Why is Python Growing so Quickly? | Future Trends

May 12
18:44

2021

Shardul Bhatt

Shardul Bhatt

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Python is becoming the top choice for companies all over the world. Here’s why Python software development is growing so quickly in 2021.

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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,Why is Python Growing so Quickly? | Future Trends Articles 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.

Read more: A Definitive Python Development Guide Pros and Cons of Python

Growth Patterns in Python App Development Growth by Visitor tags

The growth patterns in Python app development companies can also be classified by user category. As per the Stack Overflow trends, the following is the influence of each type on Python’s growth:

  • Data Scientists: The most visited tags by data scientists were Pandas, NumPy, or Matplotib.
  • Web developer: The most visited tags among Python web developers were JavaScript, Django, HTML.
  • System administrators/DevOps Engineers: The top visited tags were Linux, Bash, or Windows.
Growth by Industry

Another way to study the growth in Python language is by checking the industries and companies it is used by.

Taking into consideration the two countries for Python development as the United States and United Kingdoms, the following are the growth patterns:

  • More than 20% of the academic industry traffic is redirected towards Python development services. The reason for this is the teaching of Python as a leading programming language in colleges and universities.
  • Python is widespread and rapidly growing in the government sector, majorly for Python migration services and data security.
  • Government, manufacturing, and technology - all three industries have around 10-12% of traffic dedicated to Python app development.
  • With the latest digital transformation wave, healthcare, finance, insurance, and consulting industries have seen a spike in Python development services.

Python benefits in Healthcare: Checkout How it helps

Python Development: Future Trends 2021

With Python, we are talking about one of the most demanded programming languages in the world. The year of pandemic crisis, 2020, observed around 50% growth in Python web development across industries.

We can vouch that Python is the language for now and for the years to come. The prospective growth domains for Python are as follows:

  • Big Data Trends:
    • Being the most adaptable and chosen language among developers and an open-source framework, many sectors will benefit from its real-time facts analysis.
    • Speech processing, data synthesis, and machine learning are other attributes that promise the growth of Python in the future of Big Data.
  • Game Development:
    • The vivid network of libraries and built-ins/plug-ins make Python an easily understandable concept among game developers and programmers.
    • It is used as the ideal language to create fictional scenarios, characters, and plotlines on top of the unique C/C++ graphic and gaming engines.
    • It’s foreseen that Python will have more leverage in the gaming sector in 2021.
  • Machine Learning:
    • The flexible and highly versatile nature of Python app development makes it the most suitable language forMachine Learning projects. The same features also enable it to cater to the dynamic needs of Artificial Intelligence projects.
    • Python-based networks of libraries like SciKit, NumPy, and TensorFlow help build data processing pipelines, implement machine learning algorithms and visualization to enhance the development lifecycle.
  • Business Applications:
    • Business/Enterprise Applications demand high scalability and quality, which Python best delivers. Many domains like ERP, e-commerce, recruiting, and more have an upward growth curve for Python software development.
    • Python also offers libraries like Tryton, which provide a space for successful application development.
  • Embedded Applications:
    • In the current scenario, C remains the leader for embedded computing, but Python is rapidly growing. It is predicted that Python will take over this domain of embedded development.
    • Python is equipped to program cameras, microcontrollers, face recognition, etc., to build state-of-the-art solutions.
    • On top of this, Python’s extensive community and frameworks will make it easy for the developers to shift from C to Python shortly.

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