Introduction
In this article, we will explore various applications where Python is used.
Python
Python is an interpreted, high-level, general-purpose programming language created by Guido van Rossum and first released in 1991. He started Python as a hobby project to keep him occupied in the week around Christmas. It got its name from the name of the British comedy troupe Monty Python. It is used in:
- Software Development
- Web Development
- System Scripting
- Mathematics
Why Python?
Before we learn where all Python is used, let us know why it gained so much popularity that NASA, Facebook, Google, Walt Disney, etc, are using it.
It has gained some popularity as Python has a wide variety of libraries with pre-defined functions and also since the number of code lines needed to be written is comparatively less as compared to other languages. Hence, the resulting code is crisp and takes less time to run.
Some facts about Python:
- According to Forbes, Python has experienced a growth of 456% in the last 2 years.
- According to StackOverflow, from January 2016 to August 2017, the traffic growth rate of Python increased by 27%. And in 2019, it increased by 41%.
- Python has been ranked the top in the list of "Top Programming Languages in 2019" by IEEE
- Companies like Google, NASA, Facebook, IBM, Netflix, Instagram use Python.
Some of the features of Python are:
- Easy to use
due to simple syntax, it is very easy to implement anything and everything
- Interpreted Language
In this, every code is executed line by line.
- Cross-platform Language
It can run on Windows, Linux, Macintosh, Raspberry Pi, etc.
- Expressive Language
It supports a wide range of library
- Free & Open Source
It can be downloaded free of cost and source code can be modified for improvement
Top Companies using Python
Here we will be discussing some corporates using python.
- Google spider and search engine are written in Python
- NASA uses Python in its Integrated Planning System as the standard scripting language. Nasa website is written in Python(Django framework)
- NOKIA is using Python to provide a high-level programming environment for their S60(Symbian)
- IBM uses Python to create the business practice logic for factory tool control applications
- Amazon uses Python because of its popularity, scalable & appropriateness for dealing with Big Data that's the big plus for the kind of solutions Amazon strived to create.
- Facebook decided to use Python as the core language for the backend of their applications connected with image processing.
- Walt Disney Feature Animation uses Python as a scripting language for animation. All the magic that happens in Disneyland has a bit of Python behind it.
- Many of our choices to store our data are going online. We create a document, we save it & we share it. It is the ideal way to preserve your documents online. Dropbox is one of the most popular file hosting mechanisms that have been created by using Python.
- Reddit is a place where you can find a lot of information & entertainment across thousands of categories, popularly called the internet’s front page has been developed by using Python.
- Quora is a portal where you get your answers. Quora’s language programming has been developed using Python’s framework.
What Python is Used For?
- Web Applications
- Scientific Calculations
- Data Science
- Machine Learning
- Computer Science Education
- Computer Vision and Image Processing
- Game Development
- Medicine and Pharmacology
- Biology and Bioinformatics
- Neuroscience and Psychology
- Astronomy
- Programming Hardware
Python in Web Development
Python is a Server Side Programming language, that is, it is used to program the backend of a web application. Tasks like interacting with the server, processing all requests, interacting with the database, etc. are carried out by Python.
Python has a built-in module for unit testing and it takes less time to write the code, hence it accelerates the ROI of commercial Projects
Following are some of the Python Frameworks which are used to create web applications
- Django
It's a high-level Python Web platform that promotes quick creation and simple, practical architecture.
- Flask
It's a well-known Python microframework for creating web applications.
- Pyramid
It's a lightweight, fast, and practical Python web platform.
- Web2Py
It is a free open source full-stack architecture for rapidly developing database-driven web-based applications that are fast, scalable, stable, and portable.
- Bottle
It is a WSGI micro web-framework for Python that is fast, quick, and lightweight.
Python in Scientific Calculation
Python is widely used to perform scientific and numeric calculations. As python has a wide range of libraries and functions for everything, it becomes comparatively easy to do long and complex calculations using Python.
Scipy and NumPy are some of the libraries which are used for doing scientific and numeric calculations.
To read more about Numpy,
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Python in Data Science
Python is widely used by data scientists for manipulating, analyzing, and visualizing data.
Data Science is a detailed study of the flow of information from the colossal amounts of data present in an organization’s repository. It involves obtaining meaningful insights from raw and unstructured data which is processed through analytical, programming, and business skills.
Python has a wide variety of libraries for each of the 5 phases of the data science process which makes it easy to implement.
Some of the most used libraries are as follows:
- Pandas
- NumPy
- Seaborn
- Matplotlib
- Bokeh
To read more, please visit the following:
Python in Machine Learning
Python has its most popular application in the field of machine learning. Google's ML-based products are mostly built in python.
Machine learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.
Python has gained so much popularity that Microsoft Azure now provides IPython Notebooks (IPYNB), and Google has launched a full-fledged deep learning framework named TensorFlow, and has an online Python editor-cum-interpreter named Google Colab, to test your code.
Scikit-Learn is a Python library that provides pre-defined optimized functions to implement various machine learning algorithms. It features various classification, regression and clustering algorithms including Support Vector Machines, Random Forests, Gradient Boosting, k-Means, and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
Some of the famous Python-based ML frameworks are
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Python in Education
Python is an excellent language for teaching both at an introductory and at an intermediate level. Pointer is one of the most important concepts to understand, which sometimes becomes very difficult to understand, And since memory is managed by Python itself, it becomes easy for a beginner to code.
In other languages like Java, C++, etc. one needs to keep track of the start and end braces, in Python, one need not to keep track of these, as there are no parenthesizes used, hence a programmer can concentrate and devote more time on the business logic.
Python in Computer Vision and Image Processing
Since Python is built using C language, (and as we know that C provides the best graphics), and uses many of the C libraries to perform image processing, it is best suited for computer vision and image processing applications.
Image processing and computer vision are two terms that are used interchangeably, but they are different as image processors will only process an image i.e. suppose an image of a cat is given, then image processing may include reducing or increasing the pixels, making an image grayscale, etc.
Whereas a computer vision system would take in an image, process it, fragment/segment it, perform the required tasks, and give the result as per desired specifications. For example, a computer vision system is intended to alarm if a cat is detected, so the system will manipulate the size, convert it to grayscale ( as it takes less computation power to process grayscale as compared to RGB image), then segment the image to detect a cat, if the system detects a cat it sends a trigger and the alarm is set on.
Some of the Python Computer Vision libraries are
- OpenCV (Open Source Computer Vision)
- TensorFlow
- PyTorch
- Matlab
- CUDA (Computer Unified Device Architecture)
- Pillow
- SimpleCV
- YOLO (You Look Only Once)
- Theano
- Keras
Some of the Python Image Processing libraries are
- Scikit-image
- OpenCV
- Mahotas
- SimplelTK
- SciPy
- Pillow
- Matplotlib
Google is also using Python to create computer vision software for self-driving cars,
Python in Game Development
Although Python is not used by many for developing games due to its slow execution and also due to the fact that Python game development libraries are still under development. Then also Python has made it to the list of developers as one of the choices to create some popular games like EVE Online and Disney’s Pirates of the Caribbean. Python has an upper edge over other languages like Java, C++, and C# when we need to do fast prototyping. As Python codes are very short so Python is used when the length of the code is one of the considerable features while deciding the ROI.
Some of the Python-based game development libraries are
- Pygame
- PyKyra
- Pyglet
- PyOpenGL
- Kivy
- Panda3D
- Cocos2D
- Python-Ogre
- Ren'Py
Python in Medicine and Pharmacology
As per Wikipedia, Pharmacology is a branch of medicine and pharmaceutical sciences concerned with drug or medication action, where a drug may be defined as any artificial, natural, or endogenous molecule which exerts a biochemical or physiological effect on the cell, tissue, organ, or organism.
Over the years Python has become quite popular among health startups. Roam Analytics, AiCure, DrChrono, Qventus, Sempre Health, and Fathom Heath are using Python in their health care products.
Some of the applications of Python in Medicine and Pharmacology are
- Making clinical diagnoses based on the patients' medical records and symptoms
- Analyzing medical data
- Making computational models to speed up the process of development of new medications
- DNA Sequencing
- Doing statistical analysis on large pharmaceutical datasets
- To simulate the chemical structure of molecules and their effect on the body
- To identify and classify red blood cells shapes based on images taken from optical microscopes
According to the official Python documentation, one of the world's largest pharmaceutical firms, AstraZeneca, used Python to develop their current theoretical models to render them "more stable, extensible, and maintainable".
Some of the Python-based pharmacology libraries are
Python in Biology and Bioinformatics
According to Wikipedia, Bioinformatics is a science field that is similar to but distinct from biological computation, while it is often considered synonymous with computational biology. Biological computation uses bioengineering and biology to build biological computers, whereas bioinformatics uses computation to better understand biology.
Biopython is a Python application that offers "open-source methods for biological computation." Its mission is to "meet the needs of present and future bioinformatics work." BioPython has the ability to
- Work with sequences and perform basic operations such as encoding, translation, and weight measurements on them.
- Link to biological databases.
- Use K-Nearest Neighbors, Naive Bayes, and Help Vector Machines to classify files.
- Use phylogenetic trees and population genetics to your advantage.
Rosalind is a "forum for problem-solving-based learning in bioinformatics." It is "accessible and available to the general public" (the FAQ page indicates that it is in beta mode). Python can be used to overcome platform problems. Since Python is such a popular programming language on the web, there is a "Python Village" section where you can learn the fundamentals of the language before jumping into bioinformatics algorithms. Users solve the problems by running their solutions on their CPU, processing the provided dataset, and copying/pasting the output to verify the response.
Some of the popular Python-based Bioinformatics libraries are
- ProDy
- PySB
- The Community Simulator
Python in Neuroscience and Psychology
According to Wikipedia, Neuroscience is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science, and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. And Psychology is the science of mind and behavior. Psychology includes the study of conscious and unconscious phenomena, as well as feeling and thought. It is an academic discipline of immense scope.
PsychoPy is "an open-source package for running experiments in Python" supported by the University of Nottingham. Some of the reasons for the success of PsychoPy are
- Easy for learning.
- Precise enough for Psychophysics.
- Flexible.
- Online or lab-based depending on the user's choice
Python in Astronomy
According to Wikipedia, Astronomy is a natural science that studies celestial objects and phenomena. It uses mathematics, physics, and chemistry in order to explain their origin and evolution. Objects of interest include planets, moons, stars, nebulae, galaxies, and comets.
Python packages have advanced to the point that it is now reasonably simple for everyone to develop data reduction scripts capable of delivering high-quality data items.
Some of the popular Python-based Astronomy libraries are
- Astropy
- SunPy
- SpacePy
To know more on how Python is used in Astronomy,
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Python in Hardware World
Python is one of the very few languages that can run directly on the hardware. It is one of the most favorite languages used for IoT applications.
Given below are some of the implementations of Python that are used to program microcontroller boards
- MicroPython is a lean and efficient Python 3 implementation that contains just a limited subset of the Python standard library and is optimized for use on microcontrollers and in restricted environments. MicroPython is used to program Pyboard, ESP8266, ESP32, WiPy, and micro:bit.
- ArduPy is an Arduino and MicroPython hybrid. MicroPython controls the hardware using the Arduino API, which allows it to easily adapt to new platforms. You can validate your theories, learn Python programming, and program microcontrollers more efficiently with ArduPy.
- CircuitPython is an open-source fork of the MicroPython programming language aimed at students and newcomers. Adafruit Industries is helping to develop CircuitPython.
Raspberry Pi is the most famous Microcontroller board that uses Python. There are many boards like Mango Pi, Banana Pi, Orange Pi, and Diet Pi, to name a few, which use Python. Nowadays Arduino can also be programmed with the help of Python through ArduPy.
Zerynth offers a complete ecosystem of tools for developers, including an IDE, a production toolchain, a multithreaded RTOS (real-time operating system), a device manager, and a smartphone app for monitoring and controlling Zerynth-powered machines. Zerynth makes IoT creation easier by allowing you to write in Python or a Python-C hybrid.
Home Assistant is a Python-based open-source project for smart home automation. It can be installed on a computer or a Raspberry Pi. Home Assistant is responsible for automation; for example, it will adjust your home's lighting and monitor the temperature in each room. Home Assistant is also compliant with a wide range of drivers and sensors.
Conclusion
In this article, we discussed why python is so popular and at what all places Python is used. Please do explore more about the mentioned applications of python and comment with your views on how useful this article was.
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