rebase, format and typing

clouddrift/adapters/gdp/gdpsource.py

@@ -459,7 +459,7 @@ def _process(
         md_df=gdp_metadata_df,
         data_df=df_chunk,
         use_fill_values=use_fill_values,
-        tqdm={"disable": True}
+        tqdm={"disable": True},
     )
     ds = ra.to_xarray()
 
@@ -494,11 +494,16 @@ def to_raggedarray(
     import gzip
 
     data_files = list()
-    for compressed_data_file in tqdm([dst for (_, dst) in requests], desc="Decompressing files", unit="file"):
+    for compressed_data_file in tqdm(
+        [dst for (_, dst) in requests], desc="Decompressing files", unit="file"
+    ):
         decompressed_fp = compressed_data_file[:-3]
         data_files.append(decompressed_fp)
         if not os.path.exists(decompressed_fp):
-            with gzip.open(compressed_data_file, "rb") as compr, open(decompressed_fp, "wb") as decompr:
+            with (
+                gzip.open(compressed_data_file, "rb") as compr,
+                open(decompressed_fp, "wb") as decompr,
+            ):
                 decompr.write(compr.read())
 
     df = dd.read_csv(
@@ -509,13 +514,13 @@ def to_raggedarray(
         engine="c",
         dtype=_INPUT_COLS_PREFILTER_DTYPES,
         blocksize="1GB",
-        assume_missing=True
+        assume_missing=True,
     )
     drifter_datasets = _process(df, gdp_metadata_df, use_fill_values)
 
     # Sort the drifters by their start date.
     deploy_date_id_map = {
-        ds["id"].data[0]: ds["start_date"].data[0] for ds in drifter_datasets
+        ds["id"].data[0]: ds["start_date"].data[0] for ds in drifter_datasets.values()
     }
     deploy_date_sort_key = np.argsort(list(deploy_date_id_map.values()))
     sorted_drifter_datasets = [drifter_datasets[idx] for idx in deploy_date_sort_key]