Common Python Tricks and Best Practices

In this article we present a collection of frequently used Python tricks that improve code readability and efficiency.

Handling multiple inputs

# bad practice
n1 = input("enter a number : ")
n2 = input("enter a number : ")
n3 = input("enter a number : ")
print(n1, n2, n3)

# good practice
n1, n2, n3 = input("enter a number : ").split()
print(n1, n2, n3)

Using all() and any() for multiple conditions

# bad practice
if size == "lg" and color == "blue" and price < 100:
    print("Yes, I want to but the product.")

# good practice
conditions = [size == "lg", color == "blue", price < 100]
if all(conditions):
    print("Yes, I want to but the product.")

# bad practice
if size == "lg" or color == "blue" or price < 100:
    print("Yes, I want to but the product.")

# good practice
conditions = [size == "lg", color == "blue", price < 100]
if any(conditions):
    print("Yes, I want to but the product.")

Checking odd/even numbers

print('odd' if int(input('Enter a number: ')) % 2 else 'even')

Swapping variables

# bad practice
temp = v1
v1 = v2
v2 = temp

# good practice
v1, v2 = v2, v1

Palindrome test

v1 = "madam"  # palindrome
v2 = "master" # not a palindrome
print(v1.find(v1[::-1]) == 0)  # True
print(v2.find(v2[::-1]) == 0)  # False

Removing duplicate elements from a list

lst = [1, 2, 3, 4, 3, 4, 4, 5, 6, 3, 1, 6, 7, 9, 4, 0]
unique_lst = list(set(lst))
print(unique_lst)

Finding the most frequent element in a list

lst = [1, 2, 3, 4, 3, 4, 4, 5, 6, 3, 1, 6, 7, 9, 4, 0]
most_repeated_item = max(lst, key=lst.count)
print(most_repeated_item)

List comprehensions

numbers = [1,2,3,4,5,6,7]
evens = [x for x in numbers if x % 2 == 0]
odds = [y for y in numbers if y not in evens]

Using *args to accept multiple arguments

def sum_of_squares(*args):
    return sum(item**2 for item in args)

print(sum_of_squares(2, 3, 4))
print(sum_of_squares(2, 3, 4, 5, 6))

Enumerating with index

lst = ["blue", "lightblue", "pink", "orange", "red"]
for idx, item in enumerate(lst):
    print(idx, item)

Joining list elements into a string

names = ["john", "sara", "jim", "rock"]
print(", ".join(names))

Merging dictionaries

d1 = {"v1": 22, "v2": 33}
d2 = {"v2": 44, "v3": 55}
d3 = {**d1, **d2}
print(d3)

Creating a dictionary from two lists using zip

keys = ['a', 'b', 'c']
vals = [1, 2, 3]
zipped = dict(zip(keys, vals))
print(zipped)

Sorting a dictionary by value

d = {"v1": 80, "v2": 20, "v3": 40, "v4": 20, "v5": 10}
sorted_d = dict(sorted(d.items(), key=lambda item: item[1]))
print(sorted_d)

Pretty‑printing complex data structures

from pprint import pprint
data = {"name": "john deo", "age": "22", "address": {"country": "canada", "state": "an state of canada :)", "address": "street st.34 north 12"}, "attr": {"verified": True, "emailaddress": True}}
print(data)
pprint(data)

Reversing a list – slice vs reverse()

# slice method
mylist[::-1]
# reverse method (in‑place)
mylist.reverse()

Benchmarks show that the built‑in reverse() method is faster than slicing, though slicing returns a new list while reverse() modifies the original.