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License: Apache License 2.0
Package to Encode/Decode some common file formats to json
License: Apache License 2.0
To avoid issues when e.g. de-serializing a dict {"Path": "this is some string"}
which should return a dict and not a Path object,
it would be possible to serialize all objects to the dict {<type>: val}
which would yield{"dict": {"Path": "this is some string"}}
and therefore can not be confused with {"Path": "this is some string"}
.
It is currently possible to register two converters with the same representation: str
which can be avoided by checking for uniqueness in the register command..
A numpy (and maybe also pandas) converter could also convert to lists instead of binary.
This could be useful for small arrays.
Currently if _type
is there it will try to deserialize and fail. Sometimes it could be useful to only serialize a specific type.
see https://github.com/zincware/ZnTrack/blob/4551776c4397a1fc12b82829cbf3ee292faeea55/zntrack/fields/zn/__init__.py#L316-L320
where we only would like to serialize the converters.
Currently you have to do:
znjson.config.register(CustomConverter)
json.dump(data, cls=znjson.ZnEncoder)
but maybe you only want to use a specific converter which could look something like:
json.dump(data, cls=znjson.ZnEncoder.from_converter(CustomConverter, allow_default=True)) # this could be a list of converters
# or
json.dump(data, cls=CustomConverter) # this would allow only one converter
Currently large numpy arrays will be stored uncompressed and can take a lot of space.
provide patched zndraw.json
module and a magic patch
Lines 7 to 16 in 553e366
The package https://github.com/jsonpickle/jsonpickle provides similar functionality
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