fix: use vessels_subset.csv & guess CSV seperation ; or , automatically

src/bloom/config.py

@@ -55,7 +55,7 @@ class Settings(BaseSettings):
     port_polygon_data_csv_path:Path = Path(__file__).parent.joinpath("../../data/ports_rad3000_res10.csv")
     port_radius_m:int = 3000    # Radius in meters
     port_resolution:int = 10    # Number of points in the resulting polygon
-    vessel_data_csv_path:Path = Path(__file__).parent.joinpath("../../data/chalutiers_pelagiques.csv")
+    vessel_data_csv_path:Path = Path(__file__).parent.joinpath("../../data/vessels_subset.csv")
 
 
     vessel_positions_data_csv_path:Path = Path(__file__).parent.joinpath("../../data/spire_positions_subset.csv")

src/tasks/dimensions/load_dim_vessel_from_csv.py

@@ -27,18 +27,18 @@ def map_to_domain(self, row: pd.Series) -> Vessel:
             else None,
             external_marking=row["external_marking"] if not isna["external_marking"] else None,
             ircs=row["ircs"] if not isna["ircs"] else None,
-            mt_activated=row["mt_activated"].strip(),
+            mt_activated=row["mt_activated"],
         )
 
-    def run(self, *args, **kwarg) -> None:
+    def run(self, *args, **kwargs) -> None:
         use_cases = UseCases()
         vessel_repository = use_cases.vessel_repository()
         db = use_cases.db()
 
         ports = []
         total = 0
         try:
-            df = pd.read_csv(kwarg['vessel_data_csv_path'], sep=";")
+            df = pd.read_csv(kwargs['vessel_data_csv_path'], sep=None, engine='python')
             vessels = df.apply(self.map_to_domain, axis=1)
             with db.session() as session:
                 ports = vessel_repository.batch_create_vessel(session, list(vessels))