Advanced Python

Sure! Here’s a detailed outline for an advanced Python course that covers a wide range of topics. This content is structured to build upon fundamental Python knowledge and delve into more complex and powerful aspects of the language.

Advanced Python Course Outline

Module 1: Advanced Functions

- *1.1 Decorators*

  - Definition and basic usage

  - Function decorators

  - Class decorators

  - Practical use cases

- *1.2 Generators*

  - Generator functions and the yield statement

  - Generator expressions

  - Use cases and benefits of generators

- *1.3 Closures and Nonlocal*

  - Understanding closures

  - The nonlocal keyword

  - Use cases for closures

Module 2: Data Structures and Algorithms

- *2.1 Advanced Data Structures*

  - Collections module: deque, namedtuple, Counter, OrderedDict, defaultdict

  - Heaps and priority queues

  - Graphs and trees

- *2.2 Algorithms*

  - Sorting and searching algorithms

  - Recursive algorithms

  - Dynamic programming

Module 3: Object-Oriented Programming (OOP)

- *3.1 OOP Principles*

  - Inheritance, polymorphism, and encapsulation

  - Magic methods and operator overloading

  - Class and static methods

- *3.2 Metaclasses*

  - What are metaclasses

  - Creating and using metaclasses

  - Practical examples of metaclasses

Module 4: Concurrency and Parallelism

- *4.1 Threading*

  - Introduction to threading

  - The threading module

  - Thread synchronization and thread-safe programming

- *4.2 Multiprocessing*

  - The multiprocessing module

  - Process pools and parallel execution

  - Shared memory and inter-process communication

- *4.3 Asynchronous Programming*

  - Introduction to asyncio

  - Coroutines, tasks, and event loops

  - Using async and await

Module 5: File Handling and Serialization

- *5.1 File I/O*

  - Reading and writing files

  - Working with different file types

- *5.2 Serialization*

  - pickle module

  - JSON serialization and deserialization

  - Other serialization formats (YAML, XML)

Module 6: Testing and Debugging

- *6.1 Unit Testing*

  - Writing tests with unittest and pytest

  - Test-driven development (TDD)

- *6.2 Debugging*

  - Using the pdb debugger

  - Debugging tools and techniques

Module 7: Network Programming

- *7.1 Sockets*

  - Basics of network programming

  - TCP and UDP sockets

- *7.2 HTTP and Web Services*

  - Making HTTP requests with requests

  - Building APIs with Flask/Django

Module 8: Web Development

- *8.1 Web Frameworks*

  - Overview of Django and Flask

  - Building web applications

  - RESTful APIs

- *8.2 Frontend Integration*

  - Integrating Python with JavaScript frameworks

  - WebSockets and real-time communication

Module 9: Databases

- *9.1 SQL Databases*

  - Using SQLite and PostgreSQL with psycopg2 or SQLAlchemy

  - ORM (Object-Relational Mapping) with SQLAlchemy

- *9.2 NoSQL Databases*

  - Working with MongoDB using pymongo

  - Using Redis

Module 10: Advanced Topics

- *10.1 Design Patterns*

  - Common design patterns in Python

  - Singleton, Factory, Observer, etc.

- *10.2 Type Hinting and Annotations

  - Using typing module

  - Benefits of type hints

- 10.3 Performance Optimization

  - Profiling and optimization techniques

  - Using tools like cProfile and memory_profiler

Module 11: Project Work

- 11.1 Capstone Project

  - Building a comprehensive application that incorporates multiple aspects of the course

  - Real-world problem-solving

Module 12: Additional Tools and Libraries

- 12.1 Virtual Environments

  - Using virtualenv and pipenv

- 12.2 Package Management

  - Creating and distributing packages with setuptools

- 12.3 Popular Libraries

  - Overview of popular Python libraries such as NumPy, Pandas, Matplotlib, etc.

Learning Outcomes

By the end of this course, you will be able to:

- Understand and apply advanced Python concepts and techniques.

- Write efficient, clean, and maintainable Python code.

- Build and deploy robust Python applications.

- Handle concurrency and parallelism effectively.

- Use Python for web development, data science, network programming, and more.

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