Cherrypicker

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 cherrypicker

cherrypicker 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.