Python Packages and Modules

Introduction

Whenever you need some additional functionality in Python, you turn to the import keyword to pull in extras from Python modules. You’ve used common ones like the math module plenty of times.

Now, you will learn how to create your own Python modules and packages to compartmentalize your code. Modules are sort of like classes in that they make your code modular. While classes make code modular within a program and serve as the blueprints for objects, modules make all of your code modular across all programs and are utilities to be used just as they are.

Through the use of modules, you can create your own toolbox with all sorts of parts and pieces that you commonly use. Modules can include anything from variables and constants to functions and even classes. Because of this versatility, you can set yourself up to have everything that you need at the beginning of any project.

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Python Inheritance

Introduction

Inheritance is yet another key concept in Object Oriented Programming, and it plays a vital role in building classes. It allows a class to be based off on an existing one.

When you first started writing Python classes, you were told to just put “Object” in the parenthesis of the class definition and not think too much about it. Well, now’s the time to start thinking about it.

“Object” is actually the base class that all Python classes inherit from. It defines a basic set of functionality that all Python classes should have. By inheriting from it when you create a new class, you ensure that that class has that basic functionality.

In short, inheritance is a nice way of categorizing classes and making sure that you don’t needlessly repeat yourself.

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Python Files and the Interpreter

Introduction

Python is an interpreted language, meaning that it is compiled every time that it is run. There are a number of pros and cons when talking about an interpreted language like this.

First, on a positive note, they tend to be easier to debug. They fail immediately when they are run, and tell you what went wrong, which is nice compared to compiled languages like C/C++, which can compile just fine, but fail silently when run.

Interpreted languages are also very portable. All you have to do is install the interpreter on a system, and most code written in that language can run fine, regardless of the operating system. There are some exceptions when dealing with operating system specific code and libraries, but if you’ve planned for portability, you can work around those situations.

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Python Advanced Dictionaries

Introduction

You’ve already gotten acquainted with dictionaries, but just like the other data structures Python supports, there are methods and more powerful ways to use them. There aren’t as many methods for working with dictionaries as there are for lists, but that’s because dictionaries just don’t need them. Plus, many of the ones that do exist, work to break down dictionaries into lists and tuples to make them easier to manage. So, those list methods can be used in conjunction with the dictionary ones to create an efficient machine for handling data.

Dictionary Methods

Items, Keys, and Values

These methods work to break down dictionaries into other data structures to make working with them much more manageable. Doing so also gives access to the methods of those data structures. Through these combinations of methods and loops, you can access and manipulate data with ease.

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Experimenting With Numbers and Text In Python

Introduction

You probably want to jump in and start coding right away. That’s a great attitude to have, but it’s much better to experiment with the language and your programming environment first. If you’ve never programmed or never worked with an interpreted language like Python before, it’s important to get a feel for the way Python works and start to develop a workflow. One great aspect of Python being interpreted is the ability to write a couple of quick lines of code and test them out in real time. There really isn’t much setup beyond what you’ve already done.

Playing With Numbers

Without knowing anything about the language, you can use Python like a basic calculator. Open up either your .py file or the interpreter. Type in a basic math problem and run it.

>>> 10+25
35

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Python Functions

Introduction

Code would quickly become an ugly and unruly mess if there wasn’t a way to easily repeat and reuse it. You’ve already seen some of that with loops. They’re great for repeating the same task multiple times right away. What if you wanted to reuse a block of code whenever you wanted? Well, that’s where functions come in.

Here’s another trip back to math class. If you remember, functions took in a number, did something to it, then outputted the new value. They were often represented in tables with the input on one side and the output on the other. Functions in programming are similar. Sometimes they take input. Sometimes they don’t. Much of the time they return a value as well, but they don’t always have to. In every case, they are used to repeat an operation whenever they are used, and that’s the greatest similarity with the math concept.

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Python Variables

Introduction

Do you remember variables from math class in school? Variables in programming are actually very similar. Variables are just symbols that that represent a value and that value can be changed; thus the name variable. Unlike in math, variables in programming can be much more free form. Variables don’t just have to be a letter. Variables can be a single character, but they are more commonly a word or a short descriptive phrase in lower case with words separated by underscores. It’s actually best to name variables something descriptive so the you and anyone else that you’re working with knows exactly what that variable is, even much later on in the code.

Types of Variables

Python is a dynamic duck typed language. Don’t worry too much about the terminology, but that means that Python doesn’t force you to specify which types variables are when you create them. Oh yeah, there are types of variables. Even though you don’t necessarily have to specify their type when you create them, it’s a good idea to know what type you want them to be. Later on, having the wrong type of variable will invariably get you into big trouble.

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Working With Number Variables In Python

Introduction

Obviously working with numbers in programming is important. Python as excellent mathematical capabilities, and there are tons of additional libraries available to extend Python’s built in functionality for even the most advanced calculations. Of course, the basics are important too, and numbers and some basic calculations come into play when controlling the flow of programs and making selections. That’s why knowing your way around working with numbers in Python is especially important.

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Python Classes

Introduction

Classes are the cornerstone of Object Oriented Programming. They are the blueprints used to create objects. And, as the name suggests, all of Object Oriented Programming centers around the use of objects to build programs.

You don’t write objects, not really. They are created, or instantiated, in a program using a class as their basis. So, you design objects by writing classes. That means that the most important part of understanding Object Oriented Programming is understanding what classes are and how they work.

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Python String Basics

Introduction

Strings are called what they are because they are strings of characters. It doesn’t matter if those characters are letters, numbers, symbols or spaces. They are all taken literally and not processed within a string. That’s why strings are sometimes referred to as string literals.

String Basics

If you’ve been following along with the previous guides, you’ve already experimented with some strings. You’ve typed in some, and you’ve printed them back out. What about getting user input when the Python script runs? Python has built in functionality to take in user input and assign it to a variable. Try it out.

user_input = input("Please enter some text: ")
print(user_input)

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Python Constructors

Introduction

By now, you should be familiar with the way basic classes work in Python. If classes were just what you’ve seen, they’d be fairly rigid and not all that useful.

Thankfully, classes are much more than just that. They are designed to be much more adaptable and can take in information to shape the way they look initially. Not every car starts off exactly the same, and neither should classes. After all, how awful would it be if every car was an orange 71′ Ford Pinto? That’s not a good situation.

Writing A Class

Start off by setting up a class like the one in the last guide. This class will evolve over the course of this guide. It will move from being a rigid, photocopy-like, situation to a template that can generate multiple unique objects within the outline of the class.

Write the first line of the class, defining it as a class and naming it. This guide is going to stick with the car analogy from before. Don’t forget to pass your class object so that it extends the base object class.

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Advanced Python Strings

Introduction

In the previous guide, you learned the basics of handling strings in Python. In this guide, you will explore some of the more complex things that strings are capable of. There are tools built into Python, called string methods, that help you to handle strings and do some very powerful things. Through the use of string methods, you can masterfully manipulate text and use it to its fullest potential without writing a ton of code.

Navigating a String

Strings aren’t words. They aren’t sentences, phrases, and believe it or not, they aren’t even a collection of text. Strings are just a lists of characters. Those characters can be letter, numbers, symbols, spaces, and escape characters. Python sees strings by their parts(the characters) and uses those parts to manipulate strings. This is actually true of almost any programming language. So, that means that you can select individual characters out of a string. Try this:

phrase_string = "This phrase is a string!"
print(phrase_string[0])

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