fix naming

forcingprocessor/src/forcingprocessor/processor.py

@@ -931,9 +931,9 @@ def prep_ngen_data(conf):
 
         metadata_df = pd.DataFrame.from_dict(metadata)
         if storage_type == 's3':
-            bucket, key = convert_url2key(output_path,forcing_path)
+            bucket, key = convert_url2key(output_path,storage_type)
 
-            meta_path = f"{key}/metadata/forcings_metadata/"
+            meta_path = f"{key}metadata/forcings_metadata/"
             buf = BytesIO()   
             if "parquet" in output_file_type: 
                 filename = f"metadata.parquet"
@@ -994,8 +994,8 @@ def prep_ngen_data(conf):
         log_time("TAR_END", log_file)
 
     if storage_type == "s3": 
-        bucket, key  = convert_url2key(metaf_path,forcing_path)
-        log_path = key + '/profile_fp.txt'
+        bucket, key  = convert_url2key(metaf_path,storage_type)
+        log_path = key + 'profile_fp.txt'
         s3.upload_file(
                 f'./profile_fp.txt',
                 bucket,

forcingprocessor/src/forcingprocessor/utils.py

@@ -69,12 +69,7 @@ def convert_url2key(nwm_file,fs_type):
     _nc_file_parts = nwm_file.split('/')
     layers = _nc_file_parts[3:]
     for jlay in layers:
-        bucket_key += "/" + jlay 
+        bucket_key += jlay + "/"
 
-    if fs_type == 's3':
-        bucket_key = _nc_file_parts[2][:-17] + bucket_key
-    elif fs_type == 'google':
-        bucket_key = "gs:/" + bucket_key
-    if "s3://" in nwm_file: bucket_key = bucket_key[1:]
     bucket = _nc_file_parts[2]
     return bucket, bucket_key

forcingprocessor/tests/test_hf2ds.py

@@ -1,7 +1,6 @@
 from forcingprocessor.weights_hf2ds import hf2ds
 from pathlib import Path
 import os
-import pandas as pd
 
 HF_VERSION="v2.1.1"
 test_dir = Path(__file__).parent