style: format code with Autopep8, Black and Ruff Formatter

This commit fixes the style issues introduced in 48e7dae according to the output
from Autopep8, Black and Ruff Formatter.

Details: https://github.com/ajschofield/de-project-bentley/pull/107

1 files changed, 49 insertions, 29 deletions

diff --git a/src/load_lambda.py b/src/load_lambda.py
index 941ae97..86189dc 100644
--- a/src/load_lambda.py
+++ b/src/load_lambda.py
@@ -58,10 +58,14 @@ def retrieve_secrets(client=None, secret_name=None):
     try:
         get_secret_value_response = client.get_secret_value(SecretId=secret_name)
     except ClientError as e:
-        logger.error(f"Failed to retrieve secret {secret_name}: {str(e)}", exc_info=True)
+        logger.error(
+            f"Failed to retrieve secret {secret_name}: {str(e)}", exc_info=True
+        )
         raise e
     except KeyError:
-        logger.error(f"Secret {secret_name} does not contain a SecretString", exc_info=True)
+        logger.error(
+            f"Secret {secret_name} does not contain a SecretString", exc_info=True
+        )
         raise ValueError(f"Secret {secret_name} does not contain a SecretString")
 
     return get_secret_value_response["SecretString"]
@@ -117,6 +121,7 @@ def get_transform_bucket(client=None):
 # convert parquet files into dataframes
 # return a dictionary of dataframes with name as key, and dataframe object as value
 
+
 def get_latest_timestamp(existing_files):
     if existing_files:
         all_datetimes = []
@@ -124,19 +129,17 @@ def get_latest_timestamp(existing_files):
             match = re.search(r"\/(.+/).+_(.+)\.parquet", file_name)
             if match:
                 datetime_str = "".join(match.group(1, 2))
-                all_datetimes.append(
-                    dt.strptime(datetime_str, "%Y/%m/%d/%H:%M:%S")
-                )
+                all_datetimes.append(dt.strptime(datetime_str, "%Y/%m/%d/%H:%M:%S"))
         return max(all_datetimes) if all_datetimes else dt.min
     return existing_files
 
+
 def convert_parquet_files_to_dfs(bucket_name=None, client=None):
     mutable_df_dict = [
         "dim_currency",
         "fact_sales_order",
         "fact_purchase_order",
-        "fact_payment"
-        
+        "fact_payment",
     ]
 
     try:
@@ -145,12 +148,12 @@ def convert_parquet_files_to_dfs(bucket_name=None, client=None):
         if bucket_name is None:
             bucket_name = get_transform_bucket()
         files = client.list_objects_v2(Bucket=bucket_name)
-        
+
         dfs = {}
         if "Contents" in files:
-            s3_key_list = [file["Key"]for file in files["Contents"]]
+            s3_key_list = [file["Key"] for file in files["Contents"]]
             immutables_l = []
-            mutables_d = {prefix:[] for prefix in mutable_df_dict}
+            mutables_d = {prefix: [] for prefix in mutable_df_dict}
             for tab, s3_key in mutables_d.items():
                 for file in s3_key_list:
                     if tab in file:
@@ -161,22 +164,31 @@ def convert_parquet_files_to_dfs(bucket_name=None, client=None):
                         continue
             immutables_l = list(set(immutables_l))
             latest_s3_keys = []
-            for k,v in mutables_d.items():
-	            latest_s3_keys.append(dt.strftime(get_latest_timestamp(v), f"{k}/%Y/%m/%d/{k}_%H:%M:%S.parquet"))
-            for file_key in immutables_l+latest_s3_keys:
+            for k, v in mutables_d.items():
+                latest_s3_keys.append(
+                    dt.strftime(
+                        get_latest_timestamp(v), f"{k}/%Y/%m/%d/{k}_%H:%M:%S.parquet"
+                    )
+                )
+            for file_key in immutables_l + latest_s3_keys:
                 try:
                     file_obj = client.get_object(Bucket=bucket_name, Key=file_key)
                     parquet_file = pq.ParquetFile(BytesIO(file_obj["Body"].read()))
                     df = parquet_file.read().to_pandas()
-                    df_without_nulls = df.dropna(how='all') #>> can't do 'any' (default) because we lose rows in dim_location
-                    #print("df_without_nulls", df_without_nulls)
-                    #print("type", type(df_without_nulls))
-                    #print(df_without_nulls.columns)
+                    # >> can't do 'any' (default) because we lose rows in dim_location
+                    df_without_nulls = df.dropna(how="all")
+                    # print("df_without_nulls", df_without_nulls)
+                    # print("type", type(df_without_nulls))
+                    # print(df_without_nulls.columns)
                     dfs[file_key] = df_without_nulls
                 except ClientError as e:
-                    logger.error(f"Unable to retrieve S3 object {file_key}: {e}", exc_info=True)
+                    logger.error(
+                        f"Unable to retrieve S3 object {file_key}: {e}", exc_info=True
+                    )
                 except Exception as e:
-                    logger.error(f"Unable to process file {file_key}: {e}", exc_info=True)
+                    logger.error(
+                        f"Unable to process file {file_key}: {e}", exc_info=True
+                    )
         else:
             logger.error(f"No files found in {bucket_name}.", exc_info=True)
             return {}
@@ -199,23 +211,22 @@ def upload_dfs_to_database():
         "dim_location.parquet",
         "dim_staff.parquet",
         "dim_design.parquet",
-        'dim_transaction.parquet', #This one was missing,
-        'dim_payment_type.parquet'
+        "dim_transaction.parquet",  # This one was missing,
+        "dim_payment_type.parquet",
     ]
     mutable_df_dict = [
         "dim_currency",
         "fact_sales_order",
         "fact_purchase_order",
-        "fact_payment"
-        
+        "fact_payment",
     ]
     with db_engine.begin() as connection:
         for file_name, df in dict_of_dfs.items():
             print(df.dtypes, "dtypes")
             print(df.head())
-            print(file_name,"<<< FILE NAME")
-            print(immutable_df_dict,"<<<IMMUTABLE_DF_DICT")
-            if  file_name in immutable_df_dict: 
+            print(file_name, "<<< FILE NAME")
+            print(immutable_df_dict, "<<<IMMUTABLE_DF_DICT")
+            if file_name in immutable_df_dict:
                 table_name = file_name.split(".")[0]
                 print(table_name, "<<<<<")
                 try:
@@ -229,7 +240,10 @@ def upload_dfs_to_database():
                     upload_status["uploaded"].append(table_name)
                     print(upload_status)
                 except Exception as e:
-                    logger.error(f"Error uploading dataframe {file_name} to database: {e}", exc_info=True)
+                    logger.error(
+                        f"Error uploading dataframe {file_name} to database: {e}",
+                        exc_info=True,
+                    )
                     raise
             elif file_name.split("/")[0] in mutable_df_dict:
                 table_name = file_name.split("/")[0]
@@ -244,11 +258,17 @@ def upload_dfs_to_database():
                     )
                     upload_status["uploaded"].append(table_name)
                 except Exception as e:
-                    logger.error(f"Error uploading dataframe {file_name} to database: {e}", exc_info=True)
+                    logger.error(
+                        f"Error uploading dataframe {file_name} to database: {e}",
+                        exc_info=True,
+                    )
                     raise
             else:
                 upload_status["not_uploaded"].append(file_name)
-                logger.error(f"{file_name} does not correspond with table in database", exc_info=True)
+                logger.error(
+                    f"{file_name} does not correspond with table in database",
+                    exc_info=True,
+                )
             print(upload_status)
     db_engine.dispose()
     return upload_status