Use tuples and simplify views

app.py

@@ -53,9 +53,10 @@ def load_result(model_id):
     result_path = get_result_path_from_model(model_id, latest_result_path_per_model)
     data = load_data(result_path)
     model_name = data.get("model_name", "Model")
+    df = to_dataframe_all(data)
     result = [
-        to_vertical(to_dataframe_all(data), model_name),
-        to_vertical(to_dataframe_results(data), model_name)
+        to_vertical(df, model_name),
+        to_vertical(to_dataframe_results(df), model_name)
     ]
     return result
 
@@ -65,30 +66,42 @@ def to_dataframe(data):
 
 
 def to_vertical(df, model_name):
-    return df.iloc[0].rename_axis("Parameters").rename(model_name).to_frame()  # .reset_index()
+    df = df.iloc[0].rename_axis("Parameters").rename(model_name).to_frame()  # .reset_index()
+    df.index = df.index.str.join(".")
+    return df
 
 
 def to_dataframe_all(data):
-    return pd.json_normalize([{key: value for key, value in data.items() if key not in EXCLUDED_KEYS}])
-
-
-def to_dataframe_results(data):
-    dfs = {}
-    for key in data["results"]:
-        if key not in EXCLUDED_RESULTS_KEYS:  # key.startswith("leaderboard_"):
-            name = key[len("leaderboard_"):]
-            df = to_dataframe(
-                {
-                    key: value
-                    for key, value in data["results"][key].items()
-                    if key not in EXCLUDED_RESULTS_LEADERBOARDS_KEYS
-                }
-            )
-            # df.drop(columns=["alias"])
-            # df.columns = pd.MultiIndex.from_product([[name], df.columns])
-            df.columns = [f"{name}.{column}" for column in df.columns]
-            dfs[name] = df
-    return pd.concat(dfs.values(), axis="columns")
+    df = pd.json_normalize([{key: value for key, value in data.items() if key not in EXCLUDED_KEYS}])
+    # df.columns = df.columns.str.split(".")  # .split return a list instead of a tuple
+    df.columns = list(map(lambda x: tuple(x.split(".")), df.columns))
+    return df
+
+#
+# def to_dataframe_results(data):
+#     dfs = {}
+#     for key in data["results"]:
+#         if key not in EXCLUDED_RESULTS_KEYS:  # key.startswith("leaderboard_"):
+#             name = key[len("leaderboard_"):]
+#             df = to_dataframe(
+#                 {
+#                     key: value
+#                     for key, value in data["results"][key].items()
+#                     if key not in EXCLUDED_RESULTS_LEADERBOARDS_KEYS
+#                 }
+#             )
+#             # df.drop(columns=["alias"])
+#             # df.columns = pd.MultiIndex.from_product([[name], df.columns])
+#             df.columns = [f"{name}.{column}" for column in df.columns]
+#             dfs[name] = df
+#     return pd.concat(dfs.values(), axis="columns")
+
+
+def to_dataframe_results(df):
+    df = df.loc[:, df.columns.str[0] == "results"]
+    df = df.loc[:, ~df.columns.str[1].isin(EXCLUDED_RESULTS_KEYS)]
+    df = df.loc[:, ~df.columns.str[2].isin(EXCLUDED_RESULTS_LEADERBOARDS_KEYS)]
+    return df
 
 
 def concat_result_1(result_1, results):