Aug 22, 2022
What Is Python: Get to Know One of the Most Popular Programming Languages
Python is a general-purpose programming language that runs on almost all system architectures and can be used for a wide range of applications in different fields, from web development to machine learning.
On top of its versatility, the language is also beginner-friendly, making it one of the most popular programming languages available.
If you want to learn more about Python and its most common use cases, this article may be right for you. We will explain why you should learn Python, what it is used for, and give 10 examples of well-known companies that utilize it.
Why You Should Learn Python
This section will explain several reasons why learning how to code in the Python programming language may benefit you.
Python Is Free and Open-Source
People can use and distribute the Python source code for free, even for commercial purposes. Nowadays, anyone with a computer and a strong will to learn can teach themselves how to code in Python.
To download the latest version of Python, simply access the official Python website, click Downloads on the navigation bar, and hit the Download Python button. The default version is for Windows, but Python is also available for other operating systems, including Linux and macOS.
As of 2022, Python 3 is considered the most up-to-date language version. Meanwhile, its predecessor Python 2 was sunsetted in January 2020 and is no longer updated with bug fixes, new features, or security patches.
Python Is Easy to Learn
When learning to code, beginners may find it difficult to understand how a programming language works, especially if it is very different from their native language.
As one of the easiest programming languages to learn, Python uses simple syntax with lots of English keywords. It was designed to be a concise language with high readability. This makes it more beginner-friendly compared to other languages like C++ and Haskell.
In addition to its simplicity and consistency, another factor contributing to Python’s ease of use is that it is an interpreted programming language, as opposed to a compiled one like C or C++.
This means you can run each line of code as soon as you finish writing it and see immediate results, making adjustments if needed. As a result, this saves programmers a lot of time, helping them catch errors quickly and easily.
Lots of Job Opportunities With High Salaries for Python Developers
Python is one of the most in-demand programming languages due to its simplicity and versatility. In addition, it is one of the highest-paying programming languages in 2022. In fact, the average Python developer salary in the United States is $108,043/year.
Another research assessing LinkedIn job postings in the United States and Europe shows that Python is number one in terms of job demand in 2022, with over 200,000 job offers in the United States and 50,000 in Europe.
If you’re considering becoming a freelance web developer, Python can also lead you to lucrative job opportunities. According to a survey on the highest paying programming languages for freelancers in 2022, Python is number one on the list, with an average rate of $55-60/hour.
Python Is Popular in the Community
According to the TIOBE Programming Community Index that indicates the popularity of programming languages, Python occupies the number one position as of April 2022.
The huge Python community means programmers have many people to turn to when they have questions and coding problems.
For example, on the coding question and answer platform Stack Overflow, there are over 1 million questions carrying the Python tag. There are also over 2 million repositories tagged with Python on GitHub, the code hosting platform programmers use for version control and collaboration. Python users can also visit official forums to discuss various topics related to the language, community, and the Python Software Foundation.
In addition to its large online communities, many Python User Groups have monthly informal offline meetings to share tips and tricks. There are over 1,000 groups with more than 800,000 Python users worldwide.
Python Is Versatile
Besides being easy to learn, Python is also popular due to its versatility. The language’s usage spans multiple fields, including data science, web development, and machine learning. Python is also a cross-platform language, indicating it can work on various operating systems like Windows, Linux, and macOS.
Moreover, this popular coding language can run alongside other languages.
The CPython reference implementation, for example, is written in C and Python. Other implementation examples include Jython, written in Java and Python, and IronPython, created in Python and C# and integrated with the .NET framework.
Furthermore, there are over 100,000 Python libraries. A library is a collection of pre-written code programmers can use to perform certain repetitive tasks.
The numerous libraries or frameworks are used for different purposes across various fields. Programmers can save time by using them instead of writing and rewriting frequently used code sequences.
What Is Python Used For?
Some of the most common use cases of the Python programming language include web development, automation, software testing, data analysis, machine learning, and game development.
Let’s discuss these use cases in more detail.
Web development is the practice of making websites and maintaining them. There are two main parts of a website – front-end and back-end. Also known as the client side of the application, the front-end refers to the part of a website visitors directly interact with. This includes elements like images, buttons, and the navigation menu.
On the other hand, the back-end refers to the part of a website site visitors do not directly see. The server side or the back-end stores website data and makes sure everything on the front-end works smoothly.
Python is a back-end programming language. Web developers can use Python code to transfer data to and from servers, interact with databases, and manage a site’s security.
There are many Python frameworks often used in web development, including:
- Django. An open-source, high-level, and Python-based web framework for rapid development of secure websites with clean design.
- Flask. A microframework written in Python to provide a simple but extensible core, with little to no dependencies on external libraries.
- CherryPy. Known for its simplicity, CherryPy lets developers build web applications using object-oriented programming, producing smaller source code in less time.
- web2py. A free full-stack framework great for developing portable database-driven web applications.
- Pyramid. Acting as a middle ground between a microframework and a mega framework, Pyramid offers flexibility, control, and extensibility via add-ons and development environments.
Automation and System Scripting
Automation refers to making computers or machines complete tasks without human intervention. Meanwhile, scripting refers to writing code to create the automated system.
As a scripting language, Python can be used to automate various tasks for both programmers and non-programmers. Some examples of the tasks the automation scripts can perform are as follows:
- Solving simple math problems
- Checking for errors and duplicates in files
- Renaming files
- Converting files
- Entering data into an Excel spreadsheet
- Sending HTTP requests
- Calculating exchange rates
- Downloading content
- Sorting, sending, and replying to texts and emails
- Scraping data from websites
One of the most important parts of developing software is the quality assurance process. To maintain excellent customer satisfaction, software companies must ensure their product offers a high-quality, consistent, and smooth user experience.
However, they also have to release their software and its updates quickly and efficiently to keep up with competitors. This is where test automation comes in.
Automated testing or test automation means using computers to run tests, manage test data, and analyze test results automatically to improve software quality. This is similar to the automation we described in the previous section but more specific to the field of software development.
Test automation is great for repetitive tasks, such as regression and functional testing. On the other hand, tests requiring real people’s judgment and opinions – like usability, beta, and A/B testing – are best done manually.
Python’s versatility, scalability, and popularity make it ideal for building test automation solutions for developing software. Here are some Python modules software engineers often use for software testing:
- Robot Framework. An open-source and extensible automation framework for test and robotic process automation with an easy-to-understand syntax using human-readable keywords.
- pytest. A software testing framework letting users write various types of test code in Python. Examples include unit, integration, functional, and end-to-end tests.
- unittest. Also known as PyUnit, unittest is the standard unit-testing framework for Python. This framework is built into Python’s standard library. It was created based on JUnit for the Java programming language.
- behave. A Python framework for behavior-driven development (BDD). This refers to an Agile software development technique focused on building software according to the behaviors expected by users interacting with it.
- Selenium. A suite of various tools and modules for facilitating browser automation. It provides a single interface for writing test scripts in multiple languages, including Python. There are three main Selenium projects – Selenium WebDriver, Selenium IDE, and Selenium Grid.
Data Analysis and Machine Learning
Python has become an integral part of data science and artificial intelligence since the language is easy to learn, versatile, and flexible.
Scientists and analysts use Python code to mine big data, build machine learning algorithms, manipulate and analyze data, and perform complex statistical calculations. People can also use this popular language to create varying types of data visualizations, including pie charts, line and bar graphs, 3D plots, and histograms.
The Python language also has a vast collection of libraries useful for data analysis and machine learning. Here are some examples:
- pandas. A Python library offering tools for manipulating and analyzing data structures, numerical tables, and time series.
- Matplotlib. People use this cross-platform library to create interactive data visualization and graphical plotting for the Python language and its numerical extension, NumPy.
- NumPy. Short for Numerical Python, this open-source library supports multi-dimensional arrays and matrices and provides various routines for mathematical operations on arrays.
- SciPy. Built on top of NumPy, SciPy or Scientific Python is a library useful for scientific and technical computing. It contains algorithms for solving engineering and mathematical problems like optimization, linear algebra, interpolation, and integration.
- TensorFlow. A Python library for developing and training machine-learning models using high-level APIs. It can run deep neural networks for various purposes, such as image recognition and natural language processing.
- PyTorch. A machine-learning library for Python based on Torch, another machine learning library for the Lua programming language. It is primarily used in deep learning research.
- Scrapy. An open-source Python framework for crawling websites and extracting structured data from their pages.
Python’s simplicity makes it great for creating basic games or rapid prototyping complex ones. Popular games written in Python include The Sims 4, World of Tanks, EVE Online, and Civilization IV.
The beginner-friendly and simple syntax means rookie game developers can learn Python quickly and use it to create graphical user interfaces, build 2D and 3D games, as well as make visual novel and physics-based games.
Professional game developers can use Python code to quickly build prototypes of their games and present a playable visualization to investors to gather funding.
To deliver game prototypes in the quickest and most efficient manner, game developers can take advantage of many Python frameworks for game development. Here are some of the most commonly used ones:
- pygame. A free set of Python modules for writing video games or creating multimedia programs, built on top of the Simple DirectMedia Layer (SDL) library. It is portable and runs on almost every platform and operating system.
- pyglet. Written in pure Python, pyglet is a library providing an object-oriented API for creating games and multimedia applications. It has no external installation requirements and offers native support for windowing and standard image and audio formats.
- Kivy. A free, cross-platform, and open-source Python framework for developing applications with a natural user interface (NUI), such as games using multitouch technology.
- Panda3D. A game engine providing various subroutines useful for 3D rendering and game development. It offers such features as scene graph browsing, animation optimization, performance monitoring, and error tolerance.
- Ren’Py. A game engine for interactive digital storytelling through words, images, and sounds, focusing on visual novels and story-heavy life simulation games. In addition to the Python support, it has its own scripting language.
Who Uses the Python Programming Language
Many services we use in everyday life are coded using Python. In this section, we will discuss ten famous companies that use Python to provide their services and run business operations.
As one of Google’s main server-side languages along with Java, C++, and Go, Python is used extensively in its internal system, applications, APIs, as well as its artificial intelligence, machine learning, and robotics projects.
For example, Google developers use Python for Google’s build system, internal package format, system administration tools, and code review tool. In addition, its core search algorithms were written in C++ and Python.
Google also uses Python in building YouTube. The language is used for running the platform in various ways, such as for data analysis and visualization, viewing and administering videos, and controlling website templates.
Developers at Facebook use Python in numerous areas, including production engineering, platform services, and server configuration management.
More specifically, Python powers processes like hardware imaging, operational automation, binary distribution, server and infrastructure maintenance, and automatic service failure remedies.
Instagram uses Python for most of its business logic. This refers to the algorithms for handling back-end operations related to the information exchange between the user interface and the database.
To improve operational efficiency, developers at Instagram also use Django, a reliable Python framework with components for both front-end and back-end applications.
Although many of its internal processes are not publicly available, Dropbox developers have confirmed that Python is used in various parts of their infrastructure, operations, and software development, especially for its desktop app and back-end services. Most of its server-side code was also written in Python.
In addition, Dropbox has released a Python software development kit for people looking to integrate the service with the Python app.
Spotify uses the Apache Hadoop software library with the Luigi Python package to collect data and manage its recommendation system. Around 90% of its MapReduce jobs are written in Python, with over 6,000 individual processes running in the Hadoop cluster.
Luigi also powers internal dashboards, external reports, and other Spotify features like Radio, Discover, and top lists.
In addition, developers at Spotify use gevent, a library for asynchronous and concurrent programming in Python, to speed up coding processes and achieve scalability.
Developers at Reddit use various Python modules, such as rollingpin to increase deployment rate to servers, aws-mfa to manage the AWS Multi-Factor Authentication system, and monitors to keep track of all operations.
Python makes up a significant portion of Uber’s tech stack, along with other programming languages like Go, Java, and Node.js. In fact, the platform was originally built using only two main languages – Node.js for marketplace operations and Python for everything else.
In addition, the company has released a Python software development kit for implementing its Ride Request API in a Python app.
Lyft incorporates modules like NumPy, SciPy, pandas, PuLP, Flask, and gevent to run various operations. For example, Flask and gevent are used to calculate the prices of bike and scooter-renting options for users. SciPy helps fight fraud, while the Python-based software Salt is used for configuration management.
In addition, Lyft developers have created an open-source Python platform called Cartography, based on the idea that infrastructure asset mapping is an integral part of cybersecurity. The tool acts as a central repository for an organization’s assets and creates comprehensive maps to illustrate their relationships.
Python is used throughout various divisions of Netflix. In terms of security, for example, the language is useful for such tasks as security automation, risk classification, configuration history monitoring, SSL certificate tracking, as well as vulnerability identification and mitigation. For data science and engineering, Netflix uses Python to monitor data quality, visualize data, manage data movement and syncing, and express business logic.
The company also uses Python to instruct machine learning models to build recommendation algorithms and produce artworks. In addition, Netflix engineers use Python to put together the code written by different teams and perform chaos testing.
Twilio uses Python with the Django framework and the Wagtail content management system (CMS) to power its documentation and its educational coding game, TwilioQuest. It also uses Flask to construct its APIs. In addition, it has released its own Python library to streamline the process of interacting with the Twilio API from a Python application.
Python is one of the most widely used programming languages. It is a great language to learn due to its free and open-source nature, a shallow learning curve, numerous lucrative career opportunities, and versatility.
The popular coding language has many applications in various fields, including web development, automation, software testing, data analysis, machine learning, and game development. Many well-known companies use Python to conduct business operations and deliver their services.
We hope this article has helped you understand the Python language better. Should you have any questions, don’t hesitate to leave a comment below.
What Is Python FAQ
In this section, we will answer some of the most common questions related to the Python language.
What Type of Language Is Python?
Python is an interpreted, object-oriented, and high-level programming language. Interpreted means the language uses a piece of software called the interpreter to read the code line by line when the Python program is executed, instead of reading it all at once.
Is Python the Same as Java?
Python is not the same as Java. While both are general-purpose, high-level, and object-oriented, they are two separate programming languages with many differences. For example, Python is an interpreted language, while Java can be considered both a compiled and an interpreted one.
What Should I Learn First for Coding?
How Do I Start Learning Python?
You can start learning Python by enrolling in free or paid online courses, reading tutorials, or watching helpful videos. If you’re planning to become a professional web developer, consider getting a web developer certification.