jdata 0.3.0

Encoding and decoding Python data structrues using portable JData-annotated formats

JData for Python - a lightweight and portable data annotation method

• Copyright: (C) Qianqian Fang (2019) <q.fang at neu.edu>
• License: Apache License, Version 2.0
• Version: 0.2
• URL: https://github.com/fangq/pyjdata

The JData Specification defines a lightweight language-independent data annotation interface targetted at storing and sharing complex data structures across different programming languages such as MATLAB, JavaScript, Python etc. Using JData formats, a complex Python data structure can be encoded as a dict object that is easily serialized as a JSON/binary JSON file and share such data between programs of different languages.

How to install

• Github: download from https://github.com/fangq/pyjdata
• PIP: run pip install jdata see https://pypi.org/project/jdata/

Optional Dependency (if reading or writing Binary JData/UBJSON files):

• bjdata: PIP: run pip install bjdata see https://pypi.org/project/bjdata/
• numpy: PIP: run pip install numpy or sudo apt-get install python-numpy

How to use

The PyJData module is easy to use. You can use the encode()/decode() functions to encode Python data into JData annotation format, or decode JData structures into native Python data, for example

import jdata as jd
import numpy as np
a={'str':'test','num':1.2,'list':[1.1,[2.1]],'nan':float('nan'),'np':np.arange(1,5,dtype=np.uint8)}
jd.encode(a)
jd.decode(jd.encode(a))
d1=jd.encode(a,{'compression':'zlib','base64':1})
d1
jd.decode(d1,{'base64':1})

One can further save the JData annotated data into JSON or binary JSON (UBJSON) files using the jdata.save function, or loading JData-formatted data to Python using jdata.load

import jdata as jd
import numpy as np
a={'str':'test','num':1.2,'list':[1.1,[2.1]],'nan':float('nan'),'np':np.arange(1,5,dtype=np.uint8)}
jd.save(a,'test.json')
newdata=jd.load('test.json')
newdata