Types from typing before Python 3.10 didn't have a __name__ attribu…

…te, so split it up the hard way since there doesn't appear to be any other way to acess the name.

This is the single most frustrating bug to track down since the error is thrown in pydantic but doesn't backtrace through the pydantic.__getattr__ -> `AutoPydanticDocGenerator` -> `__get__` -> `doc_formatter` -> `annotation.__name__` function because all the exceptions are caught the whole way up. GYA!

qcelemental/models/types.py

@@ -1,3 +1,4 @@
+import warnings
 from typing import Any, Dict
 
 import numpy as np
@@ -66,6 +67,9 @@ def __get_pydantic_json_schema__(cls, _core_schema, handler) -> Dict[str, Any]:
  items = {"type": "string"}
  elif dt is bool or np.issubdtype(dt, np.bool_):
  items = {"type": "boolean"}
+ else:
+ items = {"type": "Unknown"}
+ warnings.warn(f"Unknown dtype to handle type [{dt}] for array. May result in weird serialization or typing")
  output_schema.update(type="array", items=items)
  return output_schema
 

qcelemental/util/autodocs.py

@@ -59,7 +59,13 @@ def parse_type_str(prop: Union[FieldInfo, type]) -> str:
  elif annotation.__module__ == "typing":
  # Typing Types
  prop_type_str = ""
- base_name = annotation.__name__
+ # In python 3.9 and below, annotations didn't have __name__... so... do it the hard way
+ try:
+ base_name = annotation.__name__
+ except AttributeError:
+ splits = re.split(r"\.|\[", str(annotation))
+ # typing, {actual object name}, args... So get index 1
+ base_name = splits[1]
  # Special case Optional
  annotation_args = get_args(annotation)
  prop_type_str += f"{base_name}"