Python Idioms – Write Readable and Efficient Code

Programming idioms are specific to each language. These idiomatic patterns are considered the “Pythonic” way to write code in Python. Knowing them helps you write more readable and efficient code. Let’s dive into some of the most common and useful Python idioms.

1. List Comprehensions

Instead of using a loop to generate lists, use a list comprehension.

# Non-idiomatic
squares = []
for x in range(10):
    squares.append(x**2)

# Idiomatic
squares = [x**2 for x in range(10)]

2. Swapping Values

Swap values without a temporary variable.

a, b = 5, 10
a, b = b, a

3. Using enumerate() for Index and Value

When iterating over a list, use enumerate() to get both the index and the value.

colors = ["red", "green", "blue"]
for idx, color in enumerate(colors):
    print(idx, color)

4. Multiple Assignments

Assign multiple variables at once.

x, y, z = 1, 2, 3

5. Using defaultdict

Instead of checking if a key exists in a dictionary, use defaultdict from the collections module.

from collections import defaultdict
count = defaultdict(int)
for letter in 'banana':
    count[letter] += 1

6. Using with for File Operations

The with statement ensures proper resource management.

with open('file.txt', 'r') as f:
    content = f.read()

7. Chaining Comparisons

Chain comparisons for more concise code.

if 5 < x < 10:
    pass

8. Else in Loops

Python allows an else after for and while loops, which runs if the loop completes without encountering a break.

for item in items:
    if condition(item):
        break
else:
    # Will run if no item satisfies the condition
    handle_no_matches()

9. Using join for String Concatenation

It’s more efficient than adding strings in a loop.

names = ["John", "Jane", "Doe"]
full_name = " ".join(names)

10. Dictionary Comprehensions

Similar to list comprehensions but for dictionaries.

names = ["John", "Jane", "Doe"]
lengths = {name: len(name) for name in names}

11. Using all and any

Check all or any items in a list satisfy a condition.

if all(condition(item) for item in items):
    pass

if any(condition(item) for item in items):
    pass

Conclusion

These Python idioms make code more Pythonic: clearer, more readable, and often more efficient. Familiarity with them will not only improve your code but also help you understand other people’s Python code more easily.

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