Here is information about the original jsonpickle library, that can be found here.
jsonpickle is a library for the two-way conversion of complex Python objects and JSON. jsonpickle builds upon the existing JSON encoders, such as simplejson, json, and demjson.
For complete documentation, please visit the jsonpickle homepage.
Bug reports and merge requests are encouraged at the jsonpickle repository on github.
jsonpickle supports Python 2.7 and Python 3.4 or greater.
This forked repository brings one major change: it preserves dictionary keys order when pickling. As discussed here, insertion key order preservation is now the rule in recent Python versions.
Though, in order to ensure this order preservation, only Python 3.6 and 3.7 are supported. The only supported backend is the native one: json module. Finally, setting sort_keys to True in the backend encoder options is no longer supported: this breaks the wanted behaviour, and may result in undefined behaviour.
Data serialized with python's pickle (or cPickle or dill) is not easily readable outside of python. Using the json format, jsonpickle allows simple data types to be stored in a human-readable format, and more complex data types such as numpy arrays and pandas dataframes, to be machine-readable on any platform that supports json. E.g., unlike pickled data, jsonpickled data stored in an Amazon S3 bucket is indexible by Amazon's Athena.
Install from pip for the latest stable release:
pip install jsonpickle
Install from github for the latest changes:
pip install git+https://github.com/jsonpickle/jsonpickle.git
If you have the files checked out for development:
git clone https://github.com/jsonpickle/jsonpickle.git cd jsonpickle python setup.py develop
jsonpickle includes a built-in numpy extension. If would like to encode sklearn models, numpy arrays, and other numpy-based data then you must enable the numpy extension by registering its handlers:
>>> import jsonpickle.ext.numpy as jsonpickle_numpy >>> jsonpickle_numpy.register_handlers()
jsonpickle includes a built-in pandas extension. If would like to encode pandas DataFrame or Series objects then you must enable the pandas extension by registering its handlers:
>>> import jsonpickle.ext.pandas as jsonpickle_pandas >>> jsonpickle_pandas.register_handlers()
jsonpickleJS is a javascript implementation of jsonpickle by Michael Scott Cuthbert. jsonpickleJS can be extremely useful for projects that have parallel data structures between Python and Javascript.
Licensed under the BSD License. See COPYING for details. See jsonpickleJS/LICENSE for details about the jsonpickleJS license.