Python: A versatile programming language for Web Development to Machine Learning

Guido van Rossum created Python programming language in the 1980s. The idea behind the Python programming language was to develop a general-purpose programming language that can be simple in syntax and easy for amateur developers to understand.

Python is a programming language that has gained importance over time. Python is an extensive library that supports multiple use cases, from web development to Machine learning and all other cutting-edge technology used in the software industry. Because of this, Python is considered a programming language that can also support future application needs.  According to the TIOBE index, Python ranks number one as of June 2022 based on popularity.

Ranking of Python among other programming languages

Python has been used on many large-scale projects and delivered outstanding results as an open-source programming language. A few examples of organizations that have extensively used Python as a programming language are Google, YouTube, EVE Online, and many more.

Testimonial for Python

Below are the testimonials from some of the leaders of the industry:

There are more testimonials from leaders working at top organizations. They can be found in Quotes about Python.

Why is Python popular?

There are reasons why the Python programming language has gained popularity. Let’s classify the reasons into three broad categories as stated below:

Clear syntax

Python has a clear and clean syntax, making the language intuitive and easy to read. It also reduces the complexity curve so that beginners can contribute to complex project teams. Moreover, it reads almost like plain English and has a lot of functions available that can help easily do complex tasks.

Due to its ease of learning and usage, Python has the edge over other programming languages compared to the speed of writing and executing the code. Python code is much faster to write and execute when compared to other programming languages.

Scalable

Python programming language is scalable and can easily handle massive amounts of data. It was created more than 40 years ago, and the community around Python has become stronger over time. As a result, Python comes with a wide variety of libraries supported by a huge developer community that can add application features and reduce development time.

Libraries such as NLTK or scikit-learn have been designed for the specific task of natural language processing and machine learning applications, respectively. There are a lot more frameworks and libraries that are designed for specific tasks. A few examples include the following:

• OpenCV for computer vision-related tasks
• Matplotlib, seaborn, and Bokeh for the visualization purpose
• BeautifulSoup for the HTML and XML parsing
• Tkinter to develop a GUI-based application and a lot more.

Versatile

Python programming use cases are not limited to only web or mobile app development. Python as a programming language can be used for the following use cases:

• Building web apps
• Gaming applications
• Enterprise-grade apps
• E-commerce applications
• Machine Learning and Artificial Intelligence applications
• Image recognition and text processing
• Internet of Things with devices such as Raspberry Pi
• Web scraping
• Desktop GUIs
• Automating tasks and much more.

Therefore, this makes Python one of the most versatile programming languages.

Let us look at available technology using a Python programming language that can be used to support use cases in multiple streams.

Using Python for Web Development

Another reason Python became a popular language is its versatility in web development.

The first thought that comes to mind when setting up the webserver is NodeJS or Java, but Python is also a great option. While Python may suffer in performance compared to other popular frameworks and programming languages, the ease of spinning up a Python server cannot be ruled out.

Flask and Django are the two important frameworks developed on top of Python that can be used for web development. Flask is a minimalistic framework that gives control to the developer to set up the project. Still, Django is more of a structured framework with a rigid structure than Flask and can be a good option for beginners.

Apart from Django and Flask, there are other notable frameworks, such as Pyramid, Web2Py, or Turbogears, that can be used for web development.

Using Python for Data Science

A highly demanded skill of data science is reaching the top. Data Science is one such area that is gaining more and more attention every time. Data Science is a technique to drive valuable insights from the data. Python is picking up fast for carrying out such tasks. You may also check the article about using Python programming in data science and also using Python for data visualization.

Python provides powerful libraries such as NumPy, pandas, Matplotlib, seaborn, and many more to carry out such tasks. 

Machine Learning and Artificial Intelligence are the areas that are gaining popularity. Machine Learning is a technique where machines can recognize patterns from the data.  

Python provides libraries such as scikit-learn, OpenCV, NLTK, SciPy, Keras, and TensorFlow are available to develop such use cases. These libraries support use cases of text and data processing, image recognition, and developing deep learning solutions that can benefit businesses.

Python for Internet of Things (IOT)

Internet of Things is a technology where small power devices such as RaspberryPi, Arduino, etc., can connect to the internet and run the custom code on the edge device itself. Python has also found itself where it can easily meet the needs of such low-computation devices.

It may happen that not all edge devices can use a fully-featured version of Python. Therefore, a Micropython, which is a subset version of Python developed for the specific needs of low computation devices, can be used. Such a library allows coding in Python and takes advantage of the simplicity and productivity of the language.

Python is compatible with devices such as RaspberryPi, PyBoard, ESP8266, ESP32 (compatible with Micropython), and much more.

Automation with Python

Python language provides multiple tools such as PyAutoGUI, Pywinauto, Selenium, Requests, Robot Framework, Pytest, and much more for automating tasks and helps comfortably achieve complex tasks. Multiple use cases can be automated using Python. A few examples are described below:

• Full Stack Automation: Libraries such as BeautifulSoup, Selenium, Requests, and PyBuilder can help in full-stack automation. One can connect to different web browsers and extract the data using such libraries.
• GUI Automation: Libraries like Pywinauto and PyAutoGUI can be used for GUI automation. One can control mouse and keyboard actions to automate interactions on the application.
• Test Automation: Framework such as Robot Framework can be used for Robotic Process Automation (RPA) purposes. Pytest library is also available to write the test codes using Python.

You can read this article about automating with Python for more details.

Python to Build GUI Applications

GUI applications are applications where the user uses an application or program with an interactive user interface to carry out the desired operations. Python provides multiple libraries to build such GUI applications. Libraries such as Tkinter, Tkinter, or wxPython to build such applications.

Such libraries provide multiple components, such as labels, input fields, buttons, etc., to build a GUI application that can be interactive.

And a lot more current and future use cases where Python can help solve the problem. Therefore, if someone asks, “Why Python programming language?” you have an answer here.

Furthermore, there are tremendous opportunities for Python, and I believe the opportunities will only grow because of the versatility of the Python programming language. For example, python developers can be web developers, data analysts, data scientists, optimizing data algorithms, python scripting developers, and more.