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.

IT jobs are without a doubt some of the highest paying jobs with information architects, data-security analysts and UX designers taking home $100,000 or more a year. But then again, these are high demand; high expertise jobs so don’t jump with joy as yet. But like every job and IT industry to be specific, not everyone commands such higher salaries. There are a large number of IT professionals who at some point of their career feel that their salaries have hit a standstill. Even if you are an IT professional and a great one at that, your technical expertise alone may not help you exceed the IT earning barrier. To continuously exceed your salaries, you need to work hard and smart. Here is how you can exceed the earning barrier in IT.

·         Gain Business Knowledge and Move Up The Management Ladder: IT departments for the most part are considered a part of “back office” operations. What this means is that despite being a core part of the business, IT professionals do not often get enough say in revenue generating components of the business and as a result seldom have a chance to take up senior management roles.  So if you do not want to stay content with a project manager or senior project management salary, invest time and money in gaining business knowledge. It could be through a formal business degree, online training courses or just by keeping your eyes and ears open while in the organization. Having the technical experience with business knowledge will instantly make you stand apart and open the doors for you to draw senior management salaries. For example, a survey conducted highlighted that CIOs were the biggest salary winners which clearly demonstrates the value of technical and business knowledge

·         Gain expertise on the “Hot” Technologies and Keep Learning: Say you are an expert in Java and draw a respectable salary in the industry. However, someone with less years of experience than you joins the organization and draws a higher salary than you! Why you ask. It could very well be because he/she is an expert in say big data technology such as Hadoop. Information Technology is one of the most dynamic industries with new technologies and languages coming up every now and then. When a new technology comes to the foray and gains traction, there is an instant demand-supply gap created which means that those with the specific skill sets are in a position to demand high salaries. If you have to break the IT earning barrier, always be ready to reinvent yourself by learning new technologies and this way you will be well positioned to jump on the high paying opportunities in the IT industry

·         Work On Your Own Side Projects: This one might seem controversial but let me clarify that I do not mean doing freelance work because even though your organization may never find out, it is ethically in breach of contract with your contract. If you have been lucky enough to be trained in some web based technologies such as Java, .NET or even HTML etc. spare sometime after office to build your own side projects. They could be very small projects tackling some problem that only you might have but there are multiple benefits of developing side projects. Worst case scenario, you will improve your technical skills. On the up side, you might end up creating your own business. A lot of technology start-ups were actually side projects the founders tinkered on with while they were employed full-time. You may not always succeed but there is no downside to the same

Jeff Nelson, a former Googler and inventor of Chromebook says on Quora, “One habit I've clung to is writing small prototypes when I'm trying to learn new concepts.
For example, I'll sit down with a book or a web page, and over the course of a few hours, write 30 or 40 programs all of them only a few dozen lines long.  Each program intended to demonstrate some simple concept. This prototyping makes it very easy to try out many concepts in a short period of time.”

Miguel Paraz, Software Engineering Student habit is to “keep a log in a text file or document on my work computer. Before trying to solve a problem, I write it down first. And then I describe the details as they happen.”

F# is excellent for specialties such as scientific computing and data analysis. It is an excellent choice for enterprise development as well. There are a few great reasons why you should consider using F# for your next project.

Concise

F# is not cluttered up with coding noise;  no pesky semicolons, curly brackets, and so on. You almost never have to specify the kind of object you're referencing because of its powerful type inference system. It usually takes fewer lines of code to solve the same issue.

Convenient

Common programming tasks are much easier in F#. These include generating and using state machines, comparison and equality, list processing, as well as complex type definitions. It is very easy to generate powerful and reusable code because functions are first class objects. This is done by creating functions that have other functions as parameters or that combine existing functions to generate a new functionality.

Correctness

F# has a strong type system, and, therefore, prevents many common errors such as null reference exceptions. Valuables are immutable by default which, too, prevents a huge class of errors. You can also encode business logic by utilizing the type system. When done correctly, it is impossible to mix up units of measure or to write incorrect code thereby decresing the need of unit tests.

Concurrency

F# has number of built-in libraries. These libraries help when more than one thing at a time is occurring. Parallelism and asynchronous programming are very simple. There is also a built-in actor model as well as excellent support for event handling and functional reactive programming. Sharing state and avoiding locks are much easier because data structures are immutable by default.

Completeness

F# also supports other styles that are not 100 percent pure. This makes it easier to interact with the non-pure world of databases, websites, other applications, and so on. It is actually designed as a hybrid functional/OO language. F# is also part of the .NET ecosystem. This gives you seamless access to all the third party .NET tools and libraries. It operates on most platforms. These platforms include Linux and smartphones via mono. Visual Studio is integrates with F# as well. This means you get many plug-ins for unit tests, a debugger, a IDE with IntelliSense support, other development tasks. You can use MonoDevelop IDE on Linux.

Related:

F# - Marching Towards Top 10 Programming Languages

What Are the Advantages of Python Over Ruby?

Top 10 Programming Languages Expected To Be In Demand in 2014