Python programming language is not young, but with Python, there are no limits. Tech giants such as Facebook, Amazon, Instagram, and Uber have used Python to build their mobile and desktop applications. The stack overflow graph of major programming languages’ growth depicts the steady upliftment of the PYTHON.
Stack Overflow can provide a reasonable indicator of trends in programming languages because the site attracts about 40 million visitors a month, of which an estimated 16.8 million visitors are professional developers and university-level students.
Python is a production-based language meant for enterprise and first-class projects, and it has a rich history. It can be used for just about anything, which is why it is considered so versatile. You can build Raspberry Pi applications, scripts for desktop programs and configure servers all via Python, but it is not limited to just those tasks.
There are various attributes of this programming tool which has provided it with an amazing successful journey. Python has a major role in the latest technologies of current and future times like ML and AI. The fact that it is not a complex language is important. Many web designers place less emphasis on conventional syntax, which makes it easier to work with, even for Web Development Company. Because it’s considered truly universal and used to meet various development needs, it’s a language that offers a lot of options to programmers.
Django, for instance, is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Flask is another Python web framework built with a small core and easy-to-extend philosophy. Flask is considered more Pythonic than Django because Flask web application code is in most cases more explicit. Flask is easy to get started with as a beginner because there is little boilerplate code for getting a simple app up and running.
There are many Python tools for analytics and data science such as Scikit-Learn, Theano, etc. which deem it perfect to work in the field of Machine Learning (ML) and Artificial Intelligence (AI). Also, Python is used with big data using tools such as Pandas, PySpark, etc. There are many famous Web Frameworks in Python that can be used according to the project requirements. If the project is complicated with multiple features, it is better to use a full-stack framework.
Programming languages that lack documentation and developer support do not farewell. Python has been around for quite some time, so there is plenty of documentation, guides, tutorials, and more. Plus, the developer community is incredibly active. That means any time someone needs help or support; they can get it promptly.
The 72,000+ libraries in the Python Package Index is a major reason that developers prefer Python for data analysis. Besides, the Python Data Analysis Library, called Pandas, is used to import data and conduct time-series analysis. Python’s extensive open-source community has also created several popular, task-specific libraries.
Working on future technology, AI is dominated by python. It helps in reducing the efforts of the human brain. From speech recognition to data interpretation, python has taken AI to skies of incredible success. Neural networks and machine learning are some of the AI branches which brightens up the python future.
As per the Stack Overflow trend, the industry with the highest amount of Python traffic (by a substantial margin) is the academic world, comprised of schools and universities. Academic researchers make up most of the high traffic to Python from universities. They work round the year. Python is prevalent in many other industrial public sectors as well. It is also the programming language of choice in the electronics and manufacturing industries. The future looks bright for Python.