With the rise of generative AI, a basic understanding of programming concepts can go a long way. This website aims to teach the basics of Python, an accessible and versatile programming language.
Discover the basics of binary data representation in Python with practical examples in this introductory chapter.
Learn the basics of working with numeric types and basic arithmetic in Python through illustrative Python code examples.
A comprehensive exploration of strings in Python, covering their creation, manipulation, common operations, formatting, and Unicode handling, complete with practical code examples.
Learn the basics of Boolean and logical operations in Python, and see how to make decisions and control program flow with practical examples.
Delve into the intricacies of Python's lists and tuples through a visualization and explore their creation, manipulation, and best use cases with in-depth explanations and practical code examples.
Explore the concept of hashed tables with a visualization, and explore Python's dictionaries and sets with manipulation methods and practical applications with illustrative examples.
This chapter introduces control flow and loops in Python, covering if-else conditions, for and while loops, and the use of break and continue statements, all with practical examples.
Comprehensions in Python are concise syntactic constructs that allow you to create lists, dictionaries, and sets of iterable sequences in a single line of code.
Learn how to define and call functions in Python, handle return values, use default and keyword arguments, understand the scope of variables, and work with lambda functions, all accompanied by practical examples to enhance understanding.
This chapter will guide you through error and exception handling in Python. You'll learn how to use try, except, else, and finally clauses, and how to throw your own exceptions when necessary.
This chapter covers basic concepts of file handling and I/O operations in Python. You'll learn how to read and write both text and binary files, manipulate file paths, and handle I/O errors to ensure robust file operations.
In this chapter, you will learn about modules and packages in Python, including how to create and use them, the concept of built-in modules, and how to install third-party packages to add functionality to your Python programs.
In this chapter, we will explore the concept of the three basic programming paradigms: Procedural, Object-Oriented, and Functional Programming.
Explore the concepts and practices of object-oriented programming (OOP), beginning with its basic principles and philosophy.
In this chapter, we explore the principles of functional programming in Python, including pure functions, higher-order functions, and first-class functions. Clear examples are provided to illustrate these concepts.
This chapter covers best practices and coding conventions in Python, emphasizing the importance of clear naming, PEP 8 compliance, informative docstrings and avoiding global variables.
Big-O notation is a mathematical representation that describes the upper bound of an algorithm's runtime or space requirements, helping to understand its worst-case efficiency as the input size grows.
Data structures are essential computer science concepts for efficiently storing, organizing, and managing data, and they have a significant impact on program performance and efficiency.