Extending the python json package functionality
Project description
Project: https://github.com/chrisjsewell/jsonextended
A module to extend the python json package functionality:
decoding/encoding between the on-disk JSON structure and in-memory nested dictionary structure, including:
treating path structures, with nested directories and multiple .json files, as a single json.
on-disk indexing of the json structure (using the ijson package)
extended data type serialisation (numpy.ndarray, Decimals, pint.Quantities,…)
viewing and manipulating the nested dictionaries:
enhanced pretty printer
Javascript rendered, expandable tree in the Jupyter Notebook
filter, merge, flatten, unflatten functions
Units schema concept to apply and convert physical units (using the pint package)
Parser abstract class for dealing with converting other file formats to JSON
Installation
pip install jsonextended
jsonextended has no import dependancies, on Python 3.x and only pathlib2 on 2.7 but, for full functionallity, it is advised to install the following packages:
conda install -c conda-forge ijson numpy pandas pint
Examples
For more information, all functions contain docstrings with tested examples.
Data Folders JSONisation
import jsonextended as ejson
path = ejson.get_test_path()
ejson.json_keys(path)['dir1', 'dir2', 'dir3']
jdict1 = ejson.json_to_dict(path)
ejson.dict_pprint(jdict1,depth=2)dir1:
dir1_1: {...}
file1: {...}
file2: {...}
dir2:
file1: {...}
dir3:
ejson.dict_to_html(jdict1,depth=3)To try the rendered JSON tree, output in the Jupyter Notebook, go to : https://chrisjsewell.github.io/
Nested Dictionary Manipulation
jdict2 = ejson.json_to_dict(path,['dir1','file1'])
ejson.dict_pprint(jdict2,depth=1)initial: {...}
meta: {...}
optimised: {...}
units: {...}
filtered = ejson.dict_filter_keys(jdict2,['vol*'],use_wildcards=True)
ejson.dict_pprint(filtered)initial:
crystallographic:
volume: 924.62752781
primitive:
volume: 462.313764
optimised:
crystallographic:
volume: 1063.98960509
primitive:
volume: 531.994803
ejson.dict_pprint(ejson.dict_flatten(filtered))('initial', 'crystallographic', 'volume'): 924.62752781
('initial', 'primitive', 'volume'): 462.313764
('optimised', 'crystallographic', 'volume'): 1063.98960509
('optimised', 'primitive', 'volume'): 531.994803
Units Schema
Unit schema builds on the concept of standard jsonschema, whereby one JSON can be used to validate another.
In this case one JSON, containing physical units for a given key path, is applied to a data JSON.
from jsonextended.units import apply_unitschema, split_quantities
withunits = apply_unitschema(filtered,{'volume':'angstrom^3'})
ejson.dict_pprint(withunits)initial:
crystallographic:
volume: 924.62752781 Å ** 3
primitive:
volume: 462.313764 Å ** 3
optimised:
crystallographic:
volume: 1063.98960509 Å ** 3
primitive:
volume: 531.994803 Å ** 3
newunits = apply_unitschema(withunits,{'volume':'nm^3'})
ejson.dict_pprint(newunits)initial:
crystallographic:
volume: 0.92462752781 nm ** 3
primitive:
volume: 0.462313764 nm ** 3
optimised:
crystallographic:
volume: 1.06398960509 nm ** 3
primitive:
volume: 0.531994803 nm ** 3
ejson.dict_pprint(split_quantities(newunits),depth=4)initial:
crystallographic:
volume:
magnitude: 0.92462752781
units: nanometer ** 3
primitive:
volume:
magnitude: 0.462313764
units: nanometer ** 3
optimised:
crystallographic:
volume:
magnitude: 1.06398960509
units: nanometer ** 3
primitive:
volume:
magnitude: 0.531994803
units: nanometer ** 3
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