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

Project description

# JData for Python - a lightweight and portable data annotation method

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

If you download a local copy via git clone or github download, after unzipping the package, you can

## 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 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)},'test.json') newdata=jd.load('test.json') newdata `

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