Python Foundational Concepts

As I have been away from Python for a couple of months I am getting reacquainted with how it works. Understanding and mastering Python involves understanding several foundational concepts. Once you learn the basics everything else will fall into place.

Learning Python using copy and paste isn't really helpful (as I have discovered via my own experience). For example, if you don't understand how to define and call a function, you won't understand why what you are building is not doing what you want it to do. I don't know how many times I created a function but didn't call it before I learnt that lesson. It is like asking someone to do something for you, but never telling them what it is you want them to do. Until you tell them what to do, it won't get done.

So knowing some basic python concepts is really important and here's a list of the basics I learnt and continually go over to make sure I don't forget:

Basic Syntax and Variables

• Syntax: Learn the basic structure of Python code, including indentation and comments.
• Variables: Understand how to declare and use variables to store data.

Data Types and Structures

• Primitive Data Types: Integers, floats, strings, and booleans.
• Data Structures: Lists, tuples, sets, and dictionaries.

Control Flow

• Conditional Statements: if, elif, and else statements.
• Loops: for and while loops for iteration.

Functions

• Defining Functions: How to create and call functions.
• Parameters and Return Values: Passing data to functions and getting results back.

Modules and Packages

• Importing Modules: Using built-in and third-party modules.
• Creating Packages: Organizing code into reusable packages.

File Handling

• Reading and Writing Files: Opening, reading, writing, and closing files.

Error Handling

• Exceptions: Using try, except, finally, and raise to handle errors.

Object-Oriented Programming (OOP)

• Classes and Objects: Creating and using classes and objects.
• Inheritance and Polymorphism: Extending classes and using polymorphism.

Libraries and Frameworks

• Standard Library: Familiarize yourself with Python's extensive standard library.
• Popular Libraries: Learn to use libraries like NumPy, pandas, and requests.

Advanced Topics

• Decorators: Understanding and using decorators.
• Generators: Creating and using generators for efficient looping.
• Context Managers: Using with statements for resource management.

Testing and Debugging

• Unit Testing: Writing tests using frameworks like unittest or pytest.
• Debugging: Using tools like pdb to debug code.

Version Control

• Git: Using Git for version control and collaboration.

Web Development (Optional)

• Frameworks: Learning frameworks like Django or Flask for web development.

Data Science and Machine Learning (Optional)

• Libraries: Using libraries like scikit-learn, TensorFlow, and PyTorch.

I joined DataCamp so I can learn about python libraries like TensorFlow and PyTorch. It is also helping me with my AI learning. There is a great course called building chatbots in Python.

These concepts will give a solid foundation for mastering Python. I still struggle with some concepts like testing and debugging. Also, I find if I step away from Python for a while I have to go back and relearn some of it. As with any language, if you don't use it, you lose it.

Python will play a huge part in the AI chatbots and assistants that I develop. While I can use no code or low code options, knowing Python will help me build more advanced structures. Plus I will have a better understand of how to fix the code should anything go wrong.