Advantages of list comprehension in Python

Python is renowned for encouraging developers and programmers to write efficient, easy-to-understand, and almost as simple-to-read code. One of the most distinctive aspects of the language is the python list and the list compression feature, which one can use within a single line of code to construct powerful functionality.

List comprehensions are used for creating new lists from other iterables like tuples, strings, arrays, lists, etc. A list comprehension consists of brackets containing the expression, which is executed for each element along with the for loop to iterate over each element.

Syntax:

newList = [ expression[element] for element in oldList if condition ]

Advantages of List Comprehension

• More time-efficient and space-efficient than loops.
• Require fewer lines of code.
• Transforms iterative statement into a formula.

List Comprehensions vs For Loop

There are various ways to iterate through a list. However, the most common approach is to use the for loop. Let us look at the below example:

Output:

[G, e, e, k, s, , 4, , G, e, e, k, s, !]

Above is the implementation of the traditional approach to iterate through a list, string, tuple, etc. Now list comprehension does the same task and also makes the program more simple.

List Comprehensions translate the traditional iteration approach using for loop into a simple formula hence making them easy to use. Below is the approach to iterate through a list, string, tuple, etc. using list comprehension.

Output:

[G, e, e, k, s, , 4, , G, e, e, k, s, !]

The list comprehensions are more efficient both computationally and in terms of coding space and time than a for loop. Typically, they are written in a single line of code. The below program depicts the difference between for loops and list comprehension based on performance.

Output:

Time taken for_loop: 0.56 Time taken for list_comprehension: 0.47

From the above program, we can see list comprehensions are quite faster than for loop.

Nested List Comprehensions

Nested List Comprehensions are nothing but a list comprehension within another list comprehension which is quite similar to nested for loops. Below is the program which implements nested loop:

Output:

[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

Now by using nested list comprehensions same output can be generated in fewer lines of code.

Output:

[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

List Comprehensions and Lambda

Lambda Expressions are nothing but shorthand representations of Python functions. Using list comprehensions with lambda creates an efficient combination. Let us look at the below examples:

Output:

[10, 20, 30, 40, 50]

Here, we have used for loop to print table of 10.

Output:

[10, 20, 30, 40, 50]

Now here, we have used only list comprehension to display table of 10.

Output:

[10, 20, 30, 40, 50]

Finally, we use lambda + list comprehension to display the table of 10. This combination is very useful to get efficient solutions in fewer lines of code for complex problems.

Conditionals in List Comprehension

We can also add conditional statements to the list comprehension. We can create a list using range[], operators, etc. and cal also apply some conditions to the list using the if statement.

Below are some examples which depict the use of list comprehensions rather than the traditional approach to iterate through iterables:

Example 1: Display square of numbers from 1 to 10.

Output:

[4, 16, 36, 64, 100]

Example 2: Display even elements from a list of random numbers.

Output:

[++++[+10, 40, 70], [20, 50, 80], [30, 60, 90]]

Example 3: Toggle case of each character in a string.

Output:

[g, E, E, K, S, \x14, g, E, E, K, S, \x01]

Example 4: Reverse each string in a tuple.

Output:

['skeeG', 'rof', 'skeeG']

Example 5: Display the sum of digits of all the odd elements in a list.

Output:

[16, 3, 18, 18]

Key Points

• Comprehension of the list is an effective means of describing and constructing lists based on current lists.
• Generally, list comprehension is more lightweight and simpler than standard list formation functions and loops.
• We should not write long codes for list comprehensions in order to ensure user-friendly code.
• Every comprehension of the list can be rewritten in for loop, but in the context of list interpretation, every for loop can not be rewritten.

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