Python is one of the most versatile programming languages, loved for its simplicity and elegance. Whether you’re just starting out or you’re a seasoned developer, there are always new tricks to discover that can boost your productivity. Here are 7 Python tricks that every developer should know to write cleaner and more efficient code.
1️⃣** List Comprehensions for Clean Loops**
Instead of writing long loops to create or filter lists, you can use list comprehensions for concise, readable code.
# Traditional Loopsquares = []for i in range(10):squares.append(i ** 2)# List Comprehensionsquares = [i ** 2 for i in range(10)]print(squares)# Traditional Loop squares = [] for i in range(10): squares.append(i ** 2) # List Comprehension squares = [i ** 2 for i in range(10)] print(squares)# Traditional Loop squares = [] for i in range(10): squares.append(i ** 2) # List Comprehension squares = [i ** 2 for i in range(10)] print(squares)
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2️⃣ The Walrus Operator (:=)
Introduced in Python 3.8, the walrus operator allows you to assign values inside expressions, making your code more compact.
# Beforedata = input("Enter a number: ")if data.isdigit():print(f"You entered: {data}")# With Walrusif (data := input("Enter a number: ")).isdigit():print(f"You entered: {data}")# Before data = input("Enter a number: ") if data.isdigit(): print(f"You entered: {data}") # With Walrus if (data := input("Enter a number: ")).isdigit(): print(f"You entered: {data}")# Before data = input("Enter a number: ") if data.isdigit(): print(f"You entered: {data}") # With Walrus if (data := input("Enter a number: ")).isdigit(): print(f"You entered: {data}")
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3️⃣** Use zip() for Parallel Iteration**
Need to loop through multiple lists at the same time? zip() is your best friend.
names = ['Alice', 'Bob', 'Charlie']scores = [85, 92, 78]for name, score in zip(names, scores):print(f"{name} scored {score}")names = ['Alice', 'Bob', 'Charlie'] scores = [85, 92, 78] for name, score in zip(names, scores): print(f"{name} scored {score}")names = ['Alice', 'Bob', 'Charlie'] scores = [85, 92, 78] for name, score in zip(names, scores): print(f"{name} scored {score}")
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4️⃣ F-Strings for Clean String Formatting
Python 3.6 introduced f-strings, making string interpolation a breeze.
name = "Dev.to"language = "Python"# Old wayprint("Welcome to %s, powered by %s!" % (name, language))# With f-stringsprint(f"Welcome to {name}, powered by {language}!")name = "Dev.to" language = "Python" # Old way print("Welcome to %s, powered by %s!" % (name, language)) # With f-strings print(f"Welcome to {name}, powered by {language}!")name = "Dev.to" language = "Python" # Old way print("Welcome to %s, powered by %s!" % (name, language)) # With f-strings print(f"Welcome to {name}, powered by {language}!")
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5️⃣** Using collections for Advanced Data Structures**
The collections module provides powerful alternatives to Python’s built-in data types. For example, defaultdict can simplify handling missing keys in dictionaries.
from collections import defaultdictcounts = defaultdict(int)words = ["apple", "banana", "apple", "orange", "banana", "banana"]for word in words:counts[word] += 1print(counts) # {'apple': 2, 'banana': 3, 'orange': 1}from collections import defaultdict counts = defaultdict(int) words = ["apple", "banana", "apple", "orange", "banana", "banana"] for word in words: counts[word] += 1 print(counts) # {'apple': 2, 'banana': 3, 'orange': 1}from collections import defaultdict counts = defaultdict(int) words = ["apple", "banana", "apple", "orange", "banana", "banana"] for word in words: counts[word] += 1 print(counts) # {'apple': 2, 'banana': 3, 'orange': 1}
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Final Thoughts
Python is packed with features that can simplify your code and make you a more efficient developer. By mastering these tricks, you’ll write cleaner, faster, and more Pythonic code.
What are your favorite Python tricks? Share them in the comments below!
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