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jsonpickle
==========
jsonpickle is a library for the two-way conversion of complex Python
objects
and [JSON]. jsonpickle builds upon existing JSON
encoders, such as simplejson, json, and ujson.
.. warning::
jsonpickle can execute arbitrary Python code.
Please see the Security section for more details.
For complete documentation, please visit the
[jsonpickle documentation].
Bug reports and merge requests are encouraged at the
[jsonpickle repository on github].
Why jsonpickle?
===============
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.
Security
========
jsonpickle should be treated the same as the
[Python stdlib pickle module]
from a security perspective.
.. warning::
The jsonpickle module **is not secure**. Only unpickle data you trust.
It is possible to construct malicious pickle data which will **execute
arbitrary code during unpickling**. Never unpickle data that could have
come
from an untrusted source, or that could have been tampered with.
Consider signing data with an HMAC if you need to ensure that it has not
been tampered with.
Safer deserialization approaches, such as reading JSON directly,
may be more appropriate if you are processing untrusted data.
Install
=======
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
Numpy/Pandas Support
====================
jsonpickle includes built-in numpy and pandas extensions. If you would
like to encode sklearn models, numpy arrays, pandas DataFrames, and other
numpy/pandas-based data, then you must enable the numpy and/or pandas
extensions by registering their handlers::
>>> import jsonpickle.ext.numpy as jsonpickle_numpy
>>> import jsonpickle.ext.pandas as jsonpickle_pandas
>>> jsonpickle_numpy.register_handlers()
>>> jsonpickle_pandas.register_handlers()
Development
===========
Use `make` to run the unit tests::
make test
`pytest` is used to run unit tests internally.
A `tox` target is provided to run tests using all installed and supported
Python versions::
make tox
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