Python JSON encoder convert NaNs to null instead

1. As @Gerrat points out, your hook dumps(d, cls=NanConverter) unfortunately won't work.

2. @Alexander's simplejson.dumps(d, ignore_nan=True) works but introduces an additional dependency (simplejson).

If we introduce another dependency (pandas):

3. Another obvious solution would be dumps(pd.DataFrame(d).fillna(None)), but Pandas issue 1972 notes that d.fillna(None) will have unpredictable behaviour:

   Note that fillna(None) is equivalent to fillna(), which means the value parameter is unused. Instead, it uses the method parameter which is by default forward fill.

4. So instead, use DataFrame.where:

   df = pd.DataFrame(d)
   dumps(df.where(pd.notnull(df), None)))
   

Unfortunately, you probably need to use @Bramar's suggestion. You're not going to be able to use this directly. The documentation for Python's JSON encoder states:

If specified, default is a function that gets called for objects that can’t otherwise be serialized

Your NanConverter.default method isn't even being called, since Python's JSON encoder already knows how to serialize np.nan. Add some logging/print statements - you'll see your method isn't even being called.

This seems to achieve my objective:

import simplejson


>>> simplejson.dumps(d, ignore_nan=True)
Out[3]: '{"a": 1, "c": 3, "b": 2, "e": null, "f": [1, null, 3]}'