Tweak logging

SkyTruth · Oct 27, 2023 · f392dd1 · f392dd1
1 parent 274ccec
commit f392dd1
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Showing 3 changed files with 20 additions and 24 deletions.
diff --git a/cerulean_cloud/cloud_function_ais_analysis/main.py b/cerulean_cloud/cloud_function_ais_analysis/main.py
@@ -2,6 +2,7 @@
 """
 
 import asyncio
+import logging
 import os
 from json import loads
 
@@ -54,27 +55,34 @@ async def handle_aaa_request(request):
     request_json = request.get_json()
     if not request_json.get("dry_run"):
         scene_id = request_json.get("scene_id")
+        logging.info(f"Running AAA on scene_id: {scene_id}")
         db_engine = get_engine(db_url=os.getenv("DB_URL"))
         async with DatabaseClient(db_engine) as db_client:
             async with db_client.session.begin():
                 s1 = await db_client.get_scene_from_id(scene_id)
                 slicks_without_sources = (
                     await db_client.get_slicks_without_sources_from_scene_id(scene_id)
                 )
+                logging.info(f"# Slicks found: {len(slicks_without_sources)}")
                 if len(slicks_without_sources) > 0:
                     ais_constructor = AISConstructor(s1)
                     ais_constructor.retrieve_ais()
                     # ais_constructor.add_infra()
+                    logging.info("AIS retrieved")
                     if (
                         ais_constructor.ais_gdf is not None
                         and not ais_constructor.ais_gdf.empty
                     ):
+                        logging.info("AIS is not empty")
                         ais_constructor.build_trajectories()
                         ais_constructor.buffer_trajectories()
                         for slick in slicks_without_sources:
                             ais_associations = automatic_ais_analysis(
                                 ais_constructor, slick
                             )
+                            logging.info(
+                                f"{len(ais_associations)} found for Slick ID: {slick.id}"
+                            )
                             if len(ais_associations) > 0:
                                 # XXX What to do if len(ais_associations)==0 and no sources are associated?
                                 # Then it will trigger another round of this process later! (unnecessary computation)

diff --git a/cerulean_cloud/cloud_run_orchestrator/handler.py b/cerulean_cloud/cloud_run_orchestrator/handler.py
@@ -230,8 +230,6 @@ def flatten_feature_list(
 async def _orchestrate(
     payload, tiler, titiler_client, roda_sentinelhub_client, db_engine
 ):
-    logging.basicConfig(level=logging.INFO)
-
     # Orchestrate inference
     start_time = datetime.now()
     logging.info(f"Orchestrating for sceneid {payload.sceneid}")
@@ -246,11 +244,11 @@ async def _orchestrate(
     logging.info(f"scale: {scale}")
 
     if model.zoom_level != zoom:
-        logging.info(
+        logging.warning(
             f"WARNING: Model was trained on zoom level {model.zoom_level} but is being run on {zoom}"
         )
     if model.tile_width_px != scale * 256:
-        logging.info(
+        logging.warning(
             f"WARNING: Model was trained on image tile of resolution {model.tile_width_px} but is being run on {scale*256}"
         )
 
@@ -430,22 +428,23 @@ async def _orchestrate(
                         features=flatten_feature_list(offset_tiles_inference)
                     )
                 except AttributeError as e:
-                    logging.info(f"YYY error details: {e}")
-                    logging.info(f"YYY base_tiles_inference: {base_tiles_inference}")
-                    logging.info(
+                    logging.debug(f"YYY error details: {e}")
+                    logging.debug(f"YYY base_tiles_inference: {base_tiles_inference}")
+                    logging.debug(
                         f"YYY offset_tiles_inference: {offset_tiles_inference}"
                     )
-                    logging.info(
+                    logging.debug(
                         f"YYY [r for r in base_tiles_inference]: {[r for r in base_tiles_inference]}"
                     )
-                    logging.info(
+                    logging.debug(
                         f"YYY [r for r in offset_tiles_inference]: {[r for r in offset_tiles_inference]}"
                     )
+                    raise e
 
             # XXXBUG ValueError: Cannot determine common CRS for concatenation inputs, got ['WGS 84 / UTM zone 28N', 'WGS 84 / UTM zone 29N']. Use `to_crs()` to transform geometries to the same CRS before merging."
             # Example: S1A_IW_GRDH_1SDV_20230727T185101_20230727T185126_049613_05F744_1E56
-            logging.info(f"XXXDEBUG out_fc: {out_fc}")
-            logging.info(f"XXXDEBUG out_fc_offset: {out_fc_offset}")
+            logging.debug(f"out_fc: {out_fc}")
+            logging.debug(f"out_fc_offset: {out_fc_offset}")
             merged_inferences = merge_inferences(
                 out_fc,
                 out_fc_offset,
@@ -456,17 +455,6 @@ async def _orchestrate(
             )
 
             for feat in merged_inferences.get("features"):
-                try:
-                    logging.info(f"XXX CHRISTIAN type(feat): {type(feat)}")
-                    logging.info(
-                        f"XXX CHRISTIAN type(feat['geometry']): {type(feat['geometry'])}"
-                    )
-                    logging.info(f"XXX CHRISTIAN feat['geometry']: {feat['geometry']}")
-                    logging.info(
-                        f"XXX CHRISTIAN geojson.dumps(feat['geometry']): {geojson.dumps(feat['geometry'])}"
-                    )
-                except:  # noqa
-                    pass
                 async with db_client.session.begin():
                     # mini_gdf = gpd.GeoDataframe(feat)
                     # if mini_gdf.intersects(land):
@@ -499,7 +487,7 @@ async def _orchestrate(
                 noffsettiles=noffsettiles,
             )
         else:
-            logging.info("DRY RUN!!")
+            logging.warning("WARNING: Operating as a DRY RUN!!")
             orchestrator_result = OrchestratorResult(
                 classification_base=geojson.FeatureCollection(features=[]),
                 classification_offset=geojson.FeatureCollection(features=[]),

diff --git a/stack/cloud_function_ais_analysis.py b/stack/cloud_function_ais_analysis.py
@@ -88,7 +88,7 @@
     source_archive_object=source_archive_object.name,
     trigger_http=True,
     service_account_email=cloud_function_service_account.email,
-    available_memory_mb=1024,
+    available_memory_mb=2048,
     timeout=540,
     secret_environment_variables=[gfw_credentials],
 )