🐍 Python Practice & Self-Study Repository

This repository is a structured Python self-study journey, starting from core Python fundamentals and gradually moving towards modern backend development and AI frameworks like FastAPI, LangChain, and LangGraph.

It is designed for:

• Self-learning
• Interview preparation
• Backend / AI engineering foundations
• Hands-on experimentation

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📂 Repository Structure

PYTHON-PRACTICE-SELFSTUDY
│
├── 1.0Basics
├── 2.0OOPs
├── 2.5Pydantic
├── 3.0FastAPI
├── 4.0Langchain
└── 5.0Langraph

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📘 Folder Breakdown

🔹 1.0Basics

Covers Python fundamentals:

• Variables & data types
• Conditions & loops
• Functions
• Lists, tuples, sets, dictionaries
• File handling
• Error & exception handling

📌 Goal: Build a strong Python foundation.

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🔹 2.0OOPs

Object-Oriented Programming concepts:

• Classes & objects
• Constructors
• Inheritance
• Polymorphism
• Encapsulation & abstraction

📌 Goal: Write clean, scalable, and maintainable Python code.

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🔹 2.5Pydantic

Data validation & schema modeling using Pydantic:

• BaseModel usage
• Type validation
• Nested models
• Optional & default fields
• Real-world schema examples

📌 Goal: Prepare for FastAPI & modern backend development.

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🔹 3.0FastAPI

Backend API development with FastAPI:

• REST APIs
• Request & response models
• Dependency injection
• Validation using Pydantic
• Async APIs
• Basic authentication concepts

📌 Goal: Build production-ready backend services.

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🔹 4.0Langchain

Introduction to LangChain:

• LLM chains
• Prompt templates, Embedding, Text Operations
• Memory, Vector DBs
• Tools & agents
• RAG (Retrieval Augmented Generation) basics

📌 Goal: Learn how to build AI-powered applications using LLMs.

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🔹 5.0Langraph

Advanced AI workflow orchestration using LangGraph:

• Graph-based LLM flows
• State management
• Multi-agent workflows
• Conditional routing

📌 Goal: Design scalable and controllable AI systems.

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🛠 Tech Stack Used

• Python 3.x
• FastAPI
• Pydantic
• LangChain
• LangGraph

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🚀 How to Use This Repository

1. Clone the repo:

   git clone <repo-url>

2. Start learning in order:

   1.0Basics → 2.0OOPs → 2.5Pydantic → 3.0FastAPI → 4.0Langchain → 5.0Langraph

3. Run examples, tweak code, and experiment freely.

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🎯 Learning Objective

By the end of this repository, you should be able to:

• Write clean Python code
• Build REST APIs with FastAPI
• Validate data using Pydantic
• Create AI applications using LangChain & LangGraph

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📌 Note

This repository is for learning & practice purposes. Code may evolve as concepts become clearer and more advanced patterns are learned.

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⭐ If You Find This Useful

Give the repo a ⭐ and keep building 🚀