Flatten complex data.
cherrypicker aims to make common ETL tasks (filtering data and restructuring it into flat tables) easier, by taking inspiration from jQuery and applying it in a Pythonic way to generic data objects.
pip install cherrypickercherrypicker provides a chainable filter and extraction interface to allow you to easily pick out objects from complex structures and place them in a flat table. It fills a similar role to jQuery in JavaScript, enabling you to navigate complex structures without the need for lots of complex nested for loops or list comprehensions.
Examples
>>> from cherrypicker import CherryPicker
>>> import json
>>> with open('climate.json', 'r') as fp:
... data = json.load(fp)
>>> picker = CherryPicker(data)>>> picker['id', 'city'].get()
[[1, 'Amsterdam'], [2, 'Athens'], [3, 'Atlanta GA'], ...]>>> picker(city='B*')['info'](
... population=lambda n: n > 2000000,
... area=lambda a: a < 2000
... )['area', 'population'].get()
[[1568, 8300000], [891, 3700000], [203, 2800000]]More complex filtering and flattening of nested structures is possible. Learn more in the documentation: https://cherrypicker.readthedocs.io.
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