When you choose Python for software development, you get a large language ecosystem with a wealth of packages covering all manner of programming needs. But in addition to libraries for everything from GUI development to machine learning, you can also choose from a number of Python runtimes—and some of these runtimes may be better suited to the use case you are working on than others.
Here’s a brief tour of Python distributions, from the standard implementation (CPython) to versions optimized for speed (PyPy), special use cases (Anaconda, ActivePython), different language runtimes (Jython, IronPython), and experimental use cases (MicroPython, RustPython).
