ENH: Add num_columns, num_rows to table spec

schema/definitions/0.8.0/examples/summary_table.yml

@@ -67,6 +67,8 @@ data:
       - FWPRH
       - WWPT:R_A4
       - WTIRWT1:A4
+    num_columns: 10
+    num_rows: 20
     size: 200
   table_index:
     - DATE

schema/definitions/0.8.0/examples/table_inplace.yml

@@ -112,11 +112,13 @@ data: # The data block describes the actual data (e.g. surface). Only present in
   grid_model: # Making this an object to allow for expanding in the future
     name: MyGrid # important for data identification, also important for other data types
   spec: # class/layout dependent, optional? Can spec be expanded to work for all data types?
-    size: 123921
     columns:
       - BULK_OIL
       - NET_OIL
       - PORE_OIL
+    num_columns: 3
+    num_rows: 41306
+    size: 123918
   is_prediction: true # A mechanism for separating pure QC output from actual predictions
   is_observation: false
   description:

schema/definitions/0.8.0/examples/table_wellpicks.yml

@@ -77,14 +77,16 @@ data: # The data block describes the actual data (e.g. surface). Only present in
   vertical_domain: depth # / time / null
   depth_reference: msl # / seabed / etc
   spec: # class/layout dependent, optional? Can spec be expanded to work for all data types?
-    size: 123921
     columns:
       - X_UTME
       - Y_UTMN
       - Z_TVDSS
       - MD
       - WELL
       - HORIZON
+    num_columns: 6
+    num_rows: 20653
+    size: 123918
   table_index:
     - WELL
     - HORIZON

schema/definitions/0.8.0/schema/fmu_results.json

@@ -7783,6 +7783,36 @@
           "title": "Columns",
           "type": "array"
         },
+        "num_columns": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "examples": [
+            1,
+            9999
+          ],
+          "title": "Num Columns"
+        },
+        "num_rows": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "examples": [
+            1,
+            9999
+          ],
+          "title": "Num Rows"
+        },
         "size": {
           "examples": [
             1,
@@ -7794,6 +7824,8 @@
       },
       "required": [
         "columns",
+        "num_columns",
+        "num_rows",
         "size"
       ],
       "title": "TableSpecification",

src/fmu/dataio/_model/specification.py

@@ -65,8 +65,14 @@ class TableSpecification(BaseModel):
     columns: List[str]
     """List of columns present in a table."""
 
+    num_columns: Optional[int] = Field(examples=[1, 9999])
+    """The number of columns in a table."""
+
+    num_rows: Optional[int] = Field(examples=[1, 9999])
+    """The number of rows in a table.."""
+
     size: int = Field(examples=[1, 9999])
-    """Size of data object."""
+    """The total size of the table, i.e. `rows x cols`."""
 
 
 class CPGridSpecification(RowColumnLayer):

src/fmu/dataio/providers/objectdata/_tables.py

@@ -96,8 +96,11 @@ def get_bbox(self) -> None:
     def get_spec(self) -> TableSpecification:
         """Derive data.spec for pd.DataFrame."""
         logger.info("Get spec for pd.DataFrame (tables)")
+        num_rows, num_columns = self.obj.shape
         return TableSpecification(
             columns=list(self.obj.columns),
+            num_columns=num_columns,
+            num_rows=num_rows,
             size=int(self.obj.size),
         )
 
@@ -142,5 +145,7 @@ def get_spec(self) -> TableSpecification:
         logger.info("Get spec for pyarrow (tables)")
         return TableSpecification(
             columns=list(self.obj.column_names),
+            num_columns=self.obj.num_columns,
+            num_rows=self.obj.num_rows,
             size=self.obj.num_columns * self.obj.num_rows,
         )

tests/test_units/test_ert_context.py

@@ -416,6 +416,9 @@ def test_dataframe_export_file_set_name(
 
     metaout = dataio.read_metadata(output)
     assert metaout["data"]["spec"]["columns"] == ["COL1", "COL2"]
+    assert metaout["data"]["spec"]["num_columns"] == 2
+    assert metaout["data"]["spec"]["num_rows"] == 4
+    assert metaout["data"]["spec"]["size"] == 8
 
 
 def test_pyarrow_export_file_set_name(
@@ -443,3 +446,6 @@ def test_pyarrow_export_file_set_name(
 
         metaout = dataio.read_metadata(output)
         assert metaout["data"]["spec"]["columns"] == ["COL1", "COL2"]
+        assert metaout["data"]["spec"]["num_columns"] == 2
+        assert metaout["data"]["spec"]["num_rows"] == 4
+        assert metaout["data"]["spec"]["size"] == 8

tests/test_units/test_table.py

@@ -9,17 +9,17 @@
 from fmu.dataio.providers.objectdata._provider import objectdata_provider_factory
 
 
-def _read_dict(file_path):
+def _read_dict(file_path: str) -> None:
     """Reads text file into dictionary
     Args:
         file_path (string): path to generated file
     Returns:
         dict: contents of file
     """
-    file_path = Path(file_path)
-    meta_path = file_path.parent / f".{file_path.name}.yml"
+    path = Path(file_path)
+    meta_path = path.parent / f".{path.name}.yml"
     meta = yaml_load(meta_path)
-    file_path.unlink()
+    path.unlink()
     meta_path.unlink()
     return meta