Advanced Python Topics Tutorial

Python language is a very versatile language and it is used in many technical fields. Some fields require only basic knowledge of Python but some fields require you to know advanced Python such as Data Science, Artificial Intelligence and Robotics.

Pre-requisites: Before starting Advanced Python, one should have studied basic Python.

Advanced Python Techniques

Python provides powerful tools like comprehensions, lambdas, map, filter, reduce and recursion to handle complex logic efficiently. These help write concise and readable code for a variety of tasks.

• List Comprehension
• Lambda Operator
• Filter
• Reduce
• Map
• Recursive Functions

Regular Expressions

Regular expressions (regex) provide a way to search, match and manipulate text based on patterns. They are invaluable for data validation, parsing logs, extracting information, etc.

• Advanced Regular Expressions
• Check whether a string starts and ends with the same character or not
• Password validation in Python

Object Oriented Programming

Python’s OOP features such as classes, inheritance, encapsulation and polymorphism help create reusable, modular and maintainable code for complex applications.

• Class and Object in Python
• Inheritance 
• Encapsulation
• Polymorphism
• Data Abstaraction

Iterables, Iterators and Generators

Understanding iterables, iterators and generators is key to working efficiently with large datasets and streams of data. They enable lazy evaluation and memory-efficient looping essential for scalable Python programs.

• Iterators in Python
• Generators in Python

Closures and Decorators

Closures allow functions to capture and remember their environment, while decorators provide a clean syntax for modifying or extending behavior of functions or methods.

• Closures
• Decorators
• Monkey patching

Memory Management

Concepts like garbage collection, reference counting, mutable vs immutable objects and deep vs shallow copying are crucial for writing optimized, resource-efficient Python code.

• Memory Management
• Dynamic typing
• Mutable & Immutable objects
• Memory Profiling
• Deep Copy vs Shallow Copy
• Optimization Tips for Python Code

Testing

Testing is an essential phase of software development that ensures your code works as expected and prevents regressions.

• Testing with Pytest