In this tutorial we are going to take a look at how you work with strings in Python. Now, any language worth its salt will have a number of options for working with text and Python is probably one of the best to use when it comes to processing text.

If you are new to programming in general you may be wondering what a string is. In terms of programming, a string is classed as any sequence of characters you can type with your keyboard, and let’s face it, if you want your application to be of any use to yourself or other users then you need it to tell you what it’s doing or to prompt you for an action, and that is where strings come into play.

They are your applications way of communicating with the user. Without the ability to enter and display text or software would be pretty useless.

So, how would you create a string in Python? Take a look at the following code:

Structure Rule Language

To aid in the ease of rule authoring, Blaze Software, now Fair Isaac, created the proprietary Structure Rule Language (SRL), an object-oriented programming language designed to enable those with little or no background in software development to pen rules. Although the capabilities of this language are far too extensive to detail in this article, we can examine the basic rule syntax.

Rules in the SRL take the following form:

rule RuleName [at | priority M] is

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.

The short answer is, yes and no. It depends upon who you are. The purpose of this entry is to help you determine, yes or no.

Full disclosure. This entry is created on a Mac mini. And doing so on Windows 8 (Release Preview). If you are a developer, in my humble opinion you need to test on all platforms you expect your app to run or you are not much of a developer.

To be successful you need to leave politics in geographical territory known as Washington DC. My definition of that is: 14 mi.² of real estate surrounded by reality.

Only in politics can we afford to take sides. Those of us in IT, especially developers need to do our best to be all things to all people. Certainly this is a technical impossibility. However in our game we can get some points for at least being serviceable if not outstanding.