Comprehensions and generators

In this section, we will explore a few simple strategies to speed up Python loops using comprehension and generators. In Python, comprehension and generator expressions are fairly optimized operations and should be preferred in place of explicit for-loops. Another reason to use this construct is readability; even if the speedup over a standard loop is modest, the comprehension and generator syntax is more compact and (most of the times) more intuitive.

In the following example, we can see that both the list comprehension and generator expressions are faster than an explicit loop when combined with the sum function:

    def loop(): 
        res = [] 
        for i in range(100000): 
            res.append(i * i) 
        return sum(res) 

    def comprehension(): 
        return sum([i * i for i in range(100000)]) 

    def generator(): 
        return sum(i * i for i in range(100000)) 

    %timeit loop() 
    100 loops, best of 3: 16.1 ms per loop 
    %timeit...