Certainly! Here are some coding problems commonly asked in Python interviews:
Basic Problems:
Reverse a String: Write a function to reverse a string in Python.
Factorial Calculation: Write a function to calculate the factorial of a number.
Palindrome Check: Write a function to check if a given string is a palindrome.
Fibonacci Sequence: Write a function to generate the Fibonacci sequence up to a certain number of terms.
Prime Number Check: Write a function to check if a number is prime.
Data Structures:
Implement a Stack: Implement a stack data structure with push, pop, and peek operations.
Implement a Queue using Stacks: Implement a queue data structure using two stacks.
Linked List Operations: Implement basic operations on a singly linked list (insert, delete, search).
Binary Search Tree: Implement basic operations on a binary search tree (insertion, deletion, search).
Sort a List: Write a function to sort a list of integers using a sorting algorithm of your choice (e.g., bubble sort, quicksort).
Algorithms and Problem Solving:
Find Missing Number: Given a list of numbers from 1 to n with one number missing, find the missing number.
Two Sum Problem: Given an array of integers, find two numbers such that they add up to a specific target.
Merge Intervals: Given a collection of intervals, merge overlapping intervals.
Longest Substring Without Repeating Characters: Find the length of the longest substring without repeating characters.
Maximum Subarray Sum: Find the contiguous subarray with the largest sum.
Advanced Topics:
Implement a Trie (Prefix Tree): Implement a trie data structure and perform basic operations like insert, search, and startsWith.
Graph Traversal: Implement algorithms like breadth-first search (BFS) or depth-first search (DFS) on a graph represented as an adjacency list or matrix.
Topological Sorting: Implement topological sorting of a directed graph.
Dijkstra's Algorithm: Implement Dijkstra's algorithm to find the shortest path in a graph with non-negative edge weights.
Binary Search in Rotated Sorted Array: Perform binary search on a rotated sorted array to find a target element.
Object-Oriented Programming:
Design a Parking Lot: Design classes for a parking lot system with different types of vehicles and parking slots.
Design a Vending Machine: Design classes and methods for a vending machine that dispenses products based on user input.
Design a Hotel Reservation System: Design classes and methods for booking and managing hotel rooms.
Implement an Iterator: Implement an iterator class that iterates over a custom collection.
Implement a Singleton Design Pattern: Implement a singleton class in Python ensuring only one instance exists.
Dynamic Programming:
Knapsack Problem: Solve the 0/1 knapsack problem using dynamic programming.
Longest Common Subsequence: Find the longest common subsequence (LCS) of two strings using dynamic programming.
Minimum Edit Distance: Compute the minimum number of edits (insertions, deletions, substitutions) required to transform one string into another.
Maximum Product Subarray: Find the contiguous subarray within an array (containing at least one number) which has the largest product.
Coin Change Problem: Find the minimum number of coins required to make a given amount using a set of denominations.
Python-Specific Problems:
Generator Function: Write a generator function that generates the Fibonacci sequence.
Context Manager: Implement a context manager using the
__enter__and__exit__methods.Decorators: Write a decorator function to measure the execution time of another function.
Use of
yield: Write a function that generates prime numbers using theyieldkeyword.Exception Handling: Write a function that handles exceptions and retries a certain operation a specified number of times.
Data Science and Machine Learning:
Data Manipulation with pandas: Perform basic data manipulation tasks such as filtering, aggregation, and merging using pandas.
Machine Learning Model: Implement a simple machine learning model such as linear regression or k-nearest neighbors from scratch.
Data Visualization: Plot data using matplotlib or seaborn and interpret the results.
Feature Engineering: Create new features from existing data using pandas and NumPy.
Cross-validation: Implement k-fold cross-validation to evaluate the performance of a machine learning model.
Web Development:
Basic Flask Application: Create a simple Flask application that serves a web page and handles form submissions.
REST API with Flask: Implement a RESTful API using Flask that performs CRUD operations on a database.
Authentication and Authorization: Implement user authentication and authorization in a Flask application using Flask-Login or JWT.
Database Operations: Perform database operations (CRUD) using SQLAlchemy in a Flask application.
Testing:
Unit Testing: Write unit tests for a Python function using the unittest framework.
Integration Testing: Write integration tests for a Flask application using Flask-Testing.
Mocking: Use mocking to test a function that interacts with external services or APIs.
Real-world Applications:
Web Scraping: Write a Python script using BeautifulSoup to scrape data from a website.
Data Analysis: Analyze a dataset using pandas and present findings using matplotlib or seaborn.
Scripting and Automation: Write a Python script to automate a repetitive task (e.g., file processing, data cleaning).
These coding problems cover a wide range of difficulty levels and areas within Python programming. Practice solving these problems to strengthen your Python skills and prepare for interviews effectively.