# Buildsheet autogenerated by ravenadm tool -- Do not edit.

NAMEBASE=		python-jsonpickle
VERSION=		4.0.0
KEYWORDS=		python
VARIANTS=		v12 v13
SDESC[v12]=		Serialize arbitrary object graph into JSON (3.12)
SDESC[v13]=		Serialize arbitrary object graph into JSON (3.13)
HOMEPAGE=		https://jsonpickle.readthedocs.io/
CONTACT=		Python_Automaton[python@ironwolf.systems]

DOWNLOAD_GROUPS=	main
SITES[main]=		PYPIWHL/a1/64/815460f86d94c9e1431800a75061719824c6fef14d88a6117eba3126cd5b
DISTFILE[1]=		jsonpickle-4.0.0-py3-none-any.whl:main
DIST_SUBDIR=		python-src
DF_INDEX=		1
SPKGS[v12]=		single
SPKGS[v13]=		single

OPTIONS_AVAILABLE=	PY312 PY313
OPTIONS_STANDARD=	none
VOPTS[v12]=		PY312=ON PY313=OFF
VOPTS[v13]=		PY312=OFF PY313=ON

USES=			cpe

DISTNAME=		jsonpickle-4.0.0.dist-info

CPE_PRODUCT=		jsonpickle
CPE_VENDOR=		jsonpickle_project
GENERATED=		yes

[PY312].USES_ON=			python:v12,wheel

[PY313].USES_ON=			python:v13,wheel

[FILE:2790:descriptions/desc.single]


   :alt: Github Actions

   :alt: BSD

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].

Usage
=====
The following is a very simple example of how one can use jsonpickle in
their scripts/projects. Note the usage of jsonpickle.encode and decode, and
how the data is written/encoded to a file and then read/decoded from the
file.

.. code-block:: python

    import jsonpickle
    from dataclasses import dataclass
   
    @dataclass
    class Example:
        data: str
   
   
    ex = Example("value1")
    encoded_instance = jsonpickle.encode(ex)
    assert encoded_instance == '{"py/object": "__main__.Example", "data":
"value1"}'
   
    with open("example.json", "w+") as f:
        f.write(encoded_instance)
   
    with open("example.json", "r+") as f:
        written_instance = f.read()
        decoded_instance = jsonpickle.decode(written_instance)
    assert decoded_instance == ex

For more examples, see the [examples directory on GitHub] for example
scripts. These can be run on your local machine to see how jsonpickle works
and behaves, and how to use it. Contributions from users regarding how they
use jsonpickle are welcome!

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:

::



[FILE:123:distinfo]
53730b9e094bc41f540bfdd25eaf6e6cf43811590e9e1477abcec44b866ddcd9        46157 python-src/jsonpickle-4.0.0-py3-none-any.whl