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16. Comprehensions

Comprehensions are a feature of Python which I would really miss if I ever have to leave it. Comprehensions are constructs that allow sequences to be built from other sequences. Several types of comprehensions are supported in both Python 2 and Python 3:

  • list comprehensions

  • dictionary comprehensions

  • set comprehensions

  • generator comprehensions

We will discuss them one by one. Once you get the hang of using list comprehensions then you can use any of them easily.

16.1. list comprehensions

List comprehensions provide a short and concise way to create lists. It consists of square brackets containing an expression followed by a for clause, then zero or more for or if clauses. The expressions can be anything, meaning you can put in all kinds of objects in lists. The result would be a new list made after the evaluation of the expression in context of the if and for clauses.

Blueprint

variable = [out_exp for out_exp in input_list if out_exp == 2]

Here is a short example:

multiples = [i for i in range(30) if i % 3 == 0]
print(multiples)
# Output: [0, 3, 6, 9, 12, 15, 18, 21, 24, 27]

This can be really useful to make lists quickly. It is even preferred by some instead of the filter function. List comprehensions really shine when you want to supply a list to a method or function to make a new list by appending to it in each iteration of the for loop. For instance you would usually do something like this:

squared = []
for x in range(10):
    squared.append(x**2)

You can simplify it using list comprehensions. For example:

squared = [x**2 for x in range(10)]

16.2. dict comprehensions

They are used in a similar way. Here is an example which I found recently:

mcase = {'a': 10, 'b': 34, 'A': 7, 'Z': 3}

mcase_frequency = {
    k.lower(): mcase.get(k.lower(), 0) + mcase.get(k.upper(), 0)
    for k in mcase.keys()
}

# mcase_frequency == {'a': 17, 'z': 3, 'b': 34}

In the above example we are combining the values of keys which are same but in different typecase. I personally do not use dict comprehensions a lot. You can also quickly switch keys and values of a dictionary:

{v: k for k, v in some_dict.items()}

16.3. set comprehensions

They are also similar to list comprehensions. The only difference is that they use braces {}. Here is an example:

squared = {x**2 for x in [1, 1, 2]}
print(squared)
# Output: {1, 4}

16.4. generator comprehensions

They are also similar to list comprehensions. The only difference is that they don’t allocate memory for the whole list but generate one item at a time, thus more memory efficient.

multiples_gen = (i for i in range(30) if i % 3 == 0)
print(multiples_gen)
# Output: <generator object <genexpr> at 0x7fdaa8e407d8>
for x in multiples_gen:
  print(x)
  # Outputs numbers
15. Object introspection
17. Exceptions