LearnPython

This repository contains well-organized examples and explanations of all the fundamental concepts of Python programming. It is designed for beginners and anyone who wants to revise Python basics.

Folder Structure

• 01 Hello World: Your first Python program.
• 02 Comments: How to write comments in Python.
• 03 Variables: Understanding variables and data types.
• 04 Datatypes: Detailed examples of Python data types.
• 05 Print Statements: Using print statements for output.
• 06 User Input: Taking input from users.
• 07 Operators: Arithmetic, comparison, logical, bitwise, assignment, identity, and membership operators.
• 08 Conditionals: if, if-else, if-elif-else, and ternary operations.
• 09 Loops: for loops, while loops, nested loops, break, continue, pass, and else with loops.
• 10 Inbuilt Data Structures: (To be added) Lists, tuples, dictionaries, and sets.
• 11 Functions: Defining and using functions, parameters, return values, and scope.
• 12 In Built Modules: Using Python's standard library modules.
• 13 Strings: String manipulation and methods.
• 14 File Handling: File handling in Python.
• 15 Exception Handling: Handling errors and exceptions in Python.
• 16 OOPs: Object-oriented programming concepts in Python.
• 17 Advanced Python: Iterators, generators, decorators, closures, and function copies.
• 18 Data Analysis: Using Pandas, NumPy, Seaborn and Matplotlib for data analysis.
• 19 SQLite3: Working with SQLite databases in Python.
• 20 Logging: Implementing logging in Python applications.
• 21 Multi Threading and Processing: Concurrency in Python using threading and multiprocessing.
• 22 Memory Management: Understanding memory management in Python.
• 23 Flask: Building web applications using Flask framework.
• 24 Streamlit Web Framework: Creating interactive web apps with Streamlit.

How to Use

• Browse each folder for Python scripts explaining the concept.
• All code is beginner-friendly and well-commented.

Getting Started

1. Clone this repository.
2. (Optional) Create a virtual environment and install the dependencies from requirements.txt.
3. Explore the folders or open the notebooks in VS Code or Jupyter Lab.

Contribution

Contributions are not accepted at this time. Please check back later for updates.

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Happy Learning! 🚀