There are normally two sides to the story when it comes to employment. On one hand, employers hold the view that the right candidate is a hard find; while on the other, job hunters think that it’s a tasking affair to land a decent job out there.

Regardless of which side of the divide you lay, landing good work or workers is a tedious endeavor. For those looking to hire, a single job opening could attract hundreds or thousands of applicants. Sifting through the lot in hope of finding the right fit is no doubt time consuming. Conversely, a job seeker may hold the opinion that he or she is submitting resumes into the big black hole of the Internet, never really anticipating a response, but nevertheless sending them out rather than sit back doing nothing.

A recruitment agency normally keeps an internal database of applicants and resumes for current and future opportunities. They first do a database search to try and identify qualified and screened candidates from their existing crop of talent. Most often the case, they’ll also post open positions online through industry websites and job boards so as to net other possible applicants.

When it comes to IT staffing needs, HR managers even find a more challenging process in their hands. This is because the IT department is one of the most sensitive in any given organization where a single slip-up could be disastrous for the company (think data security, think finances when the IT guys are working in tandem with accounts). You get the picture, right?

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.

As part of our Java Tutorials program, we will list a number of interview questions to aid in a better understaing of Java and J2EE and, hopefully, provide a greater likelihood of getting a job.  Let us begin with the basics:

1. What is meant by J2EE?

J2EE is an abreviation for Java 2 Platform Enterprise Edition

2.  What is the purpose of J2EE?

The purpose of J2EE is to provide a component based platform in a multitier application model with transaction management, web services and reusable component support.

3.  What is the tier structure of the typical J2EE application?

A typical J2EE application consists of the following tiers/machines:  the client machine (browser/non-browser application), the J2EE server (an application server such as Oracle, JBoss, GlassFish, Tomcat) and a database.

To add to a python dictionary is very easy.  First create a dictionary, and then associate a key with a value.

a = {'cat',"furry thing"}
a['dog']="typically likes to run and is very loyal"
print a

Here is what is printed:

{'cat':'furry thing', 'dog':'typically likes to run and is very loyal'}