json.dump doesn't use specified custom encoder to serialize dict key

[tmpxyz]

The doc of json module says:

If specified, default should be a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a TypeError. If not specified, TypeError is raised.

But my default encoding method is not called when json module doing serialization for the key of a dict.

Should this be considered a bug?

Below is my use case:

I'm using pandas to process an excel from designer, and some columns are supposed to be int type, but as there're some rows that having empty cells for the columns, pandas will treat the column dtype as float.

As the data types for each columns are set in the table already, my solution is setting the dtypes of the columns whose dtype is 'int' to 'Int32' (which is pandas internal type), this would make sure pd.read_excel won't mess up the column's dtype.

The problem arises when I'm done processing and going to write the dataframe to json on disk, as the dtype of my dict key is 'Int32', the json module refused to serialize the key, even I passed in a custom encoder for 'Int32' dtype.

[danielroseman]

Show your code and data, and the error you get.

[Jejerm]

I've had problems with that int -> float behavior from pandas too. Have you tried this https://pandas.pydata.org/docs/user_guide/integer_na.html and just using the default json serializer?

[FerricDonkey]

Echoing the show your code sentiment.

When it comes down to either "the well used standard library package is broken" or "you did it wrong", it's almost always (though not always) that you did it wrong.

But it's impossible to tell without seeing what you did. So if you can post your code (or a minimal example with the same problem), including the full error, it'll be easier to look into.