List Comprehensions in Python

🟡 Intermediate

📖 Definition

A List Comprehension is a concise, expressive Pythonic construct used to create a new list by transforming or filtering elements from an existing iterable in a single line of code.

🇮🇳 Hindi

List Comprehension ek chhota aur fast tareeqa hai nayi list banane ka. traditional for loop aur append() likhne ke bajaye aap ek hi line mein transformation aur filtering kar sakte hain: [expression for item in list if condition].

🚩 Marathi

List Comprehension mule for loop peksha ekach line madhye navin list tayar karta yete.

🤔 Why Do We Use Them?

Traditional for loops require 4 to 5 lines of boilerplate code (creating empty list, loop header, if condition, .append()). List comprehensions reduce boilerplate to a single readable line and execute faster at the CPython bytecode level.

🧠 Simple Explanation

Think of a list comprehension as a factory conveyor belt fitted with an automated filter and paint sprayer. As raw items pass along the belt (for item in iterable), the filter selector (if condition) discards flawed items, and the sprayer (expression) instantly modifies the remaining items before dropping them into a new collection box.

📝 1. Syntax Blueprint

new_list = [expression for item in iterable if condition]

numbers = [1, 2, 3, 4, 5, 6]

# Traditional For Loop (4 lines)
evens_traditional = []
for n in numbers:
    if n % 2 == 0:
        evens_traditional.append(n * 2)

# List Comprehension (1 line!)
evens_comprehension = [n * 2 for n in numbers if n % 2 == 0]

📝 2. Set and Dictionary Comprehensions

The same comprehension syntax applies to Sets {} and Dictionaries {k: v}:

# Set Comprehension (Deduplicates transformed items)
unique_lengths = {len(word) for word in ["apple", "banana", "apple", "fig"]}

# Dictionary Comprehension
word_lengths = {word: len(word) for word in ["python", "java", "sql"]}
# Result: {"python": 6, "java": 4, "sql": 3}

💡 Complete Example: E-Commerce Product Filter & Discounting

# E-Commerce Product Filter Pipeline

products = [
    {"name": "Gaming Laptop", "price": 75000.00, "in_stock": True},
    {"name": "Wireless Mouse", "price": 1200.00, "in_stock": True},
    {"name": "Desk Lamp", "price": 800.00, "in_stock": False}, # Out of stock
    {"name": "Mechanical Keyboard", "price": 4500.00, "in_stock": True}
]

print("=== PRODUCT COMPREHENSION PIPELINE ===")

# 1. Filter in-stock products and apply 10% discount to prices
discounted_prices = [p["price"] * 0.90 for p in products if p["in_stock"]]

# 2. Extract product names in uppercase for in-stock items costing > ₹1,000
premium_items = [p["name"].upper() for p in products if p["in_stock"] and p["price"] > 1000]

# 3. Dictionary Comprehension: Mapping product names to discounted prices
price_map = {p["name"]: p["price"] * 0.90 for p in products if p["in_stock"]}

print("Discounted Prices :", discounted_prices)
print("Premium Items     :", premium_items)
print("Discount Price Map:", price_map)

👀 Output

=== PRODUCT COMPREHENSION PIPELINE ===
Discounted Prices : [67500.0, 1080.0, 4050.0]
Premium Items     : ['GAMING LAPTOP', 'WIRELESS MOUSE', 'MECHANICAL KEYBOARD']
Discount Price Map: {'Gaming Laptop': 67500.0, 'Wireless Mouse': 1080.0, 'Mechanical Keyboard': 4050.0}

⚠️ Common Mistakes

  • Writing overly complex nested list comprehensions with multiple for loops and if...else logic that becomes unreadable. If a comprehension spans more than 2 lines, convert it back to a standard for loop!
  • Confusing the if filter placement (placed at the end) with if...else ternary expressions (placed before the for clause: [x if x > 0 else 0 for x in items]).

🛡️ Safety / Important Notes

If you are dealing with massive datasets with millions of items, do not build huge list comprehensions in memory—use a Generator Expression (x for x in huge_iterable) to stream items lazily one by one!

🌍 Real-World Usage

Data transformation in Pandas/data science pipelines, parsing CSV rows, filtering database search results, and transforming REST API payloads.

🧪 Try It Yourself

  1. Given numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], write a list comprehension to square only odd numbers.
  2. Given words = ["hello", "world", "python"], create a list of capitalized strings ["HELLO", "WORLD", "PYTHON"].

🎯 Mini Challenge

Given a list of temperatures in Celsius celsius = [0, 12, 25, 34, 40], write a single-line comprehension that converts them to Fahrenheit (c * 9/5) + 32 for temperatures above 20°C.

🔗 Related Topics

🧭 Navigation

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