make the endpoint front-end oriented

antarest/study/service.py

@@ -139,8 +139,8 @@
 from antarest.study.storage.rawstudy.model.filesystem.matrix.output_series_matrix import OutputSeriesMatrix
 from antarest.study.storage.rawstudy.model.filesystem.raw_file_node import RawFileNode
 from antarest.study.storage.rawstudy.model.filesystem.root.output.simulation.mode.mcall.digest import (
-    DigestDTO,
     DigestSynthesis,
+    DigestUI,
 )
 from antarest.study.storage.rawstudy.model.filesystem.root.user.user import User
 from antarest.study.storage.rawstudy.raw_study_service import RawStudyService
@@ -2752,7 +2752,7 @@ def delete_file_or_folder(self, study_id: str, path: str, current_user: JWTUser)
         updated_tree = study_tree.get()
         self.storage_service.get_storage(study).cache.put(cache_id, updated_tree)  # type: ignore
 
-    def get_digest_file(self, study_id: str, output_id: str, params: RequestParameters) -> DigestDTO:
+    def get_digest_file(self, study_id: str, output_id: str, params: RequestParameters) -> DigestUI:
         """
         Returns the digest file as 4 separated intelligible matrices.
         Raises ChildNotFoundError if the output_id doesn't exist or if the digest file wasn't generated
@@ -2762,4 +2762,4 @@ def get_digest_file(self, study_id: str, output_id: str, params: RequestParamete
         file_study = self.storage_service.get_storage(study).get_raw(study)
         digest_node = file_study.tree.get_node(url=["output", output_id, "economy", "mc-all", "grid", "digest"])
         assert isinstance(digest_node, DigestSynthesis)
-        return digest_node.get_dto()
+        return digest_node.get_ui()

antarest/study/storage/rawstudy/model/filesystem/root/output/simulation/mode/mcall/digest.py

@@ -13,6 +13,7 @@
 import typing as t
 
 import pandas as pd
+from pydantic import Field
 
 from antarest.core.model import JSON
 from antarest.core.serialization import AntaresBaseModel
@@ -21,61 +22,61 @@
 from antarest.study.storage.rawstudy.model.filesystem.root.output.simulation.mode.mcall.synthesis import OutputSynthesis
 
 
-class DigestMatrixDTO(AntaresBaseModel):
+class DigestMatrixUI(AntaresBaseModel):
     columns: t.List[t.Union[str, t.List[str]]]
     data: t.List[t.List[t.Any]]
-    groupedColumns: bool
+    grouped_columns: bool = Field(alias="groupedColumns")
 
 
-class DigestDTO(AntaresBaseModel):
-    area: DigestMatrixDTO
-    districts: DigestMatrixDTO
-    flowLinear: DigestMatrixDTO
-    flowQuadratic: DigestMatrixDTO
+class DigestUI(AntaresBaseModel):
+    area: DigestMatrixUI
+    districts: DigestMatrixUI
+    flow_linear: DigestMatrixUI = Field(alias="flowLinear")
+    flow_quadratic: DigestMatrixUI = Field(alias="flowQuadratic")
 
 
-def _get_flow_linear(df: pd.DataFrame) -> DigestMatrixDTO:
+def _get_flow_linear(df: pd.DataFrame) -> DigestMatrixUI:
     return _get_flow(df, "Links (FLOW LIN.)")
 
 
-def _get_flow_quadratic(df: pd.DataFrame) -> DigestMatrixDTO:
+def _get_flow_quadratic(df: pd.DataFrame) -> DigestMatrixUI:
     return _get_flow(df, "Links (FLOW QUAD.)")
 
 
-def _get_flow(df: pd.DataFrame, keyword: str) -> DigestMatrixDTO:
+def _get_flow(df: pd.DataFrame, keyword: str) -> DigestMatrixUI:
     first_column = df["1"].tolist()
     index = next((k for k, v in enumerate(first_column) if v == keyword), None)
     if not index:
-        return DigestMatrixDTO(columns=[], data=[], groupedColumns=False)
+        return DigestMatrixUI(columns=[], data=[], groupedColumns=False)
     index_start = index + 2
     df_col_start = 1
     df_size = next((k for k, v in enumerate(first_column[index_start:]) if v == ""), len(first_column) - index_start)
     flow_df = df.iloc[index_start : index_start + df_size, df_col_start : df_col_start + df_size]
     data = flow_df.iloc[:, 1:].to_numpy().tolist()
     cols = [""] + flow_df.iloc[0, 1:].tolist()
-    return DigestMatrixDTO(columns=cols, data=data, groupedColumns=False)
+    return DigestMatrixUI(columns=cols, data=data, groupedColumns=False)
 
 
-def _build_areas_and_districts(df: pd.DataFrame, first_row: int) -> DigestMatrixDTO:
+def _build_areas_and_districts(df: pd.DataFrame, first_row: int) -> DigestMatrixUI:
     first_column = df["1"].tolist()
     first_area_row = df.iloc[first_row, 2:].tolist()
     col_number = next((k for k, v in enumerate(first_area_row) if v == ""), df.shape[1])
     final_index = first_column[first_row:].index("") + first_row
     data = df.iloc[first_row:final_index, 1 : col_number + 1].to_numpy().tolist()
     cols_raw = df.iloc[first_row - 3 : first_row, 2 : col_number + 1].to_numpy().tolist()
     columns = [[""]] + [[a, b, c] for a, b, c in zip(cols_raw[0], cols_raw[1], cols_raw[2])]
-    return DigestMatrixDTO(columns=columns, data=data, groupedColumns=True)
+    return DigestMatrixUI(columns=columns, data=data, groupedColumns=True)
 
 
-def _get_area(df: pd.DataFrame) -> DigestMatrixDTO:
+def _get_area(df: pd.DataFrame) -> DigestMatrixUI:
     return _build_areas_and_districts(df, 7)
 
 
-def _get_district(df: pd.DataFrame) -> DigestMatrixDTO:
+def _get_district(df: pd.DataFrame) -> DigestMatrixUI:
     first_column = df["1"].tolist()
     first_row = next((k for k, v in enumerate(first_column) if "@" in v), None)
     if not first_row:
-        return DigestMatrixDTO(columns=[], data=[], groupedColumns=False)
+        return DigestMatrixUI(columns=[], data=[], groupedColumns=False)
     return _build_areas_and_districts(df, first_row)
 
 
@@ -96,7 +97,7 @@ def load(
         del output["index"]
         return t.cast(JSON, output)
 
-    def get_dto(self) -> DigestDTO:
+    def get_ui(self) -> DigestUI:
         """
         Parse a digest file and returns it as 4 separated matrices.
         One for areas, one for the districts, one for linear flow and the last one for quadratic flow.
@@ -106,7 +107,7 @@ def get_dto(self) -> DigestDTO:
         flow_quadratic = _get_flow_quadratic(df)
         area = _get_area(df)
         districts = _get_district(df)
-        return DigestDTO(area=area, districts=districts, flowLinear=flow_linear, flowQuadratic=flow_quadratic)
+        return DigestUI(area=area, districts=districts, flowLinear=flow_linear, flowQuadratic=flow_quadratic)
 
     def _parse_digest_file(self) -> pd.DataFrame:
         """

antarest/study/web/studies_blueprint.py

@@ -43,7 +43,7 @@
 from antarest.study.repository import AccessPermissions, StudyFilter, StudyPagination, StudySortBy
 from antarest.study.service import StudyService
 from antarest.study.storage.rawstudy.model.filesystem.config.model import FileStudyTreeConfigDTO
-from antarest.study.storage.rawstudy.model.filesystem.root.output.simulation.mode.mcall.digest import DigestDTO
+from antarest.study.storage.rawstudy.model.filesystem.root.output.simulation.mode.mcall.digest import DigestUI
 
 logger = logging.getLogger(__name__)
 
@@ -817,16 +817,16 @@ def unarchive_output(
         return content
 
     @bp.get(
-        "/private/studies/{study_id}/outputs/{output_id}/digest",
+        "/private/studies/{study_id}/outputs/{output_id}/digest-ui",
         tags=[APITag.study_outputs],
-        summary="Get an output digest file",
-        response_model=DigestDTO,
+        summary="Display an output digest file for the front-end",
+        response_model=DigestUI,
     )
     def get_digest_file(
         study_id: str,
         output_id: str,
         current_user: JWTUser = Depends(auth.get_current_user),
-    ) -> DigestDTO:
+    ) -> DigestUI:
         study_id = sanitize_uuid(study_id)
         output_id = sanitize_string(output_id)
         logger.info(