zincware / znjson Goto Github PK

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

provide patched zndraw.json module and a magic patch

Currently large numpy arrays will be stored uncompressed and can take a lot of space.

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.

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"}.

The package https://github.com/jsonpickle/jsonpickle provides similar functionality

A numpy (and maybe also pandas) converter could also convert to lists instead of binary.
This could be useful for small arrays.

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..