Skip to main content

Applications of python

Python supports cross-platform operating systems which makes building applications with it all the more convenient. It can be used in various fields for the easy development of our product.

python

Python can be used for:
1. Web Development
2. Web Scraping Applications
3. Desktop GUI
4. Game Development
5. Machine Learning( ML ) and Artificial Intelligence( AI )
6. Data Science and visualization
7. CAD Applications
8. Embedded Applications
9. Audio and Video Applications
10. Business Applications

applications of python
Applications of python

1. Web development

Python can be used to build server-side web applications. While a web framework is not required to build web apps, it's rare that developers would not use existing open-source libraries to speed up their progress in getting their application working.

Python is not used in a web browser. The language executed in browsers such as Chrome, Firefox, and Internet Explorer is JavaScript. Projects such as pyjs can compile from Python to JavaScript. However, most Python developers write their web applications using a combination of Python and JavaScript. Python is executed on the server-side while JavaScript is downloaded to the client and run by the web browser.

web development using python
Web development using python

Python frameworks for server-side programming:

  • Django and Pyramid framework(Use for heavy applications)
  • Flask and Bottle (Micro-framework)
  • Plone and Django CMS (Advance Content management)


2. Web Scraping Applications

Web scraping is the process of gathering information from the Internet. Even copy-pasting the lyrics of your favorite song is a form of web scraping! However, the words “web scraping” usually refer to a process that involves automation. Some websites don’t like it when automatic scrapers gather their data, while others don’t mind.

Python libraries used for web scraping:

  • Requests
  • Beautiful Soup 4
  • lxml
  • Selenium
  • Scrapy

3. Desktop GUI

Python is interactive programming that has a diverse range of options for GUI (Graphical User Interface) framework (help developers create GUI applications in an easy and secure manner).

The Best Python framework for building a desktop application and GUI:

  • PyQT
  • Tkinter
  • Kivy
  • WxPython
  • PyGUI
4. Game Development

With the advancement in the gaming industry, the Python language has proved to be an exceptional choice by the developers for rapid prototyping of video games.

game development using python
Game development

Various frameworks for game development using python:
  • Pygame
  • PyKyra
  • Pyglet
  • PyOpenGL
  • Kivy
  • Panda3D
  • Cocos2d
  • Python-Ogre
  • Ren'Py
5. Machine Learning( ML ) and Artificial Intelligence( AI )

Machine Learning (ML) and Artificial Intelligence (AI) are the new blacks of the IT industry. While discussions over the safety of its development keep escalating, developers expand the abilities and capacity of artificial intellect. Today Artificial Intelligence went far beyond science fiction ideas. It became a necessity. Being widely used for processing and analyzing huge volumes of data, AI helps to handle the work that cannot be done manually anymore because of its significantly increased volumes and intensity.

machine learning and artificial intelligence
ML & AI using Python

Python libraries used for AI and ML:
  • Scikit-learn
  • Pandas
  • Keras
  • TensorFlow
  • Matplotlib
  • NLTK
  • Scikit-image
  • PyBrain
  • Caffe
  • statsModel
6. Data Science and visualization

It is the discipline of trying to understand data by placing it in a visual context so that patterns, trends, and correlations that might not otherwise be detected can be exposed.
Python offers multiple great graphing libraries that come packed with lots of different features. No matter if you want to create interactive, live, or highly customized plots python has an excellent library for you.

data science and data visualization using python
Data visualization

Python libraries for data visualization:
  • Matplotlib
  • Pandas Visualization
  • Seaborn
  • ggplot
  • Plotly
7. CAD Applications

CAD( Computer-Aided Designing ) is quite challenging to make as many things have to be taken care of. Objects and their representation, functions are just the tip of the iceberg when it comes to something like this. Python supports a wide range of functionalities for 3D CAD & CAM applications such as FreeCAD, Fandango, CAMVOX, HeeksCNC, AnyCAD, HeeksPython, PythonOCC, PythonCAD, Blender, Vintech RCAM, etc.

8. Embedded Applications

Python is currently used in only about 5% of all embedded system code.

Python is also popular in embedded systems programming because:

  • Python is a popular language and known for its writability, concise, readable coding style, and error deduction.
  • Python is much handier in the case of complicated embedded systems such as those using neural networks.
  • Real-time embedded systems use Python quite often. MicroPython is a good example of a lean and efficient implementation for this.
9. Audio and Video Applications

Python is flexible to perform multiple tasks and can be used to create multimedia applications. Some multimedia applications which are made by using Python are TimPlayer, cplay, etc. 

The few multimedia libraries are given below.

  • Gstreamer
  • PygletQT 
  • Phonon

10. Business Applications

Python can be used to create applications that can be used within an Enterprise or an Organization. 

Some real-time applications are :
  • OpenERP
  • Tryton
  • Picalo

Comments

Popular posts from this blog

Graph Theory | Cyclomatic complexity

What is Graph Matrix? A graph matrix is a square matrix whose size represents the number of nodes in the control flow graph.  Each row and column in the matrix identifies a node and the entries in the matrix represent the edges or links between these nodes. Conventionally, nodes are denoted by digits, and edges are denoted by letters. Example: Graph Examples Since the graph has 4 nodes , so the graph matrix would have a dimension of 4 X 4 . Matrix entries will be filled as follows : (1, 1) will be filled with ‘a’ as an edge exists from node 1 to node 1 (1, 2) will be filled with ‘b’ as an edge exists from node 1 to node 2. It is important to note that (2, 1) will not be filled as the edge is unidirectional and not bidirectional (1, 3) will be filled with ‘c’ as edge c exists from node 1 to node 3 (2, 4) will be filled with ‘d’ as edge exists from node 2 to node 4 (3, 4) will be filled with ‘e’ as an edge exists from node 3 to node 4 Connection Matrix A connection matrix is a ma...