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vizro-core/examples/scratch_dev/_poc_dynamic_controls.py

@@ -1,9 +1,7 @@
 import dash
-import plotly.express as px
-
-from dash import Dash, html, dcc, Output, callback, clientside_callback, Input, State, set_props
 import dash_mantine_components as dmc
-
+import plotly.express as px
+from dash import Dash, Input, Output, State, callback, clientside_callback, dcc, html
 
 CONTROL_SELECTOR = dcc.RangeSlider
 
@@ -90,18 +88,18 @@ def categorical_filter_build(options=None):
         kwargs["multi"] = MULTI
 
     return CONTROL_SELECTOR(
-        id=f'filter',
+        id="filter",
         options=options or pre_build_options,
         value=pre_build_categorical_value,
         persistence=True,
         persistence_type="session",
-        **kwargs
+        **kwargs,
     )
 
 
 def numerical_filter_build(min_value=None, max_value=None):
     return CONTROL_SELECTOR(
-        id=f'filter',
+        id="filter",
         min=min_value or pre_build_min,
         max=max_value or pre_build_max,
         value=pre_build_numerical_value,
@@ -117,7 +115,7 @@ def _get_initial_page_build_object():
         if CONTROL_SELECTOR == dcc.Dropdown:
             # A hack explained in on_page_load To-do:"Limitations" section below in this page.
             return dmc.DateRangePicker(
-                id='filter',
+                id="filter",
                 value=pre_build_categorical_value,
                 persistence=True,
                 persistence_type="session",
@@ -133,27 +131,28 @@ def _get_initial_page_build_object():
         [
             dcc.Store(id="on_page_load_trigger_another_page"),
             html.H2("Another page"),
-
             # # This does NOT work because id="filter" doesn't exist but is used as OPL callback State.
             # dcc.Loading(id="filter_container"),
-
             # # Possible solution is to alter filter.options from on_page_load. This would work, but it's not optimal.
             # dcc.Dropdown(id="filter", options=options, value=options, multi=True, persistence=True),
-
             # # Outer container can be changed with dcc.Loading.
             html.Div(
                 _get_initial_page_build_object(),
                 id="filter_container",
             ),
-
             # # Does not work because OPL filter input is missing, but it's used for filtering figures data_frame.
             # html.Div(
             #     html.Div(id="filter"),
             #     id="filter_container",
             # ),
-
             html.Br(),
-            dcc.RadioItems(id="parameter", options=["sepal_width", "sepal_length"], value="sepal_width", persistence=True, persistence_type="session"),
+            dcc.RadioItems(
+                id="parameter",
+                options=["sepal_width", "sepal_length"],
+                value="sepal_width",
+                persistence=True,
+                persistence_type="session",
+            ),
             dcc.Loading(dcc.Graph(id="graph1")),
             dcc.Loading(dcc.Graph(id="graph2")),
         ]
@@ -206,11 +205,10 @@ def get_data(species):
     ],
     inputs=[
         Input("global_on_page_load_another_page_action_trigger", "data"),
-
         State("filter", "value"),
         State("parameter", "value"),
     ],
-    prevent_initial_call=True
+    prevent_initial_call=True,
 )
 def on_page_load(data, persisted_filter_value, x):
     # Ideally, OPL flow should look like this:
@@ -263,9 +261,13 @@ def on_page_load(data, persisted_filter_value, x):
     if CONTROL_SELECTOR in SELECTOR_TYPE["categorical"]:
         categorical_filter_options = sorted(df["species"].unique().tolist())
         if MULTI:
-            categorical_filter_value = [value for value in persisted_filter_value if value in categorical_filter_options]
+            categorical_filter_value = [
+                value for value in persisted_filter_value if value in categorical_filter_options
+            ]
         else:
-            categorical_filter_value = persisted_filter_value if persisted_filter_value in categorical_filter_options else None
+            categorical_filter_value = (
+                persisted_filter_value if persisted_filter_value in categorical_filter_options else None
+            )
         new_filter_obj = categorical_filter_build(options=categorical_filter_options)
 
         # --- Filtering data: ---
@@ -298,19 +300,28 @@ def on_page_load(data, persisted_filter_value, x):
         numerical_filter_min = float(df["sepal_length"].min())
         numerical_filter_max = float(df["sepal_length"].max())
         if MULTI:
-            numerical_filter_value = [max(numerical_filter_min, persisted_filter_value[0]), min(numerical_filter_max, persisted_filter_value[1])]
+            numerical_filter_value = [
+                max(numerical_filter_min, persisted_filter_value[0]),
+                min(numerical_filter_max, persisted_filter_value[1]),
+            ]
         else:
-            numerical_filter_value = persisted_filter_value if numerical_filter_min < persisted_filter_value < numerical_filter_max else numerical_filter_min
+            numerical_filter_value = (
+                persisted_filter_value
+                if numerical_filter_min < persisted_filter_value < numerical_filter_max
+                else numerical_filter_min
+            )
         new_filter_obj = numerical_filter_build(min_value=numerical_filter_min, max_value=numerical_filter_max)
         # set_props(component_id="numerical_filter_container", props={"children": new_filter_obj})
 
         # --- Filtering data: ---
         if MULTI:
-            df = df[(df["sepal_length"] >= numerical_filter_value[0]) & (df["sepal_length"] <= numerical_filter_value[1])]
+            df = df[
+                (df["sepal_length"] >= numerical_filter_value[0]) & (df["sepal_length"] <= numerical_filter_value[1])
+            ]
         else:
             df = df[(df["sepal_length"] == numerical_filter_value)]
 
-    print("")
+    print()
     return graph1_call(df), graph2_call(df, x), new_filter_obj
 
 
@@ -394,4 +405,4 @@ def on_page_load(data, persisted_filter_value, x):
 # IMPORTANT: also consider parametrised data case.
 
 if __name__ == "__main__":
-    app.run(debug=True, dev_tools_hot_reload=False)
+    app.run(debug=True, dev_tools_hot_reload=False)

vizro-core/examples/scratch_dev/app.py

@@ -1,4 +1,5 @@
 """Dev app to try things out."""
+
 import time
 import yaml
 
@@ -27,24 +28,35 @@
 def load_from_file(filter_column=None, parametrized_species=None):
     # Load the full iris dataset
     df = px.data.iris()
-    df['date_column'] = pd.date_range(start=pd.to_datetime("2024-01-01"), periods=len(df), freq='D')
+    df["date_column"] = pd.date_range(start=pd.to_datetime("2024-01-01"), periods=len(df), freq="D")
 
     if parametrized_species:
         return df[df["species"].isin(parametrized_species)]
 
-    with open('data.yaml', 'r') as file:
+    with open("data.yaml", "r") as file:
         data = yaml.safe_load(file)
         data = data or {}
 
     filter_column = filter_column or FILTER_COLUMN
     if filter_column == "species":
-        final_df = pd.concat(objs=[
-            df[df[filter_column] == 'setosa'].head(data.get("setosa", 0)),
-            df[df[filter_column] == 'versicolor'].head(data.get("versicolor", 0)),
-            df[df[filter_column] == 'virginica'].head(data.get("virginica", 0)),
-        ], ignore_index=True)
+        final_df = pd.concat(
+            objs=[
+                df[df[filter_column] == "setosa"].head(data.get("setosa", 0)),
+                df[df[filter_column] == "versicolor"].head(data.get("versicolor", 0)),
+                df[df[filter_column] == "virginica"].head(data.get("virginica", 0)),
+            ],
+            ignore_index=True,
+        )
     elif filter_column == "sepal_length":
-        final_df = df[df[filter_column].between(data.get("min"), data.get("max",), inclusive="both")]
+        final_df = df[
+            df[filter_column].between(
+                data.get("min"),
+                data.get(
+                    "max",
+                ),
+                inclusive="both",
+            )
+        ]
     elif filter_column == "date_column":
         date_min = pd.to_datetime(data.get("date_min"))
         date_max = pd.to_datetime(data.get("date_max"))
@@ -82,16 +94,18 @@ def load_from_file(filter_column=None, parametrized_species=None):
         vm.Graph(
             id="p1-G-2",
             figure=px.scatter(data_frame=px.data.iris(), **SCATTER_CHART_CONF),
-        )
+        ),
     ],
     controls=[
         vm.Filter(id="p1-F-1", column="species", targets=["p1-G-1"], selector=vm.Dropdown(title="Dynamic filter")),
         vm.Filter(id="p1-F-2", column="species", targets=["p1-G-2"], selector=vm.Dropdown(title="Static filter")),
         vm.Parameter(
             targets=["p1-G-1.x", "p1-G-2.x"],
-            selector=vm.RadioItems(options=["species", "sepal_width"], value="species", title="Simple X-axis parameter")
-        )
-    ]
+            selector=vm.RadioItems(
+                options=["species", "sepal_width"], value="species", title="Simple X-axis parameter"
+            ),
+        ),
+    ],
 )
 
 
@@ -110,9 +124,11 @@ def load_from_file(filter_column=None, parametrized_species=None):
         vm.Filter(id="p2-F-4", column="species", selector=vm.RadioItems()),
         vm.Parameter(
             targets=["p2-G-1.x"],
-            selector=vm.RadioItems(options=["species", "sepal_width"], value="species", title="Simple X-axis parameter")
-        )
-    ]
+            selector=vm.RadioItems(
+                options=["species", "sepal_width"], value="species", title="Simple X-axis parameter"
+            ),
+        ),
+    ],
 )
 
 
@@ -129,9 +145,11 @@ def load_from_file(filter_column=None, parametrized_species=None):
         vm.Filter(id="p3-F-2", column="sepal_length", selector=vm.RangeSlider()),
         vm.Parameter(
             targets=["p3-G-1.x"],
-            selector=vm.RadioItems(options=["species", "sepal_width"], value="species", title="Simple X-axis parameter")
-        )
-    ]
+            selector=vm.RadioItems(
+                options=["species", "sepal_width"], value="species", title="Simple X-axis parameter"
+            ),
+        ),
+    ],
 )
 
 page_4 = vm.Page(
@@ -147,9 +165,11 @@ def load_from_file(filter_column=None, parametrized_species=None):
         vm.Filter(id="p4-F-2", column="date_column", selector=vm.DatePicker()),
         vm.Parameter(
             targets=["p4-G-1.x"],
-            selector=vm.RadioItems(options=["species", "sepal_width"], value="species", title="Simple X-axis parameter")
-        )
-    ]
+            selector=vm.RadioItems(
+                options=["species", "sepal_width"], value="species", title="Simple X-axis parameter"
+            ),
+        ),
+    ],
 )
 
 page_5 = vm.Page(
@@ -170,73 +190,66 @@ def load_from_file(filter_column=None, parametrized_species=None):
                 # "p5-F-1.",
             ],
             selector=vm.Dropdown(
-                options=["setosa", "versicolor", "virginica"],
-                multi=True,
-                title="Parametrized species"
-            )
+                options=["setosa", "versicolor", "virginica"], multi=True, title="Parametrized species"
+            ),
         ),
         vm.Parameter(
             targets=[
                 "p5-G-1.x",
                 # TODO: Uncomment the following target and see the magic :D
                 # "p5-F-1.",
             ],
-            selector=vm.RadioItems(options=["species", "sepal_width"], value="species", title="Simple X-axis parameter")
+            selector=vm.RadioItems(
+                options=["species", "sepal_width"], value="species", title="Simple X-axis parameter"
+            ),
         ),
-    ]
+    ],
 )
 
 
 page_6 = vm.Page(
     title="Page to test things out",
     components=[
-        vm.Graph(
-            id="graph_dynamic",
-            figure=px.bar(data_frame="load_from_file", **BAR_CHART_CONF)
-        ),
+        vm.Graph(id="graph_dynamic", figure=px.bar(data_frame="load_from_file", **BAR_CHART_CONF)),
         vm.Graph(
             id="graph_static",
             figure=px.scatter(data_frame=px.data.iris(), **SCATTER_CHART_CONF),
-        )
+        ),
     ],
     controls=[
         vm.Filter(
             id="filter_container_id",
             column=FILTER_COLUMN,
             targets=["graph_dynamic"],
             # targets=["graph_static"],
-
             # selector=vm.Dropdown(id="filter_id"),
             # selector=vm.Dropdown(id="filter_id", value=["setosa"]),
-
             # selector=vm.Checklist(id="filter_id"),
             # selector=vm.Checklist(id="filter_id", value=["setosa"]),
-
             # TODO-BUG: vm.Dropdown(multi=False) Doesn't work if value is cleared. The persistence storage become
             #  "null" and our placeholder component dmc.DateRangePicker can't process null value. It expects a value or
             #  a list of values.
             #  SOLUTION -> Create the "Universal Vizro placeholder component".
             #  TEMPORARY SOLUTION -> set clearable=False for the dynamic Dropdown(multi=False)
             # selector=vm.Dropdown(id="filter_id", multi=False), ->
             # selector=vm.Dropdown(id="filter_id", multi=False, value="setosa"),
-
             # selector=vm.RadioItems(id="filter_id"),
             # selector=vm.RadioItems(id="filter_id", value="setosa"),
-
             # selector=vm.Slider(id="filter_id"),
             # selector=vm.Slider(id="filter_id", value=5),
-
             # selector=vm.RangeSlider(id="filter_id"),
             # selector=vm.RangeSlider(id="filter_id", value=[5, 7]),
-           ),
+        ),
         vm.Parameter(
             id="parameter_x",
-            targets=["graph_dynamic.x",],
+            targets=[
+                "graph_dynamic.x",
+            ],
             selector=vm.Dropdown(
                 options=["species", "sepal_width"],
                 value="species",
                 multi=False,
-            )
+            ),
         ),
     ],
 )

vizro-core/examples/scratch_dev/data.yaml

@@ -10,4 +10,4 @@ max: 7
 # Choose from:
 #   2020-01-01 to 2020-05-29
 date_min: 2024-01-01
-date_max: 2024-05-29
+date_max: 2024-05-29

vizro-core/src/vizro/actions/_actions_utils.py

@@ -14,7 +14,7 @@
 from vizro.models.types import MultiValueType, SelectorType, SingleValueType
 
 if TYPE_CHECKING:
-    from vizro.models import Action, VizroBaseModel, Filter
+    from vizro.models import Action, VizroBaseModel
 
 ValidatedNoneValueType = Union[SingleValueType, MultiValueType, None, list[None]]
 
@@ -162,6 +162,7 @@ def _update_nested_figure_properties(
     current_property[keys[-1]] = value
     return figure_config
 
+
 def _get_parametrized_config(
     ctd_parameter: list[CallbackTriggerDict], target: ModelID, data_frame: bool
 ) -> dict[str, Any]:
@@ -275,7 +276,9 @@ def _get_modified_page_figures(
     # Also, it was a good decision to return action output as key: value pairs for the predefined actions.
     _get_unfiltered_data_targets = list(set(figure_targets + control_targets_targets))
 
-    figure_targets_unfiltered_data: dict[ModelID, pd.DataFrame] = _get_unfiltered_data(ctds_parameter, _get_unfiltered_data_targets)
+    figure_targets_unfiltered_data: dict[ModelID, pd.DataFrame] = _get_unfiltered_data(
+        ctds_parameter, _get_unfiltered_data_targets
+    )
 
     for target, unfiltered_data in figure_targets_unfiltered_data.items():
         if target in figure_targets:
@@ -292,8 +295,7 @@ def _get_modified_page_figures(
             current_value = []
 
         outputs[target] = model_manager[target](
-            target_to_data_frame=figure_targets_unfiltered_data,
-            current_value=current_value
+            target_to_data_frame=figure_targets_unfiltered_data, current_value=current_value
         )
 
     return outputs