Top Reasons to Learn ReactJS and Python for Building a Rewarding Career

Jun 4, 2019 by

Why Is ReactJS so Popular?

In this era of online applications that dynamically refresh data without lengthy page reloads, choosing the right framework for front and back ends of an application is essential. ReactJS is a JavaScript library which can be learnt easily for leveraging its potential to build interactive user interfaces (UI). Modular UIs can be created with custom components and library elements of ReactJS. A powerful set of libraries, ReactJS enjoys an edge over others because the codes that you have written for your application can be reused multiple times.

Python: The Multi-Purpose Programming Language

The versatility of Python as a programming language is indisputable. It can be used for building simple or robust scripts, find useful applications in data science, for creating enterprise systems. The design of Python is such that the features help in accurate data analysis and visualization. In fact, Python’s expansive library carries many open-source data analytics tools, web and mobile application development frameworks, and testing mechanisms. The vibrant ecosystem is the largest online.

Why Should You Learn ReactJS and Python?

Knowledge of ReactJS and Python would prove beneficial in adding cutting-edge to your career prospects. Also, from an organizational point of view, employees with functional awareness of these can create dynamic, agile, robust and multi-pronged applications.

Learning ReactJS is useful because of the following reasons.

1) Fast, Simple, and Scalable

ReactJS has a component-based architecture. As a result, you can create websites or apps of all scales easily.

2) Faster Development Time

Components and codes once created can be reused for building other applications. This lessens the development time significantly.

3) Simple to Learn

HTML is introduced to us during school days itself. If you have a fundamental knowledge of JavaScript and HTML, learning ReactJS would not be an issue.

4) Wide Application Across Industry Verticals

ReactJS finds wide application in different domains. Some of the top sites that use this library include Instagram and Facebook. This implies that the community of developers is vibrant and active. You would always find relevant support for your project in online documents or from community members.

5) Numerous Libraries for Application Creation

ReactJS has access to a large number of libraries. You can use any component that may be required to make a web application more useful. With maps, sliders, and other components, you can put in place a fully-functional app in place within a matter of minutes. Using library components becomes easier with package managers like Yarn.

6) Quick Updates in Real Time

Web app users can get a seamless browsing experience due to the usage of virtual DOM by ReactJS. This data cache resides in memory and computes a diff when any component related data is updated. The relevant components are thus updated which means that the website is updated in the blink of an eye. Ability to design such applications would prove beneficial for you.

7) HTML Can Be Used

ReactJS uses JSX (JavaScript XML) language that facilitates scripting in HTML within JavaScript.

All of the aforesaid benefits offered by ReactJS makes it ideal for developing enterprise applications quickly. With react training, you can equip yourself with the tools needed to dynamically code large scale applications with ease. A glance at the graph below would help you gauge the interest about ReactJS among the programming community.


Python: Why You Must Learn It?

Python’s appeal as a frontline programming language can be understood from the fact that it is registering about 27% year-on-year growth followed by R. Both these languages are blazing the trail in Data Analytics and Information Visualization fields. IEEE has ranked Python as No.1 programming language successively for 2017 and 2018.


The advantages of Python from the perspective of Data Science are enumerated below.

1) Numerous Visualization Options

The visualization options in Python are numerous. Different libraries can be developed using Matplotlib visualization package for analysing data, drawing inferences, plotting charts, and building web oriented plots.

2) Highly Scalable

Python is more scalable than R. The outcomes are delivered faster compared to Stata or Matlab. The testimony of Python’s scalability lies in YouTube’s decision to migrate to it. Data scientists from various verticals use Python for building different interactive applications.

3) Programming with Less Coding

Python helps in building codes with the least number of lines. Data types are spontaneously identified and associated. The nesting pattern is based on indentation which makes Python easier to use. Data can be processed with Python driven app in any machine type.

4) Python is Compatible with Hadoop

Python is inherently compatible with the popular big data framework Hadoop. Accessibility to Hadoop’s HDFS API is provided by PyDoop package. You can easily script Hadoop MapReduce programs as well as apps with Python.

5) Easy to Learn

Python can be learnt with ease even if you are not from a programming background. Exhaustive resources for learning the program and excellent community support make Python more attractive.

By subscribing to a Data Science with Python course from a certified learning centre, you can develop command over the trendsetting language that is changing the dynamics of programming and data analytics.

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