Your First Python Program

Introduction

Hello, and thank you for taking an interest in Your First Python Program, a beginner's guide to the Python programming language. This book is written for readers with varying degrees of programming experience to give them a firm grasp of Python and its fundamentals.

Python has become extremely popular among both beginners and experienced developers in recent years, thanks to its ease of use, readability, and versatility. As an interpreted, high-level, general-purpose programming language, Python is used in a wide range of fields such as web development, data analysis, AI, and scientific data processing.

Data types, control flow, functions, modules, and file manipulation are only some of the fundamentals of Python covered in this book. Object-oriented programming, libraries, and frameworks including NumPy, pandas and matplotlib. We'll also look at Flask, Django, PyQt, and Tkinter, even though they're not covered in detail in this book. There is also a Github repository (https://github.com/EstrategiaUno/YourFirstPythonProgram) for you to clone and explore, it has examples you can experiment and learn with.

This book makes no assumptions about the development environment in which you'll be working. You can use it in a Mac, Linux, or Windows environment without making many adjustments. So that the time you spend reading isn't wasted, we worked hard to condense and optimize the content so you can learn Python as quickly as possible. We explain each topic and then put it into practice right away by showing you code examples.

At the end of this book, we hope you will see Python as a powerful tool whose potential can lead you down many different career routes, including but not limited to analytics, data engineering, data science, visualization, statistics, web development, microservices, and more. Our overarching goal in authoring these pages is to pique your interest and give you a firm grasp of the fundamentals so that you can pursue more specialized applications later on. I appreciate you letting me share in your initial steps, and I hope they are successful ones.

Chapter 1: Introduction to Python

Python is a robust high-level programming language used for a broad variety of purposes, including but not limited to web development, scientific computing, data analysis, and artificial intelligence. In the years after its initial release by Guido van Rossum in 1991, it has risen to prominence as one of the most widely used programming languages.

In this section, we will define Python and explain why it is useful to know how to write in this language. To get you up and running quickly with Python, we'll also walk you through the process of establishing a productive development environment.

What is Python?

Python is a high-level, general-purpose programming language that aims to be both simple and powerful. As a result of its easy-to-grasp grammar, which is reminiscent to English, it is an excellent language for those just starting out in linguistics. Python is not a compiled language; rather, it is an interpreted language, in which the code is run as it is typed. Your code can be easily tested and debugged in this way.

As a high-level language, Python hides away the nitty-gritty of computer hardware and memory management. As a result, development times are cut down and the Python language becomes more accessible.

Low-level or high-level programming language?

If a programming language doesn't offer much in the way of abstraction from the underlying machine's instruction set architecture, we can consider it to be low-level. The trade-off is code that is harder to comprehend and debug but gives the developer greater freedom over the computer's internals, including its hardware and memory management. Some examples of low-level languages are machine code and assembly.

A high-level programming language, on the other hand, is one that provides a higher layer of abstraction over the underlying instruction set architecture of a computer. The trade-off is simpler, easier-to-debug code, but the programmer has less say over the underlying hardware and memory management. Python, Java, and C++ are all examples of high-level languages.

Because they more closely resemble human languages and make use of natural language constructions, high-level languages make reading and writing more simpler for humans. Low-level languages, on the other hand, provide for greater direct control over the hardware and are commonly employed in the creation of operating systems and the programming of embedded devices.

Why is Python important?

Python's simplicity, readability, and adaptability make it a fantastic choice for new programmers, but the language's extensive capabilities and libraries make it well-suited for more complicated applications.

Python is also frequently used in industry, making proficiency in it a desirable trait for those seeking employment in the IT sector. Python is widely used in the software development process at firms like Google, Netflix, and Spotify.

Python is everywhere!

Google: Web scraping, data analysis, and machine learning are just some of the many uses for Python at Google, one of the largest technology businesses in the world. Python is one of the most widely used languages at Google and was essential in the development of the company's core products, including the search engine.

NASA: NASA uses Python for many mathematical and scientific tasks, including as simulations, data analysis, and image processing. In the realm of science, Python is employed for both the testing and validation of hypotheses and the scripting and automation of routine chores.

Spotify: The music streaming service Spotify uses Python for data analysis, recommendation systems, and backend services. The company's mobile and online apps, as well as the automation of playlist building and other features, are built with Python.

Netflix: Python is Netflix's go-to language for everything from data analysis to recommendation systems to split testing. The engineers at the firm have also created a variety of open-source Python libraries, such as the Metaflow library for constructing and releasing machine learning pipelines.

Instagram: When it comes to data