Some cool things you can do with Python: pyThOn - fastEst Growing LaNgUage

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Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python's elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.

Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems.
So what are some of the cool things you can do with Python?

1. Python Web Development
python web development

Web development is the umbrella term for conceptualizing, creating, deploying and operating web applications and application programming interfaces for the Web.
Python is object oriented programming language. It can be used to build server-side web applications. Python is not used in a web browser. The language executed in browsers such as Chrome, Firefox and Internet Explorer is JavaScript.
However, most web applications build using a combination of Python and JavaScript. Python is executed on the server side while JavaScript is downloaded to the client and run by the web browser.

So you can build a cool website from scratch without feeling overwhelmed. You can also take advantage of micro-frameworks like Flask and Bottle.

Advanced content management is also possible with systems like Django CMS and Plone. Further, Python’s standard library supports several internet protocols like HTML, XML, and JSON.

2. Scientific and Numeric Computing
Python is an increasingly popular tool for Data Analysis. Data analytics falls under scientific and numeric computing. So we can take advantage of many libraries which python provides for scientific and Numeric computing. Such as SciPy library which includes modules for linear algebra, optimization, integration, special functions, signal and image processing, statistics, genetic algorithms, ODE solvers, and others. Numba which is specifically suited for scientific codes and Pandas is a data analysis and modeling library, so there’s a lot going on with Python within data science.

3. Function Decorators Allow Enhanced Functionality
Function decorators allow you to enhance the functionality of existing functions. In context of design patterns, decorators dynamically alter the functionality of a function, method or class without having to directly use subclasses. You can implement the decorator pattern anywhere, but Python facilitates the implementation by providing much more expressive features and syntax for that.

4.Machine Learning
machine-learning-python

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. 
Python has a great library called scikit-learn that is specialized in machine learning. The availability of scikit-learn makes it easy to implement machine learning algorithms in python.

5.Browser Automation
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You can also use Python to do cool things like automating your browser to do social media posts,download files and web pages. This can be done by using Selenium with Python. Selenium is able to fill in forms and simulate mouse clicks in this browser.

6.Robotics
robotics-python
Python is a core language of ROS (Robot Operating System), meaning the full power of a distributed robotics system and all its libraries/tools are available to you via Python. Python can be used to code a Raspberry Pi to function as the brain of a robot. By doing this you can get the robot to react to its environment and perform multiple actions.

These six cool things made possible by this programming language is just a fraction of what you can do with it. Python’s recent 3.6 release has new features in the asyncio module (which is no longer provisional with a surprisingly stable API), formatted string literals, and the addition of a file system path protocol.
The language is also evolving fast within the data science space. The Python ecosystem is now full of data science tools, so a lot of the data science work that’s currently taking place is being done with open-source tools like Python.

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