scripts/__main__.py

@@ -79,11 +79,7 @@ def feature():
 def datamart():
     from .gold_mart import FLUXES_LOT
 
-    consume_fluxes(
+    consume_fluxes(fluxes=FLUXES_LOT, origin_path=GOLD_PATH, dest_path=MART_PATH)
-        fluxes=FLUXES_LOT,
-        origin_path=GOLD_PATH,
-        dest_path=MART_PATH,
-    )
 
 
 if __name__ == "__main__":

scripts/flux.py

@@ -4,7 +4,7 @@ from collections.abc import Callable
 from pathlib import Path
 
 import pandas as pd
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
 
 
 class Source(BaseModel):
@@ -38,51 +38,21 @@ class Transformation(BaseModel):
     extra_kwrds: dict = {}
 
 
-def to_csv(df, dest_basename: Path) -> Path:
-    dest = dest_basename.parent / (dest_basename.stem + ".csv")
-    if dest.exists():
-        df.to_csv(dest, mode="a", header=False, index=False)
-    else:
-        df.to_csv(dest, index=False)
-    return dest
-
-
-def to_excel(df, dest_basename: Path) -> Path:
-    dest = dest_basename.parent / (dest_basename.stem + ".xlsx")
-    if dest.exists():
-        raise ValueError(f"The destination exits {dest}")
-    else:
-        df.to_excel(dest)
-    return dest
-
-
 class Destination(BaseModel):
     name: str
-    writer: Callable = Field(to_csv)
-
-    def _write(
-        self,
-        df: pd.DataFrame,
-        dest_basename: Path,
-        writing_func: Callable | None = None,
-    ) -> Path:
-        if writing_func is None:
-            writing_func = self.writer
-
-        return writing_func(df, dest_basename)
 
     def write(
-        self, df: pd.DataFrame, dest_path: Path, writing_func: Callable | None = None
+        self, df: pd.DataFrame, dest_path: Path, writing_func: Callable
     ) -> list[Path]:
         dest_basename = dest_path / self.name
-        return [self._write(df, dest_basename, writing_func)]
+        return [writing_func(df, dest_basename)]
 
 
 class SplitDestination(Destination):
     split_column: str
 
     def write(
-        self, df: pd.DataFrame, dest_path: Path, writing_func: Callable | None = None
+        self, df: pd.DataFrame, dest_path: Path, writing_func: Callable
     ) -> list[Path]:
         wrote_files = []
 
@@ -90,7 +60,7 @@ class SplitDestination(Destination):
             filtered_df = df[df[self.split_column] == col_value]
 
             dest_basename = dest_path / f"{self.name}-{col_value}"
-            dest = self._write(filtered_df, dest_basename, writing_func)
+            dest = writing_func(filtered_df, dest_basename)
             wrote_files.append(dest)
 
         return wrote_files
@@ -102,6 +72,15 @@ class Flux(BaseModel):
     destination: Destination
 
 
+def to_csv(df, dest_basename: Path) -> Path:
+    dest = dest_basename.parent / (dest_basename.stem + ".csv")
+    if dest.exists():
+        df.to_csv(dest, mode="a", header=False, index=False)
+    else:
+        df.to_csv(dest, index=False)
+    return dest
+
+
 def write_split_by(
     df: pd.DataFrame, column: str, dest_path: Path, name: str, writing_func
 ) -> list[Path]:
@@ -140,13 +119,16 @@ def split_duplicates(
     return no_duplicates, duplicated
 
 
-def consume_flux(
+def consume_fluxes(
-    name: str,
+    fluxes: dict[str, Flux],
-    flux: Flux,
     origin_path: Path,
     dest_path: Path,
-    duplicated={},
+    writing_func=to_csv,
 ):
+    duplicated = {}
+    wrote_files = []
+
+    for name, flux in fluxes.items():
         logging.info(f"Consume {name}")
         src_df = []
         for filename, df in extract_sources(flux.sources, origin_path):
@@ -156,22 +138,7 @@ def consume_flux(
 
         logging.info(f"Execute {flux.transformation.function.__name__}")
         df = flux.transformation.function(src_df, **flux.transformation.extra_kwrds)
-
+        files = flux.destination.write(df, dest_path, writing_func)
-    files = flux.destination.write(df, dest_path)
-
         logging.info(f"{files} written")
-    return files
-
-
-def consume_fluxes(
-    fluxes: dict[str, Flux],
-    origin_path: Path,
-    dest_path: Path,
-):
-    duplicated = {}
-    wrote_files = []
-
-    for name, flux in fluxes.items():
-        files = consume_flux(name, flux, origin_path, dest_path, duplicated)
         wrote_files += files
     return wrote_files

scripts/gold_mart.py

@@ -11,7 +11,6 @@ from scripts.flux import (
     SplitDestination,
     Transformation,
     consume_fluxes,
-    to_excel,
 )
 
 logger = logging.getLogger(__name__)
@@ -27,9 +26,7 @@ FLUXES_LOT = {
     "Lots": Flux(
         sources=[CSVSource(filename="CRG/crg-*.csv")],
         transformation=Transformation(function=build_lots),
-        destination=SplitDestination(
+        destination=SplitDestination(name="Lot/lot", split_column="Lot"),
-            name="Lot/lot", split_column="Lot", writer=to_excel
-        ),
     ),
 }
 
@@ -78,8 +75,6 @@ if __name__ == "__main__":
     pnl_fluxes = {}
 
     files = consume_fluxes(
-        fluxes=pnl_fluxes,
+        fluxes=pnl_fluxes, origin_path=gold_path, dest_path=mart_path
-        origin_path=gold_path,
-        dest_path=mart_path,
     )
     print(files)

scripts/history_stagging.py

@@ -12,9 +12,9 @@ logger.setLevel(logging.DEBUG)
 
 
 def extract_cat(cat: pd.DataFrame):
-    cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"])
+    cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"]["Anciennes"])
-    # cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"]["Anciennes"])
     cat_trans = cat[cat["Nouvelles"] != "NE PAS IMPORTER"]
+
     trans = {}
     for _, (old, new) in cat_trans.iterrows():
         trans[old] = new
@@ -140,7 +140,7 @@ FLUXES_CRG = {
     ),
     "2022 - charge.xlsx": Flux(
         sources=[
-            ExcelSource(filename="2022 - charge.xlsx", sheet_name="DB CRG"),
+            ExcelSource(filename="2022 - charge.xlsx", sheet_name="Sheet1"),
         ],
         transformation=Transformation(
             function=trans_2022_charge,