Why the Python programming language shines for data science, machine learning, systems automation, web and API development, and more…
What Python is used for
The most basic use case for Python is as a scripting and automation language. Python isn’t just a replacement for shell scripts or batch files; it is also used to automate interactions with web browsers or application GUIs or to do system provisioning and configuration in tools such as Ansible and Salt. But scripting and automation represent only the tip of the iceberg with Python.
General application programming with Python
You can create both command-line and cross-platform GUI applications with Python and deploy them as self-contained executables. Python doesn’t have the native ability to generate a standalone binary from a script, but third-party packages like cx_Freeze and PyInstaller can be used to accomplish that.
Data science and machine learning with Python
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Sophisticated data analysis has become one of fastest-moving areas of IT and one of Python’s star use cases. The vast majority of the libraries used for data science or machine learning have Python interfaces, making the language the most popular high-level command interface to for machine learning libraries and other numerical algorithms.
Web services and RESTful APIs in Python
Python’s native libraries and third-party web frameworks provide fast and convenient ways to create everything from simple REST APIs in a few lines of code to full-blown, data-driven sites. Python’s latest versions have strong support for asynchronous operations, letting sites handle tens of thousands of requests per second with the right libraries.
Metaprogramming and code generation in Python
In Python, everything in the language is an object, including Python modules and libraries themselves. This lets Python work as a highly efficient code generator, making it possible to write applications that manipulate their own functions and have the kind of extensibility that would be difficult or impossible to pull off in other languages.
Python can also be used to drive code-generation systems, such as LLVM, to efficiently create code in other languages.
