Python Tutorial

The Best Python Tutorial for Beginners


What’s the best Python tutorial for beginners? With so many options to choose from, it can be hard to know where to start if you want to learn Python on your own. If you want to get the most out of your learning experience and avoid wasting time, energy, and money on the wrong material, consider these key factors before choosing the best Python tutorial for you. I will also tell you about some of my favorite Python tutorials, including those that are free and those that are paid with a money-back guarantee!


Installing the Interpreter

The first step is to get Python up and running on your computer. Since it’s open source, there are lots of ways to do that. If you’re a Windows user, just download the installer from the official website. If you’re a Mac user or you’re not sure which operating system you have, I recommend installing through Homebrew. Linux users should install through their package manager (check your distro’s wiki).

Then, open up your terminal or command prompt and type python to launch it. If you installed it through Homebrew, type brew install python3 . If you’re on Linux and don’t know what a terminal is, try opening a new window and searching for terminal or bash. In either case, you should be greeted with something that looks like an open box with a cursor inside. Type exit() to close it. You’ll also need to add python to your PATH environment variable if you want Python to show up as an option in your shell so you can use it anywhere. Add this line at the end of the PATH variable: C:\Python27\;C:\Python27\Scripts;. If you still need help figuring out how this works, read this tutorial about setting environment variables in Windows 10. Once you’ve done all that, test it out by typing python in any folder in File Explorer. If you see a pop-up box appear, then everything is working. Congratulations! You’ve got Python set up and ready to go!



A variable is a place in memory used to store information you’re going to use later on. Variables are useful because they allow you to make programs that can remember information from one part of your program and use it later on in another part of your program, rather than having to re-type that same value. One common type of variable is called a string. A string stores text, such as a name or instruction.

How do you know what type of data to store in a variable? It all depends on how you want to use that information. Are you going to need to spell out words or numbers? You’ll want strings, but if you only need a number, a whole different kind of variable is available: an integer! There are lots of other types of variables as well, which we’ll discuss throughout these tutorials. For now though, let’s take a look at strings and integers.

 You can tell that you’re dealing with a string variable because they’re between quotation marks.



String processing is a large component of most programming languages. The strings data type in Python is commonly used when working with text and data manipulation tasks. Let’s get started!

First, let’s create a new string called string1 by entering the following into the interpreter: string1 = ‘Hello world!’ Notice that quotes are not needed around the string itself. To concatenate two strings together, use the plus sign (+). For example: string2 = ‘+’ + ‘Hi!’. Notice that string2 now contains the value Hi!. You can also use the asterisk (*) as a wildcard character to replace any number of characters within a string. For example:

string3 = ‘I love *’ + ‘* food!’ //text becomes I love food! //To access the individual characters in a string using index notation, enter string4 = ‘H’, which returns an uppercase H.

//It’s also possible to access individual characters in a string using square brackets  would return an uppercase H if mystring5 contained the value H E L L O.



With so many tools at your disposal, deciding what to use and what not to use can be difficult. To help you sift through, we’ve created a comprehensive guide to various tools for specific tasks. If you’re interested in learning about how you can use some of these tools—for work or school or just fun—check out our guides to building with Python.

Another common programming language that beginners can learn is JavaScript. If you’re interested in learning how to build your own websites, read our JavaScript tutorial. Whether you’re looking to do some front-end web development or if you want to explore data visualization, we have a JavaScript guide just for you.

For those who prefer to learn by doing, check out our learn by building tutorials. We’ve designed these guides to be hands-on and interactive—you won’t find any dry, boring lectures here! And if you want to get started with data science, you should check out our introduction to machine learning course. Or maybe you’d like to learn more about automation and robotics? Our self-driving car design course might be the perfect fit for you. All of these courses are made with beginners in mind, so don’t worry if this is your first time coding or designing.



There’s one main benefit to dictionaries, and that’s speed. They also take up less memory than list data structures, which is especially important if you’re dealing with very large collections of data. Lists require a separate index variable to access each element in your collection; dictionaries do not (they use keys to reference values). This means less processing time and memory.

But there are a few drawbacks to using dictionaries, especially if you’re used to lists. For example, you can only get a value from a dictionary by referencing its associated key. There is no such thing as an index when it comes to dictionaries; every element in your data set must be referenced by key. This also means that your keys need to be unique—you can’t use two different items with the same key in a single collection.

Additionally, when you add a value to a dictionary, its key doesn’t have to be unique. You can add an item with multiple keys (that is, with more than one reference), and it will keep both references intact. If you try to do that with lists, though, it will raise an error (listing items with duplicate indexes are not allowed).



Learning how to use loops in Python is one of those fundamental lessons that comes up over and over again. Loops are a very important part of coding, and you’ll see them applied everywhere in coding jobs. Loops are built into most programming languages because they allow us to perform a task repeatedly, or a set number of times, saving time and effort. That way we don’t have to write code 100 times if we only need it done once!


Modules and Packages

The python language is made up of a number of modules and packages which are essentially just collections of functions. A quick, basic overview of these would be that a module contains predefined functions while a package is more like an application with features that can be activated or deactivated as needed.

A very useful package that’s included in all versions of Python is called math which provides many different mathematical tools and objects to use in calculations.

Another good one to know about is the random module which allows you to generate pseudo-random numbers and explore probability distributions through simulations with it’s built-in methods such as uniform() or randint().



Computer programming involves teaching a computer to execute commands, which is done through functions. A function is essentially a block of code that performs one (or many) tasks. For example, if we wanted to add two numbers together, we could create a function within our program called add that can do exactly that. When a specific command needs to be repeated throughout our program, it makes sense to put it in its own function—it helps simplify our coding and better organize things in general.


Debugging with pdb

Pdb, short for Python Debugger, is a helpful tool in any Python developer’s arsenal. Pdb lets you run code step-by-step, examine variables and call stack frames, and even modify your program on-the-fly by adding logging calls or changing values of variables. The learning curve can be a bit steep at first (because debugging as a concept can be difficult to master), but it’s an essential tool that all programmers should have at their disposal.


Classes and Objects

One of Python’s best features is its object-oriented programming, which simplifies a lot of what would otherwise be cumbersome and clunky. Classes and objects make it easier to break up code into organized, manageable chunks that make more sense. A class can contain functions (called methods) that you can invoke through your object using dot notation.

Classes are blueprints of objects, which are instances of a class. For example, you might define a class called Person and another one called Student. These two classes have similar attributes (like age or grade) but different functions (like attending class). However, both could be used to create objects of either type by using dot notation to specify what type of object you want to create: if p = Person(Bill, 24), then Bill is an instance of a Person object.

Although you can create objects using dot notation and call methods like p.age, you can also define a method by name in its own block: def __init__(self, name): = name. If it’s defined separately from an object, that means it’s a function and it doesn’t have access to self or any of its attributes, since they don’t exist yet! (self is explained in Chapter 7.)


More on Classes, Objects, Inheritance, Polymorphism and Dynamic Typing

Make sure you understand classes, objects, inheritance, polymorphism and dynamic typing before continuing. (You don’t have to be an expert; just familiar with these concepts.) In a nutshell: Classes are a blueprint or template (think mold) of what your object will look like and its properties; when you instantiate an object, you create a copy of that class with attributes specific to it; any changes made to one object will not change any other object.

Inheritance allows one class to be extended from another, and that’s where polymorphism comes in; it allows a parent class to inherit from more than one child class. Dynamic typing means that objects don’t have types but can be assigned types as needed when they are instantiated (and with duck typing, even if they aren’t).

In other words, classes don’t have a defined type until they are instantiated. This allows objects to be assigned a type during runtime and gives you more flexibility in how your application works. It also provides safety because each variable has a defined type that is checked at compile time. But remember: If you try to assign something incompatible to the variable (like trying to put a string into an integer), Python will throw an error!

In many programming languages, these features are built in, but in Python you can create your own classes and object types. One of these is called a factory. A factory function is used to instantiate a class from another class, which gives you more control over how objects are created and assigned to variables.

As you’ll learn in today’s video, factories are used to create classes from another class or object. Instead of creating objects directly, you can call a factory and pass it an existing object or class; a new class will be created based on that original information. This gives you more control over how new classes are created and what they look like when they are instantiated.

In today’s tutorial, you’ll use a factory to create a class from another class and specify properties for that new class. You can then instantiate (create) an object using that class or another derived class of it, which gives you more control over how your application works. This is useful if you want to implement inheritance and polymorphism into your applications without explicitly coding it.

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