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Rahul Gupta
Rahul Gupta

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Day 28/100: List Comprehensions in Python

#python #programming #learning #100daysofcode

Welcome to Day 28 of the 100 Days of Python series!
Today, we’re diving into one of Python’s most elegant and powerful features: List Comprehensions.

If you’ve ever written a loop just to create a list, Python has a much shorter — and cleaner — way of doing it. List comprehensions let you generate lists with less code and more readability.

🎯 What You'll Learn

  • What list comprehensions are
  • Basic syntax and examples
  • How to add conditions (if/else)
  • Nested list comprehensions
  • Real-world use cases

🧱 What is a List Comprehension?

A list comprehension is a concise way to create lists using a single line of code.

🔹 Basic Syntax: 

[expression for item in iterable]
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This is equivalent to:

result = [] for item in iterable: result.append(expression)
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🔍 Example 1: Squaring Numbers

✅ With loop: 

squares = [] for i in range(5): squares.append(i ** 2)
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✅ With list comprehension: 

squares = [i ** 2 for i in range(5)]
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🔍 Example 2: Convert Strings to Uppercase 

names = ["alice", "bob", "charlie"] upper_names = [name.upper() for name in names] print(upper_names) # ['ALICE', 'BOB', 'CHARLIE']
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❓ Why Use List Comprehensions?

  • ✅ Shorter and cleaner syntax
  • ✅ Faster performance
  • ✅ More readable for simple transformations

🔀 Adding Conditions

🔸 Syntax: 

[expression for item in iterable if condition]
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Example: Even Numbers Only 

evens = [i for i in range(10) if i % 2 == 0] print(evens) # [0, 2, 4, 6, 8]
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🔄 With if-else in Expression 

labels = ["even" if i % 2 == 0 else "odd" for i in range(5)] print(labels) # ['even', 'odd', 'even', 'odd', 'even']
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🔁 Nested List Comprehensions

You can even nest comprehensions, especially useful for 2D lists or matrices.

Example: Flatten a 2D List 

matrix = [[1, 2], [3, 4], [5, 6]] flattened = [num for row in matrix for num in row] print(flattened) # [1, 2, 3, 4, 5, 6]
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🧪 Real-World Examples

✅ 1. Extract Digits from String 

text = "Age: 24, Score: 89" digits = [char for char in text if char.isdigit()] print(digits) # ['2', '4', '8', '9']
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✅ 2. Filter Valid Emails 

emails = ["a@gmail.com", "b@site", "c@yahoo.com"] valid = [email for email in emails if "@" in email and "." in email] print(valid) # ['a@gmail.com', 'c@yahoo.com']
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✅ 3. Remove Duplicates from List 

data = [1, 2, 2, 3, 4, 4] unique = list({x for x in data}) print(unique) # [1, 2, 3, 4]
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🧠 Tips & Best Practices

  • 👍 Use list comprehensions for simple transformations
  • 🚫 Avoid making them too complex or nested too deeply — use loops for readability
  • 🧹 Clean and readable comprehensions can improve performance and clarity

📚 Bonus: Dictionary & Set Comprehensions

Python also supports:

🧾 Dictionary Comprehension 

squares = {x: x ** 2 for x in range(5)} # {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}
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🔁 Set Comprehension 

unique = {char for char in "hello"} # {'h', 'e', 'l', 'o'}
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🧭 Recap

Today you learned:

  • What list comprehensions are
  • How to use them with conditions
  • When to use if, if-else, and nested comprehensions
  • Real-world practical examples
  • Bonus: dictionary and set comprehensions

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