Sometimes we have to repeat ourselves before we are heard. Then again there are times where we have to perform a certain action the same way several times before we can carry on with what we want to do.

Repetition is the keyword here and for humans that is something we generally try to avoid. Yet our digital friends love repetition. They never get tired and they never get bored of doing the same thing over and over again countless times.

So it’s little wonder then that all modern programming languages give us various ways in which we can perform a certain action as many times as we need.

In python we have the for statement which gives us the power to loop over large collections of data very quickly and efficiently.

F#, which is usually pronounced as F sharp is one of the newly launched and rapidly developing programming languages.  It has recently become focus of attention due to its quick advancement to the 12^th position in the recent TIOBE index and the overall rise in popularity.

What is F#?

F# is an open source, functional and object oriented programming language which is available in cross platform. It was developed by a company called F# software foundation with help of Microsoft and other open contributors. F# runs on Linux, windows, iOS, Android and the GPUs and HTML as well. It is a mature programming language which helps the users as well as the organizations to solve the complex problems in a much simpler way with easy code. With its wide range of usage in the specialist and application areas, it is proving itself to be a worthy contender for the top 10 list.

Why choose F#?

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.

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.