Python Coding Practice

A curated collection of Python coding problems, Data Structures and Algorithms (DSA), interview questions, and problem-solving patterns.

This repository focuses on helping developers learn how to solve problems, not just memorize solutions.

Each program includes:

• Problem statement
• Input and expected output
• Multiple approaches
• Step-by-step explanation
• Interview follow-up questions
• Pattern identification

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Who Is This Repository For?

• Python developers
• Backend engineers
• Students and freshers
• Interview candidates
• Anyone looking to improve problem-solving skills

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Repository Structure

python-coding-practice/
│
└── python_basics/
    ├── strings/
    ├── lists/
    ├── sets/
    ├── dictionaries/
    ├── linked_lists/
    ├── stacks/
    ├── queues/
    ├── trees/
    └── graphs/

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Recommended Learning Sequence

Follow this order to build a strong foundation in problem solving and DSA:

Python Syntax
      ↓
Big O Basics
      ↓
Strings
      ↓
Lists
      ↓
Sets
      ↓
Dictionaries
      ↓
Stacks
      ↓
Linked Lists
      ↓
Queues
      ↓
Trees
      ↓
Graphs
      ↓
System Design
      ↓
Architecture Thinking

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How to Solve Problems

For every problem, identify:

Problem
↓
Pattern
↓
Data Structure
↓
Algorithm
↓
Python Implementation

Example:

Anagram
↓
Frequency Count
↓
Dictionary
↓
Hash Map
↓
Python Code

The objective is to build the habit of recognizing patterns and selecting the right data structure before writing code.

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Problem-Solving Patterns

Pattern	Common Problems	Data Structure
Frequency Count	Anagram, Character Frequency	Dictionary
Fast Lookup	Two Sum, Membership Lookup	Dictionary, Set
Grouping	Group Anagrams	Dictionary
Two Pointers	Palindrome, Move Zeroes	List, String
Sliding Window	Sliding Window Maximum	Queue, Deque
Stack	Valid Parentheses, Next Greater Element	Stack
Fast & Slow Pointers	Detect Cycle, Find Middle Node	Linked List
Tree Traversal	Max Depth, Lowest Common Ancestor	Tree
Graph Traversal	Number of Islands	Graph

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Topics Covered

Category	Key Concepts	Example Problems
Strings	String manipulation, frequency count	Anagram, Palindrome, String Compression
Lists	Array operations, sorting, two pointers	Move Zeroes, Merge Sorted Lists
Sets	Unique values, membership checks	Find Duplicates, Longest Consecutive Sequence
Dictionaries	Hash maps, grouping, fast lookup	Two Sum, Group Anagrams
Linked Lists	Pointer manipulation	Reverse Linked List, Detect Cycle
Stacks	LIFO operations	Valid Parentheses, Min Stack
Queues	FIFO operations	Sliding Window Maximum, Level Order Traversal
Trees	DFS, BFS, recursion	Max Depth, Invert Binary Tree
Graphs	BFS, DFS, connected components	Graph Traversal, Number of Islands

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Data Structure Quick Reference

Data Structure	Purpose	Common Use Cases
Strings	Text processing	Palindrome, Anagram, Compression
Lists	Ordered collection	Searching, Sorting, Two Pointers
Sets	Unique values and fast lookup	Duplicates, Membership Checks
Dictionaries	Key-value mapping	Frequency Count, Two Sum, Grouping
Linked Lists	Dynamic node-based data	Reverse List, Cycle Detection
Stacks	Last In, First Out (LIFO)	Valid Parentheses, Undo Operations
Queues	First In, First Out (FIFO)	BFS, Task Scheduling
Trees	Hierarchical data	Traversals, Lowest Common Ancestor
Graphs	Connected relationships	BFS, DFS, Connected Components

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Learning Outcomes

By completing this repository, you will be able to:

• Choose the appropriate data structure for a problem
• Identify common problem-solving patterns
• Analyze multiple solution approaches
• Write clean and readable Python code
• Solve coding interview questions with confidence
• Build a strong foundation in DSA
• Develop system design and architectural thinking

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Contributing

Suggestions, improvements, and additional coding problems are welcome.

Feel free to open an issue or submit a pull request.

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License

This project is licensed under the MIT License.