Gael Varoquaux • 5/20/2016

Better Python compressed persistence in joblib

This technical article details recent enhancements to the joblib Python library for persisting large data objects. It covers the limitations of the old implementation, such as high memory usage during compressed dumps/loads and multiple file generation for large numpy arrays. The new version offers stable memory consumption, single-file persistence, support for more compression formats, and maintains backward compatibility, making it more efficient for big data workflows.

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#Python #compression #Persistence