From 402ca07edbecda8bb5828596e98527c9ed2de8a4 Mon Sep 17 00:00:00 2001 From: Justus Kuhlmann Date: Mon, 23 Mar 2026 23:42:42 +0100 Subject: [PATCH] linting and hotfix --- corrlib/find.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/corrlib/find.py b/corrlib/find.py index e4ee735..3e62344 100644 --- a/corrlib/find.py +++ b/corrlib/find.py @@ -65,32 +65,32 @@ def _project_lookup_by_id(db: Path, uuid: str) -> list[tuple[str, str]]: def _time_filter(results: pd.DataFrame, created_before: Optional[str]=None, created_after: Optional[Any]=None, updated_before: Optional[Any]=None, updated_after: Optional[Any]=None) -> pd.DataFrame: drops = [] - for ind in len(results): + for ind in range(len(results)): result = results.iloc[ind] created_at = dt.datetime.fromisoformat(result['created_at']) updated_at = dt.datetime.fromisoformat(result['updated_at']) if created_before is not None: - created_before = dt.datetime.fromisoformat(created_before) - if created_before < created_at: + date_created_before = dt.datetime.fromisoformat(created_before) + if date_created_before < created_at: drops.append(ind) continue if created_after is not None: - created_after = dt.datetime.fromisoformat(created_after) - if created_before > created_at: + date_created_after = dt.datetime.fromisoformat(created_after) + if date_created_after > created_at: drops.append(ind) continue if updated_before is not None: - updated_before = dt.datetime.fromisoformat(updated_before) - if updated_before < updated_at: + date_updated_before = dt.datetime.fromisoformat(updated_before) + if date_updated_before < updated_at: drops.append(ind) continue if updated_after is not None: - updated_after = dt.datetime.fromisoformat(updated_after) - if updated_after > updated_at: + date_updated_after = dt.datetime.fromisoformat(updated_after) + if date_updated_after > updated_at: drops.append(ind) continue - return results.drop(drops) + return results.drop(drops) def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None) -> pd.DataFrame: