Gestion des montants inexistants

- possibilité de filtrer sur le champ "Source"
- création automatique d'une release Github quand je push un tag

.github/workflows/tag-release.yaml

@@ -4,11 +4,11 @@ on:
     tags:
       - 'v*' # Push events to matching v*, i.e. v1.0, v20.15.10
 
-name: Create Release
+name: Auto-release d'un tag
 
 jobs:
   build:
-    name: Auto-release d'un tag
+    name: auto-release
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code

README.md

@@ -38,6 +38,11 @@ Ne pas oublier de mettre à jour les fichier .env.
 
 ## Notes de version
 
+##### 2.1.5 (10 octobre 2025)
+
+- réparation des filtres (notamment < > sur les montants)
+- remplacement des valeurs "null" dans les tableaux par des cellules vides
+
 ##### 2.1.4 (8 octobre 2025)
 
 - possibilité de filtrer sur le champ "Source"

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "decp.info"
 description = "Interface d'exploration et d'analyse des marchés publics français."
-version = "2.1.4"
+version = "2.1.5"
 requires-python = ">= 3.10"
 authors = [
     { name = "Colin Maudry", email = "colin+decp@maudry.com" }

src/pages/acheteur.py

@@ -175,7 +175,6 @@ def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
     acheteur_siret = url.split("/")[-1]
     lff = df.lazy()
     lff = lff.filter(pl.col("acheteur_id") == acheteur_siret)
-    lff = lff.fill_null("")
     lff = lff.select(
         "id",
         "uid",
@@ -204,6 +203,8 @@ def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
 )
 def get_last_marches_table(data) -> html.Div:
     dff = pl.DataFrame(data)
+    dff = dff.cast(pl.String)
+    dff = dff.fill_null("")
     dff = format_montant(dff)
     columns, tooltip = setup_table_columns(
         dff,

src/pages/tableau.py

@@ -182,9 +182,6 @@ def update_table(page_current, page_size, filter_query, sort_by, data_timestamp)
     if len(sort_by) > 0:
         lff = sort_table_data(lff, sort_by)
 
-    # Remplace les strings null par "", mais pas les numeric null
-    lff = lff.fill_null("")
-
     # Matérialisation des filtres
     dff: pl.DataFrame = lff.collect()
 
@@ -196,6 +193,12 @@ def update_table(page_current, page_size, filter_query, sort_by, data_timestamp)
     # end_row = (page_current + 1) * page_size
     dff = dff.slice(start_row, page_size)
 
+    # Tout devient string
+    dff = dff.cast(pl.String)
+
+    # Remplace les strings null par "", mais pas les numeric null
+    dff = dff.fill_null("")
+
     # Ajout des liens vers l'annuaire des entreprises
     dff = add_links(dff)
 

src/pages/titulaire.py

@@ -180,7 +180,6 @@ def get_titulaire_marches_data(url, titulaire_year: str) -> list[dict]:
         (pl.col("titulaire_id") == titulaire_siret)
         & (pl.col("titulaire_typeIdentifiant") == "SIRET")
     )
-    lff = lff.fill_null("")
     lff = lff.select(
         "id",
         "uid",
@@ -218,6 +217,8 @@ def get_last_marches_table(data) -> html.Div:
     ]
 
     dff = pl.DataFrame(data)
+    dff = dff.cast(pl.String)
+    dff = dff.fill_null("")
     dff = format_montant(dff)
     columns, tooltip = setup_table_columns(
         dff, hideable=False, exclude=["acheteur_id", "id"]

src/utils.py

@@ -126,7 +126,7 @@ def format_number(number) -> str:
 def format_montant(dff: pl.DataFrame) -> pl.DataFrame:
     def format_function(expr, scale=None):
         # https://stackoverflow.com/a/78636786
-        expr = expr.cast(pl.String).str.splitn(".", 2)
+        expr = expr.str.splitn(".", 2)
 
         num = expr.struct[0]
         frac = expr.struct[1]
@@ -145,7 +145,13 @@ def format_montant(dff: pl.DataFrame) -> pl.DataFrame:
             .otherwise(pl.lit(""))
         )
 
-        return num + frac + pl.lit(" €")
+        montant: pl.Expr = (
+            pl.when((num + frac) == pl.lit(""))
+            .then(pl.lit(""))
+            .otherwise(num + frac + pl.lit(" €"))
+        )
+
+        return montant
 
     dff = dff.with_columns(pl.col("montant").pipe(format_function).alias("montant"))
     return dff
@@ -211,21 +217,30 @@ def filter_table_data(lff: pl.LazyFrame, filter_query: str) -> pl.LazyFrame:
     filtering_expressions = filter_query.split(" && ")
     for filter_part in filtering_expressions:
         col_name, operator, filter_value = split_filter_part(filter_part)
-
         col_type = str(schema[col_name])
         if debug:
             print("filter_value:", filter_value)
             print("filter_value_type:", type(filter_value))
+            print("operator:", operator)
             print("col_type:", col_type)
 
-        if col_type == "Date":
-            # Convertir la colonne en chaînes de caractères
-            lff = dates_to_strings(lff, col_name)
+        lff = lff.filter(pl.col(col_name).is_not_null())
 
-        if operator in ("<", "<=", ">", ">="):
-            lff = lff.filter(
-                pl.col(col_name).is_not_null() & (pl.col(col_name) != pl.lit(""))
-            )
+        if col_type == "Date":
+            # Convertir la colonne date en chaînes de caractères
+            lff = dates_to_strings(lff, col_name)
+            col_type = "String"
+        if col_type == "String":
+            lff = lff.filter(pl.col(col_name) != pl.lit(""))
+
+        elif col_type.startswith("Int") or col_type.startswith("Float"):
+            try:
+                filter_value = int(filter_value)
+            except ValueError:
+                logger.error(f"Invalid numeric filter value: {filter_value}")
+                continue
+
+        if operator in ("contains", "<", "<=", ">", ">="):
             if operator == "<":
                 lff = lff.filter(pl.col(col_name) < filter_value)
             elif operator == ">":
@@ -234,17 +249,17 @@ def filter_table_data(lff: pl.LazyFrame, filter_query: str) -> pl.LazyFrame:
                 lff = lff.filter(pl.col(col_name) >= filter_value)
             elif operator == "<=":
                 lff = lff.filter(pl.col(col_name) <= filter_value)
-
+            elif operator == "contains":
+                if col_type in ["String", "Date"]:
+                    lff = lff.filter(
+                        pl.col(col_name).str.contains("(?i)" + filter_value)
+                    )
                 elif col_type.startswith("Int") or col_type.startswith("Float"):
-            try:
-                filter_value = int(filter_value)
-            except ValueError:
-                logger.error(f"Invalid numeric filter value: {filter_value}")
-                continue
                     lff = lff.filter(pl.col(col_name) == filter_value)
-
-        elif operator == "contains" and col_type in ["String", "Date"]:
-            lff = lff.filter(pl.col(col_name).str.contains("(?i)" + filter_value))
+                else:
+                    logger.error(f"Invalid column type: {col_type}")
+        else:
+            logger.error(f"Invalid operator: {operator}")
 
         # elif operator == 'datestartswith':
         # lff = lff.filter(pl.col(col_name).str.startswith(filter_value)")