linting

src/app/vinyl/assets.py

@@ -3,16 +3,11 @@ from glob import glob
 
 import polars as pl
 import structlog
-from dagster import (
-    AssetIn,
-    DailyPartitionsDefinition,
-    DimensionPartitionMapping,
-    IdentityPartitionMapping,
-    MultiPartitionMapping,
-    MultiPartitionsDefinition,
-    StaticPartitionsDefinition,
-    TimeWindowPartitionMapping,
-    asset, Failure, Field, )
+from dagster import (AssetIn, DailyPartitionsDefinition,
+                     DimensionPartitionMapping, Failure, Field,
+                     IdentityPartitionMapping, MultiPartitionMapping,
+                     MultiPartitionsDefinition, StaticPartitionsDefinition,
+                     TimeWindowPartitionMapping, asset)
 
 from app.vinyl.plato.check_plato import scrape_plato
 from app.vinyl.sounds.fetch import fetch_deals
@@ -48,7 +43,9 @@ partition_mapping = MultiPartitionMapping(
     metadata={
         "partition_by": ["date", "source"],
     },
-    config_schema={"import_dir": Field(str, default_value="/opt/dagster/home/storage/import")},
+    config_schema={
+        "import_dir": Field(str, default_value="/opt/dagster/home/storage/import")
+    },
 )
 def deals(context):
     ic()
@@ -74,9 +71,11 @@ def deals(context):
                 file = sorted(files)[-1]
                 logger.info("Using existing CSV file", file=file)
                 try:
-                    df = pl.read_csv(file)[["id", "name", "price"]]
+                    df = pl.read_csv(file)
                     logger.info("Loaded CSV file", rows=len(df))
-                    return df.with_columns(**{k: pl.lit(v) for k, v in partition_key.items()})
+                    return df.with_columns(
+                        **{k: pl.lit(v) for k, v in partition_key.items()}
+                    )
                 except Exception as e:
                     logger.error("Failed to load CSV file!", error=e)
         raise Failure(f"Cannot materialize for the past: {date.date()}")
@@ -91,7 +90,6 @@ def deals(context):
         logger.info("Scraping Sounds")
         df = fetch_deals()
         ic(df.columns)
-        df = df[["id", "name", "price"]]
         logger.info("Scraped Sounds", rows=len(df), head=df.head().to_markdown())
         return pl.from_pandas(df.assign(**partition_key))