HISTORY OF PYTHON
Python laid its foundation in the late 1980s. The implementation of Python was started in the December 1989 by Guido Van Rossum at CWI in Netherland. In February 1991, van Rossum published the code (labeled version 0.9.0) to alt.sources. In 1994, Python 1.0 was released with new features like: lambda, map, filter, and reduce. Python 2.0 added new features like: list comprehensions, garbage collection system. On December 3, 2008, Python 3.0 (also called “Py3K”) was released. It was designed to rectify fundamental flaw of the language.
Python is influenced by following programming languages:
- Libraries of python are written mostly in Python itself, with some performance critical sections written in C.
- JPython, which is written in Java to run on the JVM.
- Iron Python which is written in C# to run on the .NET CLR
- Stackless Python which is written in C and architected to use thread based parallelism
- PyPy, which is itself recursively written in Python and is a JIT-style native compiler.
WHERE IT IS USED
Python is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. We can develop following types of application by using python language
1) Web and Internet Development
Python offers many choices for web development:
- Frameworks such as Django and
- Micro-frameworks such as Flask and Bottle.
- Advanced content management systems such as Plone and django CMS.
Python’s standard library supports many Internet protocols:
- HTML and XML
- JSON
- E-mail processing.
- Support for FTP,IMAP, and other Internet protocols.
- Easy-to-use socket interface.
2) Desktop GUI Applications
The Tk GUI library is included with most binary distributions of Python.Some toolkits that are usable on several platforms are available separately:
- wxWidgets
- Kivy, for writing multitouch applications.
3) Software Development
It works as a support language and can be used for build control and management, testing etc.
4) Scientific and Numeric Python is widely used in scientific and numeric computing:
- SciPy is a collection of packages for mathematics, science, and engineering.
- Pandas is a data analysis and modeling library.
- IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing.
5)Business Applications Python is used to build Bussiness applications like ERP and e-commerce systems.
6) Audio or Video based Applications Python is awesome to perform multiple tasks and can be used to develop multimedia applications.
7) Enterprise Applications Python can be used to create applications which can be used within an Enterprise or an Organization.
8) Applications for images Using Python several application can be developed for image.
WHY REPL?
- Life time validity (enrolled one time and revise many times)
- Interaction with best faculty and Industry Experts
- Small Batches to focus on each student
- We focus theoretical and practical both parallel because we believe that practical is very important but it depends on theory.
- You will do dummy and also live project.
- Flexible hours available (if you have any problem in timing, you can get daytime, weekends and evening batches)