Where to use Python?
Even though Python started as a general-purpose programming language with no particular application as its focus, it has emerged as the language of choice for developers in some application areas over the last few years. Some important applications of Python are summarized below:
Data Science
Python experienced a recent emergence in popularity charts, mainly because of its Data science libraries. A huge amount of data is being generated today by web applications, mobile applications, and other devices. Companies need business insights from this data.
Today Python has become the language of choice for data scientists. Python libraries like NumPy, Pandas, and Matplotlib are extensively used in the process of data analysis, including the collection, processing and cleansing of data sets, applying mathematical algorithms, and generating visualizations for the benefit of users. Commercial and community Python distributions by third-parties such as Anaconda and ActiveState provide all the essential libraries required for data science.
Machine Learning
This is another key application area of Python. Python libraries such as Scikit-learn, Tensorflow and NLTK are widely used for the prediction of trends like customer satisfaction, projected values of stocks, etc. Some of the real-world applications of machine learning include medical diagnosis, statistical arbitrage, basket analysis, sales prediction, etc.
Web Development
This is another application area in which Python is becoming popular. Web application framework libraries like django, Pyramid, Flask, etc. make it very easy to develop and deploy simple as well as complex web applications. These frameworks are used extensively by various IT companies. Dropbox, for example, uses Django as a backend to store and synchronize local folders.
Today, most of the web servers are compatible with WSGI (Web Server Gateway Interface) - a specification for the universal interface between Python web frameworks and web servers. All leading web servers such as Apache, IIS, Nginxetc can now host Python web applications. Google's App Engine hosts web applications built with almost all Python web frameworks.
Image Processing
The OpenCV library is commonly used for face detection and gesture recognition. OpenCV is a C++ library but has been ported to Python. Because of the rapid development of this feature, Python is a very popular choice from image processing.
Game Development
Python is a popular choice for game developers. The PyGame library is extensively used for building games for desktop as well as for mobile platforms. PyGame applications can be installed on Android too.
Embedded Systems and IoT
Another important area of Python application is in embedded systems. Raspberry Pi is a very popular yet low-cost single-board computer. It is extensively used in automation products, robotics, IoT, and kiosk applications. Popular microcontrollers like Arduino are used in many IoT products and are being programmed with Python. A lightweight version of Python called Micropython has been developed, especially for microcontrollers. A special Micropython-compatible controller called PyBoard has also been developed.
Android Apps
Although Android apps are predominantly developed using Android SDK, which is similar to Java, Python can also be used to develop Android apps. Python's Kivy library has all the functionalities required for a mobile application.
Automated Jobs
Python is extremely useful and widely used for automating CRON (Command Run ON) jobs. Certain tasks like backups, defined in Python scripts, can be scheduled to be invoked automatically by the operating system scheduler to be executed at predefined times.
Python is embedded as a scripting language in many popular software products. This is similar to VBA used for writing macros in Excel, PowerPoint, etc. Python API is integrated with Maya, PaintShop Pro, etc.
Rapid Development Tool
The standard distribution of Python, as developed by Rossum and maintained by Python Software Foundation, is called CPython, which is a reference implementation. Its alternative implementations - Jython, the JRE implementation of Python and IronPython - the .NET implementation, interact seamlessly with Java and C#, respectively. For example, Jython can use all Java libraries such as Swing. So the development time can be minimized by using simpler Python syntaxes and Java libraries for prototyping the software product.
The following summarises important tools and frameworks for different types of Python applications:
