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Comprehensions

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Comprehensions in Python provide a concise and efficient way to create new sequences from existing iterables using a single line of code. They enhance code readability and reduce the need for lengthy loops. Python supports four types of comprehensions:

  • List Comprehensions
  • Dictionary Comprehensions
  • Set Comprehensions
  • Generator Comprehensions

List comprehensions

List comprehensions allow for the creation of lists in a single line, improving efficiency and readability. They follow a specific pattern to transform or filter data from an existing iterable.

Syntax:

[expression for item in iterable if condition]

Where:

  • expression: Operation applied to each item
  • item: Variable representing the element from the iterable
  • iterable: The source collection
  • condition (optional): A filter to include only specific items

Example

The below list comprehension generates a list of even numbers.

a = [1, 2, 3, 4, 5, 6, 7, 8, 9]
res = [num for num in a if num % 2 == 0]
print(res)
[2, 4, 6, 8]

Dictionary comprehensions

Dictionary Comprehensions are used to construct dictionaries in a compact form, making it easy to generate key-value pairs dynamically based on an iterable.

Syntax:

{key_expression: value_expression for item in iterable if condition}

Where:

  • key_expression: Determines the dictionary key
  • value_expression: Computes the value
  • iterable: The source collection
  • condition (optional): Filters elements before adding them

Example

Creating a dictionary of numbers and their cubes.

res = {num: num**3 for num in range(1, 6)}
print(res)
{1: 1, 2: 8, 3: 27, 4: 64, 5: 125}

Set comprehensions

Set Comprehensions are similar to list comprehensions but result in sets, automatically eliminating duplicate values while maintaining a concise syntax.

Syntax:

{expression for item in iterable if condition}

Where:

  • expression: Operation applied to each item
  • item: Variable representing the element from the iterable
  • iterable: The source collection
  • condition (optional): Filters elements before adding them

Example

Extracting unique even numbers.

a = [1, 2, 2, 3, 4, 4, 5, 6, 6, 7]
 
res = {num for num in a if num % 2 == 0}
print(res)
{2, 4, 6}

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Python Comprehensions List_Comprehensions Set_Comprehensions Dictionary_Comprehensions

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