedDict	    # dict subclass that remembers the order entries were added	
    defaultdict	    # dict subclass that calls a factory function to supply missing values	

UPDATE: As noted by a few in Hacker News I could have used `Counter` instead of `defaultdict`.

    >>> from collections import Counter
    >>> c = Counter("abracadabra")
    >>> c['a']
    __eq__(self, other)      # Defines behavior for the equality operator, ==.
    __ne__(self, other)      # Defines behavior for the inequality operator, !=.
    __lt__(self, other)      # Defines behavior for the less-than operator, <.
    __gt__(self, other)      # Defines behavior for the greater-than operator, >.
    __le__(self, other)      # Defines behavior for the less-than-or-equal-to operator, <=.
    __ge__(self, other)      # Defines behavior for the greater-than-or-equal-to operator, >=.

There are several others.
    x = 3 if (y == 1) else 2
It does exactly what it sounds like: "assign 3 to x if y is 1, otherwise assign 2 to x". You can also chain it if you have something more complicated:

    x = 3 if (y == 1) else 2 if (y == -1) else 1

Though at a certain point, it goes a little too far.

Note that you can use if ... else in any expression. For example:

    (func1 if y == 1 else func2)(arg1, arg2) 

Here `func1` will be called if y is 1 and `func2`, otherwise. In both cases the corresponding function will be called with arguments arg1 and arg2.

Analogously, the following is also valid:

    x = (class1 if y == 1 else class2)(arg1, arg2)

where `class1` and `class2` are two classes.
UPDATE: As one commenter mentioned in Hacker News "Using Ellipsis for getting all items is a violation of the Only One Way To Do It principle. The standard notation is `[:]`." I do agree with him. A better example is given using numpy in [stackoverflow](http://stackoverflow.com/a/118508/504262):

The ellipsis is used to slice higher-dimensional data structures.

It's designed to mean at this point, insert as many full slices (:) to extend the multi-dimensional slice to all dimensions.


    >>> from numpy import arange
    >>> a = arange(16).reshape(2,2,2,2)

Now, you have a 4-dimensional matrix of order 2x2x2x2. To select all first elements in the 4th dimension, you can use the ellipsis notation

    >>> a[..., 0].flatten()
    array([ 0,  2,  4,  6,  8, 10, 12, 14])

which is equivalent to

    >>> a[:,:,:,0].flatten()
    array([ 0,  2,  4,  6,  8, 10, 12, 14])

**Previous suggestion.**

When creating a class you can use `__getitem__` to make you class' object work like a dictionary. Take this class as an example:

    class MyClass(object):
        def __init__(self, a, b, c, d):
            self.a, self.b, self.c, self.d = a, b, c, d

        def __getitem__(self, item):
            return getattr(self, item)

    x = MyClass(10, 12, 22, 14)

Because of `__getitem__` you will be able to get the value of `a` in the object `x` by `x['a']`. This is probably a known fact. 

This object is used to extend the Python slicing.([http://docs.python.org/library/stdtypes.html#bltin-ellipsis-object](http://docs.python.org/library/stdtypes.html#bltin-ellipsis-object)). Thus if we add a clause:

    def __getitem__(self, item):
        if item is Ellipsis:
            return [self.a, self.b, self.c, self.d]
            return getattr(self, item)

We can use `x[...]` to get a list containing all the items.

    >>> x = MyClass(11, 34, 23, 12)
    >>> x[...]
    [11, 34, 23, 12]