Python is an interpretive, high-level, and general-purpose programming language. Created by Guido van Rossum and first published in 1991, Python is dynamically typed and garbage-collected.
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Python programming language is an object-oriented language, Python is an interpretive, high-level, and general-purpose programming language. Created by Guido van Rossum and first published in 1991, Python is dynamically typed and garbage-collected.
There can be several different versions organized by release date. Some applications need a particular version of Python.
Python 2.0 and Python 3.0 type of version, python 2.0 released in 2000, Python 3.0, released in 2008, software that is written in one version may also not function properly in another version. Python 2 may stop releasing security fixes and patches after 2020. They also prolonged the deadline due to the huge number of developers using Python 2.7. Python 3 provides a 2 to 3 feature that can convert Python 2 code to Python 3.
Different between python 2 and python 3:-
Python 2.0, the latest version of 2.7, was released in 2010.
Announced Python 3.0 in 2008. The newest version, 3.6, came out in 2016, and version 3.7 is currently in the works.
Python 3 is supported by a wide group of Python users. It's quick to get help. Compared to earlier versions, it's easier to learn Python language supports modern techniques such as Data Science, machine learning, and Artificial Intelligence.
Python 2 Version
Python 2.0 - October 16, 2000
Python 2.1 - April 17, 2001
Python 2.2 - December 21, 2001
Python 2.3 - July 29, 2003
Python 2.4 - November 30, 2004
Python 2.5 - September 19, 2006
Python 2.6 - October 1, 2008
Python 2.7-July 3, 2010
Python 3 version
Python 3.0 - December 3, 2008
Python 3.1 - June 27, 2009
Python 3.2 - February 20, 2011
Python 3.3 - September 29, 2012
Python 3.4-March 16, 2014
Python 3.5 - September 13, 2015
Python 3.6- October 2016
Python 3.7- June 2018.
Programming different between python 2 and python 3:-
Python 3 :-
def main():
print("Hello World!")
if __name__== "__main__":
main()
Python 2
def main():
print "Hello World!"
if __name__== "__main__":
main()
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What makes Python so powerful?
PyPI (Python Package Index):-The PyPi package index is one of the features making python so efficient. The Python Package Index (PyPI), is a Python programming language software repository. PyPI assists you in discovering and downloading applications developed and shared by the Python community. You can browse thousands of interesting libraries with only a simple command.
Package management is so important that pip has been included with the Python installer since versions 3.4 for Python 3 and 2.7.9 for Python 2
Run the following command in the prompt code:
pip install library_name
To check the current version of PIP, type the following command:
pip --version
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Python Applications
Web development:- Python is a good option for prompt web application creation. Several frameworks, such as Django, Pyramid, and Flask, TurboGears, Web2Py, Pylons Framework, CubicWebPython, help you to create high-speed web applications. These frameworks provide the developers with a given structure when developing and writing a core logic so that they can focus on logic instead of other programming components. Apart from the framework python has a various module to use create a graphical interface like
Tkinter,
wxPython,
PyQt,
JPython
Data science:- Python has excellent resources to work with the implementation of data science. One of the key reasons why Python is commonly used in the science and academic communities is because of its ease of use and basic syntax that makes it easy to adapt to people who do not have an engineering background. It's even better suited for fast prototyping. Python provides a great deal of flexibility to work with mathematics, statistics, and the scientific process.
Artificial intelligence and Machine Learning:- Python is the most popular language for Artificial intelligence and Machine Learning. Python's accessibility, stability, platform independence, a wide set of resourceful libraries, and an engaging community render it the perfect tool to grow. AI and ML are implemented through multiple platforms and markets, major companies invest in these areas, and the requirement for ML and AI experts rises accordingly.
Python has pre-built libraries such as Numpy for Scientific Computation, Scipy for Advanced Computing, and Pybrain for machine learning
Conclusion:-
If you study python, there are several job possibilities available to you. And if you're not working as a Data Scientist or Data Processing, Python is capable of setting up! Being one of the developers in the field of Python web development and graphical user interfaces, automation development.
If you want to start studying Python, Offers Python with data science courses focused on job requirements for working professionals and freshers, Join Learnbay, and obtain a wider learning experience via the workplace support framework.
