Monday, 20 March 2017

Features of Hadoop

What Is Hadoop?
Hadoop is the framework which allows the distributed processing of large data sets across the clusters of commodity computers using a simple programming model. It also has the ability to store and analyze the data occurred in different machines at different locations quickly with effective cost and uses MapReduce concept which divide the query. Unstructured data such as log files, Twitter feeds, media files, and data from the internet are more relevant to the businesses. Regularly, there was a large amount of unstructured data that is being dumped into our machines. The main challenge is to retrieve and analyze this big data in the organizations instead of storing the large data sets.
Key Features of Hadoop
Due to its power of distributed processing, Hadoop would handle large volumes of structured and unstructured data more efficiently than the traditional enterprise data warehouse. Hadoop is open source and therefore, it also run on commodity hardware.

Wednesday, 15 March 2017

Interesting Things About Python

Introduction to Python
Python is one of the scripting language programs and which supports many open source language. 90% of peoples are using python for web development because it is easy and reliable to use. As a result of many open source techniques python helps to build application at faster and efficient manner
Uses of python
Python is widely used to develop various applications and it can support various OS like windows, UNIX, Linux… Many companies like Google, Yahoo, and Bing are using python
Feature of python
  • The main feature of python is that the codes are being written in c, c++ and it has readable syntax.
  • It has dynamic syntax.
  • Sound introspection capabilities.
  • Python also supports various integration techniques.
  • Python is an user friendly application.
  • It has less code than java.

Friday, 10 March 2017

Brief Overview Of Python


Welcome! Are you completely new to programming? If not then we presume that you will be looking for information about why and how to get started with python. Fortunately you are a fresher or experienced programmer in any programming language would pick up Python very quickly. It’s easy for beginners use and learn, so jump in! Join Python Training in Chennai at Besant Technologies to Learn from here and finally remove ‘L’ from it!

About Python

Python is the world’s most popular and versatile programming language has advanced data structure and effective object oriented programming concept that has been used in large companies such as Google, Yahoo, CERN and also in NASA. Python provides constructs which intended to enable clear programs on both small as well as large scale.

Monday, 6 March 2017

12 Reasons to Learn Python Programming

You will grasp that easily
It is always a difficult task to learn a new language, but this is not with Python. Python is designed to be easily grasped by a novice programmer. The python codes are easily readable by the developer who has little bit knowledge about codes. The standard library opens a lot of functionalities which will help you execute complex functionalities without any problem.
You will get many opportunities
Yes, you will be able to peek out through the window of programming through python. Python has a different object oriented approach which is preferred by a lot of the leading languages like Ruby, JavaScript, C#, etc.
First choice for Web Development
Python has an array of frameworks which provides a lot of flexibility in case of web development with python. There are many web frameworks offered by python like TurboGears, Pylons, Zope2, etc.

Wednesday, 1 March 2017

Goals and Architecture Overview of Python

The main is to provide a compliant, flexible and fast implementation of the Python Language which uses the RPython tool chain to enable new advanced high-level features without having to encode the low-level details. This is called as PyPy.

High Level Goals
Our main motivation to develop the translation framework that provides a full featured, customizable, fast and very compliant Python implementation, working on and interacting with a large variety of platforms and allowing the quick introduction of new advanced language features.
This Python implementation is written in RPython as a relatively simple interpreter, in some respects, it is easier to understand than CPython, that is C reference implementation of Python. Using its high level flexibility to quickly experiment the features or implementation techniques in a traditional approach, require pervasive changes to the source code.
For example, PyPy’s Python interpreter provides a lazily computed object which is a small extension that would require global changes in CPython.
Another example is the garbage collection technique: changing CPython to use a garbage collector not based on reference counting, whereas in PyPy it’s an issue localized in the translation framework which is fully orthogonal to the interpreter source code.
PyPy Python Interpreter
PyPy’s Python Interpreter is written in RPython that implements the full Python language. This interpreter very closely emulates the behavior of CPython and contains the following key components:
Bytecode Compiler - This is responsible for producing the Python code objects from the source code of a user application. The bytecode compiler is the preprocessing phase which produces a compact bytecode format via a chain of flexible passes (tokenizer, lexer, parser, abstract syntax tree builder, bytecode generator).
Bytecode Evaluator – It’s responsible for interpreting the Python code objects. The bytecode evaluator interprets this bytecode. It does most of its work by delegating all actual manipulations of user objects to the object space. The latter can be thought of as the library of built-in types. It defines the implementation of the user objects, like integers and lists, as well as the operations between them, like addition or truth-value-testing.
Standard Object Space – This is responsible for creating and manipulating the Python objects that are seen by the application. The division between bytecode evaluator and object space gives a lot of flexibility. One can plug in different object spaces to get different or enriched behaviour of the Python object.

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