Add handling for submission of subannual/hourly timeseries data

definitions/subannual/year.yaml

@@ -0,0 +1,4 @@
+# Default entry for the subannual column
+
+- Year:
+    duration: 1

workflow.py

@@ -9,7 +9,39 @@
 def main(df: pyam.IamDataFrame) -> pyam.IamDataFrame:
     """Project/instance-specific workflow for scenario processing"""
 
-    # Run the validation and region-processing
-    dsd = DataStructureDefinition(here / "definitions")
+    dimensions = ["region", "variable"]
+    if "subannual" in df.dimensions or df.time_col == "time":
+        dimensions = dimensions + ["subannual"]
+
+    # initialize the codelists and region-processing
+    dsd = DataStructureDefinition(here / "definitions", dimensions=dimensions)
     processor = RegionProcessor.from_directory(path=here / "mappings", dsd=dsd)
-    return process(df, dsd, processor=processor)
+
+    # run the validation and region-processing
+    df = process(df, dsd, processor=processor)
+
+    # convert to subannual format if data provided in datetime format
+    if df.time_col == "time":
+        logger.info('Re-casting from "time" column to categorical "subannual" format')
+        df = df.swap_time_for_year(subannual=OE_SUBANNUAL_FORMAT)
+
+    # check that any datetime-like items in "subannual" are valid datetime and UTC+01:00
+    if "subannual" in df.dimensions:
+        _datetime = [s for s in df.subannual if s not in dsd.subannual]
+
+        for d in _datetime:
+            try:
+                _dt = datetime.strptime(f"2020-{d}", "%Y-%m-%d %H:%M%z")
+            except ValueError:
+                try:
+                    datetime.strptime(f"2020-{d}", "%Y-%m-%d %H:%M")
+                except ValueError:
+                    raise ValueError(f"Invalid subannual timeslice: {d}")
+
+                raise ValueError(f"Missing timezone: {d}")
+
+            # casting to datetime with timezone was successful
+            if not (_dt.tzname() == EXP_TZ or _dt.utcoffset() == EXP_TIME_OFFSET):
+                raise ValueError(f"Invalid timezone: {d}")
+
+    return df