[record] update __doc__ (#22952)

so apidocs work

added test

`make apidoc-build`
` make next-watch-build`
load docs and ensure api entry for `DbtProject`

docs/sphinx/_ext/dagster-sphinx/dagster_sphinx/__init__.py

@@ -12,6 +12,7 @@
     is_experimental,
     is_public,
 )
+from dagster._record import get_original_class, is_record
 from sphinx.application import Sphinx
 from sphinx.environment import BuildEnvironment
 from sphinx.ext.autodoc import (
@@ -86,6 +87,11 @@ class DagsterClassDocumenter(ClassDocumenter):
     objtype = "class"
 
     def get_object_members(self, want_all: bool) -> Tuple[bool, ObjectMembers]:
+        # the @record transform creates a new outer class, so redirect
+        # sphinx to target the original class for scraping members out of __dict__
+        if is_record(self.object):
+            self.object = get_original_class(self.object)
+
         _, unfiltered_members = super().get_object_members(want_all)
         # Use form `is_public(self.object, attr_name) if possible, because to access a descriptor
         # object (returned by e.g. `@staticmethod`) you need to go in through

python_modules/dagster/dagster/_record/__init__.py

@@ -32,6 +32,7 @@
 _CHECKED_NEW = "__checked_new__"
 _DEFAULTS_NEW = "__defaults_new__"
 _INJECTED_DEFAULT_VALS_LOCAL_VAR = "__dm_defaults__"
+_ORIGINAL_CLASS_FIELD = "__original_class__"
 
 
 def _namedtuple_model_transform(
@@ -114,15 +115,17 @@ def _namedtuple_model_transform(
             _RECORD_MARKER_FIELD: _RECORD_MARKER_VALUE,
             _RECORD_ANNOTATIONS_FIELD: field_set,
             "__nt_new__": nt_new,
+            _ORIGINAL_CLASS_FIELD: cls,
             "__bool__": _true,
             "__reduce__": _reduce,
+            # functools doesn't work, so manually update_wrapper
+            "__module__": cls.__module__,
+            "__qualname__": cls.__qualname__,
+            "__annotations__": field_set,
+            "__doc__": cls.__doc__,
         },
     )
 
-    # functools doesn't work, so manually update_wrapper
-    new_type.__module__ = cls.__module__
-    new_type.__qualname__ = cls.__qualname__
-
     return new_type  # type: ignore
 
 
@@ -247,9 +250,15 @@ def has_generated_new(obj) -> bool:
 
 
 def get_record_annotations(obj) -> Mapping[str, Type]:
+    check.invariant(is_record(obj), "Only works for @record decorated classes")
     return getattr(obj, _RECORD_ANNOTATIONS_FIELD)
 
 
+def get_original_class(obj):
+    check.invariant(is_record(obj), "Only works for @record decorated classes")
+    return getattr(obj, _ORIGINAL_CLASS_FIELD)
+
+
 def as_dict(obj) -> Mapping[str, Any]:
     """Creates a dict representation of a model."""
     if not is_record(obj):

python_modules/dagster/dagster_tests/general_tests/test_record.py

@@ -402,3 +402,11 @@ def _some_func():
         @record
         class _(Base):
             thing: Any = _some_func
+
+
+def test_docs():
+    @record
+    class Documented:
+        """So much to know about this class."""
+
+    assert Documented.__doc__

python_modules/libraries/dagster-dbt/dagster_dbt/dbt_project.py

@@ -137,8 +137,8 @@ class DbtProject(IHaveNew):
 
     Using this helps achieve a setup where the dbt manifest file
     and dbt dependencies are available and up-to-date:
-        * during development, pull the dependencies and reload the manifest at run time to pick up any changes.
-        * when deployed, expect a manifest that was created at build time to reduce start-up time.
+    * during development, pull the dependencies and reload the manifest at run time to pick up any changes.
+    * when deployed, expect a manifest that was created at build time to reduce start-up time.
 
     The cli ``dagster-dbt project prepare-and-package`` can be used as part of the deployment process to
     handle the project preparation.