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superset2/tests/unit_tests/mcp_service/chart/test_chart_utils.py

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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""Tests for chart utilities module"""
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from superset.constants import NO_TIME_RANGE
from superset.mcp_service.chart.chart_utils import (
_add_adhoc_filters,
_ensure_temporal_adhoc_filter,
adhoc_filters_to_query_filters,
configure_temporal_handling,
create_metric_object,
generate_chart_name,
generate_explore_link,
is_column_truly_temporal,
map_config_to_form_data,
map_filter_operator,
map_table_config,
map_xy_config,
validate_chart_dataset,
)
from superset.mcp_service.chart.schemas import (
AxisConfig,
ColumnRef,
FilterConfig,
LegendConfig,
TableChartConfig,
XYChartConfig,
)
from superset.utils.core import FilterOperator, GenericDataType
class TestCreateMetricObject:
"""Test create_metric_object function"""
def test_create_metric_object_with_aggregate(self) -> None:
"""Test creating metric object with specified aggregate"""
col = ColumnRef(name="revenue", aggregate="SUM", label="Total Revenue")
result = create_metric_object(col)
assert isinstance(result, dict)
assert result["aggregate"] == "SUM"
assert result["column"]["column_name"] == "revenue"
assert result["label"] == "Total Revenue"
assert result["optionName"] == "metric_revenue"
assert result["expressionType"] == "SIMPLE"
def test_create_metric_object_default_aggregate(self) -> None:
"""Test creating metric object with default aggregate"""
col = ColumnRef(name="orders")
result = create_metric_object(col)
assert isinstance(result, dict)
assert result["aggregate"] == "SUM"
assert result["column"]["column_name"] == "orders"
assert result["label"] == "SUM(orders)"
assert result["optionName"] == "metric_orders"
def test_create_metric_object_saved_metric_returns_string(self) -> None:
"""Test that saved metrics return a plain string metric name"""
col = ColumnRef(name="total_revenue", saved_metric=True)
result = create_metric_object(col)
assert result == "total_revenue"
assert isinstance(result, str)
def test_create_metric_object_saved_metric_ignores_aggregate(self) -> None:
"""Test that saved metrics ignore aggregate even if somehow set"""
col = ColumnRef(name="total_revenue", saved_metric=True, aggregate="SUM")
result = create_metric_object(col)
# saved_metric validator clears aggregate, result is plain string
assert result == "total_revenue"
class TestMapFilterOperator:
"""Test map_filter_operator function"""
def test_map_filter_operators(self) -> None:
"""Test mapping of various filter operators"""
assert map_filter_operator("=") == "=="
assert map_filter_operator(">") == ">"
assert map_filter_operator("<") == "<"
assert map_filter_operator(">=") == ">="
assert map_filter_operator("<=") == "<="
assert map_filter_operator("!=") == "!="
def test_map_filter_operators_pattern_matching(self) -> None:
"""Test mapping of pattern matching operators"""
assert map_filter_operator("LIKE") == "LIKE"
assert map_filter_operator("ILIKE") == "ILIKE"
assert map_filter_operator("NOT LIKE") == "NOT LIKE"
def test_map_filter_operators_set(self) -> None:
"""Test mapping of set operators"""
assert map_filter_operator("IN") == "IN"
assert map_filter_operator("NOT IN") == "NOT IN"
def test_map_filter_operator_unknown(self) -> None:
"""Test mapping of unknown operator returns original"""
assert map_filter_operator("UNKNOWN") == "UNKNOWN"
class TestMapTableConfig:
"""Test map_table_config function"""
def test_map_table_config_basic(self) -> None:
"""Test basic table config mapping with aggregated columns"""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="product", aggregate="COUNT"),
ColumnRef(name="revenue", aggregate="SUM"),
],
)
result = map_table_config(config)
assert result["viz_type"] == "table"
assert result["query_mode"] == "aggregate"
# Aggregated columns should be in metrics, not all_columns
assert "all_columns" not in result
assert len(result["metrics"]) == 2
assert result["metrics"][0]["aggregate"] == "COUNT"
assert result["metrics"][1]["aggregate"] == "SUM"
def test_map_table_config_raw_columns(self) -> None:
"""Test table config mapping with raw columns (no aggregates)"""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="product"),
ColumnRef(name="category"),
],
)
result = map_table_config(config)
assert result["viz_type"] == "table"
assert result["query_mode"] == "raw"
# Raw columns should be in all_columns
assert result["all_columns"] == ["product", "category"]
assert "metrics" not in result
def test_map_table_config_with_filters(self) -> None:
"""Test table config mapping with filters"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
filters=[FilterConfig(column="status", op="=", value="active")],
)
result = map_table_config(config)
assert "adhoc_filters" in result
assert len(result["adhoc_filters"]) == 1
filter_obj = result["adhoc_filters"][0]
assert filter_obj["subject"] == "status"
assert filter_obj["operator"] == "=="
assert filter_obj["comparator"] == "active"
assert filter_obj["expressionType"] == "SIMPLE"
def test_map_table_config_with_like_filter(self) -> None:
"""Test table config mapping with LIKE filter for pattern matching"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="name")],
filters=[FilterConfig(column="name", op="LIKE", value="%mario%")],
)
result = map_table_config(config)
assert "adhoc_filters" in result
assert len(result["adhoc_filters"]) == 1
filter_obj = result["adhoc_filters"][0]
assert filter_obj["subject"] == "name"
assert filter_obj["operator"] == "LIKE"
assert filter_obj["comparator"] == "%mario%"
assert filter_obj["expressionType"] == "SIMPLE"
def test_map_table_config_with_ilike_filter(self) -> None:
"""Test table config mapping with ILIKE filter for case-insensitive matching"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="name")],
filters=[FilterConfig(column="name", op="ILIKE", value="%mario%")],
)
result = map_table_config(config)
assert "adhoc_filters" in result
filter_obj = result["adhoc_filters"][0]
assert filter_obj["operator"] == "ILIKE"
assert filter_obj["comparator"] == "%mario%"
def test_map_table_config_with_in_filter(self) -> None:
"""Test table config mapping with IN filter for list matching"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="platform")],
filters=[
FilterConfig(
column="platform", op="IN", value=["Wii", "PS3", "Xbox360"]
)
],
)
result = map_table_config(config)
assert "adhoc_filters" in result
filter_obj = result["adhoc_filters"][0]
assert filter_obj["subject"] == "platform"
assert filter_obj["operator"] == "IN"
assert filter_obj["comparator"] == ["Wii", "PS3", "Xbox360"]
def test_map_table_config_with_not_in_filter(self) -> None:
"""Test table config mapping with NOT IN filter"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="status")],
filters=[
FilterConfig(
column="status", op="NOT IN", value=["archived", "deleted"]
)
],
)
result = map_table_config(config)
assert "adhoc_filters" in result
filter_obj = result["adhoc_filters"][0]
assert filter_obj["operator"] == "NOT IN"
assert filter_obj["comparator"] == ["archived", "deleted"]
def test_map_table_config_with_mixed_filters(self) -> None:
"""Test table config mapping with mixed filter operators"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="name"), ColumnRef(name="sales")],
filters=[
FilterConfig(column="platform", op="=", value="Wii"),
FilterConfig(column="name", op="ILIKE", value="%mario%"),
FilterConfig(column="genre", op="IN", value=["Sports", "Racing"]),
],
)
result = map_table_config(config)
assert len(result["adhoc_filters"]) == 3
assert result["adhoc_filters"][0]["operator"] == "=="
assert result["adhoc_filters"][1]["operator"] == "ILIKE"
assert result["adhoc_filters"][1]["comparator"] == "%mario%"
assert result["adhoc_filters"][2]["operator"] == "IN"
assert result["adhoc_filters"][2]["comparator"] == ["Sports", "Racing"]
def test_map_table_config_with_sort(self) -> None:
"""Test table config mapping with sort"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
sort_by=["product", "revenue"],
)
result = map_table_config(config)
assert result["order_by_cols"] == ["product", "revenue"]
def test_map_table_config_ag_grid_table(self) -> None:
"""Test table config mapping with AG Grid Interactive Table viz_type"""
config = TableChartConfig(
chart_type="table",
viz_type="ag-grid-table",
columns=[
ColumnRef(name="product_line"),
ColumnRef(name="sales", aggregate="SUM", label="Total Sales"),
],
)
result = map_table_config(config)
# AG Grid tables use 'ag-grid-table' viz_type
assert result["viz_type"] == "ag-grid-table"
assert result["query_mode"] == "aggregate"
assert len(result["metrics"]) == 1
assert result["metrics"][0]["aggregate"] == "SUM"
# Non-aggregated columns should be in groupby
assert "groupby" in result
assert "product_line" in result["groupby"]
def test_map_table_config_ag_grid_raw_mode(self) -> None:
"""Test AG Grid table with raw columns (no aggregates)"""
config = TableChartConfig(
chart_type="table",
viz_type="ag-grid-table",
columns=[
ColumnRef(name="product_line"),
ColumnRef(name="category"),
ColumnRef(name="region"),
],
)
result = map_table_config(config)
assert result["viz_type"] == "ag-grid-table"
assert result["query_mode"] == "raw"
assert result["all_columns"] == ["product_line", "category", "region"]
assert "metrics" not in result
def test_map_table_config_default_viz_type(self) -> None:
"""Test that default viz_type is 'table' not 'ag-grid-table'"""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
)
result = map_table_config(config)
assert result["viz_type"] == "table"
def test_map_table_config_row_limit(self) -> None:
"""Test that row_limit is mapped to form_data."""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
row_limit=500,
)
result = map_table_config(config)
assert result["row_limit"] == 500
def test_map_table_config_default_row_limit(self) -> None:
"""Test that default row_limit is mapped to form_data."""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product", aggregate="SUM")],
)
result = map_table_config(config)
assert result["row_limit"] == 1000
def test_map_table_config_saved_metric_as_metric(self) -> None:
"""Test that saved metrics are routed to metrics, not raw columns."""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="product_line"),
ColumnRef(name="total_revenue", saved_metric=True),
],
)
result = map_table_config(config)
assert result["query_mode"] == "aggregate"
assert result["metrics"] == ["total_revenue"]
assert "product_line" in result["groupby"]
def test_map_table_config_saved_metric_only(self) -> None:
"""Test table with only saved metrics (no raw columns)."""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="total_revenue", saved_metric=True),
ColumnRef(name="avg_order_value", saved_metric=True),
],
)
result = map_table_config(config)
assert result["query_mode"] == "aggregate"
assert result["metrics"] == ["total_revenue", "avg_order_value"]
assert "all_columns" not in result
class TestAddAdhocFilters:
"""Test _add_adhoc_filters helper function"""
def test_adds_filters_to_form_data(self) -> None:
"""Test that filters are correctly added to form_data."""
form_data: dict[str, Any] = {}
filters = [
FilterConfig(column="region", op="=", value="US"),
FilterConfig(column="year", op=">", value=2020),
]
_add_adhoc_filters(form_data, filters)
assert "adhoc_filters" in form_data
assert len(form_data["adhoc_filters"]) == 2
assert form_data["adhoc_filters"][0]["subject"] == "region"
assert form_data["adhoc_filters"][0]["operator"] == "=="
assert form_data["adhoc_filters"][1]["subject"] == "year"
assert form_data["adhoc_filters"][1]["operator"] == ">"
def test_no_filters_does_nothing(self) -> None:
"""Test that None filters leave form_data unchanged."""
form_data: dict[str, Any] = {"viz_type": "table"}
_add_adhoc_filters(form_data, None)
assert "adhoc_filters" not in form_data
def test_empty_list_does_nothing(self) -> None:
"""Test that empty filter list leaves form_data unchanged."""
form_data: dict[str, Any] = {"viz_type": "table"}
_add_adhoc_filters(form_data, [])
assert "adhoc_filters" not in form_data
class TestMapXYConfig:
"""Test map_xy_config function"""
def test_map_xy_config_line_chart(self) -> None:
"""Test XY config mapping for line chart"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_line"
assert result["x_axis"] == "date"
assert len(result["metrics"]) == 1
assert result["metrics"][0]["aggregate"] == "SUM"
def test_map_xy_config_with_groupby(self) -> None:
"""Test XY config mapping with group by"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue")],
kind="bar",
group_by=ColumnRef(name="region"),
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert result["groupby"] == ["region"]
def test_map_xy_config_with_axes(self) -> None:
"""Test XY config mapping with axis configurations"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue")],
kind="area",
x_axis=AxisConfig(title="Date", format="%Y-%m-%d"),
y_axis=AxisConfig(title="Revenue", scale="log", format="$,.2f"),
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_area"
assert result["x_axis_title"] == "Date"
assert result["x_axis_format"] == "%Y-%m-%d"
assert result["y_axis_title"] == "Revenue"
assert result["y_axis_format"] == "$,.2f"
assert result["y_axis_scale"] == "log"
def test_map_xy_config_with_legend(self) -> None:
"""Test XY config mapping with legend configuration"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue")],
kind="scatter",
legend=LegendConfig(show=False, position="top"),
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_scatter"
assert result["show_legend"] is False
assert result["legend_orientation"] == "top"
def test_map_xy_config_with_time_grain_month(self) -> None:
"""Test XY config mapping with monthly time grain"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="bar",
time_grain="P1M",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert result["x_axis"] == "order_date"
assert result["time_grain_sqla"] == "P1M"
def test_map_xy_config_with_time_grain_day(self) -> None:
"""Test XY config mapping with daily time grain"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="created_at"),
y=[ColumnRef(name="count", aggregate="COUNT")],
kind="line",
time_grain="P1D",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_line"
assert result["x_axis"] == "created_at"
assert result["time_grain_sqla"] == "P1D"
def test_map_xy_config_with_time_grain_hour(self) -> None:
"""Test XY config mapping with hourly time grain"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="timestamp"),
y=[ColumnRef(name="requests", aggregate="SUM")],
kind="area",
time_grain="PT1H",
)
result = map_xy_config(config)
assert result["time_grain_sqla"] == "PT1H"
def test_map_xy_config_without_time_grain(self) -> None:
"""Test XY config mapping without time grain (should not set time_grain_sqla)"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue")],
kind="line",
)
result = map_xy_config(config)
assert "time_grain_sqla" not in result
def test_map_xy_config_with_time_grain_and_groupby(self) -> None:
"""Test XY config mapping with time grain and group by"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
time_grain="P1W",
group_by=ColumnRef(name="category"),
)
result = map_xy_config(config)
assert result["time_grain_sqla"] == "P1W"
assert result["groupby"] == ["category"]
assert result["x_axis"] == "order_date"
def test_map_xy_config_bar_horizontal_orientation(self) -> None:
"""Test XY config mapping for horizontal bar chart"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="department"),
y=[ColumnRef(name="headcount", aggregate="SUM")],
kind="bar",
orientation="horizontal",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert result["orientation"] == "horizontal"
def test_map_xy_config_bar_vertical_orientation(self) -> None:
"""Test XY config mapping for vertical bar chart (explicit)"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="category"),
y=[ColumnRef(name="sales", aggregate="SUM")],
kind="bar",
orientation="vertical",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert result["orientation"] == "vertical"
def test_map_xy_config_bar_no_orientation(self) -> None:
"""Test XY config mapping for bar chart without orientation."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="category"),
y=[ColumnRef(name="sales", aggregate="SUM")],
kind="bar",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert "orientation" not in result
def test_map_xy_config_line_orientation_ignored(self) -> None:
"""Test that orientation is ignored for non-bar chart types"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
orientation="horizontal",
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_line"
assert "orientation" not in result
def test_map_xy_config_bar_horizontal_with_stacked(self) -> None:
"""Test horizontal bar chart with stacked option"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="department"),
y=[ColumnRef(name="headcount", aggregate="SUM")],
kind="bar",
orientation="horizontal",
stacked=True,
group_by=ColumnRef(name="level"),
)
result = map_xy_config(config)
assert result["viz_type"] == "echarts_timeseries_bar"
assert result["orientation"] == "horizontal"
assert result["stack"] == "Stack"
assert result["groupby"] == ["level"]
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_map_xy_config_with_filters(self, mock_is_temporal) -> None:
"""Test that filters are mapped to adhoc_filters in XY form_data."""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
filters=[FilterConfig(column="region", op="=", value="US")],
)
result = map_xy_config(config)
assert "adhoc_filters" in result
# User filter + auto-added TEMPORAL_RANGE filter for temporal x-axis
assert len(result["adhoc_filters"]) == 2
assert result["adhoc_filters"][0]["subject"] == "region"
assert result["adhoc_filters"][0]["operator"] == "=="
assert result["adhoc_filters"][0]["comparator"] == "US"
assert result["adhoc_filters"][1]["operator"] == "TEMPORAL_RANGE"
assert result["adhoc_filters"][1]["subject"] == "date"
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_map_xy_config_row_limit(self, mock_is_temporal) -> None:
"""Test that row_limit is mapped to form_data."""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
row_limit=250,
)
result = map_xy_config(config)
assert result["row_limit"] == 250
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_map_xy_config_default_row_limit(self, mock_is_temporal) -> None:
"""Test that default row_limit is mapped to form_data."""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="bar",
)
result = map_xy_config(config)
assert result["row_limit"] == 10000
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_map_xy_config_saved_metric(self, mock_is_temporal: Any) -> None:
"""Test XY config with saved metric emits string in metrics list"""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="total_revenue", saved_metric=True)],
kind="line",
)
result = map_xy_config(config, dataset_id=1)
assert result["metrics"] == ["total_revenue"]
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_map_xy_config_mixed_saved_and_adhoc_metrics(
self, mock_is_temporal: Any
) -> None:
"""Test XY config with both saved and ad-hoc metrics"""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[
ColumnRef(name="total_revenue", saved_metric=True),
ColumnRef(name="quantity", aggregate="SUM"),
],
kind="line",
)
result = map_xy_config(config, dataset_id=1)
assert len(result["metrics"]) == 2
assert result["metrics"][0] == "total_revenue"
assert isinstance(result["metrics"][1], dict)
assert result["metrics"][1]["aggregate"] == "SUM"
class TestMapConfigToFormData:
"""Test map_config_to_form_data function"""
def test_map_table_config_type(self) -> None:
"""Test mapping table config type"""
config = TableChartConfig(chart_type="table", columns=[ColumnRef(name="test")])
result = map_config_to_form_data(config)
assert result["viz_type"] == "table"
def test_map_xy_config_type(self) -> None:
"""Test mapping XY config type"""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue")],
kind="line",
)
result = map_config_to_form_data(config)
assert result["viz_type"] == "echarts_timeseries_line"
def test_map_unsupported_config_type(self) -> None:
"""Test mapping unsupported config type raises error"""
with pytest.raises(ValueError, match="Unsupported config type"):
map_config_to_form_data("invalid_config") # type: ignore
class TestGenerateChartName:
"""Test generate_chart_name function"""
def test_table_no_aggregates(self) -> None:
"""Table without aggregates uses column names."""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="product"),
ColumnRef(name="revenue"),
],
)
result = generate_chart_name(config)
assert result == "Product, Revenue Table"
def test_table_no_aggregates_with_dataset_name(self) -> None:
"""Table without aggregates includes dataset name when available."""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
)
result = generate_chart_name(config, dataset_name="Orders")
assert result == "Orders Records"
def test_table_with_aggregates(self) -> None:
"""Table with aggregates produces a summary name."""
config = TableChartConfig(
chart_type="table",
columns=[
ColumnRef(name="product"),
ColumnRef(name="revenue", aggregate="SUM"),
],
)
result = generate_chart_name(config)
assert result == "Sum(Revenue) Summary"
def test_line_chart_over_time(self) -> None:
"""Line chart without group_by uses 'Over Time' format."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
)
result = generate_chart_name(config)
assert result == "Sum(Revenue) Over Time"
def test_bar_chart_by_dimension(self) -> None:
"""Bar chart uses 'by [X]' format."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="product_category"),
y=[ColumnRef(name="order_count", aggregate="COUNT")],
kind="bar",
)
result = generate_chart_name(config)
assert result == "Count(Order Count) by Product Category"
def test_line_chart_with_group_by(self) -> None:
"""Line chart with group_by uses 'by [group]' format."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
group_by=ColumnRef(name="sales_rep"),
)
result = generate_chart_name(config)
assert result == "Sum(Revenue) by Sales Rep"
def test_scatter_plot(self) -> None:
"""Scatter plot uses 'Y vs X' format."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="age"),
y=[ColumnRef(name="income")],
kind="scatter",
)
result = generate_chart_name(config)
assert result == "Income vs Age"
def test_time_grain_in_context(self) -> None:
"""Time grain is appended as context."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="line",
time_grain="P1M",
)
result = generate_chart_name(config)
assert result == "Sum(Revenue) Over Time \u2013 Monthly"
def test_filter_context(self) -> None:
"""Filters are appended as context."""
config = TableChartConfig(
chart_type="table",
columns=[ColumnRef(name="product")],
filters=[FilterConfig(column="region", op="=", value="West")],
)
result = generate_chart_name(config, dataset_name="Orders")
assert result == "Orders Records \u2013 Region West"
def test_name_truncation(self) -> None:
"""Names exceeding 60 chars are truncated."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[
ColumnRef(
name="very_long_metric_name_that_goes_on_and_on", aggregate="SUM"
)
],
kind="line",
group_by=ColumnRef(name="another_very_long_dimension_name_here"),
)
result = generate_chart_name(config)
assert len(result) <= 60
def test_unsupported_config_type(self) -> None:
"""Unsupported config type returns generic name."""
result = generate_chart_name("invalid_config") # type: ignore
assert result == "Chart"
def test_custom_labels_used(self) -> None:
"""Column labels are preferred over names."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="ds", label="Date"),
y=[ColumnRef(name="cnt", aggregate="COUNT", label="Order Count")],
kind="bar",
)
result = generate_chart_name(config)
assert result == "Order Count by Date"
class TestGenerateExploreLink:
"""Test generate_explore_link function"""
@patch("superset.mcp_service.chart.chart_utils.get_superset_base_url")
def test_generate_explore_link_uses_base_url(self, mock_get_base_url) -> None:
"""Test that generate_explore_link uses the configured base URL"""
from urllib.parse import urlparse
mock_get_base_url.return_value = "https://superset.example.com"
form_data = {"viz_type": "table", "metrics": ["count"]}
# Mock dataset not found to trigger fallback URL
with patch("superset.daos.dataset.DatasetDAO.find_by_id", return_value=None):
result = generate_explore_link("123", form_data)
# Should use the configured base URL - use urlparse to avoid CodeQL warning
parsed_url = urlparse(result)
expected_netloc = "superset.example.com"
assert parsed_url.scheme == "https"
assert parsed_url.netloc == expected_netloc
assert "/explore/" in parsed_url.path
assert "datasource_id=123" in result
@patch("superset.mcp_service.chart.chart_utils.get_superset_base_url")
def test_generate_explore_link_fallback_url(self, mock_get_base_url) -> None:
"""Test generate_explore_link returns fallback URL when dataset not found"""
mock_get_base_url.return_value = "http://localhost:9001"
form_data = {"viz_type": "table"}
# Mock dataset not found scenario
with patch("superset.daos.dataset.DatasetDAO.find_by_id", return_value=None):
result = generate_explore_link("999", form_data)
assert (
result
== "http://localhost:9001/explore/?datasource_type=table&datasource_id=999"
)
@patch("superset.mcp_service.chart.chart_utils.get_superset_base_url")
@patch("superset.mcp_service.commands.create_form_data.MCPCreateFormDataCommand")
def test_generate_explore_link_with_form_data_key(
self, mock_command, mock_get_base_url
) -> None:
"""Test generate_explore_link creates form_data_key when dataset exists"""
mock_get_base_url.return_value = "http://localhost:9001"
mock_command.return_value.run.return_value = "test_form_data_key"
# Mock dataset exists
mock_dataset = type("Dataset", (), {"id": 123})()
with patch(
"superset.daos.dataset.DatasetDAO.find_by_id", return_value=mock_dataset
):
result = generate_explore_link(123, {"viz_type": "table"})
assert (
result == "http://localhost:9001/explore/?form_data_key=test_form_data_key"
)
mock_command.assert_called_once()
@patch("superset.mcp_service.chart.chart_utils.get_superset_base_url")
def test_generate_explore_link_exception_handling(self, mock_get_base_url) -> None:
"""Test generate_explore_link handles SQLAlchemy exceptions gracefully"""
from sqlalchemy.exc import SQLAlchemyError
mock_get_base_url.return_value = "http://localhost:9001"
# Mock SQLAlchemy exception during dataset lookup
with patch(
"superset.daos.dataset.DatasetDAO.find_by_id",
side_effect=SQLAlchemyError("DB error"),
):
result = generate_explore_link("123", {"viz_type": "table"})
# Should fallback to basic URL
assert (
result
== "http://localhost:9001/explore/?datasource_type=table&datasource_id=123"
)
class TestCriticalBugFixes:
"""Test critical bug fixes for chart utilities."""
def test_time_series_aggregation_fix(self) -> None:
"""Test that time series charts preserve temporal dimension."""
# Create a time series chart configuration
config = XYChartConfig(
chart_type="xy",
kind="line",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="sales", aggregate="SUM", label="Total Sales")],
)
form_data = map_xy_config(config)
# Verify the fix: x_axis should be set correctly
assert form_data["x_axis"] == "order_date"
# Verify the fix: groupby should not duplicate x_axis
# This prevents the "Duplicate column/metric labels" error
assert "groupby" not in form_data or "order_date" not in form_data.get(
"groupby", []
)
# Verify chart type mapping
assert form_data["viz_type"] == "echarts_timeseries_line"
def test_time_series_with_explicit_group_by(self) -> None:
"""Test time series with explicit group_by different from x_axis."""
config = XYChartConfig(
chart_type="xy",
kind="line",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="sales", aggregate="SUM", label="Total Sales")],
group_by=ColumnRef(name="category"),
)
form_data = map_xy_config(config)
# Verify x_axis is set
assert form_data["x_axis"] == "order_date"
# Verify groupby only contains the explicit group_by, not x_axis
assert form_data.get("groupby") == ["category"]
assert "order_date" not in form_data.get("groupby", [])
def test_duplicate_label_prevention(self) -> None:
"""Test that duplicate column/metric labels are prevented."""
# This configuration would previously cause:
# "Duplicate column/metric labels: 'price_each'"
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="price_each", label="Price Each"), # Custom label
y=[
ColumnRef(name="sales", aggregate="SUM", label="Total Sales"),
ColumnRef(name="quantity", aggregate="COUNT", label="Order Count"),
],
group_by=ColumnRef(name="price_each"), # Same column as x_axis
kind="line",
)
form_data = map_xy_config(config)
# Verify the fix: x_axis is set
assert form_data["x_axis"] == "price_each"
# Verify the fix: groupby is empty because group_by == x_axis
# This prevents the duplicate label error
assert "groupby" not in form_data or not form_data["groupby"]
def test_metric_object_creation_with_labels(self) -> None:
"""Test that metric objects are created correctly with proper labels."""
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[
ColumnRef(name="sales", aggregate="SUM", label="Total Sales"),
ColumnRef(name="profit", aggregate="AVG"), # No custom label
],
kind="bar",
)
form_data = map_xy_config(config)
# Verify metrics are created correctly
metrics = form_data["metrics"]
assert len(metrics) == 2
# First metric with custom label
assert metrics[0]["label"] == "Total Sales"
assert metrics[0]["aggregate"] == "SUM"
assert metrics[0]["column"]["column_name"] == "sales"
# Second metric with auto-generated label
assert metrics[1]["label"] == "AVG(profit)"
assert metrics[1]["aggregate"] == "AVG"
assert metrics[1]["column"]["column_name"] == "profit"
def test_chart_type_mapping_comprehensive(self) -> None:
"""Test that chart types are mapped correctly to Superset viz types."""
test_cases = [
("line", "echarts_timeseries_line"),
("bar", "echarts_timeseries_bar"),
("area", "echarts_area"),
("scatter", "echarts_timeseries_scatter"),
]
for kind, expected_viz_type in test_cases:
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="date"),
y=[ColumnRef(name="value", aggregate="SUM")],
kind=kind,
)
form_data = map_xy_config(config)
assert form_data["viz_type"] == expected_viz_type
class TestIsColumnTrulyTemporal:
"""Test is_column_truly_temporal function using db_engine_spec"""
def _create_mock_dataset(
self,
column_name: str,
column_type: str,
generic_type: GenericDataType,
):
"""Helper to create a mock dataset with proper db_engine_spec"""
from unittest.mock import MagicMock
from superset.utils.core import ColumnSpec
mock_column = MagicMock()
mock_column.column_name = column_name
mock_column.type = column_type
mock_db_engine_spec = MagicMock()
mock_column_spec = ColumnSpec(
sqla_type=MagicMock(), generic_type=generic_type, is_dttm=False
)
mock_db_engine_spec.get_column_spec.return_value = mock_column_spec
mock_database = MagicMock()
mock_database.db_engine_spec = mock_db_engine_spec
mock_dataset = MagicMock()
mock_dataset.columns = [mock_column]
mock_dataset.database = mock_database
return mock_dataset
def test_returns_true_when_no_dataset_id(self) -> None:
"""Test returns True (default) when dataset_id is None"""
result = is_column_truly_temporal("year", None)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_true_when_dataset_not_found(self, mock_dao) -> None:
"""Test returns True when dataset is not found"""
mock_dao.find_by_id.return_value = None
result = is_column_truly_temporal("year", 123)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_false_for_numeric_column(self, mock_dao) -> None:
"""Test returns False for NUMERIC generic type (e.g., BIGINT)"""
mock_dataset = self._create_mock_dataset(
"year", "BIGINT", GenericDataType.NUMERIC
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("year", 123)
assert result is False
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_false_for_integer_column(self, mock_dao) -> None:
"""Test returns False for INTEGER column (NUMERIC generic type)"""
mock_dataset = self._create_mock_dataset(
"month", "INTEGER", GenericDataType.NUMERIC
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("month", 123)
assert result is False
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_true_for_temporal_column(self, mock_dao) -> None:
"""Test returns True for TEMPORAL generic type (e.g., TIMESTAMP)"""
mock_dataset = self._create_mock_dataset(
"created_at", "TIMESTAMP", GenericDataType.TEMPORAL
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("created_at", 123)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_true_for_date_column(self, mock_dao) -> None:
"""Test returns True for DATE column (TEMPORAL generic type)"""
mock_dataset = self._create_mock_dataset(
"order_date", "DATE", GenericDataType.TEMPORAL
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("order_date", 123)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_case_insensitive_column_name_lookup(self, mock_dao) -> None:
"""Test column name lookup is case insensitive"""
mock_dataset = self._create_mock_dataset(
"Year", "BIGINT", GenericDataType.NUMERIC
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("year", 123)
assert result is False
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_true_on_value_error(self, mock_dao) -> None:
"""Test returns True (default) when ValueError occurs"""
mock_dao.find_by_id.side_effect = ValueError("Invalid ID")
result = is_column_truly_temporal("year", 123)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_returns_true_on_attribute_error(self, mock_dao) -> None:
"""Test returns True (default) when AttributeError occurs"""
mock_dao.find_by_id.side_effect = AttributeError("Missing attribute")
result = is_column_truly_temporal("year", 123)
assert result is True
@patch("superset.daos.dataset.DatasetDAO")
def test_handles_uuid_dataset_id(self, mock_dao) -> None:
"""Test handles UUID string as dataset_id"""
mock_dataset = self._create_mock_dataset(
"year", "BIGINT", GenericDataType.NUMERIC
)
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("year", "abc-123-uuid")
assert result is False
mock_dao.find_by_id.assert_called_with("abc-123-uuid", id_column="uuid")
@patch("superset.daos.dataset.DatasetDAO")
def test_falls_back_to_is_dttm_when_no_column_spec(self, mock_dao) -> None:
"""Test falls back to is_dttm flag when get_column_spec returns None"""
from unittest.mock import MagicMock
mock_column = MagicMock()
mock_column.column_name = "year"
mock_column.type = "UNKNOWN_TYPE"
mock_column.is_dttm = False
mock_db_engine_spec = MagicMock()
mock_db_engine_spec.get_column_spec.return_value = None
mock_database = MagicMock()
mock_database.db_engine_spec = mock_db_engine_spec
mock_dataset = MagicMock()
mock_dataset.columns = [mock_column]
mock_dataset.database = mock_database
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("year", 123)
assert result is False
@patch("superset.daos.dataset.DatasetDAO")
def test_falls_back_to_is_dttm_when_no_type(self, mock_dao) -> None:
"""Test falls back to is_dttm flag when column has no type"""
from unittest.mock import MagicMock
mock_column = MagicMock()
mock_column.column_name = "year"
mock_column.type = None
mock_column.is_dttm = True
mock_dataset = MagicMock()
mock_dataset.columns = [mock_column]
mock_dao.find_by_id.return_value = mock_dataset
result = is_column_truly_temporal("year", 123)
assert result is True
class TestConfigureTemporalHandling:
"""Test configure_temporal_handling function"""
def test_temporal_column_with_time_grain(self) -> None:
"""Test temporal column sets time_grain_sqla and granularity_sqla"""
form_data: dict[str, Any] = {"x_axis": "order_date"}
configure_temporal_handling(form_data, x_is_temporal=True, time_grain="P1M")
assert form_data["time_grain_sqla"] == "P1M"
assert form_data["granularity_sqla"] == "order_date"
def test_temporal_column_without_time_grain(self) -> None:
"""Test temporal column sets granularity_sqla but not time_grain_sqla"""
form_data: dict[str, Any] = {"x_axis": "order_date"}
configure_temporal_handling(form_data, x_is_temporal=True, time_grain=None)
assert "time_grain_sqla" not in form_data
assert form_data["granularity_sqla"] == "order_date"
def test_non_temporal_column_sets_categorical_config(self) -> None:
"""Test non-temporal column sets categorical configuration"""
form_data: dict[str, Any] = {}
configure_temporal_handling(form_data, x_is_temporal=False, time_grain=None)
assert form_data["x_axis_sort_series_type"] == "name"
assert form_data["x_axis_sort_series_ascending"] is True
assert form_data["time_grain_sqla"] is None
assert form_data["granularity_sqla"] is None
def test_non_temporal_column_ignores_time_grain(self) -> None:
"""Test non-temporal column ignores time_grain parameter"""
form_data: dict[str, Any] = {}
configure_temporal_handling(form_data, x_is_temporal=False, time_grain="P1M")
# Should still set categorical config, not time_grain
assert form_data["time_grain_sqla"] is None
assert form_data["x_axis_sort_series_type"] == "name"
class TestMapXYConfigWithNonTemporalColumn:
"""Test map_xy_config with non-temporal columns (DATE_TRUNC fix)"""
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_non_temporal_column_disables_time_grain(self, mock_is_temporal) -> None:
"""Test non-temporal column sets categorical config"""
mock_is_temporal.return_value = False
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="year"),
y=[ColumnRef(name="sales", aggregate="SUM")],
kind="bar",
)
result = map_xy_config(config, dataset_id=123)
assert result["x_axis"] == "year"
assert result["x_axis_sort_series_type"] == "name"
assert result["x_axis_sort_series_ascending"] is True
assert result["time_grain_sqla"] is None
assert result["granularity_sqla"] is None
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_temporal_column_allows_time_grain(self, mock_is_temporal) -> None:
"""Test temporal column allows time_grain to be set"""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="created_at"),
y=[ColumnRef(name="count", aggregate="COUNT")],
kind="line",
time_grain="P1W",
)
result = map_xy_config(config, dataset_id=123)
assert result["x_axis"] == "created_at"
assert result["time_grain_sqla"] == "P1W"
assert result["granularity_sqla"] == "created_at"
assert "x_axis_sort_series_type" not in result
# Temporal x-axis should have a TEMPORAL_RANGE adhoc filter
temporal_filters = [
f
for f in result.get("adhoc_filters", [])
if f.get("operator") == "TEMPORAL_RANGE"
]
assert len(temporal_filters) == 1
assert temporal_filters[0]["subject"] == "created_at"
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_non_temporal_ignores_time_grain_param(self, mock_is_temporal) -> None:
"""Test non-temporal column ignores time_grain even if specified"""
mock_is_temporal.return_value = False
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="year"),
y=[ColumnRef(name="sales", aggregate="SUM")],
kind="bar",
time_grain="P1M", # This should be ignored for non-temporal
)
result = map_xy_config(config, dataset_id=123)
# time_grain_sqla should be None, not P1M
assert result["time_grain_sqla"] is None
assert result["x_axis_sort_series_type"] == "name"
class TestEnsureTemporalAdhocFilter:
"""Test _ensure_temporal_adhoc_filter helper and its integration in map_xy_config"""
def test_adds_filter_to_empty_form_data(self) -> None:
"""Test adds TEMPORAL_RANGE filter when no adhoc_filters exist"""
form_data: dict[str, Any] = {}
_ensure_temporal_adhoc_filter(form_data, "order_date")
assert len(form_data["adhoc_filters"]) == 1
f = form_data["adhoc_filters"][0]
assert f["operator"] == FilterOperator.TEMPORAL_RANGE.value
assert f["subject"] == "order_date"
assert f["comparator"] == NO_TIME_RANGE
assert f["expressionType"] == "SIMPLE"
assert f["clause"] == "WHERE"
def test_appends_to_existing_filters(self) -> None:
"""Test appends temporal filter after existing user filters"""
form_data: dict[str, Any] = {
"adhoc_filters": [
{"subject": "region", "operator": "==", "comparator": "US"}
]
}
_ensure_temporal_adhoc_filter(form_data, "order_date")
assert len(form_data["adhoc_filters"]) == 2
assert form_data["adhoc_filters"][0]["subject"] == "region"
assert (
form_data["adhoc_filters"][1]["operator"]
== FilterOperator.TEMPORAL_RANGE.value
)
def test_does_not_duplicate_existing_temporal_filter(self) -> None:
"""Test skips adding if a TEMPORAL_RANGE filter already exists for the column"""
form_data: dict[str, Any] = {
"adhoc_filters": [
{
"subject": "order_date",
"operator": FilterOperator.TEMPORAL_RANGE.value,
"comparator": "Last 7 days",
}
]
}
_ensure_temporal_adhoc_filter(form_data, "order_date")
# Should still be just 1 filter (no duplicate)
assert len(form_data["adhoc_filters"]) == 1
def test_adds_filter_for_different_column(self) -> None:
"""Test adds filter when existing temporal filter is on a different column"""
form_data: dict[str, Any] = {
"adhoc_filters": [
{
"subject": "created_at",
"operator": FilterOperator.TEMPORAL_RANGE.value,
"comparator": NO_TIME_RANGE,
}
]
}
_ensure_temporal_adhoc_filter(form_data, "order_date")
assert len(form_data["adhoc_filters"]) == 2
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_temporal_x_axis_adds_filter_in_map_xy(self, mock_is_temporal) -> None:
"""Test map_xy_config adds TEMPORAL_RANGE filter for temporal x-axis"""
mock_is_temporal.return_value = True
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="order_date"),
y=[ColumnRef(name="revenue", aggregate="SUM")],
kind="bar",
)
result = map_xy_config(config, dataset_id=123)
temporal_filters = [
f
for f in result.get("adhoc_filters", [])
if f.get("operator") == FilterOperator.TEMPORAL_RANGE.value
]
assert len(temporal_filters) == 1
assert temporal_filters[0]["subject"] == "order_date"
assert temporal_filters[0]["comparator"] == NO_TIME_RANGE
@patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
def test_non_temporal_x_axis_no_temporal_filter(self, mock_is_temporal) -> None:
"""Test non-temporal x-axis skips TEMPORAL_RANGE filter"""
mock_is_temporal.return_value = False
config = XYChartConfig(
chart_type="xy",
x=ColumnRef(name="year"),
y=[ColumnRef(name="sales", aggregate="SUM")],
kind="bar",
)
result = map_xy_config(config, dataset_id=123)
temporal_filters = [
f
for f in result.get("adhoc_filters", [])
if f.get("operator") == FilterOperator.TEMPORAL_RANGE.value
]
assert len(temporal_filters) == 0
class TestFilterConfigValidation:
"""Test FilterConfig validation for new operators"""
def test_like_operator_with_wildcard(self) -> None:
"""Test LIKE operator accepts string with % wildcards"""
f = FilterConfig(column="name", op="LIKE", value="%mario%")
assert f.op == "LIKE"
assert f.value == "%mario%"
def test_ilike_operator(self) -> None:
"""Test ILIKE operator accepts string value"""
f = FilterConfig(column="name", op="ILIKE", value="%Mario%")
assert f.op == "ILIKE"
assert f.value == "%Mario%"
def test_not_like_operator(self) -> None:
"""Test NOT LIKE operator accepts string value"""
f = FilterConfig(column="name", op="NOT LIKE", value="%test%")
assert f.op == "NOT LIKE"
def test_in_operator_with_list(self) -> None:
"""Test IN operator accepts list of values"""
f = FilterConfig(column="platform", op="IN", value=["Wii", "PS3", "Xbox360"])
assert f.op == "IN"
assert f.value == ["Wii", "PS3", "Xbox360"]
def test_not_in_operator_with_list(self) -> None:
"""Test NOT IN operator accepts list of values"""
f = FilterConfig(column="status", op="NOT IN", value=["archived", "deleted"])
assert f.op == "NOT IN"
assert f.value == ["archived", "deleted"]
def test_in_operator_rejects_scalar_value(self) -> None:
"""Test IN operator rejects non-list value"""
with pytest.raises(ValueError, match="requires a list of values"):
FilterConfig(column="platform", op="IN", value="Wii")
def test_not_in_operator_rejects_scalar_value(self) -> None:
"""Test NOT IN operator rejects non-list value"""
with pytest.raises(ValueError, match="requires a list of values"):
FilterConfig(column="status", op="NOT IN", value="active")
def test_equals_operator_rejects_list_value(self) -> None:
"""Test = operator rejects list value"""
with pytest.raises(ValueError, match="requires a single value, not a list"):
FilterConfig(column="name", op="=", value=["a", "b"])
def test_like_operator_rejects_list_value(self) -> None:
"""Test LIKE operator rejects list value"""
with pytest.raises(ValueError, match="requires a single value, not a list"):
FilterConfig(column="name", op="LIKE", value=["%a%", "%b%"])
def test_in_operator_with_numeric_list(self) -> None:
"""Test IN operator with numeric values"""
f = FilterConfig(column="year", op="IN", value=[2020, 2021, 2022])
assert f.value == [2020, 2021, 2022]
def test_in_operator_with_empty_list(self) -> None:
"""Test IN operator with empty list"""
f = FilterConfig(column="platform", op="IN", value=[])
assert f.value == []
class TestValidateChartDataset:
"""Test validate_chart_dataset function"""
@patch("superset.mcp_service.auth.has_dataset_access")
@patch("superset.daos.dataset.DatasetDAO.find_by_id")
def test_validate_chart_dataset_no_datasource_id(
self, mock_find: MagicMock, mock_access: MagicMock
) -> None:
"""Chart with no datasource_id returns invalid result."""
chart = MagicMock(spec=[]) # no datasource_id attribute
result = validate_chart_dataset(chart)
assert not result.is_valid
assert result.dataset_id is None
assert "no dataset reference" in (result.error or "").lower()
mock_find.assert_not_called()
@patch("superset.mcp_service.auth.has_dataset_access")
@patch("superset.daos.dataset.DatasetDAO.find_by_id", return_value=None)
def test_validate_chart_dataset_deleted_dataset(
self, mock_find: MagicMock, mock_access: MagicMock
) -> None:
"""Chart whose dataset was deleted returns invalid result."""
chart = MagicMock()
chart.datasource_id = 42
result = validate_chart_dataset(chart)
assert not result.is_valid
assert result.dataset_id == 42
assert "deleted" in (result.error or "").lower()
@patch("superset.mcp_service.auth.has_dataset_access", return_value=True)
@patch("superset.daos.dataset.DatasetDAO.find_by_id")
def test_validate_chart_dataset_valid(
self, mock_find: MagicMock, mock_access: MagicMock
) -> None:
"""Valid chart with accessible dataset returns valid result."""
dataset = MagicMock()
dataset.table_name = "my_table"
dataset.sql = None
mock_find.return_value = dataset
chart = MagicMock()
chart.datasource_id = 7
result = validate_chart_dataset(chart)
assert result.is_valid
assert result.dataset_id == 7
assert result.dataset_name == "my_table"
assert result.warnings == []
@patch("superset.mcp_service.auth.has_dataset_access", return_value=True)
@patch("superset.daos.dataset.DatasetDAO.find_by_id")
def test_validate_chart_dataset_virtual_warns(
self, mock_find: MagicMock, mock_access: MagicMock
) -> None:
"""Virtual dataset emits a warning."""
dataset = MagicMock()
dataset.table_name = "virt_ds"
dataset.sql = "SELECT 1"
mock_find.return_value = dataset
chart = MagicMock()
chart.datasource_id = 10
result = validate_chart_dataset(chart)
assert result.is_valid
assert len(result.warnings) == 1
assert "virtual" in result.warnings[0].lower()
@patch("superset.mcp_service.auth.has_dataset_access")
@patch("superset.daos.dataset.DatasetDAO.find_by_id")
def test_validate_chart_dataset_sqlalchemy_error(
self, mock_find: MagicMock, mock_access: MagicMock
) -> None:
"""SQLAlchemy errors are caught and produce an invalid result."""
from sqlalchemy.exc import SQLAlchemyError
mock_find.side_effect = SQLAlchemyError("connection lost")
chart = MagicMock()
chart.datasource_id = 99
result = validate_chart_dataset(chart)
assert not result.is_valid
assert result.dataset_id == 99
assert "error" in (result.error or "").lower()
@patch(
"superset.mcp_service.chart.chart_utils.get_superset_base_url",
return_value="http://localhost:8088",
)
@patch("superset.daos.dataset.DatasetDAO.find_by_id")
def test_generate_explore_link_sqlalchemy_error(
self,
mock_find: MagicMock,
mock_base_url: MagicMock,
) -> None:
"""SQLAlchemy errors in generate_explore_link fall back to basic URL."""
from sqlalchemy.exc import SQLAlchemyError
mock_find.side_effect = SQLAlchemyError("db gone")
url = generate_explore_link(5, {"viz_type": "table"})
assert "datasource_id=5" in url
class TestAdhocFiltersToQueryFilters:
"""Tests for adhoc_filters_to_query_filters conversion."""
def test_converts_simple_filters(self) -> None:
adhoc = [
{
"clause": "WHERE",
"expressionType": "SIMPLE",
"subject": "genre",
"operator": "==",
"comparator": "Action",
}
]
result = adhoc_filters_to_query_filters(adhoc)
assert result == [{"col": "genre", "op": "==", "val": "Action"}]
def test_converts_multiple_filters(self) -> None:
adhoc = [
{
"clause": "WHERE",
"expressionType": "SIMPLE",
"subject": "genre",
"operator": "==",
"comparator": "Action",
},
{
"clause": "WHERE",
"expressionType": "SIMPLE",
"subject": "year",
"operator": ">=",
"comparator": "2010",
},
]
result = adhoc_filters_to_query_filters(adhoc)
assert len(result) == 2
assert result[0] == {"col": "genre", "op": "==", "val": "Action"}
assert result[1] == {"col": "year", "op": ">=", "val": "2010"}
def test_empty_list(self) -> None:
assert adhoc_filters_to_query_filters([]) == []
def test_skips_non_simple_expression_types(self) -> None:
adhoc = [
{
"clause": "WHERE",
"expressionType": "SQL",
"sqlExpression": "col > 5",
}
]
result = adhoc_filters_to_query_filters(adhoc)
assert result == []