Python Lab: Explore the Syntax

This repository is dedicated to exploring Python syntax through examples and explanations.

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Main Component

Comprehensive_Python_Exploration.ipynb: A Jupyter notebook serving as an interactive guide to Python's syntax and features.

Purpose

The notebook is designed to be a learning resource for both beginners and those looking to deepen their understanding of Python. It covers various aspects of Python syntax with practical examples and clear explanations.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Topics Covered

1. Basic Syntax and Core Data Types

• Variables and Constants
• Core Data Types
  • Numeric Types: int, float
  • Text Type: str
  • Boolean Type: bool
  • None Type: NoneType
• Type Conversion
• Operators
  • Arithmetic Operators
  • Comparison Operators
  • Logical Operators
  • Assignment Operators
  • Bitwise Operators
• Comments
  • Single-line Comments
  • Multi-line Comments
• Basic Input/Output
  • print() function
  • input() function

2. Compound Data Types -Data Structures

• Sequence Types:
  • Lists (list)
    • Creating and Accessing Lists
    • List Methods (append, extend, insert, etc.)
  • Tuples (tuple)
    • Creating and Using Tuples
    • Tuple Packing and Unpacking
• Sequence Unpacking (for both lists and tuples)
• Mapping Type: Dictionaries (dict)
  • Creating and Accessing Dictionaries
  • Dictionary Methods
• Set Types: Sets (set) and Frozen Sets (frozenset)
  • Creating Sets
  • Set Operations

3. Special Data Types and Concepts

• Numeric Types: complex
• range Function and Sequence
• Binary Types: bytes, bytearray, memoryview

4. Advanced Operations and Comprehensions

• List Comprehensions
• Dictionary Comprehensions
• Set Comprehensions
• Advanced String Operations

5. Control Flow

• Conditional Statements
  • if Statements
  • elif and else Clauses
• Loops
  • for Loops
  • while Loops
  • else clause in loops
• Control Statements
  • break
  • continue
  • pass

6. Functions

• Defining and Calling Functions
• Arguments and Return Values
  • Positional Arguments
  • Keyword Arguments
  • Default Arguments
• Lambda Functions

7. Object-Oriented Programming

• Classes and Objects
  • Defining Classes
  • Creating and Using Objects
• Inheritance
  • Single Inheritance
  • Multiple Inheritance
• Encapsulation and Polymorphism

8. Modules and Packages

• Importing Modules
  • import Statement
  • from ... import Statement
• Creating Custom Modules
• Working with Packages
  • __init__.py Files
  • Importing from Packages

9. File Handling

• Reading and Writing Files
  • open() Function
  • Reading Methods (read(), readline(), readlines())
  • Writing Methods (write(), writelines())
• Working with CSV
  • csv Module
• Working with JSON
  • json Module

10. Error Handling

• Try-Except Blocks
• Raising Exceptions
• Custom Exceptions

11. Advanced Topics

• Generators
  • Generator Functions
  • Generator Expressions
• Decorators
  • Creating and Using Decorators
• Context Managers
  • with Statement
  • Creating Custom Context Managers
• Asynchronous Programming
  • async and await keywords
  • Coroutines

12. Python Standard Library Highlights

• datetime Module
  • Working with Dates and Times
• random Module
  • Generating Random Numbers
• math Module
  • Mathematical Functions
• collections Module
  • Specialized Container Datatypes