Python List Comprehensions

List Comprehensions

• A list comprehension is a way to compress a list building for loop into a shorter line of code.

• Example list building for loop

  L = []
  for n in range(12):
      L.append(n ** 2)

• The equivalent list comprehension

  L = [n ** 2 for n in range(12)]

• Basic syntax:
  [expression for variable in iterable ]

Multiple Iteration

• A list can be built from multiple values

  [(i,j) for i in range(2) for j in range(3)]

• This is equivalent to nested for loops; the interior index varies the fastest.

Conditionals on the Iterator

• A conditional can be added to the end of the expression

  >>> [val for val in range(20) if val % 3 > 0]
  [1, 2, 4, 5, 7, 8, 10, 11, 13, 14, 16, 17, 19]

• This is equivalent to the following loop:

  L = []
  for val in range(20):
      if val % 3 > 0:
          L.append(val)

Conditionals on the Value

• Python has a conditional expression (note, not statement)

  >>> val = -10
  >>> val if val >= 0 else -val
  10

• This is often used within list comprehensions and lambda functions

  >>> [v if v % 2 else -v for v in range(10)]
  [1, -2, 3, -4, 5, -6, 7, -8, 9]

Other Comprehensions

• set comprehensions

  >>> {n ** 2 for n in range(10)}
  {0, 1, 4, 9, 16, 25, 36, 49, 64, 81}

• dict comprehensions

  >>> {n:n ** 2 for n in range(6)}
  {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

• generator expression

  >>> (n**2 for n in range(12))
  <generator object <genexpr> at 0x1027a5a50>

Generators

• A list is a collection of values

• A generator produces values as they are needed

• A generator exposes the iterator interface

  for val in (n ** 2 for n in range(10)):
      print(val, end=' ')

• A generator can only be iterated through once

Generator Functions

• A generator function makes use of the yield statement

• The generator expression

  G1 = (n ** 2 for n in range(10))

  is equivalent to

  def gen():
      for n in range(10):
          yield n ** 2
  
  G2 = gen()