|Application Start Date||Application End Date|
22nd July 2017
23rd July 2017
Organizations of all sizes and industries – from the top financial institutions to the smallest big data start-ups are using Python programming language to run their business.
Python language is among the popular data science programming languages not only with the top big data companies but also with the tech start up crowd. Python language ranks among the top 10 programming languages to learn in 2017.
Python language comes in the former category and is finding increased adoption in numerical computations, machine learning and several data science applications. Python language can do anything, excluding performance dependent and low level stuff. The best bet to use Python programming language is for data analysis and statistical computations. Learning Python programming for web development requires programmers to master various web frameworks like Django that can help the build websites whereas learning Python for data science requires data scientists to learn the usage of regular expressions, get working with the scientific libraries and master the data visualization concepts. With completely different purposes, programmers or professionals who are not knowledgeable about web programming concepts with Python language can easily go ahead and pursue data science in Python programming language without any difficulty.
Python is a 23-year-old powerful expressive dynamic programming language where a programmer can write the code once and execute it without using a separate compiler for the purpose. Python in web development supports various programming paradigms such as structured programming, functional programming and object oriented programming. Python language code can be easily embedded into various existing web application that require a programming interface. However, Python language is a preeminent choice for academic, research and scientific applications which need faster execution and precise mathematical calculations.
Python web programming requires programmers to learn about the various python web development frameworks, which can be intimidating because the documentation available for the python web development frameworks might be somewhat difficult to understand. However, it is undeniable that to develop a dynamic website or a web application using Python language, learning a web framework is essential.
There are several Python web application frameworks available for free like-
Django is the python web development framework for perfectionists with deadlines. Python web development with django is best suited for developing database driven web applications with attractive features like automatic admin interface and a templating system. For web development projects that don’t require extensive features, Django may be an overkill because of its confusing file system and strict directory structure. Some companies that are using python web development with django are The New York Times, Instagram, and Pinterest.
It is a simple and lightweight solution for beginners who want to get started with developing single-page web applications. This framework does not support for validation, data abstraction layer and many other components that various other frameworks include. It is not a full stack framework and is used only in the development of small websites.
It emphasizes on Pythonic conventions so that programmers can build web applications just the way they would do it using object oriented Python programming. CherryPy is the base template for other popular full stack frameworks like TurboBears and Web2py.
There are so many other web frameworks like Pyramid, Bottle, and Pylons etc. but regardless of the fact, whichever web framework a python programmer uses, the challenge is that he/she needs to pay close attention to detailing on the tutorials and documentation