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.

The python keyword global is used in a function to distinguish a local representation of a variable with the same name. 

glbvar = 0

def setglbvar():
    global glbvar # include this declaration so that updates to glbvar are NOT LOCAL to this function
    glbvar = 1

def printglbvar():
    print glbvar     # No need for global declaration to read value of globvar

setglbvar()
printglbvar()       # Prints 1

In this tutorial I am going to give you a gentle introduction to network programming in Python. If you are new to programming or new to Python then that may seem like a daunting thought. But read on and you will be pleasantly surprised how easy it is.

Like most modern programming languages, Python was designed for networking from the very beginning, and thanks to that, a lot of the networking tasks you would want to accomplish with the language are made a whole lot easier.

Network communication is a large topic, but if it is something that interests you then read on because in this tutorial I will show you how to download a web page. I will show you how easy Python makes tasks like this.

Take a look at the following code:

import urllib
	
con = urllib.urlopen("http://hartmannsoftware.com")
page = con.read()
con.close()
print page

Java still has its place in the world of software development, but is it quickly becoming obsolete by the more dynamically enabled Python programming language? The issue is hotly contested by both sides of the debate. Java experts point out that Java is still being developed with more programmer friendly updates. Python users swear that Java can take up to ten times longer to develop. Managers that need to make the best decision for a company need concrete information so that an informed and rational decision can be made.

First, Java is a static typed language while Python is dynamically typed. Static typed languages require that each variable name must be tied to both a type and an object. Dynamically typed languages only require that a variable name only gets bound to an object. Immediately, this puts Python ahead of the game in terms of productivity since a static typed language requires several elements and can make errors in coding more likely.

Python uses a concise language while Java uses verbose language. Concise language, as the name suggests, gets straight to the point without extra words. Removing additional syntax can greatly reduce the amount of time required to program.  A simple call in Java, such as the ever notorious "Hello, World" requires three several lines of coding while Python requires a single sentence. Java requires the use of checked exceptions. If the exceptions are not caught or thrown out then the code fails to compile. In terms of language, Python certainly has surpassed Java in terms of brevity.

Additionally, while Java's string handling capabilities have improved they haven't yet matched the sophistication of Python's. Web applications rely upon fast load times and extraneous code can increase user wait time. Python optimizes code in ways that Java doesn't, and this can make Python a more efficient language. However, Java does run faster than Python and this can be a significant advantage for programmers using Java. When you factor in the need for a compiler for Java applications the speed factor cancels itself out leaving Python and Java at an impasse.

While a programmer will continue to argue for the language that makes it easiest based on the programmer's current level of knowledge, new software compiled with Python takes less time and provides a simplified coding language that reduces the chance for errors. When things go right, Java works well and there are no problems. However, when errors get introduced into the code, it can become extremely time consuming to locate and correct those errors. Python generally uses less code to begin with and makes it easier and more efficient to work with.

Ultimately, both languages have their own strengths and weaknesses. For creating simple applications, Python provides a simpler and more effective application. Larger applications can benefit from Java and the verbosity of the code actually makes it more compatible with future versions. Python code has been known to break with new releases. Ultimately, Python works best as a type of connecting language to conduct quick and dirty work that would be too intensive when using Java alone. In this sense, Java is a low-level implementation language. While both languages are continuing to develop, it's unlikely that one language will surpass the other for all programming needs in the near future.