Python Tip of the Day

Python Tip of the Day

Welcome to the Python Tip of the Day — a daily series where you learn one short, powerful Python concept, trick, or best practice. Every tip is simple, practical, and beginner-friendly, with examples you can use immediately.

Tip 1 — Use `enumerate()` Instead of `range(len())`

When looping through a list, use enumerate() to get both index and value cleanly.


for i, item in enumerate(["a", "b", "c"], start=1):
    print(i, item)

Why? Cleaner, more Pythonic, and avoids mistakes with indexing.

Tip 2 — Use List Comprehensions for Cleaner Loops

Instead of building lists with a for loop and .append(), use a list comprehension to keep your code short and Pythonic.

# Traditional way
squares = []
for x in range(10):
    squares.append(x * x)

# List comprehension way
squares = [x * x for x in range(10)]
print(squares)

When to use: whenever you are creating a new list from another iterable (filtering, transforming, mapping).

Why it matters: list comprehensions are usually faster, shorter, and more readable than manual loops with .append().

Tip 3 — Swap Variables Without a Temporary Variable

Python allows you to swap variables in a single line, without using a temporary variable. This is clean, fast, and very useful in many logic-based problems.

a = 10
b = 5

# Swap values
a, b = b, a

print(a, b)  # Output: 5 10

When to use: in algorithms, sorting, and anywhere you need quick value swaps.

Why it matters: shorter, cleaner, and avoids using extra memory compared to temp variables.

Tip 4 — Use `set()` for Fast Membership Checks

Checking if an item exists in a list is slow because lists use linear search. Using a set() makes membership checks extremely fast (O(1) time).

items = [1, 2, 3, 4, 5]
lookup = set(items)

print(3 in lookup)   # True
print(10 in lookup)  # False

When to use: searching large lists, filtering data, checking duplicates.

Why it matters: sets make lookups instantly fast, improving performance dramatically.

Tip 5 — Use `dict.get()` to Avoid KeyError

Directly accessing a dictionary key can crash your code if the key does not exist. Using .get() lets you provide a safe default value instead.

user = {"name": "Sachin"}

# Risky: may raise KeyError
# age = user["age"]

# Safe: returns None (or default) if key is missing
age = user.get("age", 0)
print(age)  # 0

When to use: anytime you are not sure a key exists in a dictionary, especially when handling JSON or API responses.

Why it matters: prevents crashes, makes your code more robust, and keeps default behavior clear in one line.

Tip 6 — Use `f-strings` for Fast and Clean String Formatting

Python’s f-strings provide the cleanest and fastest way to insert variables into strings. They are easier to read and much faster than % formatting or .format().

name = "Sachin"
score = 95

print(f"Hello {name}, your score is {score}.")

When to use: anytime you need dynamic text — logging, printing, messages, filenames, etc.

Why it matters: f-strings are faster, cleaner, more readable, and avoid syntax errors.

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