Python never sits still. With each iteration, both the Python language and its most widely used implementation, CPython, move forward to make life a little easier for everyone using them.As Python becomes more popular, and its use cases expand, certain Python limitations—from slow startup to the lack of concurrency—become more glaring.
The latest set of improvements are driven by the demands being imposed on Python in realms as diverse as automation, machine learning, and microservices. Here we look at four key areas in which Python’s core development team is pushing for major improvements.
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Shortening Python’s startup time
Many of the improvements planned for Python fall into the general bucket of “make things faster.” One optimization at the top of the list is reducing the amount of time the CPython interpreter needs to start up.
This may provide the biggest short-term bang for the development buck.To read this article in full or to leave a comment, please click here