Python Practice Programs & Logic Building: 100+ Essential Coding Exercises

Logic Building & Problem Solving in Python

Coding test rounds at IT service companies and product startups evaluate algorithmic reasoning, corner case handling, and space-time efficiency. Below are core coding patterns extracted from our Basic Programs & Logic Handbook.

1. Prime Number Checking with Optimized Square-Root Bound

Checking divisibility up to √N reduces time complexity from O(N) to O(√N).

import math

def is_prime(n: int) -> bool:
    if n <= 1:
        return False
    if n in (2, 3):
        return True
    if n % 2 == 0 or n % 3 == 0:
        return False
    
    # Check 6k +/- 1 primes
    for i in range(5, int(math.isqrt(n)) + 1, 6):
        if n % i == 0 or n % (i + 2) == 0:
            return False
    return True

print("Is 97 prime?", is_prime(97)) # True
print("Is 100 prime?", is_prime(100)) # False

2. String Anagram Detection (Hash Map vs Sorting)

from collections import Counter

def are_anagrams(s1: str, s2: str) -> bool:
    # Clean whitespace and case
    clean_s1 = s1.replace(" ", "").lower()
    clean_s2 = s2.replace(" ", "").lower()
    return Counter(clean_s1) == Counter(clean_s2)

print("Listen & Silent:", are_anagrams("Listen", "Silent")) # True

3. Flattening Nested Arrays Recursively

def flatten(nested_list: list) -> list:
    flat = []
    for item in nested_list:
        if isinstance(item, list):
            flat.extend(flatten(item))
        else:
            flat.append(item)
    return flat

sample = [1, [2, [3, 4], 5], 6, [7, 8]]
print("Flattened:", flatten(sample)) # [1, 2, 3, 4, 5, 6, 7, 8]