Python offers concise syntax to create lists and dictionaries using comprehensions. These are powerful tools that make your code more readable and efficient by combining loops and conditional logic into a single line.

In this blog post, we’ll explore how to use list and dictionary comprehensions with multiple examples and best practices.

1. What is Comprehension?

Comprehension is a compact way of creating sequences (like lists or dictionaries) by embedding for loops and if conditions inside a single expression.

2. List Comprehension

Basic Syntax:

[expression for item in iterable]

Example 1: Square of Numbers

squares = [x**2 for x in range(5)]
print(squares)  # Output: [0, 1, 4, 9, 16]

Example 2: Filtering Even Numbers

evens = [x for x in range(10) if x % 2 == 0]
print(evens)  # Output: [0, 2, 4, 6, 8]

Example 3: Convert Strings to Uppercase

words = ["apple", "banana", "cherry"]
upper_words = [word.upper() for word in words]
print(upper_words)  # Output: ['APPLE', 'BANANA', 'CHERRY']

Example 4: Flatten a List of Lists

nested = [[1, 2], [3, 4], [5, 6]]
flat = [num for sublist in nested for num in sublist]
print(flat)  # Output: [1, 2, 3, 4, 5, 6]

Example 5: Using if-else in List Comprehension

result = ["even" if x % 2 == 0 else "odd" for x in range(5)]
print(result)  # Output: ['even', 'odd', 'even', 'odd', 'even']

3. Dictionary Comprehension

Basic Syntax:

{key_expression: value_expression for item in iterable}

Example 6: Mapping Numbers to Their Squares

square_dict = {x: x**2 for x in range(5)}
print(square_dict)  # Output: {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

Example 7: Swapping Keys and Values

original = {"a": 1, "b": 2, "c": 3}
swapped = {v: k for k, v in original.items()}
print(swapped)  # Output: {1: 'a', 2: 'b', 3: 'c'}

Example 8: Filtering Items in Dictionary Comprehension

scores = {"Alice": 85, "Bob": 40, "Charlie": 90}
passed = {k: v for k, v in scores.items() if v >= 50}
print(passed)  # Output: {'Alice': 85, 'Charlie': 90}

Example 9: Conditional Assignment in Dictionary

status = {k: ("Pass" if v >= 50 else "Fail") for k, v in scores.items()}
print(status)  # Output: {'Alice': 'Pass', 'Bob': 'Fail', 'Charlie': 'Pass'}

Example 10: Dictionary from Two Lists

keys = ["name", "age", "city"]
values = ["Alice", 25, "New York"]
info = {k: v for k, v in zip(keys, values)}
print(info)  # Output: {'name': 'Alice', 'age': 25, 'city': 'New York'}

4. Summary Table

5. Best Practices

• Use comprehensions for simple operations; avoid overly complex expressions.
• Make use of conditionals to filter or transform elements.
• When readability suffers, use regular loops instead.

6. Final Thoughts

List and dictionary comprehensions are elegant and efficient features in Python that help you write cleaner and faster code. Once you get comfortable using them, they become a natural way to build and transform collections in a single readable line.