Avoid these mistakes while using Python for Big Data

Python – A true friend of web developer: Python is one of those old languages which were developed to give tough competition with C and C++. No need to say, it is highly inspired from the object oriented programming approach of C++ with some enhanced features within it. Due to its similarity with C and C++, it can be used for developing machine programming, mobile application development, desktop application and web application too. Its motto is “Batteries included” indicates its potential to develop huge applications at a very less time due to presence of all necessary and common methods and modules. Hence, Python gets maximum priority from the software developers while developing any big data application. It has the potential to develop big applications in small time with maximum efficiency. At the same time due to its large library, often the web developer miss to use the inbuilt optimized functions which creates trouble in future like performance issue, optimisation issue and synchronization issues. Let us have a quick look over these common mistakes made by the Python developers while dealing with big data projects.

Is the popularity of Python reducing worldwide?

The choice of a programming language is often the result of personal preference and experience. Almost all the modern languages are quite capable of performing most of the major programming tasks as well as include the libraries essential for daily uses. Pyhton is a powerful, easy to use scripting language that is loved as well as hated by programmers across the globe. Although it is powerful but is equally opinionated and idiosyncratic. It is an excellent glue language that is preferred by the Python developers as they find it more productive than others. While there is constant competition from a new and advanced languages, the existence of Python might be threatened. One of the primary reasons why Python is seen as a limited language is because it differs considerably from others.

Django - The web framework for perfectionists

Django a web framework for modern web developers: In the era of web applications, it will be unfair if we don’t discuss about an powerful web development tool of the industry. We are talking about Django!! Last week, one of my friends asked me about Python programming. I told him that, Python is a super powerful language just like Java or in some cases it is better than Java. Moreover, if we compare the inbuilt functions, modules etc then Python is simply unbeatable. Python developers can deveop any complex and huge project with much better efficiency and accuracy that any other language. That time, we discussed about Django which is a Python web framework. Though Python can be used to develop any type of applications starting from web apps, Desktop apps, Mobile Apps etc but, Django is dedicated to web apps only and fortunately it performs outstanding for its cause.

Jython and its Support for Python Programming

The very term, ‘Jython’ itself says that it is some sort of modified avatar of Python. Alternatively speaking, Jython is a successful marriage between two top ranked languages – Java and Python. Therefore, it is understandable that it will have comprehensive support for Python programming. This marriage has resulted in something new along with extraordinary.

Jython, frankly speaking is an extremely powerful language, more so because it comes up with the combined features of Java (J) and Python (P). It is also an Object Oriented Programming Language (OOPS) just like the two. The combination of these two high profile languages makes Jython more efficient and stronger than any of the core languages. Still, for some reason or other, it is not that famous amongst the developers.

Technically speaking, it is the ‘descendant’ of Jpython and is actually a Python Programming language, which is written in Java. Jpython, which is the previous version of Jython was absolutely pure J only in a different form. On the other hand, the language is a combination of J and P. So anyway, Jython has an unblemished support for P, which cannot be ignored. As per the statistics, Python is the first choice of the programmers when it comes to writing code. Especially following its amalgamation with green Java, it has become more effective as well as handy, especially from the perspective of the developers. Therefore, it will be more sensible for the developers to take to Jython, rather than continue with P. In fact, the most fascinating part of this language is that it is capable of importing as well as using any library or a J Class, whenever needed.

It is an open source language. Hence, it is available free of cost for both personal as well as commercial use. Besides, the language takes the advantage of the Java classes, making it one of the most versatile as well as one of the largest libraries of any programming language. Also, it is not entirely Java – besides, is composed of a considerable number of conventional Python modules or classes. It is this combination that makes the language so much effective as well as efficient, particularly when it comes to development of a huge application.

While developing applications with larger volume, it is really a Himalayan task to write the entire code using J, as J coding is more time consuming than any other programming language. That is why it comes in handy in these circumstances by making things much easier as well as faster. It is seen that whenever an application is developed at a brisk pace, the quality has to be compromised with. It scores on this front as well, for though it speeds up the development process, it never compromises with the quality. Hence, it can well be said that Jython is the perfect option when it comes to developing application faster with security as well as accuracy.

Coming back to Jython and its support for P programming, the language compiles source code to the Byte code of Java as an intermediate script from the statistical point of view and hence, it can run on the JVM.

Also, it provides an effective platform for communicating with Java with Javascript, a process which is extremely easy as well as effective. It also permits rapid prototyping, a fact that makes code writing process backed by its unconditional support for P, much faster. The support for P indicates any developer, who is working with P or J can without any hassle seamlessly transform to Jython. Also, the fact that it is extremely well designed, and is structured with neat and clean syntax makes their job easier. In fact, the developers coming in from Python or Java environment will feel as if they are in the same environment.

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Why is Python preferred over other languages?

Large number of software engineers, business owners, as well as the users choose Python rather than some other programming languages. Python is a general purpose interpretative, user friendly, object oriented and high-ranking programming language which was designed by Guido Van Rossum in the year 1991. It is actually created from a number of other languages, such as ABC, Modula-3, C, C++, SmallTalk, Algol-68, and UNIX shell along with other scripting languages. In a short time frame, Python has drawn interest of several developers. Google, YouTube, Facebook (PHP & Python), Reddit (Pylon), FriendFeed, SuggestionBox (Django), Tabblo (Django), Disqus, Bitbucket (Django), and Quora are among the well known websites which are with the Python programming language. A lot of companies are offering Python Development Services at a very affordable price to the people who run businesses to obtain the entire advantages of Python. With the help of these facilities, businessmen can produce their own website in a very professional and rich way.

Jython - Things to know about

Jython, an open source, implements the Python programming language that is integrated with the Java platform. To run this object-oriented and dynamic language a programmer has to compile Python source code with Java bytecode. When a programmer integrates Python and Java, it gives him an access to all the Java libraries. By using the libraries, Applets and JavaBeans can be used by assigning the classes of any of these languages as sub-classes under the other. Jython is written in Java and seamlessly integrates Python so that it can run on any Java platform. It has been designed to perform various kinds of tasks, like, embedded scripting. Its original version was known as JPython in 1997. Jython 2.0 is a later version that has been developed through a combined volunteer effort and it is available without any cost for both non-commercial and commercial uses.

History of Python - Versions, Features, and Upgrades

Python is a hugely popular general-purpose as well as high-end programming language that is based on code readability. The syntax of Python provides the programmers the unique option of expressing concepts by writing new codes that are better than what is needed in case of other languages like C or C++. The language helps in creating constructs that are designed to develop clearer programs on a large scale as well as a small scale.

It can well be termed as an interpreted, high level, object oriented programming language, that comes up with a series of dynamic semantics. The high end data structures, that are combined with dynamic binding as we’ll as typing, make the language so lucrative, especially when it comes to RAD or Rapid Application Development or using the language for scripting or as a glue language for connecting the existing components with each other. It is simple and its syntaxes are all extremely easy to learn. They put more focus on readability. Hence, they come in handy in reducing the expenses of maintaining the program. The language also supports modules as well as packages. This encourages program modularity as well as reuse of codes. The interpreter and its extensive customary library are present in source as well as in the binary form and they are freely distributable.

Python is designed to support multiple programming models that include object-oriented, functional, as well as imperative programming patterns. It also comes up with automatic as well as system memory management along with a comprehensive standardized library.

Python is generally used for scripting for web based apps and for facilitating these apps, a standard API has been designed with WSGI or Web Server Gateway Interface. Various web app frameworks such as Pylons, TurboGears, Tornado, Zone, Flask, and the likes, support the developers when it comes to designing or maintaining the complex applications, while IronPython and Pyjamas are used for developing the client side of the Ajax-based apps.

Like any other dynamic programming language, Python can be used for scripting though it is also possible to use it as a non-scripting language. The codescan can also be used as a standalone program, especially with the use of certain third party tools like Py2exe and Pyinstaller.

Python, technically speaking can be termed as a multi-paradigm language that is used for structured, aspect-oriented, as well as object-oriented programming. It uses dynamic typing technique along with a combination of cycle-detecting garbage collector and reference counting for the purpose of memory management. Another very significant feature of Python is its dynamic name resolution mechanism that binds method as well as the variable names when executing a particular program.

Python saw the daylight for the first time towards the end of 1980, while the implementation commenced from the month of December, 1989 and was considered as a successor to ABC programming language.

Python 2.0 was ultimately released on October 2000. This version came up with a number of fresh features that also included a full garbage collector along with Unicode support. However, the most significant feature that this particular version came up with was the development mechanism that was followed. It involved a major tilt towards a process that was more transparent as well as community-backed.

The next version, P 3.0 was released in December, 2008 and this version came up with a lot of features that have been back ported to the 2.6 and 2.7 versions.

Then came the next version, P3.0, which is also called Py3K or Python 3000, which was designed and developed for rectification of the fundamental designing loopholes that were earlier detected in the language.

The language has successfully been embedded in quite a number of products like Abaqus alongside a few 3D animation languages like Max, Cinema 4D, Houdini, Maya, etc.

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