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Python for Production: Accelerating Number-Crunching Without Recoding

April 4, 2018

Via: InfoWorld

So you’ve probably been using Python for prototyping data science and number-crunching jobs, but when it comes to putting code into production, you go for some variant of C. Why? Well, by its very nature, Python is single-threaded, and the global interpreter lock (GIL) is the main culprit, forcing threads to wait for completion before launching another. The end effect is an awesome interpreter that can be slower than molasses when it comes to big jobs.

What most “Pythonistas” don’t know is that the performance bottleneck for Python code has been largely eliminated, without the need to change the Python code at all! You can get machine-language execution speeds, unlock the GIL blockade, and enable Python to take advantage of multiple threads and cores for nearly every project by utilizing a group of libraries and tools created by none other than Intel.

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