Improve Python Run-time Without Changing A Single Line of Code
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Improve Python Run-time Without Changing A Single Line of Code
Switching to a smarter implementation of CPython.
Python's default interpreter — CPython, isn't smart at dealing with for-loops, lists, and more.
It serves as a standard interpreter for Python and offers no built-in optimization.
Pypy, however, is an alternative implementation of CPython, which is much smarter.
How does it work?
It takes existing Python code and generates fast machine code using just-in-time compilation.
As a result, post compilation, the code runs at native machine code speed.
And Pypy can be used without modifying a single line of existing Python code.
👉 You should consider Pypy when:
you're dealing with standard Python objects.
speedups aren't possible with NumPy/Pandas.
So remember...
When you have some native Python code, don't run it with the default interpreter of Python.
Instead, look for alternative smarter implementations, such as Pypy.
Pypy will help you:
improve run-time of code, and
execute it at machine speed,
without modifying the code.
Find some more benchmarking results between Python and Pypy below:
Get started with Pypy here: Pypy docs.
👉 Over to you: What are some other smarter implementations of Python interpreter?
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Avi
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Find the code for my tips here: GitHub.
I like to explore, experiment and write about data science concepts and tools. You can read my articles on Medium. Also, you can connect with me on LinkedIn and Twitter.