The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

The importance of variables in any programming language can’t be emphasised enough. Even if you are a novice, the chances are good that you will have been using variables for quite a while now.

They are the cornerstone of any language and without them we would not be able to accomplish much of anything. However, most of you up until this point have probably only been working with standard variables, variables which can hold single values such as an integer, a single character, or a string of text.

In this tutorial we are going to take a look at a more special type of variable called an array. Arrays can seem quite daunting at first glance but once you get used to working with them you will wonder how you ever managed to program without them.

The reason arrays are special is because they can hold more than one value. Think about this: say you create a variable which contains a line of text like the code below:

How Can Managers Work More Efficiently with IT?

Would you rather work under someone who is an excellent developer but lacks people skills or leadership capabilities - or for someone that has excellent people skills, communicates well, and is a great leader but has limited understanding of productive coding practices? That’s not to say that the choice is one or the other but in many professional situations it does.

Managing an IT staff comes with numerous challenges, especially if the manager has no previous experience with the coding necessary for completing the project. Managing a business and IT's execution of tasks vary greatly in required skill sets, but it's important to find a cohesive and cooperative middle ground in order to see a project to its end. To fully grasp the intricacies of IT's involvement in the project at hand, managers can do the following to help further their efforts.

Get a basic understanding of coding and technical practices necessary for the project at hand by taking the time to research and practice enough to get a grip on the concept. This will allow managers insight on what their IT folks are really working on daily. Expertise in a programming language is not required, only an overview of the stuff that matters, i.e. understanding the concept of OOP (Object Oriented Programming.) Having this knowledge cannot be overlooked and will gain respect among multiple spectrums in the organization.

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.