Class bases ETL for Glide, Emdat.

apps/etl/etl_tasks/emdat.py

@@ -1,17 +1,104 @@
+from datetime import datetime
+
 from celery import chain, shared_task
+from django.conf import settings
+
+from apps.etl.extraction.sources.emdat.extract import EMDATExtraction, EMDATQueryVars
+from apps.etl.transform.sources.emdat import EMDATTransformHandler
 
-from apps.etl.extraction.sources.emdat.extract import (
-    extract_emdat_historical_data,
-    extract_emdat_latest_data,
-)
-from apps.etl.transform.sources.emdat import transform_emdat_data
+QUERY = """
+query monty(
+    $limit: Int
+    $offset: Int
+    $include_hist: Boolean
+    $from: Int
+    $to: Int
+) {
+    api_version
+    public_emdat(
+        cursor: { offset: $offset, limit: $limit }
+        filters: { include_hist: $include_hist, from: $from, to: $to }
+    ) {
+        total_available
+        info {
+            timestamp
+            filters
+            cursor
+            version
+        }
+        data {
+            disno
+            classif_key
+            group
+            subgroup
+            type
+            subtype
+            external_ids
+            name
+            iso
+            country
+            subregion
+            region
+            location
+            origin
+            associated_types
+            ofda_response
+            appeal
+            declaration
+            aid_contribution
+            magnitude
+            magnitude_scale
+            latitude
+            longitude
+            river_basin
+            start_year
+            start_month
+            start_day
+            end_year
+            end_month
+            end_day
+            total_deaths
+            no_injured
+            no_affected
+            no_homeless
+            total_affected
+            reconstr_dam
+            reconstr_dam_adj
+            insur_dam
+            insur_dam_adj
+            total_dam
+            total_dam_adj
+            cpi
+            admin_units
+            entry_date
+            last_update
+        }
+    }
+}
+"""
 
 
 @shared_task
-def ext_and_transform_emdat_historical_data(**kwargs):
-    chain(extract_emdat_historical_data.s(), transform_emdat_data.s()).apply_async()
+def ext_and_transform_emdat_latest_data(**kwargs):
+    # FIXME: Why are we getting data from settings.EMDAT_START_YEAR to get the latest data?
+    # Also, the filtering only filters using year so we might have lot of duplicate data
+    variables: EMDATQueryVars = {
+        "limit": -1,
+        "from": int(settings.EMDAT_START_YEAR),
+        "to": datetime.now().year,
+        "include_hist": None,
+    }
+
+    chain(EMDATExtraction.task.s(QUERY, variables), EMDATTransformHandler.task.s()).apply_async()
 
 
 @shared_task
-def ext_and_transform_emdat_latest_data(**kwargs):
-    chain(extract_emdat_latest_data.s(), transform_emdat_data.s()).apply_async()
+def ext_and_transform_emdat_historical_data(**kwargs):
+    variables: EMDATQueryVars = {
+        "limit": -1,
+        "from": None,
+        "to": None,
+        "include_hist": True,
+    }
+
+    chain(EMDATExtraction.task.s(QUERY, variables), EMDATTransformHandler.task.s()).apply_async()

apps/etl/etl_tasks/glide.py

@@ -1,61 +1,102 @@
+from datetime import datetime
+
 from celery import chain, shared_task
+from django.conf import settings
+
+from apps.etl.extraction.sources.glide.extract import GlideExtraction, GlideQueryVars
+from apps.etl.models import ExtractionData, HazardType
+from apps.etl.transform.sources.glide import GlideTransformHandler
 
-from apps.etl.extraction.sources.glide.extract import (
-    extract_glide_historical_data,
-    extract_glide_latest_data,
-)
-from apps.etl.models import HazardType
-from apps.etl.transform.sources.glide import transform_glide_event_data
+GLIDE_HAZARDS = [
+    HazardType.EARTHQUAKE,
+    HazardType.FLOOD,
+    HazardType.CYCLONE,
+    HazardType.EPIDEMIC,
+    HazardType.STORM,
+    HazardType.DROUGHT,
+    HazardType.TSUNAMI,
+    HazardType.WILDFIRE,
+    HazardType.VOLCANO,
+    HazardType.COLDWAVE,
+    HazardType.EXTRATROPICAL_CYCLONE,
+    HazardType.EXTREME_TEMPERATURE,
+    HazardType.FIRE,
+    HazardType.FLASH_FLOOD,
+    HazardType.HEAT_WAVE,
+    HazardType.INSECT_INFESTATION,
+    HazardType.LANDSLIDE,
+    HazardType.MUD_SLIDE,
+    HazardType.SEVERE_LOCAL_STROM,
+    HazardType.SLIDE,
+    HazardType.SNOW_AVALANCHE,
+    HazardType.TECH_DISASTER,
+    HazardType.TORNADO,
+    HazardType.VIOLENT_WIND,
+    HazardType.WAVE_SURGE,
+]
 
 
 @shared_task
-def ext_and_transform_glide_historical_data(hazard_type: str, hazard_type_str: str, **kwargs):
-    event_workflow = chain(
-        extract_glide_historical_data.s(
+def _ext_and_transform_glide_latest_data(hazard_type: HazardType):
+    ext_object = (
+        ExtractionData.objects.filter(
+            source=ExtractionData.Source.GLIDE,
             hazard_type=hazard_type,
-            hazard_type_str=hazard_type_str,
-        ),
-        transform_glide_event_data.s(),
+            status=ExtractionData.Status.SUCCESS,
+            resp_data__isnull=False,
+        )
+        .order_by("-created_at")
+        .first()
     )
-    event_workflow.apply_async()
+
+    if ext_object:
+        from_date = ext_object.created_at.date()
+    else:
+        from_date = datetime.strptime(settings.GLIDE_START_DATE, "%Y-%m-%d").date()
+
+    to_date = datetime.today().date()
+
+    # FIXME: Check if the date filters are inclusive
+    url = f"{settings.GLIDE_URL}/glide/jsonglideset.jsp"
+    variables: GlideQueryVars = {
+        "fromyear": from_date.year,
+        "frommonth": from_date.month,
+        "fromday": from_date.day,
+        "toyear": to_date.year,
+        "tomonth": to_date.month,
+        "today": to_date.day,
+        "events": hazard_type.value,
+    }
+
+    chain(GlideExtraction.task.s(url, variables), GlideTransformHandler.task.s()).apply_async()
 
 
 @shared_task
-def ext_and_transform_data(hazard_type, hazard_type_str):
-    event_workflow = chain(
-        extract_glide_latest_data.s(
-            hazard_type=hazard_type,
-            hazard_type_str=hazard_type_str,
-        ),
-        transform_glide_event_data.s(),
-    )
-    event_workflow.apply_async()
+def _ext_and_transform_glide_historical_data(hazard_type: HazardType):
+    to_date = datetime.today().date()
+
+    # FIXME: Check if the date filters are inclusive
+    url = f"{settings.GLIDE_URL}/glide/jsonglideset.jsp"
+    variables: GlideQueryVars = {
+        "fromyear": None,
+        "frommonth": None,
+        "fromday": None,
+        "toyear": to_date.year,
+        "tomonth": to_date.month,
+        "today": to_date.day,
+        "events": hazard_type.value,
+    }
+
+    chain(GlideExtraction.task.s(url, variables), GlideTransformHandler.task.s()).apply_async()
 
 
 @shared_task
 def ext_and_transform_glide_latest_data():
-    ext_and_transform_data.delay("EQ", HazardType.EARTHQUAKE)
-    ext_and_transform_data.delay("TC", HazardType.CYCLONE)
-    ext_and_transform_data.delay("FL", HazardType.FLOOD)
-    ext_and_transform_data.delay("DR", HazardType.DROUGHT)
-    ext_and_transform_data.delay("WF", HazardType.WILDFIRE)
-    ext_and_transform_data.delay("VO", HazardType.VOLCANO)
-    ext_and_transform_data.delay("TS", HazardType.TSUNAMI)
-    ext_and_transform_data.delay("CW", HazardType.COLDWAVE)
-    ext_and_transform_data.delay("EP", HazardType.EPIDEMIC)
-    ext_and_transform_data.delay("EC", HazardType.EXTRATROPICAL_CYCLONE)
-    ext_and_transform_data.delay("ET", HazardType.EXTREME_TEMPERATURE)
-    ext_and_transform_data.delay("FR", HazardType.FIRE)
-    ext_and_transform_data.delay("FF", HazardType.FLASH_FLOOD)
-    ext_and_transform_data.delay("HT", HazardType.HEAT_WAVE)
-    ext_and_transform_data.delay("IN", HazardType.INSECT_INFESTATION)
-    ext_and_transform_data.delay("LS", HazardType.LANDSLIDE)
-    ext_and_transform_data.delay("MS", HazardType.MUD_SLIDE)
-    ext_and_transform_data.delay("ST", HazardType.SEVERE_LOCAL_STROM)
-    ext_and_transform_data.delay("SL", HazardType.SLIDE)
-    ext_and_transform_data.delay("AV", HazardType.SNOW_AVALANCHE)
-    ext_and_transform_data.delay("SS", HazardType.STORM)
-    ext_and_transform_data.delay("AC", HazardType.TECH_DISASTER)
-    ext_and_transform_data.delay("TO", HazardType.TORNADO)
-    ext_and_transform_data.delay("VW", HazardType.VIOLENT_WIND)
-    ext_and_transform_data.delay("WV", HazardType.WAVE_SURGE)
+    for hazard_type in GLIDE_HAZARDS:
+        _ext_and_transform_glide_latest_data(hazard_type)
+
+
+@shared_task
+def ext_and_transform_glide_historical_data():
+    for hazard_type in GLIDE_HAZARDS:
+        _ext_and_transform_glide_historical_data(hazard_type)

apps/etl/etl_tasks/usgs.py

@@ -6,7 +6,6 @@
 
 @shared_task
 def ext_and_transform_usgs_latest_data():
-    url = "https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_day.geojson"
     url = f"{settings.USGS_DATA_URL}/all_day.geojson"
     ext_and_transform_data.delay(url)
 

apps/etl/extraction/sources/base/handler.py

@@ -27,7 +27,7 @@ def store_extraction_data(
         validate_source_func: Callable[[Any], None],
         source: int,
         response: dict,
-        instance_id: int = None,
+        instance_id: int | None = None,
     ):
         """
         Save extracted data into data base. Checks for duplicate conent using hashing.
@@ -72,14 +72,15 @@ def _create_extraction_instance(cls, url: str, source: int) -> ExtractionData:
             status=ExtractionData.Status.PENDING,
             source_validation_status=ExtractionData.ValidationStatus.NO_VALIDATION,
             trace_id=str(uuid.uuid4()),
+            # FIXME Pass hazard type
             hazard_type=None,
             attempt_no=0,
             resp_code=0,
         )
 
     @classmethod
     def _update_instance_status(
-        cls, instance: ExtractionData, status: int, validation_status: int = None, update_validation: bool = False
+        cls, instance: ExtractionData, status: int, validation_status: int | None = None, update_validation: bool = False
     ) -> None:
         """
         Update the status of the extraction instance.
@@ -116,7 +117,7 @@ def _save_response_data(cls, instance: ExtractionData, response: requests.Respon
         return json.loads(response.content)
 
     @classmethod
-    def handle_extraction(cls, url: str, params: dict, headers: dict, source: int) -> dict:
+    def handle_extraction(cls, url: str, params: dict | None, headers: dict, source: int) -> dict:
         """
         Process data extraction.
         Returns:

apps/etl/extraction/sources/desinventar/extract.py

@@ -26,7 +26,7 @@ def store_extraction_data(
         instance_id: int = None,
     ):
         """
-        Save extracted data into database. Checks for duplicate content using hashing.
+        Save extracted data into database.
         """
         file_name = f"{source}.zip"
         resp_data = response
@@ -41,6 +41,7 @@ def store_extraction_data(
             # manage duplicate file content.
             manage_duplicate_file_content(
                 source=extraction_instance.source,
+                # FIXME: We need to calculate has for zip file
                 hash_content=None,
                 instance=extraction_instance,
                 response_data=resp_data.content,