7 Python Snippets I Use Almost Every Day (And You Might Too)

Not all Python tricks are flashy — some are just quietly powerful. These are the ones I keep reaching for, day after day.

7 Python Snippets I Use Almost Every Day (And You Might Too)

As a developer who lives and breathes Python, I’ve accumulated a toolbox of go-to snippets that save me time, reduce boilerplate, and keep my code elegant.

These aren’t just flashy one-liners — they’re practical, battle-tested fragments I find myself reaching for daily, whether I’m scripting something small or working on large-scale backend systems.

Here are 7 Python snippets I use almost every day — and why they’ve become indispensable.

1. Pretty Printing with pprint

Debugging complex nested data structures like JSON or deeply nested dictionaries?

from pprint import pprint 
 
data = { 
    "name": "Aashish", 
    "scores": { 
        "math": 95, 
        "science": {"physics": 89, "chemistry": 92}, 
        "languages": ["English", "Spanish"] 
    } 
} 
 
pprint(data)

It makes the output readable without changing the data itself. Ideal for logs, CLI scripts, or quick debugging sessions.

2. Quick Timer with time

Need to benchmark a block of code without importing heavy profiling tools?

import time 
 
start = time.time() 
# Some code that takes time 
time.sleep(1) 
end = time.time() 
 
print(f"Execution time: {end - start:.4f} seconds")

Perfect for sanity-checking performance when optimizing loops, database queries, or API calls.

3. Swapping Variables Without a Temp

Classic, Pythonic, and something you miss the moment you switch to another language.

a, b = 10, 20 
a, b = b, a

It’s elegant, fast, and avoids cluttering your code with temporary variables.

4. List Deduplication While Preserving Order

Python sets remove duplicates — but you lose the original order. This preserves both.

def dedup(seq): 
    seen = set() 
    return [x for x in seq if not (x in seen or seen.add(x))] 
 
items = ["apple", "banana", "apple", "orange", "banana"] 
print(dedup(items))  # ['apple', 'banana', 'orange']

Perfect for cleaning data, especially when order matters — like user input or logs.

5. Safe Dictionary Access with .get()

Avoid those pesky KeyErrors with a default fallback.

user = {"name": "Aashish", "age": 25} 
 
email = user.get("email", "not_provided@example.com")

Makes your code more resilient and readable — no more verbose if key in dict checks.

6. One-Liner File Read

Grab all lines from a file in one readable statement.

with open("data.txt") as f: 
    lines = [line.strip() for line in f if line.strip()]

It’s concise, skips blank lines, and keeps file handling tidy. Perfect for config files or data preprocessing.

7. Unpacking in Loops

Unpack values directly in for loops — Python’s tuple unpacking is a beauty.

people = [("Aashish", 30), ("Bob", 25), ("Charlie", 35)] 
 
for name, age in people: 
    print(f"{name} is {age} years old")

It makes the loop more readable and expressive. No need to access via indices (person[0], person[1]).

Final Thoughts

These snippets might look simple — and that’s exactly the point. Python’s real power shines in its ability to make everyday tasks intuitive and expressive.

You don’t need to memorize every obscure standard library module. Just mastering a few clean patterns can massively boost your productivity.

What about you?
Got a snippet you can’t live without? Drop it in the comments — I’d love to add a few more to my daily toolkit.

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