{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/6"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"}],"enrichment":{"capability":"Serializes and deserializes NumPy arrays and Python complex types using the msgpack binary format, preserving numerical data types during encoding and decoding.","skillfed_tags":["serialization","numpy-integration"],"use_cases":["Serialize NumPy arrays for storage or network transmission while preserving dtype information across systems.","Exchange numerical data between Python processes or services using msgpack's efficient binary protocol.","Monkey-patch msgpack in a library or application to make all downstream serialization NumPy-aware without code changes.","Manually encode/decode specific NumPy arrays in a custom serialization pipeline where msgpack is already in use.","Handle Python complex numbers in msgpack serialization when NumPy arrays are not the primary payload."],"what_it_does":"msgpack-numpy bridges NumPy and msgpack by adding custom encoders and decoders that let you serialize NumPy arrays and Python complex numbers into msgpack's compact binary format while preserving their data types. It works in two modes: monkey-patching msgpack globally to make all serialization NumPy-aware, or passing its encoder and decoder functions manually to msgpack routines.\n\nThe package trades some storage overhead for type fidelity\u2014serialized data includes type information so deserialized arrays come back as the correct dtype. For object-dtype arrays, it falls back to pickle, which adds overhead and negates some of msgpack's efficiency gains. Deserialized arrays are read-only and must be copied if you need to modify them.","worth_installing":"Yes, if you need to serialize NumPy arrays with msgpack and your project tolerates dormant maintenance. The package is stable, has no known vulnerabilities, and low install friction. However, verify compatibility with your Python version (last release was 2022-06-09) and confirm that read-only deserialized arrays and the object-dtype pickle fallback fit your workflow."},"id":"msgpack-numpy","links":{"html":"https://skillfed.io/packages/msgpack-numpy","md":"https://skillfed.io/packages/msgpack-numpy.md","pypi":"https://pypi.org/project/msgpack-numpy/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2022-06-09","license_spdx":null,"license_treatment":"permissive","name":"msgpack-numpy","python_support":"unspecified","summary":"Numpy data serialization using msgpack"},"popularity":{"monthly_downloads":1129000,"position":4321,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.4.8"}