implement schema check and use automation instead of sensor

apps/vinyl/src/assets.py

@@ -3,9 +3,10 @@ from glob import glob
 
 import polars as pl
 import structlog
+from models import Deal
 from plato.fetch import scrape_plato
 from plato.parse import parse as parse_plato
-from shared.utils import get_partition_keys, parse_partition_keys
+from shared.utils import get_partition_keys, load_partitions
 from sounds.fetch import fetch_deals
 from sounds.parse import parse as parse_sounds
 
@@ -37,12 +38,12 @@ partitions_mapping = dg.MultiToSingleDimensionPartitionMapping(
     },
     config_schema={"import_dir": dg.Field(str, default_value="/storage/import")},
 )
-def deals(context):
+def deals(context: dg.AssetExecutionContext) -> pl.DataFrame:
     ic()
     ic(context.partition_key)
     ic(context.op_config)
     import_dir = context.op_config["import_dir"]
-    partition_key = context.partition_key.keys_by_dimension
+    partition_key = get_partition_keys(context)
     date_str = partition_key["date"]
     source = partition_key["source"]
     logger.info("Materializing deals", date=date_str, source=source)
@@ -88,22 +89,6 @@ def deals(context):
     )
 
 
-@dg.asset(
-    io_manager_key="polars_parquet_io_manager",
-    partitions_def=daily_partitions_def,
-    ins={"partitions": dg.AssetIn(key=deals.key, partition_mapping=partitions_mapping)},
-    automation_condition=dg.AutomationCondition.eager(),
-)
-def new_deals(
-    context: dg.OpExecutionContext, partitions: dict[str, pl.DataFrame]
-) -> None:  # pl.DataFrame:
-    """Combine deals from Plato and Sounds into a single DataFrame."""
-    ic()
-    partition_keys = parse_partition_keys(context)
-    ic(partition_keys)
-    return
-
-
 @dg.asset(
     io_manager_key="polars_parquet_io_manager",
     partitions_def=deals.partitions_def,
@@ -113,8 +98,9 @@ def new_deals(
     ),
 )
 def cleaned_deals(
-    context: dg.OpExecutionContext, df: pl.LazyFrame
+    context: dg.AssetExecutionContext, df: pl.LazyFrame
-) -> pl.DataFrame | None:
+) -> Deal.DataFrame | None:
+    """Clean and parse deals from the raw source tables."""
     ic()
     partition_keys = get_partition_keys(context)
     ic(partition_keys)
@@ -129,22 +115,32 @@ def cleaned_deals(
             context.log.warning(f"Unknown source: {source}!")
             return None
 
+    ic(parsed_df.collect_schema())
+
     # Deduplicate and sort the DataFrame
     columns = ["source", "id", "artist", "title", "price"]
-    return (
+    return Deal.DataFrame(
-        parsed_df.collect()
+        parsed_df.sort("date", descending=True)
-        .sort("date", descending=True)
         .unique(subset=columns, keep="first")
         .sort("date", descending=False)
         .select(*columns, "date", "release", "url")
+        .collect()
     )
 
 
 @dg.asset(
-    ins={"df": dg.AssetIn(key=new_deals.key)},
+    deps=[cleaned_deals],
     io_manager_key="polars_parquet_io_manager",
-    automation_condition=dg.AutomationCondition.eager(),
+    automation_condition=dg.AutomationCondition.on_missing().without(
+        dg.AutomationCondition.in_latest_time_window()
+    ),
 )
-def works(df: pl.DataFrame) -> pl.DataFrame:
+def works(context: dg.AssetExecutionContext) -> pl.DataFrame | None:
-    columns = ["artist", "title", "release"]
+    """Aggregate works from cleaned deals."""
-    return df[columns].unique()
+    partitions = context.instance.get_materialized_partitions(cleaned_deals.key)
+    ic(partitions)
+    dfs = list(load_partitions(context, cleaned_deals.key, partitions))
+    if dfs:
+        columns = ["artist", "title", "release"]
+        return pl.concat(dfs, how="vertical_relaxed").select(columns).unique()
+    return None

apps/vinyl/src/definitions.py

@@ -1,9 +1,8 @@
 import assets
 from dagster_polars import PolarsParquetIOManager
 from icecream import install
-from jobs import check_partitions_job, deals_job, musicbrainz_lookup_job
+from jobs import check_partitions_job, deals_job
 from schedules import deals_schedule
-from sensors import musicbrainz_lookup_sensor
 
 import dagster as dg
 
@@ -17,16 +16,8 @@ definitions = dg.Definitions(
         for asset in dg.load_assets_from_modules([assets])
     ],
     resources={
-        "polars_parquet_io_manager": PolarsParquetIOManager(base_dir="/storage"),
+        "polars_parquet_io_manager": PolarsParquetIOManager(base_dir="/storage/vinyl"),
     },
-    jobs=[deals_job, check_partitions_job, musicbrainz_lookup_job],
+    jobs=[deals_job, check_partitions_job],
     schedules=[deals_schedule],
-    sensors=[
-        # dg.AutomationConditionSensorDefinition(
-        #     "run_tags_automation_condition_sensor",
-        #     target=dg.AssetSelection.all(),
-        #     default_status=dg.DefaultSensorStatus.RUNNING,
-        # ),
-        musicbrainz_lookup_sensor,
-    ],
 )

apps/vinyl/src/jobs.py

@@ -1,5 +1,5 @@
 import polars as pl
-from assets import deals, new_deals, works
+from assets import deals
 
 import dagster as dg
 
@@ -12,11 +12,11 @@ deals_job = dg.define_asset_job(
 def check_partitions(context: dg.OpExecutionContext):
     asset_key = "deals"
 
-    # Fetch the materializations for the asset key
+    # Fetch the materialized partitions for the asset key
-    materializations = context.instance.get_materialized_partitions(
+    materialized_partitions = context.instance.get_materialized_partitions(
         asset_key=dg.AssetKey(asset_key)
     )
-    ic(materializations)
+    ic(materialized_partitions)
 
     storage_dir = context.resources.polars_parquet_io_manager.base_dir
     ic(storage_dir)
@@ -30,7 +30,7 @@ def check_partitions(context: dg.OpExecutionContext):
         .iter_rows()
     ):
         partition = "|".join(row)
-        if partition not in materializations:
+        if partition not in materialized_partitions:
             context.log.info(f"Missing partition: {partition}")
             context.log_event(
                 dg.AssetMaterialization(asset_key=asset_key, partition=partition)
@@ -40,8 +40,3 @@ def check_partitions(context: dg.OpExecutionContext):
 @dg.job
 def check_partitions_job():
     check_partitions()
-
-
-musicbrainz_lookup_job = dg.define_asset_job(
-    "musicbrainz_lookup_job", selection=[works.key, new_deals.key]
-)

apps/vinyl/src/models.py

@@ -0,0 +1,14 @@
+import datetime
+
+import patito as pt
+
+
+class Deal(pt.Model):
+    source: str = pt.Field(description="Source of the deal, e.g., 'plato' or 'sounds'.")
+    id: str = pt.Field(description="Unique identifier that is used at the source.")
+    artist: str = pt.Field(description="Artist.")
+    title: str = pt.Field(description="Title of the deal.")
+    url: str = pt.Field(description="URL to the deal.")
+    date: datetime.date = pt.Field(description="Day the deal was listed.")
+    release: datetime.date = pt.Field(description="Release date.")
+    price: float = pt.Field(description="Price of the deal in EUR.")

apps/vinyl/src/test.py

@@ -1,16 +1,15 @@
 import logging
-import warnings
 from datetime import datetime
 from typing import Any
 
-from assets import cleaned_deals, deals, new_deals
+from assets import cleaned_deals, deals, works
 from dagster_polars import PolarsParquetIOManager
 from definitions import definitions
 from jobs import check_partitions_job
 
 import dagster as dg
 
-warnings.filterwarnings("ignore", category=dg.ExperimentalWarning)
+# warnings.filterwarnings("ignore", category=dg.Ex)
 
 logging.getLogger().setLevel(logging.INFO)
 
@@ -35,10 +34,10 @@ def test_deals(resources: dict[str, Any], source="sounds", date: str = None):
 
 
 if __name__ == "__main__":
-    run = 4
+    run = 3
     resources = {
         "polars_parquet_io_manager": PolarsParquetIOManager(
-            base_dir="/opt/dagster/storage"
+            base_dir="/opt/dagster/storage/vinyl"
         )
     }
     source = "sounds"  # or "plato"
@@ -48,19 +47,19 @@ if __name__ == "__main__":
             check_partitions_job.execute_in_process(resources=resources)
         case 2:
             test_deals(resources, source=source)
+
         case 3:
-            dg.materialize(
-                assets=definitions.assets,
-                selection=[new_deals.key],
-                partition_key=today_str(),
-                resources=resources,
-            )
-        case 4:
             dg.materialize(
                 assets=definitions.assets,
                 selection=[cleaned_deals.key],
                 partition_key=f"{today_str()}|{source}",
                 resources=resources,
             )
+        case 4:
+            dg.materialize(
+                assets=definitions.assets,
+                selection=[works.key],
+                resources=resources,
+            )
         case _:
-            raise ValueError("Invalid run number")
+            raise ValueError(f"Invalid run number: {run}!")