Advanced Python Training in Thimphu, Bhutan

This course is aimed at experienced Python developers who want to deepen their understanding of advanced Python features and enhance their ability to write efficient, scalable, and maintainable Python code. It covers object-oriented programming, design patterns, decorators, generators, concurrency, memory management, testing, and best practices in software engineering.

Advanced OOP, Functional Python & Design Patterns

Module 1: Advanced Object-Oriented Programming

• Deep Dive into OOP Concepts
• Class design, encapsulation, inheritance, and polymorphism
• Abstract classes and interfaces (abc module)
• Special Methods and Operator Overloading
• Implementing __str__, __repr__, __eq__, __lt__, and arithmetic operators
• Customizing class behavior with __new__, __init__, and __call__
• Hands-on Exercise
  

Module 2: Functional and Declarative Programming

• Decorators and Higher-Order Functions
• Writing function decorators and class decorators
• Practical use cases: logging, caching, authorization
• Closures and Lambdas
• Leveraging closures for encapsulated state
• Lambda expressions in data transformations
• Iterators and Generators
• Custom iterator classes
• Generator functions and expressions
• Lazy evaluation and memory efficiency
• Hands-on Exercise

Module 3: Design Patterns and Module Usage

• Common Python Design Patterns
• Singleton, Factory, Strategy, Observer, and Decorator patterns
• When and why to use each pattern
• Powerful Standard Libraries
• functools: caching, partials, and decorators
• collections: defaultdict, Counter, namedtuple, deque
• itertools: combinatorics and iteration utilities
• Custom Context Managers
• Using with statements
• Creating custom context managers with __enter__ and __exit__
• Hands-on Exercise

File Handling, Concurrency & Performance Optimization

Module 4: File Handling and Data Serialization

• File and Directory Handling
• Reading/writing files with open(), os, pathlib, and shutil
• Directory traversal and file management
• Serialization and Persistence
• Storing and loading data using pickle, json, and yaml
• Safe serialization practices
• Hands-on Exercise

Module 5: Concurrency and Parallelism

• Multithreading and Multiprocessing
• Understanding the Global Interpreter Lock (GIL)
• Using threading and multiprocessing modules for performance
• Queues and process pools
• Asynchronous Programming
• Introduction to asyncio and async/await syntax
• Running coroutines concurrently
• Hands-on Exercise
  

Module 6: Testing, Debugging, and Performance Tuning

• Profiling and Optimization
• Using cProfile, timeit, and memory profiling tools
• Identifying bottlenecks and optimizing code
• Testing and Quality Assurance
• Writing unit tests with unittest and pytest
• Mocking and test fixtures
• Logging and Debugging
• Structured logging with logging module
• Debugging techniques and IDE tools
• Hands-on Capstone Exercise