REGR: setting numeric value in Categorical Series with enlargement raise internal error

[jorisvandenbossche]

With the last release, we have this behaviour (when setting with enlargement, we cast the categorical dtype to object):

In [1]: pd.__version__
Out[1]: '1.4.3'

In [2]: s = pd.Series(["a", "b", "c"], dtype="category")

In [3]: s.loc[3] = 0

In [4]: s
Out[4]: 
0    a
1    b
2    c
3    0
dtype: object

However on the main branch I see:

In [1]: s = pd.Series(["a", "b", "c"], dtype="category")

In [2]: s.loc[3] = 0
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File ~/scipy/pandas/pandas/core/dtypes/cast.py:558, in maybe_promote(dtype, fill_value)
    555 try:
    556     # error: Argument 3 to "__call__" of "_lru_cache_wrapper" has incompatible type
    557     # "Type[Any]"; expected "Hashable"  [arg-type]
--> 558     return _maybe_promote_cached(
    559         dtype, fill_value, type(fill_value)  # type: ignore[arg-type]
    560     )
    561 except TypeError:
    562     # if fill_value is not hashable (required for caching)

File ~/scipy/pandas/pandas/core/dtypes/cast.py:571, in _maybe_promote_cached(dtype, fill_value, fill_value_type)
    566 @functools.lru_cache(maxsize=128)
    567 def _maybe_promote_cached(dtype, fill_value, fill_value_type):
    568     # The cached version of _maybe_promote below
    569     # This also use fill_value_type as (unused) argument to use this in the
    570     # cache lookup -> to differentiate 1 and True
--> 571     return _maybe_promote(dtype, fill_value)

File ~/scipy/pandas/pandas/core/dtypes/cast.py:704, in _maybe_promote(dtype, fill_value)
    702     dtype = np.dtype(np.object_)
--> 704 fill_value = _ensure_dtype_type(fill_value, dtype)
    705 return dtype, fill_value

File ~/scipy/pandas/pandas/core/dtypes/cast.py:730, in _ensure_dtype_type(value, dtype)
    729 # Note: before we get here we have already excluded isna(value)
--> 730 return dtype.type(value)

TypeError: type.__new__() takes exactly 3 arguments (1 given)

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
Input In [2], in <cell line: 1>()
----> 1 s.loc[3] = 0

File ~/scipy/pandas/pandas/core/indexing.py:816, in _LocationIndexer.__setitem__(self, key, value)
    813 self._has_valid_setitem_indexer(key)
    815 iloc = self if self.name == "iloc" else self.obj.iloc
--> 816 iloc._setitem_with_indexer(indexer, value, self.name)

File ~/scipy/pandas/pandas/core/indexing.py:1780, in _iLocIndexer._setitem_with_indexer(self, indexer, value, name)
   1777     indexer, missing = convert_missing_indexer(indexer)
   1779     if missing:
-> 1780         self._setitem_with_indexer_missing(indexer, value)
   1781         return
   1783 if name == "loc":
   1784     # must come after setting of missing

File ~/scipy/pandas/pandas/core/indexing.py:2115, in _iLocIndexer._setitem_with_indexer_missing(self, indexer, value)
   2113     curr_dtype = self.obj.dtype
   2114     curr_dtype = getattr(curr_dtype, "numpy_dtype", curr_dtype)
-> 2115     new_dtype = maybe_promote(curr_dtype, value)[0]
   2116 else:
   2117     new_dtype = None

File ~/scipy/pandas/pandas/core/dtypes/cast.py:563, in maybe_promote(dtype, fill_value)
    558     return _maybe_promote_cached(
    559         dtype, fill_value, type(fill_value)  # type: ignore[arg-type]
    560     )
    561 except TypeError:
    562     # if fill_value is not hashable (required for caching)
--> 563     return _maybe_promote(dtype, fill_value)

File ~/scipy/pandas/pandas/core/dtypes/cast.py:704, in _maybe_promote(dtype, fill_value)
    701 if issubclass(dtype.type, (bytes, str)):
    702     dtype = np.dtype(np.object_)
--> 704 fill_value = _ensure_dtype_type(fill_value, dtype)
    705 return dtype, fill_value

File ~/scipy/pandas/pandas/core/dtypes/cast.py:730, in _ensure_dtype_type(value, dtype)
    727     return value
    729 # Note: before we get here we have already excluded isna(value)
--> 730 return dtype.type(value)

TypeError: type.__new__() takes exactly 3 arguments (1 given)

[CloseChoice]

First bad commit: bd9a6f0
#47342

cc @phofl

[CloseChoice]

The underlying issue here is that maybe_promote does not work for pd.CategoricalDtype and int correctly,
This throws an error, even before the bad commit. The bad commit just used a route where this function gets called

a = pd.CategoricalDtype(categories=['a', 'b', 'c'], ordered=False)
pd.core.dtypes.cast.maybe_promote(a, 0)