JSON in data science projects: tips & tricks

• orjson

  17 5,540 8.3 Python

  Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy

orjson is the fastest JSON library available for python. It natively manages dataclass objects, datetime, numpy and UUID objects.

• NumPy

  272 26,360 10.0 Python

  The fundamental package for scientific computing with Python.

  

Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:

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• jsonlines

  5 118 5.3 CSS

  Documentation for the JSON Lines text file format

This can be remedied by using the [JSON Lines] format (https://jsonlines.org/). This involves nothing more and nothing less than placing one JSON object per line, so that you can browse the objects without having to parse the entire collection all at once.

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