PYTHON FOR BEGINNERS: Master the Basics of Python Programming and Start Writing Your Own Code in No Time (2023 Guide for Beginners)

By Glen Jennings

Python has become one of the most popular programming languages in the world, and for good reason. It's a versatile language that can be used for everything from web development to data analysis, and it's easy to learn for beginners. In this book, "Python for Beginners," readers

• Language: English
• Publisher: Glen Jennings
• Release date: Feb 27, 2023
• ISBN: 9783988311535

Book preview

Chapter 1: Python Installation

The most recent edition, which includes binaries, current source code, documentation, and the most recent news, can be found at the official Python website: http://www.Python.org/.

It is available in a variety of formats, including PDF, HTML, and PostScript. Python documentation is available at www.Python.org/doc/.

Python is divided into two major versions: Python 2 and Python 3. Python 3 is a new version that includes features that Python 2 does not. However, because Python 3 was not designed with backward compatibility in mind, Python 2 remains the primary product in use (although Python 3 has been released almost 10 years at the time of writing this book). The code in this book is Python 2 and Python 3 compatible.

The steps below will walk you through installing Python and some essential libraries.

Windows

The author does not recommend developing on the Windows platform. There are numerous reasons for this, the most important of which is that data in the Big Data era is stored using the Linux operating system. As a result, data scientists' programs will eventually run in the Linux environment in production. Furthermore, there is a lack of compatibility between Windows and Linux. Thus, programs that run normally under Windows (for example, on a local machine) may not run normally in a real-world production environment.

If you are using a Windows system, he can install a Linux virtual machine and then develop it. If you insist on using Windows, the only solution, given the limitations of certain libraries (such as TensorFlow) under Windows, is to install the most recent version of Python 3.

To find out which one it is, go to https://www.python.org/downloads. IPython, Jupyter, Conda, and Spyder are some of the applications available for Windows. We'll go over some of them in greater detail below.

Conda

Conda is a Python development environment and open-source library management system. If you're familiar with Linux, Conda is the equivalent of pip+virtualenv. By entering Condolist on the command line, you can see a list of all the Python libraries that have been installed.

Spyder

Spyder is an Integrated Development Environment (IDE) for Python-based scientific computing. If you are familiar with the mathematical analysis software MATLAB, you will notice that the syntax and interface of Spyder and MATLAB are very similar.

Mac

Python is pre-installed on Macs beginning with Mac OS X version 10.2. You can use the preinstalled Python version directly for educational purposes. The pre-installed Python is likely to cause problems when installing third-party libraries for development purposes, and the latest version of Python must be reinstalled.

The Mac version, unlike the Windows version, does not include the TensorFlow Deep Learning library, which must be installed using pip (preferred installer program). Although pip requires a command line, it is extremely simple to use. Also, because pip is more widely used, it is recommended that the required libraries be installed with pip from the start.

Linux

Linux comes in a variety of flavors. Only the installation on Ubuntu will be covered in this article. Although Python is pre-installed in most Ubuntu versions, the version is outdated and it is recommended that you install a newer version. To find out what version of Python you have, open a terminal window and type: python -version.

If your version is less than 3.7.x, use the command sudo apt install python3.8 to install Python 3.8.

Everything is now ready for us to run our first Python commands!

Python can be executed in two ways: interactively or through an Integrated Development Environment (IDE) (IDE).

Python Shell Interactive Interpreter

Python is a dynamic language that can be used in two ways: as a script interpreter to run programs, or as a standalone program that allows you to enter and execute any stream of instructions. Python provides a real-time interactive command window called the Python shell to accomplish this. This allows you to write code, debug instructions, and test them.

Type python in the terminal (Linux or Mac) or command prompt to launch the Python shell (Windows). Once you've begun, you'll notice this symbol at the beginning of the line:

>>>

You can then begin to familiarize yourself by entering commands. Here are some observations:

1. Because the shell can execute any Python command, some people use it as a calculator as well.

2. Variables can be given values. For example, you could write: >>> a=5

>>> b=3

In this case, you've given the variable a the value of 5 and the variable b the value of 3. You can use these variables until the shell is closed, for example, to calculate the sum: >>> a+b 5

Because Python is a dynamic type language, there is no need to declare a variable's type when assigning values to it.

3. You can also use the shell to import and use a third-party library, such as numpy (numerical python), which contains a large collection of high-level mathematical functions and allows you to work with large matrices and multidimensional arrays:

>>> np import numpy

x = np.array([1, 2, 3]) x array ([1, 2, 3])

We can see in the code that the third-party library numpy can be given an alias, such as np, when imported. When numpy is required later, it is replaced by np to reduce character input. We used numpy to create an array of integers in the example code.

The options available in the command line are listed in the table below.

Environment for Integrated Development (IDE)

An IDE, or Integrated Development Environment, is a piece of software that aids in the creation of other applications. The IDE, which is designed to encapsulate all programming tasks in a single application, allows you to consolidate the various aspects of writing a program.

The primary benefit of an IDE is that it provides a centralized interface for all of the tools required by a developer, including

Code editors are designed to simplify and improve the process of writing and editing source code. They differ from text editors in that they simplify and improve the process of writing and editing code.

Compilers convert source code written in a human-readable/writable language into a form that computers can execute.

Debuggers are used during testing to assist developers in debugging their application programs.

Prerequisites for a Good Python IDE

Python can be used with a variety of open-source IDEs. Let's look at what features an IDE should have:

Reload and save the source code

An IDE should automatically save your work and reopen everything in the same state it was in when you left. This will save you time during development. Starting from within the environment

To run your code, the IDE should include a compiler. You're probably using a text editor if you have to open another application to run it. Debugger support The debugger must be able to run the code partially through so-called breakpoints. Highlighting syntax

The ability to quickly identify keywords, variables, and symbols within the code, even with different text colors, simplifies reading and understanding. Formatting of code automatically

When the developer uses loops, functions, or other block code, the code indents itself.

Given the features listed above, Pycharm is unquestionably a good IDE. JetBrains created it as an integrated development environment. It distinguishes itself from the competition through productivity tools such as quick fixes.

It is available in three flavors: the Apache-licensed Community version, the Educational version, and the proprietary Professional version. The first two versions are open source and thus free, whereas the Professional version requires payment.

Environment Variables in Python

Chapter 2:  Python Variables

Understanding Python variables, classes, and how they work is critical for both novice and experienced programmers looking to expand their programming skills.

In Python, what is a variable?

When you write complex code, your program will require some structure before it can be changed.

Variables are sections of memory used to store values that will be used later in the program's development. Python, unlike other programming languages, lacks the command to declare a variable.

In Python, variables are thus defined as memory segments used to store data. As such, they serve as memory units, supplying data to the computer for processing.

Each value has its own database, and all data is organized into categories such as numbers, tuples, dictionaries, and lists, to name a few.

It's critical to understand how variables work and how they can help you write an effective Python script. In the following sections, we will learn how to declare, redeclare, and delete local and global variables.

Constants and Variables

Variables and constants are both Python components, but they serve different purposes. Variables and constants are values that are used to create code that will be executed during the program's creation. They serve as essential memory storage locations for data, whereas constants are variables whose values remain constant. Variables thus store data reserves, whereas constants have a fixed value. Constants are distinguished by the use of capital letters separated by underscores. Literals and Variables

A literal is unprocessed data stored in a variable or constant. Literals in Python are classified into three types: numeric, string, and Boolean. There are also Literal collections such as tuples, dictionaries, lists, and sets.

Variables and literals both deal with raw data. The distinction is that variables save them.

foo = 42 \s^ ^

| |—- literal, 42 is *literally* 42 | |—variable foo, the content can change

Variables and arrays

Variables in Python have a unique feature in that they store a value in memory to be