Introduction
Python is the high-level, general-purpose programming language developed by Guido van Rossum in 1991. It is one of the most popular programming languages from last three years according to Google. Python language is relatively easy to learn and understand and it has a large number of communities so that there will be a fast-flowing of information in case of problems while doing projects. Python has many applications from web development to GUI development and is used in the leading technologies such as machine learning, robotics, artificial intelligence, and data science.
Python Applications
Let’s discuss various types of Python applications:
1) Web Development
We are simply aware of websites and their uses. We know how important they are to convey information about any organization. There is a large number of tools for web development where each programming languages have their own frameworks. In the race, Python is also one of the popular contenders for developing powerful websites. Python has the following frameworks for web development:
- Django: Django is a high-level Python Web framework that helps to build interactive websites and is free and open source. There are lots of companies that use Django such as Instagram, Pinterest, Coursera, Udemy, etc.
- Pyramid: Pyramid is a lightweight open-source Python Web framework that believes in “The Start Small, Finish Big, Stay Finished Framework”.
- Flask: Flask is a micro-framework for Python Web Development that is designed to make lightweight websites quickly and easily.
- Bottle: Bottle is also a lightweight WSGI micro web framework for Python. It is distributed as a single file module and does not support dependencies other than the Python Standard Library.
- CherryPy: CherryPy is an object-oriented Python Web framework designed for the rapid development of web applications.
2) Software Development
Software development is the process of converting system specifications into a working system that involves different cycles like designing, testing, maintenance, and others. Here, in this case, Python provides different tools for automating these steps which save lots of time for software developers.
- SCons: SCons is an open-source software construction tool that is used to build control in software.
- Buildbot: Buildbot is an open-source framework for automating software build, test, and release processes.
- Roundup: Roundup is simple to use the software in Python for bug tracking and project management.
3) Business Applications
From the term ‘Business’ we can say that it is not normal applications and it is not available to all. We have to pay a certain amount to use these applications. To make such types of applications python provides features like readability, extensibility, and scalability. Python is used to make ERP(Enterprise Resource Planning) and e-commerce applications.
- Odoo: Odoo is the business management software that provides all the essential management software like CRM(Customer Relationship Management), billing, accounting, and others ranging from small to large companies.
- Tryton: Tryton is the open source business software that can be used by any type of company including features like CRM, financial accounting, sales, project management, etc.
4) GUI Development
Graphical User Interface is the interface that allows users to directly interact with the electronics devices by clicking or giving commands to them. Python provides different frameworks for GUI Development:
- Kivy: Kivy is the cross-platform, business-friendly, and GPU accelerated framework for developing multi-touch apps and it is open source too.
- PySide: PySide is the official set of Python bindings provided by Qt for Python. It provides power and simplicity for Python developers.
- WxPython: WxPython is the cross-platform GUI framework for Python that helps developers to truly create native user interfaces with little or no modifications to different available operating systems like Mac, Windows, Linux.
- Tkinter: Tkinter is the Python built-in framework for GUI development. It is the most commonly used and available in different python distributions.
5) Scientific and Numeric Applications
We know that the internet is receiving a huge amount of users’ unprocessed data from various sources. To represent those raw data in a meaningful way, Python provides different frameworks for scientific and numeric computation on those types of data:
- NumPy: NumPy is a very popular and the best library for scientific computing in Python. It is extensively used in manipulating data and tensors in neural networks and machine learning.
- Pandas: Pandas is a Python library for munging data and preparing data. It is not so great for data analysis and modeling compared with databases using SQL or Excel.
- SciPy: SciPy is the collection of functions for scientific computing in Python that provides functions like linear algebra, signal and image processing, genetic algorithm, and others.
- IPython: IPython provides an interactive interpreter that allows very fast testing of ideas by avoiding the creation of test files. It supports instant data visualizations and parallel computing.
6) Web Scraping Applications
Web Scraping is the process of extracting a large amount of meaningful data from websites that could be helpful in price comparison, model training, and others. It is also known as web harvesting or web data extraction. Python provides the following frameworks for web scraping:
- Beautiful Soup: Beautiful Soup is the Python framework for pulling data from HTML as well as XML files. It is user-friendly and easy to learn and master.
- Scrapy: Scrapy is an open-source framework that is fast, powerful, portable, and extensible. It is not user-friendly as compared to Beautiful soup.
- Selenium: Selenium is mostly used for testing web applications than web scraping. It is versatile and works well with Javascript language too.
7) Education
Since python language is relatively easy to learn and understand it will be a great language for teaching programming from introductory to advanced levels. Python syntaxes are way lot easier, clear and it requires very less code to write the same program that will require more lines of codes in other programming languages.
Conclusion
In this blog, we discussed various applications of Python and got knowledge that Python can be used in different fields with the help of its powerful frameworks. I hope you understood the Python applications. At last, if I miss any Python applications in the blog you can suggest me from the comment section below.
Happy Learning 🙂
