Applications of Python

Python is a language, that is almost dominating over all other computer programming languages. It is dominating, of course, because of its simplified syntax and extensive number of applications.

A language with simplified syntax that can be used in almost every field to interact with computer, is something a computer programmer needs. Specially in the field of Automation like data science and artificial intelligence, Python dominates all. But including this, here are the list of applications of Python language, or we can say Python used for:

  1. Artificial Intelligence (AI) and Machine Learning (ML)
  2. Data Science
  3. Data Visualization
  4. Data Analytics
  5. Web Scraping Applications
  6. Search Engine Optimization (SEO)
  7. Web Development
  8. Game Development
  9. Desktop Graphical User Interface (GUI)
  10. Software Development
  11. Business Applications
  12. Image Processing Applications
  13. Text Processing Applications
  14. Design
  15. Embedded Applications
  16. Console-based Applications

The first 2 and the fifth one, are the three most famous category where Python used most of the time. Let me briefly elaborate these applications of Python, one by one.

Python for AI and ML

Python is a well-known language to be used in the field of Artificial Intelligence and Machine Learning. Let's talk about artificial intelligence first.

Python for Artificial Intelligence (AI)

Anything made or produced by human beings known as artificial, whereas the ability to acquire and then apply the knowledge and skills is known as intelligence.

If we combine the two, the we can say, a system developed by a computer programmer that performs the tasks such as decision making, problem solving, speech recognition, visual perception, translation etc. automatically.

For example, an application that requires only the face picture of customers/users. Then we have two options, either we manually check and allow the customer's picture, if it is of face. Or, we implement the code that automatically scans the pic and stores if it is of face, otherwise displays the message to the customer to remind a message saying something like, only face pictures are allowed.

This is just an example. A lot of fields, where we can implement the artificial intelligence in our applications to automate the task, using of course, the one and only "Python".

Another example of artificial intelligence is, while using YouTube, our day-to-day activities gets analyzed by the system, and we get the best recommendation based on previous activities.

Note - Pandas is a library available in Python, mostly used for data analysis and modeling. Whereas SciPy is mostly used for science, engineering, and mathematics.

Python for Machine Learning (ML)

Machine learning is one step forward to an artificial intelligence. We can say ML as a type of AI.

Like we human beings learns the things based on our success and failure or whatever the incidents goes in our life/past, that helps us to learn. Similarly machine can also learn, and that is known as machine learning.

Therefore we can say that the ability to learn by the computer system itself, using data statics, and the past experience, or whatever the data needs to learn by the machine, is known as machine learning.

Note - The two famous library of Python used in machine learning are NumPy and SciPy.

Python for Data Science

Data science is the process of extracting knowledge and insights from both structured and unstructured data across multiple applications. Data mining and Data Processing and Modeling comes under data science.

In short and simple words if we say, then data mining is the conversion of large number of raw data into a meaningful or useful information.

Data processing is the collection of data to manipulate and produce a meaningful information. Basically data processing can be called as a subset of information processing. The cycle to process the data are:

  • Collect the data
  • Input the data
  • Process the data
  • Produce the meaning information

Data modeling is used to provide the relationship of one data object to another. Basically data modeling is a process of creating a data model for an information system using some techniques.

Note - The Scrapy is most used library in Python, for data data mining. Whereas NumPy, Pandas, and TensorFlow are most used libraries in Python, for data processing and modeling.

Python for Data Visualization

Data visualization is basically a part of data science. That is, after extracting the knowledge and insights from the data, we need to present the information in the form of graphical or pictorial representation.

Note - The Matplotlib and Seaborn are the two most used libraries of Python, used for data visualization.

Python for Data Analytics

Data analytics is little similar to data science. But in case of data analytics, instead of extracting, here the process that goes under the data analytics are inspecting, cleansing, transforming, and modeling the data to of course acquire some useful information.

Note - The three most used libraries in the field of data analytics using Python, are Pandas, Numpy and Scipy.

Python for Web Scraping Applications

Web scraping is a process of extracting data across the web. For example, a search engine like Google, Yahoo etc. crawl the web to scrap the data from all the websites to index and rank on the search engine.

Note - The Scrapy is the most used library in Python, for web scraping purpose.

Python for Search Engine Optimization (SEO)

Search engine optimization or SEO in short, is a process of improving the website traffic. In this field too, Python plays an important role. For example, Python developer can create an application that can analyze the website to find some improvements such as broken links, multiple main headings, unmatched title and headings, duplicate contents, and many more.

Python for Web Development

The development of a website over the internet is web development. Most of the larger applications that requires some AI and ML at the back-end of website, uses Python. But it is not limited to AI and ML only, a normal website connected with database can also be implemented using Python.

Note - The Django is the most used web framework of Python.

Python for Game Development

The Pygame is the most used Python library for game development using Python. Some other libraries for game development using Python are PyKyra, Pyglet, PyOpenGL, and Kivy etc.

Python for Desktop Graphical User Interface (GUI)

Application created to interact with electronic devices through graphical icons is GUI. Python is useful in developing Desktop GUI.

Note - The two most used library for GUI development using Python are Tkinter and Kivy.

Python for Software Development

Using Python, we can also develop a collection of instructions to perform specific task. In other words, Python is useful in the software development field too.

For example, if we need to implement a feature like ChatBot in our application, then Python is the best and recommended language to build the ChatBot for your application to of course automate the chat with your client.

There are many libraries available in Python that can be helpful in software development. But I'm not going to mention any particular one in this section, as it totally depends on the category requirement of your application.

Python for Business Application

Basically business application comes under the category of software development. In business application, a business person or an enterprise needs some applications to trend the business, measure and increase the productivity, perform business functions and many more like application for communication, application to mange the things like files and employees details etc., depends on the requirement.

Python for Image Processing Applications

Image processing applications are created to process the image to enhance it based on the requirement of application. Sometime Python is useful to create image processing application that scan the image to enhance the image or to sharpen, restore, process the color, detect the face, recognize the finger print, or any pattern recognition of the image, etc. type purposes.

Note - Some of the most used Python libraries to create an image processing applications are OpenCV, Pillow/PIL, and Scikit-Image.

Python for Text Processing Applications

Similar to image processing, text processing application also be created using Python. An application created to process the text is text processing applications.

The text processing is required when our application needs to analyze the text, extract the useful text, analyze and auto-reply the text like ChatBots, auto-correct the text, etc.

Python for Design

As already told under the section of Python for Desktop GUI, Libraries like Kivy and Libavg and many more, used to design an application or a part of an application using Python.

Python for Embedded Applications

From creating a small-purpose application to an embedded application, Python is useful. Embedded applications are basically developed to run a device for some particular task.

Python for Console-based Applications

A console-based applications can also be called as applications without GUI. Basically a console application is created to be used via the text-only computer interface like command-line, Boot-loader, Kernel etc.

Note - A famous console-based application in Python is IPython.

Python Online Test

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