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.

As part of our C++ Tutorials series, here is a tutorial on the tricks of the trade for using C++ I/O.  Keep in mind that an application without I/O is just a black box; no communcation is taking place. 

Tricks and Tips for using C++ I/O

Passbook is one of the newest features of the iPhone. What many people were offput by standards today is that we rely too much on disposable tickets, and the like, such as when you go to the airport for a boarding pass, or a movie ticket. Apple strove to solve that with a new application that is bundled with the newest update: Passbook.

Passbook offers everything you need, especially when a ticket, coupon, or gift card is needed. When you first open the application you are greeted by a sampling of applications that support Passbook, and its features. To begin, install the particular application you want to use. For example, we will be going with the Starbucks application to satiate our coffee needs every morning, as we have a gift card to spend.

Open up the freshly downloaded application, and get ready to be blown away. Like most applications, especially when it has to do with airlines, or coffee, you are almost always required to sign up for a respective account. Don’t worry, it is easy. All you will be asked is to fill out your email, a password, and other miscellaneous information to identify you when you lose your password or others.

Once you have finished signing up, you’re ready to roll. It will prompt you to enter a gift card that you already own, or begin a digital gift card. If you don’t have a gift card, you can start a digital gift card (or, as many may call it: a prepaid card), and pay for your coffee in a fast, and efficient way. Just tap on “Tap to Pay” when you are ready to pay, and tap again after you have paid. It’s really that easy.

Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.