big-o / cherrypicker

A Python package for extracting flat tables of data from complex structures.

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.