Explanation of why Python continues to grow

Which programming language has been around for over 30 years and is growing in popularity each year?

If you guessed Python, you nailed it. In the 2022 October Report, it turns out that Python is still the second most used programming language on GitHub. Interestingly, Python usage has grown by over 22% year-over-year, and at some point in 2022 he will have over 4 million developers using Python on GitHub.

In this article, we’ll delve into a brief history of Python, its benefits and use cases, and explore why the programming language invented in the 1980s continues to dominate development. And since this is his GitHub, he also provides some helpful tips and tricks for developers new to Python and those with experience.

So what is Python? πŸ€”

Python is a high-level interpreted programming language with a simple syntax that is easy to read and very easy to use for both users and beginners.originally built to satisfy Guido Van Rossum’s Aspirations for Programming Languages Easy to use and beautiful to look at, Python was first released to the world in 1991.

Fun facts: Python is Named after a BBC TV show“Monty Python’s Flying Circus”.

Since its development, it has been widely applied by developers, data scientists, researchers, etc. But how can you make your coding language look simple and beautiful? Here’s some evidence:


print("Hello world.")



public class HelloWorld {
    public static void main (String[]args) {
      System.out.println.("Hello world");

Python is a general-purpose language, so it can be used in a wide variety of applications. Its simplicity makes it the perfect language for automating tasks, building websites and software, and analyzing data.

Python has several other features that make it popular among developers and engineers. These include:

What is Python commonly used for? πŸ’»

Python can be used for just about anything, from web and software development to machine learning and artificial intelligence (AI). Let’s look at some of the most common use cases.

import antigravity

def main():

if __name__ == '__main__':

Run this command to check out the inside jokes among Python developers.

Using Python for web and software development

Python is a popular language for web and software development because it allows you to create complex multi-protocol applications while maintaining a clean and readable syntax. In fact, some of the most popular applications are built with Python. Additionally, Python’s open source community provides developers with a wealth of reusable code, frameworks, and support. Case in point: Django It is one of the most used Python frameworks designed by experienced developers to help others build their applications faster and avoid issues that can slow them down.

Use Python for task automation

One of the main advantages of Python is the ability to automate repetitive manual tasks. With Python, you can learn how to automate almost anything using pre-built code from built-in modules or robust libraries. Alternatively, you can write your own custom scripts to perform specific actions.For example, you can easily automate emails “smtplib” module or copy the file “shutil” modulePython also has a robust set of test frameworks, making it an excellent language for test automation.frameworks such as pie test, behaveand robot Developers can create simple yet effective tests to ensure build quality.

Use Python for machine learning and data science

I have an interesting fact. Python is the language of choice for data science and research. Its syntax is easy to understand and adaptable, so people with little or no development experience can easily learn Python and use it to analyze data for research, reporting, predictive or regression analysis, and more. can be operated. Collecting and analyzing data can be a time-consuming task for a data scientist. Python is also one of the top languages ​​for training machine learning (ML) models. Through specific algorithms, these models can analyze and identify patterns in data and make predictions or decisions based on that data. It also constantly evolves and faces new variables based on the output of previous datasets. Data scientists and developers training ML models often rely on libraries such as: NumPy, pandaand Matplotlibto automate functions such as cleaning, data transformation, and visualization.

Using Python for financial analysis

Similar to how Python helps data scientists work with large data sets, Python is widely used in the financial industry to quickly perform complex calculations. The stock market generates an enormous amount of data and Python can be used to import data about stock prices and generate strategies through algorithms to identify trading opportunities. The language can be used for portfolio optimization, risk management, financial modeling and visualization, cryptocurrency analysis, and even fraud detection.

and using Python for artificial intelligence

Python is also found in some of the most complex artificial intelligence (AI) technologies. In fact, Python is one of the preferred languages ​​for AI. Python’s clean, readable code enables developers to create consistent and reliable systems. Its vast library offers numerous frameworks such as: pie brain, providing developers with powerful algorithms for machine learning tasks. Additionally, Python’s visualization capabilities help transform these large datasets into easy-to-understand charts or reports for AI or ML. Interestingly, OpenAI, an artificial intelligence research institute, utilizes the Python framework. pie torchas a standard framework for deep learning to train AI systems.

Besides Python’s relative ease of learning, there are several other reasons why its popularity continues to grow consistently. These include:


Python is everywhere and is used to build quite a few technologies, websites, and even systems that most people encounter on a daily basis. Power everything from your favorite video streaming service to the ML algorithms that power your next cryptocurrency trade. For an even broader example (pun intended absolutely), NASA uses Python to power data analysis on sophisticated James Webb Space Telescope, making it one of the few programming languages ​​that is literally otherworldly. πŸš€

How to get started with Python πŸ““

A quick Google search will find hundreds of resources to jump-start your Python journey. To keep things simple, here are some useful GitHub repositories to help you get started with Python.

To get started, Download the latest version of Python.

Start building now on GitHub

GitHub offers two easy ways to get started with Python. GitHub Codespaces and GitHub Copilot.

Start building today for free with GitHub codespace, every developer on GitHub gets 60 free hours per month to spin up a development environment in the cloud faster from any device.examine django Quick start template Start coding right in your browser!

You can also use GitHub co-pilot, AI Pair Programmers on GitHub, writing the first lines of Python. Method is as follows.

  1. Install the GitHub Copilot extension to your code editor.
  2. Please describe the purpose of the project in the comments.
  3. Write a comment describing the required library.
  4. As you start tabbing, GitHub Copilot will suggest lines of code to help you learn new techniques and methods.

From machine learning to data analytics, Python’s versatility allows for continued explosive growth for both developers and non-developers alike. Try Python on GitHub or on your local machine, be a part of this growth and get started today!

https://github.blog/2023-03-02-why-python-keeps-growing-explained/ Explanation of why Python continues to grow

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