diff --git a/clouddrift/adapters/gdp/gdpsource.py b/clouddrift/adapters/gdp/gdpsource.py index 7bd2993b..83a77903 100644 --- a/clouddrift/adapters/gdp/gdpsource.py +++ b/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]