This repository contains a collection of exercises and examples covering advanced Python concepts and techniques. It is designed to help Python developers enhance their skills and gain a deeper understanding of the language’s advanced features.

make install 
make venv
make new-exercise

• Introduced in Python 2.4 (2005)
• Similar concepts: Annotations (Java), Attributes (C#)

• Introduced in Python 2.2 (2001)
• Similar concepts: Iterator (Java), IEnumerable (C#)

• Introduced in Python 2.5 (2006)
• Similar concepts: try-with-resources (Java), using (C#)

• Introduced in Python 2.2 (2001)
• Similar concepts: Reflection (Java), Reflection (C#)

• Introduced in Python 2.2 (2001)
• Similar concepts: Property (C#), Getter/Setter (Java)

• Introduced in Python 2.6 (2008)
• Similar concepts: Interface (Java), Abstract Class (C#)

• Coroutines introduced in Python 2.5 (2006)
• Async/await syntax introduced in Python 3.5 (2015)
• Similar concepts: Coroutines (C#), CompletableFuture (Java)

• Introduced in Python 1.0 (1994)
• Similar concepts: Operator Overloading (C++), Operator Overloading (C#)

• List comprehensions introduced in Python 2.0 (2000)
• Generator expressions introduced in Python 2.4 (2005)
• Similar concepts: Stream API (Java), LINQ (C#)

• Introduced in Python 2.2 (2001)
• Similar concepts: Lambda Expressions (Java), Anonymous Functions (C#)

• One-to-Many and Many-to-Many Relationships
• Modeling Pet, Category, Tag

• Passing arguments to decorators
• Decorators with optional arguments

• Important functions in the itertools module
• Creating efficient iterators and combinatoric generators

• Useful functions in the functools module
• Partial function application and reducing functions

• Singleton, Factory, and Observer patterns
• Implementing design patterns in Python

• Threading and multiprocessing modules
• Concurrent execution and parallel processing

• Custom exceptions and exception hierarchies
• Contextual exception handling and logging

• Code introspection and manipulation
• Modifying behavior at runtime

• Profiling and benchmarking code
• Techniques for optimizing Python performance

• Mocking and patching in unit tests
• Integration testing and test automation

• Avoiding naming conflicts

• Creating reusable libraries
• Packaging and distributing code

• Effective logging techniques
• Configuring and managing log messages

• Serializing and deserializing objects
• Working with JSON, Pickle, and other formats

• Socket programming
• Client-server communication

• Extracting data from websites
• Using libraries like BeautifulSoup and Scrapy

• Creating visual representations of data
• Using libraries like Matplotlib and Seaborn

• Building graphical user interfaces
• Using frameworks like Tkinter and PyQt

• Interacting with databases
• Using libraries like SQLAlchemy and Psycopg2

• Designing and building APIs
• Using frameworks like Flask and FastAPI

• Declaring variables
• Primitive data types (int, float, bool, str)
• Type conversion

• if-else statements
• for and while loops
• break, continue, and pass statements

• Defining and calling functions
• Parameters and arguments
• Return values

• Creating and manipulating lists
• Accessing elements
• List methods and functions
• Tuples and immutability

• Creating and working with dictionaries
• Accessing and modifying key-value pairs
• Sets and set operations

• String manipulation
• Formatting strings
• Common string methods

• Reading from and writing to files
• File modes and permissions
• Context managers for file handling

• Importing modules
• Creating and using packages
• Namespace and scope

• Handling exceptions with try-except
• Raising exceptions
• Custom exception classes

• Classes and objects
• Inheritance and polymorphism
• Encapsulation and data hiding

For each topic, complete the exercise in the corresponding Python file. The exercises are designed to help you practice and understand the advanced Python language features.

• Python Documentation
• Python Tutorial
• Python Standard Library
• Python Language Reference

• Fluent Python by Luciano Ramalho
• Python Workout by Reuven M. Lerner
• Practices of the Python Pro by Dane Hillard
• Effective Python: 90 Specific Ways to Write Better Python by Brett Slatkin
• Python Cookbook by David Beazley and Brian K. Jones
• Python Tricks: A Buffet of Awesome Python Features by Dan Bader

• Real Python
• Learn Python
• Codecademy: Learn Python
• Coursera: Python for Everybody Specialization
• edX: Introduction to Python - Absolute Beginner
• Udemy: Complete Python Bootcamp
• SICP in Python

• Real Python: Advanced Tutorials
• Python for Beginners
• Full Stack Python
• GeeksforGeeks: Python Programming Language
• Programiz: Python Programming

• Stack Overflow: Python Questions
• Reddit: Python Subreddit
• Reddit: Learn Python Subreddit
• Python Forum
• Python.org Community

• Real Python Podcast
• Talk Python To Me
• Python Bytes
• Podcast.__init__

• Corey Schafer
• Real Python
• Programming with Mosh
• Sentdex
• Tech With Tim

• Python Documentation: https://docs.python.org/
• Real Python: https://realpython.com/