In this article we will learn about different applications of Python programming language.
As we already know that Python is a general purpose high-level language, we can use it for creating almost any type of application or software. Following are some of the important applications of Python language:
Systems Programming: Python’s built-in interfaces to operating-system services make it ideal for writing portable, maintainable system-administration tools and utilities (sometimes called shell tools). Python programs can search files and directory trees, launch other programs, do parallel processing with processes and threads, and so on.
GUIs: Python’s simplicity and rapid turnaround also make it a good match for graphical user interface programming on the desktop. Python comes with a standard object-oriented interface to the Tk GUI API called tkinter (Tkinter in 2.X) that allows Python programs to implement portable GUIs with a native look and feel.
Internet Scripting: Python comes with standard Internet modules that allow Python programs to perform a wide variety of networking tasks, in client and server modes. Scripts can communicate over sockets; extract form information sent to server-side CGI scripts; transfer files by FTP; parse and generate XML and JSON documents; send, receive, compose, and parse email; fetch web pages by URLs; parse the HTML of fetched web pages; communicate over XML-RPC, SOAP, and Telnet; and more. Python’s libraries make these tasks remarkably simple.
Component Integration: Python’s ability to be extended by and embedded in C and C++ systems makes it useful as a flexible glue language for scripting the behavior of other systems and components.
Tools such as the SWIG and SIP code generators can automate much of the work needed to link compiled components into Python for use in scripts, and the Cython system allows coders to mix Python and C-like code.
Database Programming: For traditional database demands, there are Python interfaces to all commonly used relational database systems like Sybase, Oracle, Informix, ODBC, MySQL, PostgreSQL, SQLite, and more. The Python world has also defined a portable database API for accessing SQL database systems from Python scripts, which looks the same on a variety of underlying database systems.
In the non-SQL department, Python’s standard pickle module provides a simple object persistence system—it allows programs to easily save and restore entire Python objects to files and file-like objects.
Rapid Prototyping: To Python programs, components written in Python and C look the same. Because of this, it’s possible to prototype systems in Python initially, and then move selected components to a compiled language such as C or C++ for delivery.
Numeric and Scientific Computing: Python is also heavily used in numeric programming. Prominent here, the NumPy high-performance numeric programming extension for Python includes such advanced tools as an array object, interfaces to standard mathematical libraries, and much more.
Go back to introduction to Python programming.
Suryateja Pericherla, at present is a Research Scholar (full-time Ph.D.) in the Dept. of Computer Science & Systems Engineering at Andhra University, Visakhapatnam. Previously worked as an Associate Professor in the Dept. of CSE at Vishnu Institute of Technology, India.
He has 11+ years of teaching experience and is an individual researcher whose research interests are Cloud Computing, Internet of Things, Computer Security, Network Security and Blockchain.
He is a member of professional societies like IEEE, ACM, CSI and ISCA. He published several research papers which are indexed by SCIE, WoS, Scopus, Springer and others.
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