Following our exploration of Understanding None, this article dives into the world of interactive Python scripts. We'll learn how to get input from the user and display output to the console using the input() and print() functions.
Following our exploration of break and continue, this article delves into combining loops and conditionals. This concept is essential for building complex logic and is a foundational element in modern Python development.
Following our exploration of Basic Console Input and Output, this article focuses on how to make your code more readable and understandable using comments and docstrings.
Following our exploration of Operator Precedence and Associativity, this article introduces some of Python's most common and useful built-in functions. These functions are always available to you, without the need to import any modules.
Over the last several articles, we've explored Python's powerful built-in collection types: lists, tuples, dictionaries, and sets, as well as the specialized containers in the collections module. This article serves as a capstone, summarizing the best practices and helping you decide which collection to use in different scenarios.
Following our exploration of Common Built-in Functions, this article introduces a fundamental concept in programming: conditional statements. We'll start with the most basic conditional statement, the if statement.
Following our exploration of Conditional Statements: if-else (Part 2), this article introduces the if-elif-else statement, which allows you to check multiple conditions in a sequence.
Following our exploration of Conditional Statements: if (Part 1), this article delves into the if-else statement, which allows you to execute a different block of code when the if condition is not met.
Following our exploration of The "What" and "Why" of Python (Part 2), this article delves into two fundamental concepts that define how Python works: its nature as an interpreted language and its use of dynamic typing. Understanding these concepts is key to writing effective Python code.
After exploring the ordered worlds of lists and **tuples**, we now dive into one of Python's most powerful and flexible data structures: the dictionary. Unlike lists and tuples which are indexed by a range of numbers, dictionaries are indexed by keys, which can be any immutable type.
In the previous article, we learned how to create dictionaries and access their values. Now, we'll explore how to modify, manage, and iterate over them using dictionary methods. We'll also introduce a powerful, Pythonic feature for creating dictionaries: dictionary comprehensions.
Following our exploration of Fundamental Data Types booleans. We'll cover what booleans are, the concept of "truthiness", and the logical operators used to work with them.
Following our exploration of Variables and Assignment, this article dives into one of the most fundamental data types in Python: numbers. We'll cover integers and floating-point numbers, and the common operations you can perform on them.
Following our exploration of Fundamental Data Types strings. We'll cover how to create strings, use f-strings for formatting, and some of the most common string methods.
Following our exploration of Fundamental Data Types: Strings (Part 1), this article delves deeper into the world of strings, covering indexing, slicing, and more advanced string methods.
We've now mastered Python's four core collection types. But what happens when you need a more specialized tool? The collections module in Python's standard library provides high-performance, specialized container datatypes. In this article, we'll introduce three of the most useful: namedtuple, deque, and Counter.
Following our exploration of combining loops and conditionals, this article kicks off a new series on Working with Collections, starting with an introduction to Python lists. This concept is essential for storing and manipulating groups of data and is a foundational element in modern Python development.
Following our introduction to declaring and initializing lists, this article dives deeper into manipulating them. We'll explore the powerful tools Python provides: list methods, slicing, and list comprehensions. Mastering these is key to effectively working with data in Python.
Following our exploration of foreach loops, this article delves into break and continue statements. These concepts are essential for writing efficient and readable Python code and are a foundational element in modern Python development.
Following our exploration of Conditional Statements, this article introduces another fundamental concept in programming: loops. We'll start with the for loop, which allows you to iterate over a sequence of elements.
Following our exploration of Loops: for loops (Part 1), this article delves deeper into the world of for loops, covering nested loops and more advanced patterns for iterating over different data structures.
Following our exploration of Loops: while and do-while loops, this article focuses on what is often called a "foreach" loop in other languages. In Python, this is simply the standard for loop used to iterate over collections.
Following our exploration of Loops the while loop. We'll also see how to simulate a do-while loop, which is not a native feature of Python.
Following our exploration of Operators operator precedence and associativity.
Following our exploration of Comments and Docstrings, this article dives into the world of arithmetic operators in Python. These operators allow you to perform mathematical calculations in your code.
Following our exploration of Operators: Arithmetic Operators, this article dives into the world of comparison operators in Python. These operators allow you to compare two values and get a boolean result (True or False).
Following our exploration of Operators logical operators and bitwise operators.
Welcome! This interactive online book is your comprehensive guide to mastering the Python programming language. Whether you are a complete novice taking your first steps into the world of code or a developer looking to solidify your Python skills, this resource is crafted for you.
We've explored ordered collections like lists and **tuples**, and the key-value world of dictionaries. Now we introduce the final core collection type: the set. Sets are all about uniqueness and are modeled after the mathematical concept of a set.
Following our exploration of The Python Ecosystem installing Python and the package manager, pip.
Following our exploration of Setting Up Your Development Environment (Part 1) configuring your Integrated Development Environment (IDE) and setting up virtual environments.
Following our exploration of Conditional Statements the ternary operator.
Following our exploration of Core Concepts the Python Standard Library and the Python Package Index (PyPI).
Welcome to the beginning of your Python journey! This first article dives into the fundamental questions: What is Python, and why has it become one of the most popular programming languages in the world? We'll explore its core philosophy, its fascinating history, and the diverse use cases that make it such a versatile tool for developers.
Following our exploration of The "What" and "Why" of Python (Part 1), this article delves into Python's role in modern software development. We'll explore why Python is the go-to language for web development, data science, machine learning, and automation.
After mastering the flexibility of lists in Part 1 and Part 2, we now turn to their close relative they are immutable. Understanding this distinction is key to writing robust and efficient Python code.
Following our exploration of Fundamental Data Types: Booleans (True, False), this article covers type conversion, also known as casting. We'll learn how to convert variables from one data type to another.
Following our exploration of Type Conversion (Casting), this article delves into a special and important value in Python: None. We'll learn what None represents, how to use it, and how to check for it.
Following our exploration of Your First Python Script variables. We'll learn how to create and use variables in Python, and the best practices for naming them.
Following our exploration of Setting Up Your Development Environment (Part 2): Configuring Your IDE and Virtual Environments, it's time to write and run your very first Python script. In this article, we'll cover the classic "Hello, World!" program and how to run it from the command line.
Following our exploration of Your First Python Script: "Hello, World!" (Part 1), this article delves deeper into the structure of a Python script and the versatile print() function.