Summary -
In this topic, we described about the below sections -
Python is a powerful language and used in many application development areas. Python supports cross-platform operating systems that makes building applications in more convenient way.
Below are some of the major applications where python is used -
Web Applications -
Python provides standard libraries to support, manage internet protocols like JSON, XML and HTML, Email processing, support for FTP, IMAP, other internet protocols and easy-to-use socket interface.
Python provides many options to design and develop web-based applications. Those are –
- Django and Pyramid frameworks.
- Flask and Bottle micro-frameworks.
- Plone and Django CMS advanced content management systems.
Python package index has more libraries that supports web applications development. Those are –
- Beautiful Soap is an HTML parser handles all types of oddball HTML.
- Feedparser is parsing tool used for parsing RSS/Atom feeds.
- Paramiko, used to implement the SSH2 protocol.
- Requests is a powerful HTTP client library.
- Twisted Python is a framework used for asynchronous network programming.
Some of the application that are developed using Python are - PythonBlogSoftware, PythonWikiEngines, Pocoo, etc.
Education –
Python is an excellent language for teaching programming both at entry level and in advanced level.
Desktop GUI Applications -
Python used to develop client interface using Tk GUI library. Tk GUI library provides the Tkinter library that uses in developing user interfaces. Certain other useful toolkits such as wxWidgets, Kivy, pyqt used to create applications on several different platforms. The Kivy is famous for writing multitouch applications.
Software Development -
Python is helpful for the software development process and used as a support language for software development. Python used for build control, management, testing, and so on.
Below are the list of tools available that are used for different purposes in software development. Those are -
- SCons used for build control.
- Buildbot and Apache Gump used for automated continuous compilation and testing.
- Roundup or Trac used for bug tracking and project management.
Scientific and Numeric -
Python is incredibly famous for wide usage in scientific and numeric computing. Some useful library and packages are SciPy, Pandas, IPython, Software Carpentry Course etc.
- SciPy is group of packages of engineering, mathematics and science.
- Pandas is data analysis and modelling library.
- IPython is a powerful interactive shell uses for easy editing, recording of a work session, and supports visualizations and parallel computing.
- Software Carpentry Course explains about the basic skills for scientific computing, running bootcamps and supplying open-access teaching materials.
Business Applications -
Python used to develop Business applications like e-commerce and ERP systems. Below are the list of tools that are used for business applications development.
- Odoo is an all-in-one management software with a wide range of business applications that forms a complete suite of enterprise management applications.
- Tryton is a three-tier high-level general-purpose application platform.
Console Based Application -
Python used to develop console-based applications. For example - IPython.
Audio or Video based Applications -
Python used to develop multimedia applications that can performs multi-tasks. The application that are developed using Python provide better stability and performance when compared to other application developed using other technologies. Some of the application that are developed using Python are - cplay, TimPlayer, and so on.
3D CAD Applications -
Python has features that are extremely helpful in 3D CAD Applications development. Fandango is a true application to create CAD application that provides the complete features of CAD.
Enterprise Applications -
Python used to create applications for an Enterprise or for an Organization. Some of the application that are developed using Python are - OpenErp, Tryton, Picalo etc.
Applications for Images -
Many applications developed for images processing using Python. Some of the application that are developed using Python are - imgSeek, VPython, Gogh, and so on.
Game Development -
Python used in the development of interactive games. PySoy and PyGame libraries supports to develop the interactive or non-interactive games.
- PySoy is a 3D game engine that was introduced in Python 3.
- PyGame is a library and provides functionality for game development.
Games such as Civilization-IV, Disney’s Toontown Online, Vega Strike etc. are developed using Python.
Machine Learning and Artificial Intelligence -
Python is the programming language that is mostly everyone chooses in machine learning and artificial intelligence. Python is simplifying the design for better solution and much easier when compared to other languages.
Data Science and Data Visualization -
Python provides support to perform operations and extract the required information from the raw data. This can help in calculate the risks and increase the profits. Python libraries such as Pandas, NumPy used in extracting information.
Python is very much useful to visualize the data by creating graphics and much more using the extracted data. Python libraries Matplotlib, Seaborn are used in creating graphics.
These python features offer anyone to become a Data Scientist.
Web Scraping Applications –
Python used to pull a huge amount of data from websites that is used in various real-world processes such as price difference, job listings, research and development and much more.
Embedded Applications -
Python used to create Embedded software for embedded applications as it is developed based on C language. Developing embedded applications helps to perform higher-level applications on smaller devices.
Raspberry Pi is most well-known embedded application and uses Python for its computing.
Database Access -
Python provides interfaces to connect with all major databases. Those interfaces are -
- Custom and ODBC interfaces to MySQL, Oracle, PostgreSQL, MS SQL Server, and others.
- Object databases like Durus and ZODB.
- Standard Database API.