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The official http://raymon.ai data profiling and logging library.

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Let users simply log bytes (instead of raymon types)

the report should be updated. ```json { "reference": {}, "alternativeA": {}, "component_reports": { "name": { "drift": {}, "invalids": {}, "cardinality": {} } }, "global_reports": { "scores": {}, "global_drift": {} }...

We should make the example notebooks available on colab. This will make it easier to test.

For precipitation part, I created 5 class but I showed only 3 class(rain, snow, clear) in the output. After predicting, I converted "light_rain and snowing" into "rain and snow".

From: https://setuptools.readthedocs.io/en/latest/pkg_resources.html > Use of pkg_resources is discouraged in favor of importlib.resources, importlib.metadata, and their backports (resources, metadata). Please consider using those libraries instead of pkg_resources. https://docs.python.org/3/library/importlib.html#module-importlib.resources

enhancement

When logging nested data, we should gracefully check for types like `np.int64` and such and convert them to something json dumpable. Packes will probably exist for this.