Provide None defaults for pydantic parameters

lsst · Jul 3, 2023 · 6934312 · 6934312
1 parent 6618b21
commit 6934312
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Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/python/lsst/daf/butler/core/datastoreCacheManager.py b/python/lsst/daf/butler/core/datastoreCacheManager.py
@@ -135,7 +135,7 @@ class CacheEntry(BaseModel):
     ref: DatasetId
     """ID of this dataset."""
 
-    component: str | None
+    component: str | None = None
     """Component for this disassembled composite (optional)."""
 
     @classmethod

diff --git a/python/lsst/daf/butler/core/logging.py b/python/lsst/daf/butler/core/logging.py
@@ -175,10 +175,10 @@ class ButlerLogRecord(BaseModel):
     filename: str
     pathname: str
     lineno: int
-    funcName: str | None
+    funcName: str | None = None
     process: int
     processName: str
-    exc_info: str | None
+    exc_info: str | None = None
     MDC: dict[str, str]
 
     class Config:

diff --git a/python/lsst/daf/butler/core/quantum.py b/python/lsst/daf/butler/core/quantum.py
@@ -78,8 +78,8 @@ def _reconstructDatasetRef(
 class SerializedQuantum(BaseModel):
     """Simplified model of a `Quantum` suitable for serialization."""
 
-    taskName: str | None
-    dataId: SerializedDataCoordinate | None
+    taskName: str | None = None
+    dataId: SerializedDataCoordinate | None = None
     datasetTypeMapping: Mapping[str, SerializedDatasetType]
     initInputs: Mapping[str, tuple[SerializedDatasetRef, list[int]]]
     inputs: Mapping[str, list[tuple[SerializedDatasetRef, list[int]]]]

diff --git a/python/lsst/daf/butler/tests/_examplePythonTypes.py b/python/lsst/daf/butler/tests/_examplePythonTypes.py
@@ -266,9 +266,9 @@ def makeFromDict(cls, exportDict: dict[str, list | dict | None]) -> MetricsExamp
 class MetricsExampleModel(BaseModel):
     """A variant of `MetricsExample` based on model."""
 
-    summary: dict[str, Any] | None
-    output: dict[str, Any] | None
-    data: list[Any] | None
+    summary: dict[str, Any] | None = None
+    output: dict[str, Any] | None = None
+    data: list[Any] | None = None
 
     @classmethod
     def from_metrics(cls, metrics: MetricsExample) -> MetricsExampleModel: