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.

I remember the day like it was yesterday. Pac Man had finally arrived on the Atari 2600.  It was a clear and sunny day, but it was slightly brisk. My dad drove us down to the video store about three miles from our Michigan house. If I remember correctly, the price for the game was $24.99.  It was quite expensive for the day, probably equaling a $70 game in today’s market, but it was mine. There *was* no question about it. If you purchase a game, it’s your game… right?

You couldn’t be more wrong.  With all the licensing agreements in games today, you only purchase the right to play it. You don’t actually “own” the game. 

Today, game designers want total control over the money that comes in for a game. They add in clauses that keep the game from being resold, rented, borrowed, copied, etc. All of the content in the game, including the items you find that are specifically for you, are owned by the software developer. Why, you ask, do they do this? It’s all about the money.

This need for greed started years ago, when people started modifying current games on the market. One of the first games like this was Doom. There were so many third part mods made, but because of licensing agreement, none of these versions were available for resale. The end user, or you, had to purchase Doom before they could even install the mod.  None of these “modders” were allowed to make any money off their creation.

One of the most recent updates to the iPhone, and more specifically the operating system that is packaged with the iPhone, iOS, brought one of the most fantastic and phenomenal updates ever: an update to Maps. Maps has been used as an application that provides an easy way to find routes, and (obviously) maps about certain areas, businesses in the local vicinity, and also leaving pins on favorited locations, or pins where you have explored, and for many other reasons. However, although Maps has always been a great way to travel with, it has always been redundant to travel with, also. When you used Maps a while ago, you had to route your map, and then manually click each next button as you reached each turn or freeway exit, and the like. So, if you had to turn left on a certain street, you had to tell your phone you had done so, so it would give you the next directions. As a result, it could become very dangerous to always have your phone out, looking at it, while you are on a high-speed freeway. But, the newest update solved that, and brought a great amount of new features.

Using Maps GPS

Using Maps is as easy as it gets. Most of the time, when you are using Maps, you are using it to search for a location, and finding a way to get there. To start off, let’s search for the nearest mall, and routes to get there. Simply search a nearby mall you know about, or search the general word “mall” by tapping on the top text box, and typing in mall, and searching. Pins will drop down on the screen, and locating the mall by zooming into certain streets and locations will help you find the mall you want. Once you find the mall you desire to go to, click on the blue arrow, and scroll down, and tap on the button that says “Directions To Here.”

As a result of tapping on that particular button, a new window should show up asking where your starting location is. On default, this location is your current location; if it is anything else, simply type in the starting location into the top address bar, such as your house. Once you are ready to go, tap on route, and you should be ready to go. Well, not exactly. One of the best features that has been implemented in the new system is suggested routes, and alternative routes. If you don’t like to drive on certain streets, or roads, the system provides you with different methods to get to your destination, which may avoid a road you don’t feel like driving on that certain day, or time, or you simply don’t want to take the freeway. It’s all okay, as Maps provides you with many different routes to take. Once you find the route you want (by tapping on the certain route’s outline), click start, and you should be ready to go. Make sure you turn up your volume so you can hear the directions!

Maps for Alternative Transportation

Millions of people experienced the frustration and failures of the Obamacare website when it first launched. Because the code for the back end is not open source, the exact technicalities of the initial failings are tricky to determine. Many curious programmers and web designers have had time to examine the open source coding on the front end, however, leading to reasonable conclusions about the nature of the overall difficulties.

Lack of End to End Collaboration
The website was developed with multiple contractors for the front-end and back-end functions. The site also needed to be integrated with insurance companies, IRS servers, Homeland Security servers, and the Department of Veterans Affairs, all of whom had their own legacy systems. The large number of parties involved and the complex nature of the various components naturally complicated the testing and integration of each portion of the project.

The errors displayed, and occasionally the lack thereof, indicated an absence of coordination between the parties developing the separate components. A failed sign up attempt, for instance, often resulted in a page that displayed the header but had no content or failure message. A look at end user requests revealed that the database was unavailable. Clearly, the coding for the front end did not include errors for failures on the back end.

Bloat and the Abundance of Minor Issues
Obviously, numerous bugs were also an issue. The system required users to create passwords that included numbers, for example, but failed to disclose that on the form and in subsequent failure messages, leaving users baffled. In another issue, one of the pages intended to ask users to please wait or call instead, but the message and the phone information were accidentally commented out in the code.

While the front-end design has been cleared of blame for the most serious failures, bloat in the code did contribute to the early difficulties users experienced. The site design was heavy with Javascript and CSS files, and it was peppered with small coding errors that became particularly troublesome when users faced bottlenecks in traffic. Frequent typos throughout the code proved to be an additional embarrassment and were another indication of a troubled development process.

NoSQL Database
The NoSQL database is intended to allow for scalability and flexibility in the architecture of projects that will use it. This made NoSQL a logical choice for the health insurance exchange website. The newness of the technology, however, means personnel with expertise can be elusive. Database-related missteps were more likely the result of a lack of experienced administrators than with the technology itself. The choice of the NoSQL database was thus another complication in the development, but did not itself cause the failures.

Another factor of consequence is that the website was built with both agile and waterfall methodology elements. With agile methods for the front end and the waterfall methodology for the back end, streamlining was naturally going to suffer further difficulties. The disparate contractors, varied methods of software development, and an unrealistically short project time line all contributed to the coding failures of the website.