Python Language Summit: Python Without the GIL

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • nogil

    Multithreaded Python without the GIL

  • That is just not true.

    1 - This helps parallelize regular python code too, like the kind that goes into writing web services.

    2 - While you'd still write native extensions to get optimum performance for single threaded code, having the thread dispatch layer in python makes parallelizing execution convenient and robust. For example, see this comment from people who maintain scikit-learn: (https://github.com/colesbury/nogil/issues/36#issuecomment-10...). I'd love to see python get composable task parallelism like Julia where you can freely spawn threads within threads without worrying about their lifetimes.

  • numpy

    The fundamental package for scientific computing with Python. (by colesbury)

  • Numpy.

    Here's a patch the author himself wrote to fix a spot where this change break's numpy's thread safety: https://github.com/colesbury/numpy/commit/2ad41a1fb8b0c28fa8...

    Maybe that's the only one? Maybe it isn't? But I think the point still stands that people saying this has the potential to break existing Python packages in subtle ways are not just being hyperbolic.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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