Python Learning Repository

Overview

The Python Learning repository contains scripts that were created during my journey of learning Python. It encompasses a variety of essential topics, including loops, dictionaries, lists, strings, object-oriented programming (OOP), classes, and more. This repository serves as a practical resource for applying and reinforcing the concepts learned throughout my studies. Each script offers hands-on experience with Python's syntax and features, facilitating a deeper understanding of programming in Python.

Key Features

• Diverse Topics: This repository encompasses a wide range of Python topics, including:

  • Object-Oriented Programming (OOP): Scripts in the Classes_OOP folder demonstrate OOP concepts.
  • Data Structures: Explore modules and collections like namedtuple, deque, and more in the Collection files.
  • Regular Expressions (RegEx): Learn and practice regex through various examples in the RegEx folder.
  • Functional Programming: Includes exercises on higher-order functions, generators, and lambda functions in video_20_lambda.py, video_22_yield_generatory.py, and others.
  • Recursion and Loops: Deep dives into recursion techniques and nested loops are found in recursion.py and nested loops.py.
  • File Operations: Understand file handling with examples in video_14_operacjeNaPlikach.py.

• Hands-on Practice: Each script is an opportunity to experiment with Python's syntax and features. Users are encouraged to run, modify, and expand upon the provided code to deepen their learning.

• Video Tutorials: The repository includes code from various video tutorials (e.g., video_11_math.py, video_12_try_except.py), which offer practical examples of Python concepts.

Main Skills and Competencies

1. Loops and Control Flow

   • Nested loops
   • For and while loops
   • Using break, continue, and pass statements

2. Data Structures

   • Lists: Creation, manipulation, and comprehension
   • Tuples: Understanding immutability and usage
   • Dictionaries: Key-value pairs and dictionary comprehension
   • Sets: Operations and usage

3. Strings and String Manipulation

   • String methods and formatting
   • String slicing and indexing
   • Regular expressions for pattern matching

4. Functions and Functional Programming

   • Defining and calling functions
   • Lambda functions
   • Higher-order functions: map(), filter(), and reduce()
   • Decorators and their applications

5. Object-Oriented Programming (OOP)

   • Class and object creation
   • Inheritance and polymorphism
   • Encapsulation and data hiding

6. Modules and Libraries

   • Importing and using standard libraries (e.g., datetime, collections, random)
   • Understanding and applying modules such as RegEx, args and kwargs

7. File Handling

   • Reading from and writing to files
   • Using context managers for file operations

8. Error Handling and Exceptions

   • Using try, except, and finally blocks
   • Raising exceptions and assertions

9. Recursion

   • Understanding recursive functions
   • Base case and recursive case

10. Data Manipulation and Analysis

    • Using lists and dictionaries for data storage
    • Basic data analysis techniques

11. Testing and Debugging

    • Writing test scripts to validate code
    • Debugging techniques and tools

12. Date and Time Manipulation

    • Working with the datetime module
    • Formatting dates and times

Technologies Used

• Python: All scripts are written in Python, showcasing its versatility and capabilities.

Goals

• Improve Python programming skills through practical coding exercises and tutorials.
• Explore a wide range of Python features, from basic syntax to advanced programming paradigms.
• Create a personal learning resource that can be referenced and updated over time.

Feel free to explore the scripts, run the examples, and use them as a foundation for your own Python projects!