Python has various applications ranging from Python for web development to data science to system administration and DevOps.
The fastest-growing Python-related tag is Pandas, responsible for academic research, data science, and machine learning.
Python is evenly growing across all industries, predominantly in manufacturing, software, government, and universities.
The fastest-growing application of Python is visible in data science, Machine Learning, and academic research.
Many organizations have adopted these technologies for business development and growth, making Python their programming language of choice.
The different frameworks of Python support the various applications. For example, Django and Flask are used for web andapplication development with Python.
On the other hand, NumPy and Pandas are used for data science packages.
Checkout 10 real-world Python Use Cases and Applications
Why is Python Growing so Quickly?
Python development services are booming in the digital landscape, majorly because of their versatility, robust features, and simple syntax.
1. Vast Library and Framework Support
Dedicated Python developers have access to libraries with many tried and tested modules. This allows them to be able to develop software faster and in a cost-effective manner.
As a result, the cost of development is also effectively reduced.
Some popular libraries that support Python are:
- Tensorflow: Released by Google, TensorFlow allows developers to keep Deep Learning functionalities, including image detection, face recognition, and others.
- Pandas: It is involved with high-performance data structure management and will enable developers to use analysis models.
- Scikit Learn: It is used for data mining, Machine Learning, and data analysis in Python web application development.
- Keras: It is used as a Machine Learning guidance for Python app development.
- Numpy: It provides support in scientific and mathematical computing to developers.
Some popular frameworks that Python supports are:
- Django: It is an efficient and secure framework for complex application development. It allows developers to build customizable apps with the benefits of Python.
- Pyramid: As the name suggests, this framework allows developers to scale their applications as the project grows.
- Tornado: It is a non-blocking network library that scales up to thousands of open connections and makes it the best-suited alternative for long polling.
- Flask: This is a microframework that allows developers to build small and flexible applications with reduced effort and time.
2. Easy to decipher and learn
Python contributes to building superior quality applications in less time than any other software in the market. The simple reason behind it is the easily understandable language and clean syntax that Python offers.
It allows developers to detect and debug the codes written by other developers and data engineers as it has a close resemblance to English.
Time saved is money saved with Python software development. It also reduces the time to launch applications into the market.
Several applications, including scientific computations, AI, data science, and Machine Learning, use Python because of its lean learning curve.
3. Open Source Environment
Python has a robust environment that is most suitable for enterprise development.
All latest versions of Python are affiliated with the Open Source Initiative, which ensures all benefits of Python to its developers without a subscription fee.
Its open-source environment includes a wide range of frameworks and libraries like Django, Pyramid, Pandas, Numpy, etc.
Python development companies can benefit from the range of free tools that the software ensures.
They can also work on Graphic User Interfaces, web development, app development, image analysis, game development, data science, and AI, etc.
