This is a reference page (mainly for Matrix developers, but other Python programmers are welcome to contribute) for Python idioms and constructions that may not be completely transparent for non-Pythonistas.

List comprehensions are a convenient form for creating (or filtering, mapping, etc) lists. They take the form:

   1 result = []
   2 for x in a_list:
   3   if condition:
   4     result += expression(x)

and make it into:

   1 result = [expression(x) for x in a_list if condition]

Here are some examples:

   1 >>> [x*2 for x in range(4)]
   2 [0, 2, 4, 6]
   3 >>> [x*2 for x in range(4) if x > 0]
   4 [2, 4, 6]
   5 >>> [x/2 for x in [y*2 for y in range(4)]]
   6 [0, 1, 2, 3]
   7 >>> [x + '_name' for x in ['noun', 'verb', 'det']]
   8 ['noun_name', 'verb_name', 'det_name']
   9 >>> d = {'a':[1,2,3], 'b':[4,5,6]}
  10 >>> [x + str(y) for x in d for y in d[x]]
  11 ['a1', 'a2', 'a3', 'b4', 'b5', 'b6']
  12 >>> [x + str(y) for x in d if x != 'a' for y in d[x] if y > 4]
  13 ['b5', 'b6']

Inline conditionals are similar to the C syntax of x = condition ? value_if_true : value_if_false, but is slightly more legible. In Python it replaces the following:

   1 if condition:
   2   x = value1
   3 else:
   4   x = value2

or the more compact, but slightly less clear:

   1 x = value2
   2 if condition:
   3   x = value1

with the following:

   1 x = value1 if condition else value2

Inline conditionals are available from Python 2.5.

or operators are useful in assignment when the first value may be "None", and empty string, or something else that evaluates to False.

   1 x = y or z

These are especially useful for functions with default parameters, especially when the default parameter is a list or some other referenced object:

   1 class MyClass:
   2   def func(self, x=None):
   3     self.x = x or []