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Python Projects & Resources
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Python Interview Questions with Answers
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🚀 Roadmap to Master Python Programming 🔰

📂 Python Fundamentals
 ∟📂 Learn Syntax, Variables & Data Types
  ∟📂 Master Control Flow & Functions
   ∟📂 Practice with Simple Projects

📂 Intermediate Concepts
 ∟📂 Object-Oriented Programming (OOP)
  ∟📂 Work with Modules & Packages
   ∟📂 Understand Exception Handling & File I/O

📂 Data Structures & Algorithms
 ∟📂 Lists, Tuples, Dictionaries & Sets
  ∟📂 Algorithms & Problem Solving
   ∟📂 Master Recursion & Iteration

📂 Python Libraries & Tools
 ∟📂 Get Comfortable with Pip & Virtual Environments
  ∟📂 Learn NumPy & Pandas for Data Handling
   ∟📂 Explore Matplotlib & Seaborn for Visualization

📂 Web Development with Python
 ∟📂 Understand Flask & Django Frameworks
  ∟📂 Build RESTful APIs
   ∟📂 Integrate Front-End & Back-End

📂 Advanced Topics
 ∟📂 Concurrency: Threads & Asyncio
  ∟📂 Learn Testing with PyTest
   ∟📂 Dive into Design Patterns

📂 Projects & Real-World Applications
 ∟📂 Build Command-Line Tools & Scripts
  ∟📂 Contribute to Open-Source
   ∟📂 Showcase on GitHub & Portfolio

📂 Interview Preparation & Job Hunting
 ∟📂 Solve Python Coding Challenges
  ∟📂 Master Data Structures & Algorithms Interviews
   ∟📂 Network & Apply for Python Roles

✅️ Happy Coding

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Clean code advice for Python:

Do not add redundant context.
Avoid adding unnecessary data to variable names, especially when working with classes.

Example:

This is bad:

class Person:
    def __init__(self, person_first_name, person_last_name, person_age):
        self.person_first_name = person_first_name
        self.person_last_name = person_last_name
        self.person_age = person_age


This is good:

class Person:
    def __init__(self, first_name, last_name, age):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age
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Important Python Functions
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Closures & Decorators in Python 👆
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🚀 Learn API development with Python

🔑 Core Skills Before API Development

Python Fundamentals
- Functions, classes, error handling
- JSON handling (json module)
- Virtual environments (venv, pipenv, or poetry)

HTTP Basics
- What is an API? (REST, GraphQL, gRPC basics)
- HTTP methods: GET, POST, PUT, PATCH, DELETE
- Status codes: 200, 201, 400, 401, 404, 500


🛠️ API Development with Python

1. Frameworks
- Flask (lightweight, easy for beginners)
- FastAPI (modern, async, automatic docs with Swagger/OpenAPI – highly recommended)
- Django REST Framework (DRF) (for large apps with Django)
👉 Start with FastAPI if your goal is modern, production-ready APIs.

2. Core Concepts
- Routing (endpoints like /users, /products)
- Path & query parameters
- Request & response handling (JSON input/output)
- Middleware (logging, authentication, error handling)


3. Data & Persistence
- Working with databases:
- SQL (PostgreSQL, MySQL, SQLite)
- ORMs: SQLAlchemy or Django ORM
- CRUD operations with database integration


4. Authentication & Security
- JWT (JSON Web Tokens)
- OAuth2 (Google, GitHub login)
- API key-based authentication
- CORS handling


5. Testing & Documentation
- Writing tests with pytest or unittest
- Automatic API docs (FastAPI auto-generates Swagger UI)
- Postman or cURL for testing endpoints


6. Deployment & Scaling
- Running APIs with Uvicorn or Gunicorn
- Containerization with Docker
- CI/CD (GitHub Actions, GitLab CI)
- Cloud deployment (AWS, GCP, Azure, or Heroku)


📚 Suggested Learning Path:
Learn FastAPI → build a simple "To-Do API"
Connect a database → PostgreSQL + SQLAlchemy
Add authentication → JWT-based login
Write tests → pytest for endpoints
Deploy on Docker + Cloud
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