Valeurs possibles dans la description des champs
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+6
-13
@@ -972,21 +972,14 @@ def make_donut(
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def make_column_picker(page: str):
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def make_column_picker(page: str):
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table_data = []
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table_data = []
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table_columns = [
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for col in schema.names():
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{
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column_data_schema = DATA_SCHEMA[col]
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column_data = {
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"id": col,
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"id": col,
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"name": DATA_SCHEMA[col]["title"],
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"name": column_data_schema["title"],
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"description": DATA_SCHEMA[col]["description"],
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"description": column_data_schema["description"],
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}
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}
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for col in schema.names()
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table_data.append(column_data)
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]
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for column in table_columns:
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new_column = {
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"id": column["id"],
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"name": column["name"],
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"description": DATA_SCHEMA[column["id"]]["description"],
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}
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table_data.append(new_column)
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table = (
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table = (
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DataTable(
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DataTable(
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+10
-1
@@ -124,7 +124,16 @@ def get_data_schema() -> dict:
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raw = _load_schema_file(cache_path)
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raw = _load_schema_file(cache_path)
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if raw is None:
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if raw is None:
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raise RuntimeError("Aucun schéma disponible (ni distant ni cache).")
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raise RuntimeError("Aucun schéma disponible (ni distant ni cache).")
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return OrderedDict((c["name"], c) for c in raw["fields"])
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schema = OrderedDict((c["name"], c) for c in raw["fields"])
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for col in schema.keys():
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new_obj = schema[col]
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if "enum" in new_obj:
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enums = ", ".join(new_obj["enum"])
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new_obj["description"] = (
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f"{new_obj['description']} Valeurs possibles : {enums}"
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)
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print(schema["titulaire_typeIdentifiant"])
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return schema
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def prepare_dashboard_data(**filter_params) -> pl.DataFrame:
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def prepare_dashboard_data(**filter_params) -> pl.DataFrame:
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