feat(ingest): support dynamic imports for transfomer methods

metadata-ingestion/src/datahub/configuration/import_resolver.py

@@ -0,0 +1,13 @@
+import pydantic
+
+from datahub.ingestion.api.registry import import_key
+
+
+def _pydantic_resolver(v):
+    if isinstance(v, str):
+        return import_key(v)
+    return v
+
+
+def pydantic_resolve_key(field):
+    return pydantic.validator(field, pre=True, allow_reuse=True)(_pydantic_resolver)

metadata-ingestion/src/datahub/ingestion/api/registry.py

@@ -1,6 +1,6 @@
 import importlib
 import inspect
-from typing import Dict, Generic, Type, TypeVar, Union
+from typing import Any, Dict, Generic, Type, TypeVar, Union
 
 import entrypoints
 import typing_inspect
@@ -11,6 +11,13 @@
 T = TypeVar("T")
 
 
+def import_key(key: str) -> Any:
+    assert "." in key, "import key must contain a ."
+    module_name, item_name = key.rsplit(".", 1)
+    item = getattr(importlib.import_module(module_name), item_name)
+    return item
+
+
 class Registry(Generic[T]):
     def __init__(self):
         self._mapping: Dict[str, Union[Type[T], Exception]] = {}
@@ -68,8 +75,7 @@ def get(self, key: str) -> Type[T]:
         if key.find(".") >= 0:
             # If the key contains a dot, we treat it as a import path and attempt
             # to load it dynamically.
-            module_name, class_name = key.rsplit(".", 1)
-            MyClass = getattr(importlib.import_module(module_name), class_name)
+            MyClass = import_key(key)
             self._check_cls(MyClass)
             return MyClass
 

metadata-ingestion/src/datahub/ingestion/transformer/add_dataset_ownership.py

@@ -2,6 +2,7 @@
 
 import datahub.emitter.mce_builder as builder
 from datahub.configuration.common import ConfigModel
+from datahub.configuration.import_resolver import pydantic_resolve_key
 from datahub.ingestion.api.common import PipelineContext, RecordEnvelope
 from datahub.ingestion.api.transform import Transformer
 from datahub.metadata.schema_classes import (
@@ -22,6 +23,8 @@ class AddDatasetOwnershipConfig(ConfigModel):
     ]
     default_actor: str = builder.make_user_urn("etl")
 
+    _resolve_owner_fn = pydantic_resolve_key("get_owners_to_add")
+
 
 class AddDatasetOwnership(Transformer):
     """Transformer that adds owners to datasets according to a callback function."""

metadata-ingestion/src/datahub/ingestion/transformer/add_dataset_tags.py

@@ -2,6 +2,7 @@
 
 import datahub.emitter.mce_builder as builder
 from datahub.configuration.common import ConfigModel
+from datahub.configuration.import_resolver import pydantic_resolve_key
 from datahub.ingestion.api.common import PipelineContext, RecordEnvelope
 from datahub.ingestion.api.transform import Transformer
 from datahub.metadata.schema_classes import (
@@ -20,6 +21,8 @@ class AddDatasetTagsConfig(ConfigModel):
         Callable[[DatasetSnapshotClass], List[TagAssociationClass]],
     ]
 
+    _resolve_tag_fn = pydantic_resolve_key("get_tags_to_add")
+
 
 class AddDatasetTags(Transformer):
     """Transformer that adds tags to datasets according to a callback function."""

metadata-ingestion/tests/unit/test_transform_dataset.py

@@ -4,7 +4,10 @@
 from datahub.ingestion.transformer.add_dataset_ownership import (
     SimpleAddDatasetOwnership,
 )
-from datahub.ingestion.transformer.add_dataset_tags import SimpleAddDatasetTags
+from datahub.ingestion.transformer.add_dataset_tags import (
+    AddDatasetTags,
+    SimpleAddDatasetTags,
+)
 
 
 def make_generic_dataset():
@@ -120,3 +123,22 @@ def test_simple_dataset_tags_transformation(mock_time):
     assert tags_aspect
     assert len(tags_aspect.tags) == 2
     assert tags_aspect.tags[0].tag == builder.make_tag_urn("NeedsDocumentation")
+
+
+def dummy_tag_resolver_method(dataset_snapshot):
+    return []
+
+
+def test_import_resolver():
+    transformer = AddDatasetTags.create(
+        {
+            "get_tags_to_add": "tests.unit.test_transform_dataset.dummy_tag_resolver_method"
+        },
+        PipelineContext(run_id="test-tags"),
+    )
+    output = list(
+        transformer.transform(
+            [RecordEnvelope(input, metadata={}) for input in [make_generic_dataset()]]
+        )
+    )
+    assert output