Quick Summary:

Python is always the talk of the town not only for its simplicity and cross-platform compatibility but also for its versatility. You can trust and leverage Python for multiple uses; you name it, and Python does it. Everything from web development to data science and machine learning to Artificial Intelligence answers a common question; what is Python used for? Python has tremendous development potential, making the scripting language undefeatable over other languages.

Table of Contents


Python is an object-oriented programming language that generally works around data, and it is majorly used in the fields like Machine Learning, Artificial Intelligence, IoT, Game Development, web application development, and data analytics. The most accessible programming language has become the product owner’s most preferred choice to launch their next-gen product. Due to the ease of syntax in Python, the programmers can complete coding in fewer steps than in Java or C++. Python is considerably one of the fastest-growing languages.

Google trends report Python

Ever evolving Python libraries make it a viable choice for any project, whether mobile app, web app, IoT, Data Science, or AI.

Why Use Python

Python can be solely used to accomplish tasks or paired with new-age technologies to build business automation processes.

According to a recent study, Python again ranks number 1 on Tiobe and Pypl. And not only developers but even entrepreneurs and business owners believe in the potential of Python. All you need to know is why choose Python and what makes it a sure-shot solution for developing online platforms.

  • Firstly, Python is an easy-to-learn programming language, resembling English and making it easily understandable to beginners and professionals.
  • Allows to leverage an extensive set of libraries to enable the development.
  • Huge supporting community for development and improvement.
  • Open for integration with other technologies.
  • Widely used across industries.

What is Python Used For in 2024

Python is an interpreted language widely used to create websites, and software products, automate tasks and analyze data. Python as a language is not a compiled one like C++ or Java, meaning it can be used to create a wide range of programs and is not specialized for any particular problem. Python is used for web development, app development, and desktop applications—including games! You’ll find Python at the heart of many tools and frameworks used by developers to build things like search engines like Google, social networks like Facebook, and email services like Gmail. Let’s understand in detail what is Python used for.

Applications for Python include;

  • Python Web development
  • Python For Data Science and Data Analysis
  • Python For IoT
  • Python For FinTech
  • Python For AI and ML
  • Python for Everyday Tasks

Python for Web Development

Python is great for scalable, reliable, and secure web application development. It is an excellent option and widely preferred due to the frameworks like Django, Flask, and Pyramid. Web application development using Python has become very popular.

Some top applications are built using Mozilla, Reddit, Spotify, etc. Python libraries and modules offered by Python provide database access, data authorization, and content management are easy to access and help in quick web development.

Why use Python for web development?

Python is an amazing programming language that has many use cases. As per the discussion with our senior Python developer, he has used Python primarily to create scripts to build releases and run tests. This has been incredibly helpful in speeding up his workflow and debugging software issues.

Top reasons to use Python for web development

🟠 Open Source
Python is an open-source programming language that offers numerous free frameworks and tools for successful web application development. It allows developers to choose libraries, development tools, and frameworks to reduce the development cost. Product owners can use the top free frameworks such as Flask, Cherrypy, Django, and many others for scalable and quick web application development.

🟠 Strong Standard Library
Python has large and strong standard top libraries that make it different and provide additional features compared to other programming languages. It allows selecting your specific modules according to your demand from the wide variety of standard libraries. Python enables the addition of additional functionalities in the web app from those modules without writing extra code. Python permits product owners to use more information on modules, which are freely available in the documentation of the Python standard library.

🟠 Grab Test-Driven Development
Python helps to develop fast web application prototypes, allowing developers to write codes and test simultaneously with the help of test-driven development process. Product owners can use source code used in web applications to check whether the web application fulfills the predefined product requirements. Python also allows the development of web applications by using prototypes and rewriting the Python code.

🟠 Brings Simplicity To Complex Development
Python is a universal programming language that allows application development for web applications and desktops. Python allows the development of complex numeric and scientific web applications development. It is compatible with designing data visualization and data analysis in web apps.

With this feature, it becomes easier for product owners to target the development of big data solutions without wasting extra time and effort. Compared to other programming languages, it gets complicated to visualize the data interactively. However, it is far easier to work in Python with the help of data visualization APIs and libraries.

🟠 High Readability and Low Code Maintenance
When it comes to Python for software development, it becomes necessary to keep the source code simple and easy to understand to simplify the updates and maintenance. While using Python, the syntax offered by Python is much easier than in other languages as it uses simple English words for the development to improve the readability. The ease of readability and clean code base helps improve, maintain, and update the source code without additional time and effort.

🟠 Multiple Programming Model
We know that Python supports object-oriented programming. However, like other programming languages, it supports various programming features, including aspect-oriented programming and functions. Python has the feature of automation memory management that helps Python in the development of complex and big web application development.

🟠 Convenient To Work With Variety of Platforms
Python is convenient for working with various operating systems and allows Python interpreters to run codes on specific tools and platforms. Python is an interpreted programming language that enables it to run the same code base on various platforms by avoiding recompilation. Developers are not required to recompile the code after making any code base changes. This feature offered by Python saves the web application development time.

Python for Web Development Use Cases

Python use cases for web development include sending data to and from servers, ensuring smooth communication & agile processing, tightening security, and ensuring routing.

Other use cases of Python for web development include:

  • Progressive web apps
  • Integrated animations
  • ML-backed chatbots
  • Asymmetrical layout

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Python for Architectural Design

Another crucial vertical where Python can greatly help is architectural design. Along with automating several manual and repetitive tasks, Python does wonders for architecture. Python is good for creating scripts for 3D modeling software, such as Rhino, Blender, and Autodesk Maya.

Now that you know where Python is used, let’s discuss in detail how Python simplifies architectural processes. These are also known as use cases of Python for architectural design.

🟠 CAD Automation

CAD means computer-aided design, meaning a design generated leveraging computer technology. Along with generation, CAD also helps in tweaking, analyzing, and optimizing the designs. Python developers can automate CAD tasks like building elements, evaluating quality checks, and fetching information through CAD files.

🟠 Optimization

Optimization is another area that Python looks upon when it comes to streamlining architectural tasks. During optimization, considering the environmental factors, Python can greatly help find the perfect location for a building.

🟠 Data Visualization & Analysis

Another use of Python can be for data visualization and analysis, which includes energy usage, environmental factors, and building performance data. Python developers can leverage scripts to fetch information from CAD files or geospatial data to analyze and visualize.

🟠 3D Modeling

When it comes to automating repetitive tasks, Python becomes the first choice. From modeling processes to making designers focus on curating creative designs for you, Python is a leading language and the first choice for any developer. The scripting language also helps generate design variations, curate complex geometrical shapes, and optimize design after deciding the particular criteria.

🟠 GIS Integration

You can trust Python scripting language to integrate geospatial data into designs and spatial analysis into visualization. This programming language shall be used with GIS software like ArcGIS or QGIS.

Python for Scientific & Numeric Computing

Scientific and numeric computing is one of the new-age applications of Python. It helps scientists and researchers. What set of things does Python do for Scientific & Numeric computing are as follows:

  • Leverage Pandas (library) for data analysis and modeling
  • Use SciPy for Mathematics, Engineering, and Science
  • Edit and record work sessions and help in parallel computing through the IPython shell
  • Use FreeCAD and Abaqus by Python

Python for Data Science and Data Analysis

Like Artificial Intelligence and Machine Learning in Python, Data Analytics is one of the most trending and fast-growing industries, heavily depending on Python usage. As the usage and collection of data are increasing rapidly, it is required to use that data and present it in an organized way. Python for Data Analytics and Data Science is very convenient as it provides full support, flexibility, and ease of quickly analyzing the data.

🟠 Python for Scientific Computing
Python is used for scientific research and computing, among other real-world applications, and has many science-friendly or science-specific libraries, such as SciPy and scikit-learn.

These are some use case of PYython for Scientific Computing:

  • Astropy in support of astronomy
  • Biopython is utilized in biology and bioinformatics.
  • Graph-analysis software for graphs
  • For neuroscience and experimental psychology, psychotherapy

Python’s position in data parsing, scripting, and algorithm creation functionality is undoubtedly a major advantage of adopting it. Python is one of the most popular programming languages for dealing with large amounts of data because modules such as pandas and NumPy facilitate data set navigation and data visualization.

🟠 Astropy in support of astronomy
Biopython is utilized in biology and bioinformatics. Graph-analysis software for graphs For neuroscience and experimental psychology, psychotherapy Python’s position in data parsing, scripting, and algorithm creation functionality is undoubtedly a major advantage of adopting it. Python is one of the most popular programming languages for dealing with large amounts of data because modules such as pandas and NumPy facilitate data set navigation and data visualization.

🟠 Python for Data Science
Data scientists and analysts use data science and programming languages like Python and R to alter data for reporting, forecasting, and other purposes. Data scientists don’t have time to squander on difficult syntax or compile their findings. Python for data science is an excellent choice because of its straightforward syntax and wide range of third-party libraries.

🟠 Python ETL
Another suitable use case for Python is integration flows and data transformation. Many ETL tools are out there now, and most of them support Python. One of the widely used tools is AirFlow. It allows you to describe scenarios for receiving, processing, and transmitting data using Python, and also allows you to run Jupyter Notebooks, which greatly simplifies the work of data engineers. In general, Python is a very convenient programming language for working with data that supports scripts, which makes it one of the most requested tools for data engineers

🟠 Data Visualization with Python
Data Visualization in Python is also a trending and developing area, widely used to provide a presentable graphical representation of data. Python helps in providing flexibility and a variety of graphic libraries filled with the latest features to create a visual presentation based on the requirements. Some of the standard libraries offered by Python for Data Visualization are Plotty and Pandas. These libraries transform unorganized data into meaningful insights.

Python For IoT

For IoT, product owners require a programming language that is scalable, strong, and lightweight. Python best suits IoT development as it is highly embedded, expandable, and portable. For the development of IoT systems organizing and managing complex data is mandatory and Python plays an essential role in successful development.

Python in IoT projects generally revolves around real-time processes and analysis. Therefore, it becomes necessary for business owners to choose a language just like Python that is compatible with these types of queries.

When talking about Python use cases for Internet of Things, these are some of the possibilities:

  • Big data & machine learning
  • Wireless sensor networks
  • Data analytics
  • Cyber physical systems

Python For FinTech

Python is the most sought-after programming language for FinTech businesses. Python isn’t only used by FinTech companies. Python’s data processing skills and third-party modules for financial analysis make it a popular choice in the financial sector. Python has been widely used in Fintech Industry as Python offers highly compatible with Analyzing model. Many big giants have used Python for the development of the Fintech platform. The organizations include JP Morgan and Citigroup.

Below are some quite amazing use case of Python for financial sector:

  • Risk analytics
  • Portfolio construction & management
  • Credit scoring
  • Fraud detection
  • Financial analysis
  • Consumer data management
  • Cybersecurity
  • Algorithmic trading

Python For AI and ML

Python is a simple programming language, making it a perfect choice for Artificial Intelligence and Machine Learning projects. Python provides various libraries and packages, making it a preferred choice for Data Scientists. Python for AI offers a standard coding environment that helps fulfill the project requirements. Python for Machine Learning allows you to access, process, and transform your data to improve its predictions, functioning, and user experience.

Python for Automation

Python is good for the field of robotics and automation for various reasons, some of which include:

Robotics Frameworks: Python has a variety of robotics frameworks available, such as ROS (Robot Operating System) and PyRobot, which provide pre-built libraries and tools for robot control, perception, and simulation.
Machine Learning: Python has many libraries for machine learning, such as TensorFlow and PyTorch, which can train robots to perform tasks such as object recognition and grasping.
Control and Automation: Python can control and automate various devices and processes, such as industrial machinery, drones, and home appliances.
Computer Vision: Python has several libraries for computer vision, such as OpenCV, which can enable robots to perceive and understand their environment.
Interoperability: Python’s simplicity and readability make it easy for developers to integrate and interact with other programming languages and technologies.
Rapid prototyping: Python allows for fast and easy prototyping of robotic systems, allowing developers to test and iterate on their designs quickly.

Python for Everyday Tasks

If you still want to explore what is Python used for, then here are the best uses for Python programming in everyday tasks.

1. Automating Tasks with Python: Python’s powerful automation features make it perfect for automating routine tasks like data entry, report generation, and system administration.
2. Python for Desktop App: With libraries like PyQt or wxPython, you can use Python to develop slick desktop applications with all the functionality of traditional Windows apps.
3. Python for Game Development: Python is a great language for game development. It’s easy to learn and supports both 2D and 3D graphics programming.

Top Python Frameworks For App Development in 2024

Python offers a variety of frameworks for web app development. These popular Python frameworks are highly reliable and support successful web application development. Below mentioned are the best Python frameworks for web app development in 2024.

Top Python Frameworks for Web Development


Django is the most preferred and highly used Python web framework. The primary reason behind the usage of Django is its completeness. It provides all the tools in a single package required to develop web applications. If you are looking to develop a product that allows you to omit the initial steps for quick web app development, Django is the right choice! All you need is skilled and experienced Django developers to turn your idea into reality.


In comparison to Django, the working process of Flask is more towards microservices, and that’s the reason behind its popularity. Flask allows combining the other available libraries for scalable web development. One of the key characteristics of Flask is that it adds services and features one at a time to keep the process smooth and clean.


Pyramid is a very stable and mature Python framework highly preferred for project development requiring frequent customization. A pyramid could be a great choice for non-standard and more complex projects. The pyramid framework is so compatible and lightweight that it allows you to develop a framework layout in a single file to have quick app development.


Tornado is a Python web application development framework and an asynchronous library, which FriendFeed initially developed. This framework similarly works to Django, primarily used to improve the speed of web applications. Moreover, it is also capable of handling large web traffic.

Let’s explore why globally renowned brands and most popular companies using Python in 2024.

Popular Tech Companies Using Python


Spotify is one of the biggest and most popular online music streaming platforms. It has started using Python to fulfill the requirements in two main areas: data analysis and back-end services.

As we know, Spotify is popular for the suggestions and recommendations that it provides to its users. To suggest and recommend Spotify requires analyzed data; for that, Spotify uses Luigi, one of the Python modules. Moreover, Spotify’s back-end is all made of various interdependent services directly connected with the messaging protocol developed on Python.


The best example of Python business applications is Odoo. It is a management software written in Python that offers a wide range of business applications taking care of everything from front to back end. Organizations leverage Odoo to build client base & track leads, monitor performance, and provide long-term customer support.


Dropbox is one of the most popular online storage platforms that has received full support from Python. Python has improved the overall experience of Dropbox, including the front-end and back-end. The key reason behind the selection of Python for Dropbox was to have cross-platform development support, ease of learning, and high readability to avoid errors in the development process.


Netflix is another important and popular brand using Python for its product development. In the initial stage, Netflix used Python for analysis and operational management. However, after a while, they started using it for security and networking purposes. I hope you are getting more precise clarity on what Python is used for.


Instagram is one of the most popular social media platforms, with millions of users worldwide. Instagram has chosen the Django framework to have fast and secure development for their product development. The Team of Instagram always chooses technology that is easy to use, scalable, and secure. Therefore, for Instagram, Python remains the core back-end technology of the application.


The biggest social media platform in the world has also used Python for configuration management, production engineering, and service-related tasks. Python is Facebook’s third most popular programming language after C++ and PHP.

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Tryton is an open-source three-tier high level general purpose computer application platform with an enterprise resource planning (ERP) It is suitable for a multiple segments of organizations irrespective of their size. It has its front-end and backend all written in Python language. It possesses an app server aligning with a PostgreSQL database. And, it has a web client client presentation along with a set of server modules that contributing to the business logic.

What is Python used for? - Conclusion

We hope that your purpose of landing on this blogpost what is Python used for, is served with all the solid reasons justifying why to use Python as well as when to use. Using Python libraries, frameworks, and modules, Python can be the best choice for custom web application development. Also, product owners prefer the best Python development company for quick and remarkable development outcomes.

Frequently Asked Questions (FAQs)

Python has various benefits, including easy learning and flexible development procedure. However, the top reasons one should consider before choosing Python are:

  • It offers multiple web development solutions
  • It best suits the top trending domains such as Data Science and AI/ML.
  • It has a strong, active community for constant support.

Python has now become part of every possible industry type. IoT, Game development, Healthcare, Finance, Aerospace, and many others are the list industries that use Python.

DevOps use Python to write automation scripts because the standard library is quite powerful and makes it easier to implement complex logic than Bash scripts.

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