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.

If you’re interested in building modern websites or applications which use ASP, XML, or mobile technology, you’ve heard of Visual Studio .NET.  It is one of the more popular suites of development tools available to aspiring programmers, as it consolidates several different tools and languages into the same development environment, which helps in turn to integrate this code across development languages.  Here are three important benefits to using the visual studio suite:

·         Use of Visual J# - This development tool is specifically oriented towards people who already are familiar with basic Java syntax, and is designed for use by those people to build apps or services which will then run on the Microsoft .NET Framework.  This is useful because it fully supports Microsoft Extensions, among other reasons.  Visual J# was developed completely independently by Microsoft.

·         Utility for Smart Devices – Another huge benefit of using visual studio .NET is the ability to immediately integrate your programming efforts with deployment across a variety of smart devices.  PDAs, smartphones, Pocket PCs, and any device which has a limited amount of resources all require a compact framework for the programming of applications it is designed to run.

·         XML Web Usage and Support – Because XML services aren’t married to any particular technology or programming language, they can be accessed by any system, and this broad-based utility has made the services increasingly popular.  Visual Studio .NET takes advantage of this by fully integrating with XML services, including the ability to create and edit them from scratch.

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

Unless you have a great product, service or idea for which people are willing to wait, chances are highly likely that these potential clients will leave your website should your response time take too long to their incoming requests.  Ignore your application’s performance and you are more likely to be dumped by your users sooner than expected.

To improve the performance of an ASP.Net application you need to optimize your front-end UI (user interface) code as well as the back-end database. You can also think of the following tips as a brief best practices guide for the ASP.net performance optimization. So, whether you are a developer, UI designer or member of the deployment team, the following tips may help you. No matter what’s your role in the project or what you do to boost performance of your application, always remember that your goal should be to:

·          Minimize the amount of data you sent across the network.

·          Reduce the number of server requests.

Here you go (in no particular order)

At Database level