Pre-commit fixes

Author: bosd

src/odoo_data_flow/import_threaded.py

@@ -8,7 +8,7 @@
 import concurrent.futures
 import csv
 import sys
-import time  # noqa
+import time
 from collections.abc import Generator, Iterable
 from concurrent.futures import ThreadPoolExecutor, as_completed  # noqa
 from typing import Any, Optional, TextIO, Union
@@ -691,8 +691,8 @@ def _execute_load_batch(
                 or "poolerror" in error_str.lower()
             ):
                 log.warning(
-                    f"Database connection pool exhaustion detected. "
-                    f"Reducing chunk size and retrying to reduce server load."
+                    "Database connection pool exhaustion detected. "
+                    "Reducing chunk size and retrying to reduce server load."
                 )
                 is_scalable_error = True
 

src/odoo_data_flow/lib/relational_import.py

@@ -196,7 +196,9 @@ def run_direct_relational_import(
 
     # Check if the field exists in the DataFrame
     if field not in source_df.columns:
-        log.error(f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}")
+        log.error(
+            f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}"
+        )
         return None
 
     # 2. Prepare the related model's IDs using the resolver
@@ -269,14 +271,18 @@ def _prepare_link_dataframe(
 
     # Check if the field exists in the DataFrame
     if field not in source_df.columns:
-        log.error(f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}")
+        log.error(
+            f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}"
+        )
         # Return an empty DataFrame with the expected schema
-        return pl.DataFrame(schema={
-            "external_id": pl.Utf8,
-            field: pl.Utf8,
-            owning_model_fk: pl.Int64,
-            f"{related_model_fk}/id": pl.Int64
-        })
+        return pl.DataFrame(
+            schema={
+                "external_id": pl.Utf8,
+                field: pl.Utf8,
+                owning_model_fk: pl.Int64,
+                f"{related_model_fk}/id": pl.Int64,
+            }
+        )
 
     # Create the link table DataFrame
     link_df = source_df.select(["id", field]).rename({"id": "external_id"})
@@ -343,7 +349,9 @@ def run_write_tuple_import(
 
     # Check if the field exists in the DataFrame
     if field not in source_df.columns:
-        log.error(f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}")
+        log.error(
+            f"Field '{field}' not found in source DataFrame. Available columns: {source_df.columns}"
+        )
         return False
 
     # 2. Prepare the related model's IDs using the resolver