consolidate and remove unused fixtures

vizro-ai/tests/unit/vizro-ai/dashboard/_response_models/conftest.py

@@ -33,29 +33,13 @@ def fake_llm_layout():
 
 @pytest.fixture
 def fake_llm_filter():
-    response = ['{"column": "a", "targets": ["gdp_chart"]}']
+    response = ['{"column": "a", "targets": ["bar_chart"]}']
     return MockStructuredOutputLLM(responses=response)
 
 
-@pytest.fixture
-def fake_llm_filter_1():
-    response = ['{"column": "country", "targets": ["gdp_chart"]}']
-    return MockStructuredOutputLLM(responses=response)
-
-
-@pytest.fixture
-def df_cols():
-    return ["continent", "country", "population", "gdp"]
-
-
-@pytest.fixture
-def df_schema_1():
-    return {"continent": "object", "country": "object", "population": "int64", "gdp": "int64"}
-
-
 @pytest.fixture
 def controllable_components():
-    return ["gdp_chart"]
+    return ["bar_chart"]
 
 
 @pytest.fixture
@@ -69,8 +53,12 @@ def df():
 
 
 @pytest.fixture
-def df_sample():
-    df = pd.DataFrame({"a": [1, 2, 3, 4, 5], "b": [4, 5, 6, 7, 8]})
+def df_cols():
+    return ["a", "b"]
+
+
+@pytest.fixture
+def df_sample(df):
     return df.sample(5, replace=True, random_state=19)
 
 
@@ -82,7 +70,7 @@ def df_schema():
 @pytest.fixture
 def df_metadata(df, df_schema, df_sample):
     df_metadata = AllDfMetadata({})
-    df_metadata.all_df_metadata["gdp_chart"] = DfMetadata(
+    df_metadata.all_df_metadata["bar_chart"] = DfMetadata(
         df_schema=df_schema,
         df=df,
         df_sample=df_sample,
@@ -118,6 +106,6 @@ def page_plan(component_card):
 @pytest.fixture
 def filter_prompt():
     return """
-        Create a filter from the following instructions: Filter the gdp chart by country.
+        Create a filter from the following instructions: Filter the bar chart by column `a`.
         Do not make up things that are optional and DO NOT configure actions, action triggers or action chains.
         If no options are specified, leave them out."""

vizro-ai/tests/unit/vizro-ai/dashboard/_response_models/test_controls.py

@@ -10,32 +10,32 @@
     from pydantic import ValidationError
 
 # Needed for testing control creation.
-model_manager.__setitem__("gdp_chart", VizroBaseModel)
+model_manager.__setitem__("bar_chart", VizroBaseModel)
 
 
 class TestFilterProxyCreate:
     """Tests filter proxy creation."""
 
     def test_create_filter_proxy_validate_targets(self, df_cols, df_schema, controllable_components):
-        actual = _create_filter_proxy(df_cols, df_schema, controllable_components)
+        filter_proxy = _create_filter_proxy(df_cols, df_schema, controllable_components)
         with pytest.raises(ValidationError, match="targets must be one of"):
-            actual(targets=["population_chart"], column="gdp")
+            filter_proxy(targets=["population_chart"], column="a")
 
     def test_create_filter_proxy_validate_targets_not_empty(self, df_cols, df_schema, controllable_components):
-        actual = _create_filter_proxy(df_cols=df_cols, df_schema=df_schema, controllable_components=[])
+        filter_proxy = _create_filter_proxy(df_cols=df_cols, df_schema=df_schema, controllable_components=[])
         with pytest.raises(ValidationError):
-            actual(targets=[], column="gdp")
+            filter_proxy(targets=[], column="a")
 
     def test_create_filter_proxy_validate_columns(self, df_cols, df_schema, controllable_components):
-        actual = _create_filter_proxy(df_cols, df_schema, controllable_components)
+        filter_proxy = _create_filter_proxy(df_cols, df_schema, controllable_components)
         with pytest.raises(ValidationError, match="column must be one of"):
-            actual(targets=["gdp_chart"], column="x")
+            filter_proxy(targets=["bar_chart"], column="x")
 
     def test_create_filter_proxy(self, df_cols, df_schema, controllable_components):
-        actual = _create_filter_proxy(df_cols, df_schema, controllable_components)
-        actual_filter = actual(targets=["gdp_chart"], column="gdp")
+        filter_proxy = _create_filter_proxy(df_cols, df_schema, controllable_components)
+        actual_filter = filter_proxy(targets=["bar_chart"], column="a")
 
-        assert actual_filter.dict(exclude={"id": True}) == vm.Filter(targets=["gdp_chart"], column="gdp").dict(
+        assert actual_filter.dict(exclude={"id": True}) == vm.Filter(targets=["bar_chart"], column="a").dict(
             exclude={"id": True}
         )
 
@@ -50,7 +50,7 @@ def test_control_plan_invalid_df_name(self, fake_llm_filter, df_metadata):
             df_name="population_chart",
         )
         default_control = control_plan.create(
-            model=fake_llm_filter, controllable_components=["gdp_chart"], all_df_metadata=df_metadata
+            model=fake_llm_filter, controllable_components=["bar_chart"], all_df_metadata=df_metadata
         )
         assert default_control is None
 
@@ -59,19 +59,18 @@ def test_control_plan_invalid_type(self, fake_llm_filter, df_metadata):
             ControlPlan(
                 control_type="parameter",
                 control_description="Create a parameter that targets the data based on the column 'a'.",
-                df_name="gdp_chart",
+                df_name="bar_chart",
             )
 
 
-def test_create_filter(filter_prompt, fake_llm_filter_1, df_cols, df_schema_1, controllable_components):
-
-    actual = _create_filter(
+def test_create_filter(filter_prompt, fake_llm_filter, df_cols, df_schema, controllable_components):
+    actual_filter = _create_filter(
         filter_prompt=filter_prompt,
-        model=fake_llm_filter_1,
+        model=fake_llm_filter,
         df_cols=df_cols,
-        df_schema=df_schema_1,
+        df_schema=df_schema,
         controllable_components=controllable_components,
     )
-    assert actual.dict(exclude={"id": True}) == vm.Filter(targets=["gdp_chart"], column="country").dict(
+    assert actual_filter.dict(exclude={"id": True}) == vm.Filter(targets=["bar_chart"], column="a").dict(
         exclude={"id": True}
     )