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adk-python/tests/unittests/tools/bigquery/test_bigquery_data_insights_tool.py
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# Copyright 2026 Google LLC
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#
# Licensed 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.
import pathlib
from unittest import mock
from google.adk.tools.bigquery import data_insights_tool
import pytest
import yaml
@pytest.mark.parametrize(
"case_file_path",
[
pytest.param("test_data/ask_data_insights_penguins_highest_mass.yaml"),
],
)
@mock.patch.object(data_insights_tool.requests.Session, "post")
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def test_ask_data_insights_pipeline_from_file(mock_post, case_file_path):
"""Runs a full integration test for the ask_data_insights pipeline using data from a specific file."""
# 1. Construct the full, absolute path to the data file
full_path = pathlib.Path(__file__).parent / case_file_path
# 2. Load the test case data from the specified YAML file
with open(full_path, "r", encoding="utf-8") as f:
case_data = yaml.safe_load(f)
# 3. Prepare the mock stream and expected output from the loaded data
mock_stream_str = case_data["mock_api_stream"]
fake_stream_lines = [
line.encode("utf-8") for line in mock_stream_str.splitlines()
]
# Load the expected output as a list of dictionaries, not a single string
expected_final_list = case_data["expected_output"]
# 4. Configure the mock for requests.post
mock_response = mock.Mock()
mock_response.iter_lines.return_value = fake_stream_lines
# Add raise_for_status mock which is called in the updated code
mock_response.raise_for_status.return_value = None
mock_post.return_value.__enter__.return_value = mock_response
# 5. Call the function under test
result = data_insights_tool._get_stream( # pylint: disable=protected-access
url="fake_url",
ca_payload={},
headers={},
max_query_result_rows=50,
)
# 6. Assert that the final list of dicts matches the expected output
assert result == expected_final_list
@mock.patch.object(data_insights_tool, "_get_stream")
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def test_ask_data_insights_success(mock_get_stream):
"""Tests the success path of ask_data_insights using decorators."""
# 1. Configure the behavior of the mocked functions
mock_get_stream.return_value = "Final formatted string from stream"
# 2. Create mock inputs for the function call
mock_creds = mock.Mock()
mock_creds.token = "fake-token"
mock_settings = mock.Mock()
mock_settings.max_query_result_rows = 100
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# 3. Call the function under test
result = data_insights_tool.ask_data_insights(
project_id="test-project",
user_query_with_context="test query",
table_references=[],
credentials=mock_creds,
settings=mock_settings,
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)
# 4. Assert the results are as expected
assert result["status"] == "SUCCESS"
assert result["response"] == "Final formatted string from stream"
mock_get_stream.assert_called_once()
@mock.patch.object(data_insights_tool, "_get_stream")
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def test_ask_data_insights_handles_exception(mock_get_stream):
"""Tests the exception path of ask_data_insights using decorators."""
# 1. Configure one of the mocks to raise an error
mock_get_stream.side_effect = Exception("API call failed!")
# 2. Create mock inputs
mock_creds = mock.Mock()
mock_creds.token = "fake-token"
mock_settings = mock.Mock()
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# 3. Call the function
result = data_insights_tool.ask_data_insights(
project_id="test-project",
user_query_with_context="test query",
table_references=[],
credentials=mock_creds,
settings=mock_settings,
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)
# 4. Assert that the error was caught and formatted correctly
assert result["status"] == "ERROR"
assert "API call failed!" in result["error_details"]
mock_get_stream.assert_called_once()
@pytest.mark.parametrize(
"initial_messages, new_message, expected_list",
[
pytest.param(
[{"Thinking": None}, {"Schema Resolved": {}}],
{"SQL Generated": "SELECT 1"},
[
{"Thinking": None},
{"Schema Resolved": {}},
{"SQL Generated": "SELECT 1"},
],
id="append_when_last_message_is_not_data",
),
pytest.param(
[{"Thinking": None}, {"Data Retrieved": {"rows": [1]}}],
{"Data Retrieved": {"rows": [1, 2]}},
[{"Thinking": None}, {"Data Retrieved": {"rows": [1, 2]}}],
id="replace_when_last_message_is_data",
),
pytest.param(
[],
{"Answer": "First Message"},
[{"Answer": "First Message"}],
id="append_to_an_empty_list",
),
pytest.param(
[{"Data Retrieved": {}}],
{},
[{"Data Retrieved": {}}],
id="should_not_append_an_empty_new_message",
),
],
)
def test_append_message(initial_messages, new_message, expected_list):
"""Tests the logic of replacing the last message if it's a data message."""
messages_copy = initial_messages.copy()
data_insights_tool._append_message(messages_copy, new_message) # pylint: disable=protected-access
assert messages_copy == expected_list
@pytest.mark.parametrize(
"response_dict, expected_output",
[
pytest.param(
{"parts": ["The answer", " is 42."]},
{"Answer": "The answer is 42."},
id="multiple_parts",
),
pytest.param(
{"parts": ["Hello"]}, {"Answer": "Hello"}, id="single_part"
),
pytest.param({}, {"Answer": ""}, id="empty_response"),
],
)
def test_handle_text_response(response_dict, expected_output):
"""Tests the text response handler."""
result = data_insights_tool._handle_text_response(response_dict) # pylint: disable=protected-access
assert result == expected_output
@pytest.mark.parametrize(
"response_dict, expected_output",
[
pytest.param(
{"query": {"question": "What is the schema?"}},
{"Question": "What is the schema?"},
id="schema_query_path",
),
pytest.param(
{
"result": {
"datasources": [{
"bigqueryTableReference": {
"projectId": "p",
"datasetId": "d",
"tableId": "t",
},
"schema": {
"fields": [{"name": "col1", "type": "STRING"}]
},
}]
}
},
{
"Schema Resolved": [{
"source_name": "p.d.t",
"schema": {
"headers": ["Column", "Type", "Description", "Mode"],
"rows": [["col1", "STRING", "", ""]],
},
}]
},
id="schema_result_path",
),
],
)
def test_handle_schema_response(response_dict, expected_output):
"""Tests different paths of the schema response handler."""
result = data_insights_tool._handle_schema_response(response_dict) # pylint: disable=protected-access
assert result == expected_output
@pytest.mark.parametrize(
"response_dict, expected_output",
[
pytest.param(
{"generatedSql": "SELECT 1;"},
{"SQL Generated": "SELECT 1;"},
id="format_generated_sql",
),
pytest.param(
{
"result": {
"schema": {"fields": [{"name": "id"}, {"name": "name"}]},
"data": [{"id": 1, "name": "A"}, {"id": 2, "name": "B"}],
}
},
{
"Data Retrieved": {
"headers": ["id", "name"],
"rows": [[1, "A"], [2, "B"]],
"summary": "Showing all 2 rows.",
}
},
id="format_data_result_table",
),
],
)
def test_handle_data_response(response_dict, expected_output):
"""Tests different paths of the data response handler, including truncation."""
result = data_insights_tool._handle_data_response(response_dict, 100) # pylint: disable=protected-access
assert result == expected_output
@pytest.mark.parametrize(
"response_dict, expected_output",
[
pytest.param(
{"code": 404, "message": "Not Found"},
{"Error": {"Code": 404, "Message": "Not Found"}},
id="full_error_message",
),
pytest.param(
{"code": 500},
{"Error": {"Code": 500, "Message": "No message provided."}},
id="error_with_missing_message",
),
],
)
def test_handle_error(response_dict, expected_output):
"""Tests the error response handler."""
result = data_insights_tool._handle_error(response_dict) # pylint: disable=protected-access
assert result == expected_output