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Learn how to process large JSON files in Python without running out of memory or experiencing crashes in this 30-minute conference talk from PyCon US. Discover techniques for measuring memory usage and understand why loading JSON consumes excessive memory resources. Master practical solutions including implementing more efficient in-memory representations, loading only necessary data subsets, utilizing streaming parsing for arbitrarily-large files with fixed memory allocation, and adopting alternative file formats like JSON Lines. Gain essential skills for handling large-scale data processing while optimizing memory usage and reducing cloud computing costs.
Syllabus
Processing large JSON files without running out of memory - Itamar Turner-Trauring
Taught by
PyCon US