History of Python
- Python was developed by Guido van Rossum, and released in Feb. 1991 as Version 0.9.0., at Centrum Wiskunde & Informatica (CWI) in the Netherlands as a successor to the ABC language. He named this language after a popular comedy show called ‘Monty Python’s Flying Circus’ (and not after Python-the snake).
- Python was developed & copyright by Python Software Foundation (PSF), a non-profit organization.
- The latest version of Python is Python 3.9 and released in Oct. 2020.
- The official web site of python is : https://www.python.org
Introduction of Python
- Python is the most popular and demandable programming language in the world because this language can be used to do almost all types of computer applications thesedays used widely such as offline, online or web, Server, AI, Data science related applicaitons etc.
Definition of Python
- Python is an advanced, free, pure object-orientd, high-level, cross-platform, general-purpose and open-sourced programming language.
Characteristics of Python
- Python has a simple syntax.
- Python provides enhanced readability.
- Python is an interpreter-based programming language.
- Python has rich basic data types such as numbers (floating point, complex, and unlimited-length long integers), strings (both ASCII and Unicode), array & lists, and dictionaries.
- Variables in Python are strongly typed as well as dynamic typed.
- Python supports full object-oriented programming concepts.
- Python has automatic memory management.
- There are various built-in and third-party modules can be used & available independently in the Python application, which can be imported as per need in the program.
- Python can be treated in a procedural way, an object-oriented way or a functional way.
Advantages of Python
- Python is an extensible language i.e., additional functionalities(other than what is provided in their core part) can be made available through modules and packages written in other languages (such as C, C++, Java, etc.)
- Python is a cross-platform language. It works equally on different OS platforms like Windows, Linux, Mac OSX, Raspberry Pi etc. Hence Python applications can be easily ported across OS platforms.
- Python supports multiple programming paradigms including imperative, procedural, object-oriented, and functional programming styles.
- Python has a standard DB-API for database connectivity. It can be enabled using any data source (Oracle, MySQL, SQLite etc.) as a backend to the Python program for storage, retrieval, and processing of data.
- Python has rich GUI toolkits i.e.,The standard distribution of Python contains the Tkinter GUI toolkit, which is the implementation of a popular GUI library called Tcl/Tk. An attractive GUI can be constructed using Tkinter. Many other GUI libraries like Qt, GTK, WxWidgets, etc. are also ported to Python.
- Python can be integrated with other popular programming technologies like C, C++, Java, ActiveX, and CORBA.
Applications of Python
- Python is used to create a commercial level of web applications.
- Python is used to handle and analyse big data and perform complex mathematics(=Data science).
Common Python Tools & Frameworks
- Python IDE Tools : Pycharm, IDLE (Integrated Development and Learning Environment), Visual Studio Code, Sublime Text 3, Atom, Jupyter, Spyder, PyDev(IDE for Eclipse), Thonny, Wing, PyLin etc.
- IDE for Beginner users – IDLE & Thonny are good options.
- IDE for Intermediate users – PyCharm, VS Code, Atom, Sublime Text 3 are good options.
- IDE for Data Science Work – Jupyter Notebook, Spyder, PyCharm professional(Paid).
- IDE for Web Development – VS Code, PyCharm professional(Paid).
- IDE for Scripting work – PyCharm Community(Free), Atom, PyDev, Sublime Text 3.
- Python Web Development Framworks : Django, Pyramid, Flask, Bottle, Tornado, web2py etc.
- Python Automation Testing Python tools : Selenium, Robot Framework, TestComplete etc.
- Python Web Scraping Python tools : Beautiful Soup, LXML, Scrapy etc.
- Python GUI Development Tools : Tkinter, PyGObject, PyQt5, PySide, Kivy, wxPython, Libavg, PySimpleGUI, PyForms, Wax etc.
- Python Scientific and Numeric(Data Science & Machine Learning) Tools : Theano, Scikit-Learn, SciPy, Pandas, IPython, Keras etc.
- Python Software Development Tools : Buildbot, Trac, Roundup etc.
- Python System Administration Tools: Ansible, Salt, OpenStack etc.
0 Comments