Facebook has recently released a collection of C++ software modules that it uses to run the popular website.  With Facebook releasing Folly (the name it designated for the collection), more of the internal programs could become open source since they need different parts of the collection.

Jordan DeLong, a Facebook software engineer, said one concerning holdup to releasing additional work is that any open source project had to cut away from the dependencies on non-released internal collection code.

One of the biggest challenges in pursuing a career in software development is to figure out which language you want to work. In addition to commonly used software programming languages like C, C++, Java a lot of new programming languages such as Python, Ruby on Rails have surfaced especially because they are used by a lot of consumer based start-ups these days.

With so many front and back end languages, the choice of learning Java is a failsafe decision and mastering Java can ensure that you have a bright future in software programming.

What is Java

Java is a computer programming language that is designed to be platform independent meaning that the language can virtually run on any hardware platform. This platform independence and an object oriented framework make Java the preferred language of development especially for client-server web applications.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Different programming languages gain popularity for different features.  Java tutorials have proven particular popular over a long period of time, thanks to a diverse group of strengths inherent to the language itself.  Let’s examine some of the basic elements of Java, and find out what it is both powerful and popular:

·         WORA – Write Once Run Anywhere is a programming ideal that has never been effectively achieved.  The goal is to be able to write code a single time, and have it deploy in the same way across multiple platforms.  Although it is still an ideal, proper Java tutorials exist that demonstrate how we are moving closer to success.

·         Object-Oriented – This programming philosophy designates that there is no coding that takes place outside established class definitions.  A large class library is also available right within the core language pack.

·         Compiler plus Interpreter – Once you have written your code, you can compile it into bytecodes which are then fed into a JVM, or Java virtual machine.  You can then follow popular Java tutorials to see how you can extensively debug your code using this functionality.