Top 20 Python Real World Applications | Python tutorials
July 1, 2021 2022-12-19 1:59Top 20 Python Real World Applications | Python tutorials
Top 20+ Python Real World Applications | Must Read
In this tutorial, we have to discuss Python’s real world applications. In which we will explore and everything as related to our topic as possible. If you are interested in the Python programming language then must read this tutorial, because it has more beneficial information which will be helpful for you.
There are different examples of Python real world applications like Health Care and Medicine, Images generation. Language generation or translation, speech recognition, AI systems, etc. These are all can be developed with Python due to its powerful features, which we will discuss in this tutorial. InshaAllah!
What is Python?
Python is the interpreted programming language that is the most famous programing language in the field of soft development. It is developed by Guido van Rossum in 1991. It has more applications used in a variety of fields. In fact, it is the king of another programming language.
If you are a beginner then you can learn Python from basic level to advanced level due to its easy and simple syntax. There are lots of libraries/packages related to a variety of fields which make python a powerful language.
What is Real World Application?
To understand real world application, you need to understand what is the real world actually? The real world is the existing state of things or objects dislike to one that is imaginary, simulated, or theoretical. This definition is taken from Google dictionary. But I want to explore it, that makes it easy for you to understand.
Basically, real world of objects in the world in which they really live and have a real life. In that world, they exist really and interact with other things they are not like theoretical or simulated things.
So now come to the topic that is real world application. When real world event occurs, applications perform actions that application is called the real world. They are both linked in such a way that applications can senes real world events. In such applications there are programming languages are used with other technologies. So real world events are input and the result which is given by real world application is the output.
Why did Python use in Real-World applications?
As we have discussed different features of Python which make python a powerful language which used in high-level applications and projects as game development, Machine learning, data science, data analytics, web development, embedded system, etc. So, in this section, we shared some features or properties of Python, due to that developers select Python programing language for their projects like real world applications. So let’s start to get it!
- Versatility
- Cross-platform Operating system
- Efficiency
- Easy and Simple syntax
- Reliability
- Flexibility
- Automation
- Speed
- A lot of Libraries and Frameworks
- Mature Python Community
Python used by BIG companies
Python is the most famous and trended programming language used in different variety of fields to get different functionalities. TOP companies used Python as a programming language in their projects to get the required functionalities. The biggest company is Google which uses a different variety of programs like building system soft, code evaluation tools, and system administration tools, APIs, etc. The following are the company that used the Python programming language in their projects for different purposes.
- Netflix
- Dropbox
- Spotify
- Quora
Python Real World Applications
1) Web Development
Web development is the field in which we develop websites/web applications. We can develop websites through different technologies like PHP, Node.js, or Using a CMS system. We can also use Python to develop a website because there are different web frameworks are there.
Python libraries used in Web Development
- Pyramid
- Django
- Flask
2) Image Processing
Python is a powerful programming language that has the ability to process images. Processing on images means you can get information from the image or you can detect anything inside the image. There are secret data, that can be store in images through programming languages like Python.
we can say that image processing is to analyze the digital image. That image’s quality can be control or can be extract information or can also be store secret information in the image.
The python libraries related to Image processing
- Pillow
- OpenCV
- Mahotas
- Matplotlib
- Scikit-image
- Outlook
- SimplelTK
- SciPy
3) Data Science
The aim of data science is to extract useful and meaningful information from structured or unstructured data. Data science is the interdisciplinary field that uses mathematical, engineering or scientific methods, algorithms to get useful information. On the basis of received information, we can make a decision. To learn Data science you need to strengthen your programming skills and other relevant technologies.
These are Python libraries related to Data Science you can learn!
- PyTorch
- Pandas
- Scrapy
- BeautifulSoup
- NumPy
- SciPy
- Keras
- TensorFlow
- XGBoost
4) Data analytics
The word Data analytics is also showing its definition that is to analyze data. Data is the figures and facts, analyzing means, we analyze the figures, facts, and unstructured data to extract useful information on the basis we can make a decision.
There are different definitions, you can search on the internet. The following definition of data analytics is taken
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information.
We want to explore Wikipedia definition to better understand for beginners
Inspection: It is the careful examination or scrutiny of data.
Cleaning: You have to clearly analyze the data to extract information
Transforming: It means you need to transfer data into information, on the basis we can make decisions.
Modeling: To making data modeling means, you have to make a conceptual design for better understanding.
Discovering information: Now at the end, we need to extract information from structured and unstructured data, that we need.
The libraries used in Data analyticsÂ
- Pandas
- Matplotlib
- Scikit-learn
- StatsModels
- Seaborn
5) Data Visualization
According to Google dictionary, What is visualization?
It is the representation of an object, situation, or set of information as a chart or other image.
Understand? It means if you want to make a graph for resultant data, you can create using a programing language like Python. For example, you make a result sheet for students, as each student gets marks from different subjects. Then you can make a graph or chart for your students’ marks of subjects.
We used data visualization for a better understanding of data. Because viewing charts or graphs we can understand easily which situations are going?
The following libraries are used in data visualization
- Matplotlib
- Plotly
- Bokeh
- Altair
- Folium
- Seaborn
6) Audio Data Analysis Applications
Have you used an Audio application in which the system can understand your language what you are talking about and can convert it to another language, it is audio-based? On the google search box, you have noticed a small mic in the search box which gives an offer to their user to speak to search anything else. Actually, you can speak with a google search engine to find anything on the google search engines.
In other words, we can process manipulate audio in different easy with Python programming language.
The following libraries are used in Python Audio processing applicationÂ
- PYO
- pyAudioAnalysis
- Dejavu
- Mingus
- hYPerSonic
- Pydub
- Loris
7) Video Data Analysis Applications
Video applications can be developed with the Python programming language. Face recognition is the system in which we can detect any face in the video. You have noticed while capturing pictures from your cell phone, the boxes are created on the faces because inside your system, a system is developed which detects faces in the camera.
There are other examples of Video application that are developed in Python, as the detection of the number plate of motorcar through a live camera.
I share some Python libraries that are used in video applications.
- OpenCV
- Mahotas
- Pillow
- Matplotlib
- SimplelTK
- SciPy
- Scikit-image
7) Game Development
Game development is also included in Python Real World Applications, this is a very vast field and beginners students take an interest to learn. They take interset how to develop a game but don’t know which technologies and how much hard work is required. So high-level development of games can be done with the Python programming language. But some say, it is suitable for the simple game due to its low speed, I got such theory from quora when some developer saying about Python game development.
The following Python libraries are used in Game Development:
- Pygame
- PyKyra
- Pyglet
- PyOpenGL
- Kivy
- Panda3D
- Cocos2D
8) Scientific Applications
The application is used in the field of Science and used by Scientists for different purposes. For example Scientists work in different variety of fields as Biology, Chemistry, Physics, Nuclear Power, Mathematics, etc. They need applications or software which help in exploring more knowledge and in reserach. And the application related to the real world which works on real-world events also called scientific application.
The Python library used in scientific application developmentÂ
- SciPy
- Pandas
- Keras
- SciKit-Learn
- PyTorch
- TensorFlow
- XGBoost
- NumPy
9) Artificial Intelligence
It is the system that work and think like human beigns. It is very vast and trended field whcih have high scope in the word’s IT industrites. The system related to artifical intelligence are used in mostly all fields. We simpley called it AI. The high level applicaiton which work, think, behave and treat like human beings, can be develop with Python programming lanaguage. AIÂ is the practice of computer recognition, reasoning, and action also.
Differetn exmapels of artifical intelligcen systems
- Face Detection and Recognition
- Manufacturing robots.
- Chatbots
- Proactive healthcare management.
- Disease mapping.
- Automated financial investing
- Self-driving cars.
- Smart assistants.
- Google Maps and Ride-Hailing Applications
- Text Editors or Autocorrect
- Search and Recommendation Algorithms
The Python libraries used in Artificial intelligence.
- Tensor Flow
- Pandas
- NumPy
- Seaborn
- Theano
- Scikit-learn
- Keras
- PyTorch
10) Machine Learning
It is the application of artificial intelligence which gives a system that learns and improves from their experience without doing anything else. It is done automatically, just we have to design a system. Actually, ML systems learn from their experience you did not need to write coding for such functionality. Because it is a subset of AI which works, thinks behaves, and treats like human beings. There are more examples related to Machine learning, as when we buy any products from an eCommerce website, we also see the other products that are relevant to our product.
The Python libraries related to Machine Learning
- Pandas
- TensorFlow
- Matplotlib
- Numpy
- Scipy
- PyTorch
- Theano
- Scikit-learn
- Keras
