# Buildsheet autogenerated by ravenadm tool -- Do not edit. NAMEBASE= python-jsonpickle VERSION= 3.2.2 KEYWORDS= python VARIANTS= v11 v12 SDESC[v11]= Serialize arbitrary object graph into JSON (3.11) SDESC[v12]= Serialize arbitrary object graph into JSON (3.12) HOMEPAGE= https://github.com/jsonpickle/jsonpickle CONTACT= Python_Automaton[python@ironwolf.systems] DOWNLOAD_GROUPS= main SITES[main]= PYPIWHL/e4/cb/1fb5ed5f1bc65779f0a14cb428ffe205924b2941ca50c53cfa566aed9583 DISTFILE[1]= jsonpickle-3.2.2-py3-none-any.whl:main DF_INDEX= 1 SPKGS[v11]= single SPKGS[v12]= single OPTIONS_AVAILABLE= PY311 PY312 OPTIONS_STANDARD= none VOPTS[v11]= PY311=ON PY312=OFF VOPTS[v12]= PY311=OFF PY312=ON USES= cpe DISTNAME= jsonpickle-3.2.2.dist-info CPE_PRODUCT= jsonpickle CPE_VENDOR= jsonpickle_project GENERATED= yes [PY311].USES_ON= python:v11,wheel [PY312].USES_ON= python:v12,wheel [FILE:2625: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]. 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 [FILE:112:distinfo] 87cd82d237fd72c5a34970e7222dddc0accc13fddf49af84111887ed9a9445aa 41758 jsonpickle-3.2.2-py3-none-any.whl