PYTHON FOR BEGINNERS: A Comprehensive Guide to Learning Python Programming from Scratch (2023)

By Denton Freeman

"Python for Beginners: A Comprehensive Guide to Learning Python Programming from Scratch" is your essential companion for mastering the fundamentals of Python programming, catering to individuals with little to no prior coding experience. This book offers a step-by-step approach to learning Python, equipping you with the knowledge and skills to

• Language: English
• Publisher: Denton Freeman
• Release date: Nov 3, 2023
• ISBN: 9783988315786

Denton Freeman

Denton Freeman, based in Austin, Texas, is a seasoned programmer and educator with a passion for simplifying complex concepts. With years of experience in Python programming, Freeman has dedicated his career to teaching programming to beginners. His expertise lies in making programming accessible and engaging for learners at all levels, fostering a love for coding and problem-solving from the ground up.

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Introduction

Python is one of the top programming languages that academic institutions and businesses favor teaching and using, respectively. Python’s attractiveness is concealed by the fact that it has incredibly broad applications in a variety of fields. The fact that Python is used to create AI models makes most people detest it. They worry that these Python-powered AI models may grab people’s jobs and force them out of various businesses. They use Tesla’s driverless taxi initiative as an example, which intends to displace Uber’s taxis in the US market. But the truth is otherwise. In actuality, Python-powered AI models will increase employment significantly rather than decrease it. For instance, creating these models will develop into a separate sector of the economy. Additionally, the use of these AI models will develop into a new industry.

The corporate world is about to be completely changed by data science. Python is the computer language on which data science is founded, as more and more businesses compete against one another.

They only want a means to have an advantage over their rivals. They will stop at nothing to gain control and advance. Python seems to hold promise in this area. Python-backed data science has a tendency to provide industries with sophisticated data on previous and present sales patterns, which can aid corporate sector CEOs in developing more informed sales and marketing strategy decisions.

The fact that you can learn Python without having to build the code is its major benefit. In C++, you must first compile the complete program before running it. You won’t be able to tell if your application works or produces an error until that point. Python provides programming at a similar level, if not higher, but it is still an interpreted language that is simple to write, modify, and correct.

It’s incredibly simple to read and understand Python. It is simple to read the source codes for a variety of programs made by other programmers.

But regardless of how simple it appears to be to read and learn, it requires consistent practice, just like all the other programming languages.

You must open the Python editor and practice all of the codes. To start, all you need to do is copy the code and paste it into the editor to see the results. You can make a few small changes to the code and observe the effects in the second stage. You will be able to totally redesign a program and observe how it functions in the Python shell during the third phase. From the perspective of the global employment market, studying Python is quite profitable given its expanding uses. Python can provide you with the competitive advantage you need to land well-paying employment over other applicants.

Chapter 1: Installation of Python

At the official Python website, http://www.Python.org/, you may access the most recent edition, which includes binaries, the most recent source codes, documentation, and the most recent news, among other things.

It is available in a number of formats, including PostScript, HTML, and PDF.

Website for Python documentation: www.Python.org/doc

Python 2 and Python 3 are its two main iterations. There are new features in Python 3 that Python 2 does not have. Although Python 3 has been available for about ten years at the time this book was written, Python 2 is still the primary product in use since Python 3 was not created with backward compatibility in mind. Both Python 2 and Python 3 are compatible with the code in this book.

The steps for installing Python and a few key libraries are provided below.

Windows

The author does not advise using Windows for development. There are several causes, but the biggest one is that in the Big Data age, data is stored using the Linux operating system. The programs created by data scientists will therefore finally function in a Linux environment in production. Furthermore, there are certain issues with Windows and Linux compatibility. Programs that operate on Windows without any criticality (for example, on a local PC) could not function properly in a genuine production setting.

He can decide to install a Linux virtual machine and carry out development on it if you utilize a Windows system. Installing the most recent Python 3 version is the only option if you insist on using Windows due to the limitations of some libraries (like TensorFlow) on Windows.

Visit https://www.python.org/downloads to check which one it is.

IPython, Jupyter, Conda, and Spyder are a few programs that can be used with Windows. Below, we’ll go into more detail about a few of them.

Conda

Conda is a management solution for open-source libraries and the Python development environment. If you are familiar with Linux, you can compare Conda to pip+virtualenv. By typing Condolist into the command line, you may view every Python library that has been installed.

Spyder

Python’s scientific computing uses the Integrated Development Environment (IDE) called Spyder. If you are familiar with the mathematical analysis program MATLAB, you will see that Spyder’s syntax and user interface are extremely similar to those of MATLAB.

Mac

Python is pre-installed on Macs as of Mac OS X 10.2, the most recent version. You could decide to utilize Python directly from the preloaded copy for instructional purposes. The most recent version of Python must be installed because the pre-installed Python is likely to cause issues when installing third-party libraries for development reasons.

The TensorFlow Deep Learning library is not included in the Mac version, which means pip (recommended installer program) must be used to install it. Despite requiring a command line, pip is fairly simple to use. Additionally, pip is more extensively used, so it is advised to install the necessary libraries using pip right away.

Linux

There are numerous Linux variations. We will solely discuss Ubuntu installation here. Despite the fact that Python comes pre-installed on the majority of Ubuntu editions, it is advised to install a more recent version. Open a terminal and type:

python -version

to see what version of Python you are using.

The command sudo apt install python3.8 can be used to install Python 3.8 if the version you currently have is less than version 3.7.x.

Everything is all prepared, so let’s launch our first Python commands!

Running Python

Using an Integrated Development Environment (IDE) or an Interactive Interpreter to execute Python Python can be executed in two different methods.

Python Shell Interactive Interpreter

Python is a dynamic language that may be used in two different ways: as an actual program that lets you enter and execute any stream of instructions, or as a script interpreter to run programs. Python has a live, interactive command window for this purpose called the Python shell. You can use this to create code, fix bugs, and test instructions.

Enter python at the command prompt (Windows) or terminal (Linux or Mac) to launch the Python shell. Once the line has begun, you will see this symbol at the beginning:

>>>_

After that, you can start using commands and familiarizing yourself.

Some findings:

Since the shell can run any Python command, some users also use it as a calculator.

Variables can have values assigned to them. By composing, for instance:

>>> a=5

>>> b=3

In this instance, you have given the variable a the value of 5 and the variable b the value of 3. Until the shell is closed, you can utilize these variables to, for instance, calculate the sum:

>>> a+b 5

Python is a dynamic type language, so when assigning values to a variable, the type of the variable does not need to be declared.

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

>>> import numpy as np

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

>>> x

array([1, 2, 3]) is displayed.

We can see that the third-party library numpy can be given an alias, like np, while being imported, as demonstrated in the code. To cut down on the number of characters required, numpy is swapped out for np when it is later required. Numpy was used to build an array of numbers in the example code.

A list of options that you can type into the command line is shown in the following table.

Option Description

-d Provide the output after debugging

-o Optimized byte code generation i.e., the .pyo file is generated

-s Don’t run the import site for searching Python paths in a startup.

-v Details of the import statement

-x Disable the class-based built-in exceptions

-c cmd This runs the Python script sent in cmd String

file The python script is run from the given file

The provided file is used to launch the Python script.

A development environment that is integrated

An integrated development environment, or IDE, is a piece of software that makes it easier to create other programs. The IDE enables you to combine the various components of building a program because it was created to incorporate all programming duties into a single application.

An IDE’s fundamental benefit is that it provides a single interface with all the tools a developer requires, such as:

Code editor: These editors are made specifically for writing and editing source code, and they differ from text editors in that they make the process of writing and editing code simpler and better.

Compiler: Compilers convert human-readable/writable source code into a format that computers can understand and execute.

Debugger: During testing, debuggers are employed to assist programmers in fixing bugs in their applications.

What makes a decent Python IDE?

Python may be used with a number of open source IDEs. What characteristics must an IDE have?

Reload and save the source code

An IDE should immediately save your work and open it back up later in the exact same condition as when you last closed it. You’ll cut down on development time by doing this.

Leaving the environment and running

For running your code, the IDE ought to contain a built-in compiler. You are probably using a text editor if you have to launch another program to use it.

Debugger assistance

The code must be partially run via the so-called break points by the debugger.

Highlighting syntax

Even with varying font colors, being able to easily recognize keywords, variables, and symbols within the code makes it much simpler to read and comprehend.

Format codes automatically

When a developer uses loops, functions, or any other type of block code, the code