Replace Klaxon with kotlinx-serialization

[devcrocod]

This is the first step in migrating from klaxon to kotlinx-serialization #312

• Removed klaxon dependency
• Added kotlinx-serialization
• Klaxon objects replaced with JsonElement from serialization
• All other behavior is preserved. Unlike klaxon, kotlinx-serialization works better with primitives. For example, klaxon does not work with float, only with double, so I had to specially handle the float case. Also, nulls are wrapped in serialization.

This PR should be accepted after #574, after which I will resolve the conflicts.

[Jolanrensen]

What do you mean with "specially handle the float case". Looking at your code I see you skip it and convert it to a Double sometimes. I don't really understand why; DataFrame understands Floats just fine, so you can keep them as Floats

[zaleslaw]

@devcrocod you wrote that this is a first step, what could be the next step?

[devcrocod]

@devcrocod you wrote that this is a first step, what could be the next step?

Check related issue

[devcrocod]

What do you mean with "specially handle the float case". Looking at your code I see you skip it and convert it to a Double sometimes. I don't really understand why; DataFrame understands Floats just fine, so you can keep them as Floats

By default, klaxon translates all floating-point numbers into Double. kotlinx-serialization can work with float. So, the question here is not what DataFrame can do, but what klaxon could do. It was possible to support Float in JSON parsing, but then it would have been necessary to additionally change the logic in JSON parsing. I decided not to do this because these subsequent parsers should ultimately change, and because it maximally preserves the previous behavior of the library.

[Jolanrensen]

What do you mean with "specially handle the float case". Looking at your code I see you skip it and convert it to a Double sometimes. I don't really understand why; DataFrame understands Floats just fine, so you can keep them as Floats

By default, klaxon translates all floating-point numbers into Double. kotlinx-serialization can work with float. So, the question here is not what DataFrame can do, but what klaxon could do. It was possible to support Float in JSON parsing, but then it would have been necessary to additionally change the logic in JSON parsing. I decided not to do this because these subsequent parsers should ultimately change, and because it maximally preserves the previous behavior of the library.

I think the previous behavior of the library was not intended, but rather a limit imposed on the library by Klaxon. It seems odd to keep this broken behavior if both Kotlinx-serialization ánd DataFrame support Floats to convert them to Doubles. So yes, this might require updating some tests and logic, but it's ultimately for the best I believe.

[devcrocod]

I agree that such behavior is not entirely correct, as it also carries computational errors when converting float to double. But I will repeat that this behavior will be changed in the future when serializers for dataframe objects are written.

Moreover, in the current version, there is a question:
During serialization, it's obvious how it should look:

1.1f -> 1.1 (float)
1.1 -> 1.100000 (double)

But during deserialization, we look at each element, and the logic is as follows: if the number fits within 32, then it's a float; if it's more than 32, then it's a double. And it turns out that our list can easily contain both Float and Double, and instead of the output type being Double, we get Number.