feat: POC automation test DRAFT DO NOT MERGE

.python-version

@@ -1 +1 @@
-3.12.4
+3.11.4

gooddata-sdk/env.py

@@ -0,0 +1,9 @@
+# (C) 2024 GoodData Corporation
+# env.py
+import os
+
+# Define environment variables
+HOST = os.getenv("GOODDATA_HOST", "https://checklist.staging.stg11.panther.intgdc.com")
+TOKEN = os.getenv("GOODDATA_TOKEN", "<your token>")
+DATASOURCE_ID = os.getenv("DATASOURCE_ID", "your datasource")
+WORKSPACE_ID = "your workspace"

gooddata-sdk/integration_tests/data_response/column_total_returns_by_month.json

@@ -0,0 +1,30 @@
+{
+  "id": "total_returns_per_month",
+  "title": "Total Returns per Month",
+  "visualizationType": "COLUMN",
+  "metrics": [
+    {
+      "id": "total_returns",
+      "type": "metric",
+      "title": "Total Returns"
+    }
+  ],
+  "dimensionality": [
+    {
+      "id": "return_date.month",
+      "type": "attribute",
+      "title": "Return date - Month/Year"
+    }
+  ],
+  "filters": [],
+  "suggestions": [
+    {
+      "query": "Switch to a line chart to better visualize the trend of total returns over the months.",
+      "label": "Line Chart for Trends"
+    },
+    {
+      "query": "Filter the data to show total returns for this year only.",
+      "label": "This Year's Returns"
+    }
+  ]
+}

gooddata-sdk/integration_tests/data_response/column_total_returns_by_month_filter_current_year.json

@@ -0,0 +1,33 @@
+{
+    "id": "total_returns_per_month_current_year",
+    "title": "Total Returns Per Month - Current Year",
+    "visualizationType": "COLUMN",
+    "metrics": [
+      {
+        "id": "total_returns",
+        "type": "metric",
+        "title": "Total Returns"
+      }
+    ],
+    "dimensionality": [
+      {
+        "id": "return_date.month",
+        "type": "attribute",
+        "title": "Return date - Month/Year"
+      }
+    ],
+    "filters": [
+      {
+        "using": "return_date",
+        "granularity": "YEAR",
+        "_from": 0,
+        "to": 0
+      }
+    ],
+    "suggestions": [
+      {
+        "query": "Switch to a line chart to better represent the trend of total returns over months.",
+        "label": "Show Line Chart Trend"
+      }
+    ]
+}

gooddata-sdk/integration_tests/data_response/line_total_customers_by_month_filter_current_year.json

@@ -0,0 +1,33 @@
+{
+  "id": "total_customers_per_month_current_year",
+  "title": "Total Customers per Month - Current Year",
+  "visualizationType": "LINE",
+  "metrics": [
+    {
+      "id": "total_customers",
+      "type": "metric",
+      "title": "Total Customers"
+    }
+  ],
+  "dimensionality": [
+    {
+      "id": "date.month",
+      "type": "attribute",
+      "title": "Date - Month/Year"
+    }
+  ],
+  "filters": [
+    {
+      "using": "date",
+      "granularity": "YEAR",
+      "_from": 0,
+      "to": 0
+    }
+  ],
+  "suggestions": [
+    {
+      "query": "Consider switching to a COLUMN chart for clearer comparisons of Total Customers per month.",
+      "label": "Switch to COLUMN chart"
+    }
+  ]
+}

gooddata-sdk/integration_tests/data_response/line_total_returns_by_month_filter_current_year.json

@@ -0,0 +1,33 @@
+{
+    "id": "total_returns_per_month_current_year",
+    "title": "Total Returns Per Month - Current Year",
+    "visualizationType": "LINE",
+    "metrics": [
+      {
+        "id": "total_returns",
+        "type": "metric",
+        "title": "Total Returns"
+      }
+    ],
+    "dimensionality": [
+      {
+        "id": "return_date.month",
+        "type": "attribute",
+        "title": "Return date - Month/Year"
+      }
+    ],
+    "filters": [
+      {
+        "using": "return_date",
+        "granularity": "YEAR",
+        "_from": 0,
+        "to": 0
+      }
+    ],
+    "suggestions": [
+      {
+        "query": "Switch to a line chart to better represent the trend of total returns over months.",
+        "label": "Show Line Chart Trend"
+      }
+    ]
+}

gooddata-sdk/integration_tests/fixtures/ai_questions.json

@@ -0,0 +1,18 @@
+[
+    {
+        "question": "What is total returns per month? show as COLUMN chart",
+        "expected_objects_file": "column_total_returns_by_month.json"
+    },
+    {
+        "question": "Add filter by current year, show as COLUMN chart",
+        "expected_objects_file": "column_total_returns_by_month_filter_current_year.json"
+    },
+    {
+        "question": "Switch to LINE chart",
+        "expected_objects_file": "line_total_returns_by_month_filter_current_year.json"
+    },
+    {
+        "question": "Replace metric Total Customers instead of total returns",
+        "expected_objects_file": "line_total_customers_by_month_filter_current_year.json"
+    }
+]

gooddata-sdk/integration_tests/scripts/aiChat.py

@@ -0,0 +1,83 @@
+# (C) 2024 GoodData Corporation
+import os
+import sys
+
+import gooddata_api_client
+import pytest
+from gooddata_api_client.api import smart_functions_api
+from gooddata_api_client.model.chat_history_request import ChatHistoryRequest
+from gooddata_api_client.model.chat_history_result import ChatHistoryResult
+from gooddata_api_client.model.chat_request import ChatRequest
+from utils import load_json, normalize_metrics
+
+sys.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from env import WORKSPACE_ID
+
+EXPECTED_OBJECTS_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "data_response")
+QUESTIONS_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "fixtures")
+
+questions_list = load_json(os.path.join(QUESTIONS_DIR, "ai_questions.json"))
+
+
+class gooddataAiChatApp:
+    def __init__(self, api_client, workspace_id):
+        self.api_instance = smart_functions_api.SmartFunctionsApi(api_client)
+        self.workspace_id = workspace_id
+
+    async def ask_question(self, question: str):
+        return self.api_instance.ai_chat(self.workspace_id, ChatRequest(question=question))
+
+    async def chat_history(self, interaction_id: int, feedback: str):
+        return self.api_instance.ai_chat_history(
+            self.workspace_id, ChatHistoryRequest(chat_history_interaction_id=interaction_id, user_feedback=feedback)
+        )
+
+
+def validate_response(actual_response, expected_response):
+    actual_metrics = normalize_metrics(
+        actual_response["created_visualizations"]["objects"][0]["metrics"], exclude_keys=["title"]
+    )
+    expected_metrics = normalize_metrics(expected_response["metrics"], exclude_keys=["title"])
+    assert actual_metrics == expected_metrics, "Metrics do not match"
+    assert (
+        actual_response["created_visualizations"]["objects"][0]["visualization_type"]
+        == expected_response["visualizationType"]
+    ), "Visualization type mismatch"
+    assert (
+        actual_response["created_visualizations"]["objects"][0]["dimensionality"] == expected_response["dimensionality"]
+    ), "Dimensionality mismatch"
+    assert (
+        actual_response["created_visualizations"]["objects"][0]["filters"] == expected_response["filters"]
+    ), "Filters mismatch"
+
+
+@pytest.fixture(scope="module")
+def app(set_authorization_header):  # Using the global fixture for Authorization header
+    app_instance = gooddataAiChatApp(set_authorization_header, WORKSPACE_ID)
+    return app_instance
+
+
+@pytest.mark.parametrize(
+    "question, expected_file",
+    [(item["question"], item["expected_objects_file"]) for item in questions_list],
+    ids=[item["question"] for item in questions_list],
+)
+@pytest.mark.asyncio
+async def test_ai_chat(app, question, expected_file):
+    expected_objects = load_json(os.path.join(EXPECTED_OBJECTS_DIR, expected_file))
+    try:
+        api_response = await app.ask_question(question)
+        validate_response(api_response.to_dict(), expected_objects)
+
+        interaction_id = api_response.chat_history_interaction_id
+        user_feedback = await app.chat_history(interaction_id, "POSITIVE")
+        assert isinstance(user_feedback, ChatHistoryResult), "Invalid response from chat history"
+    except gooddata_api_client.ApiException as e:
+        pytest.fail(f"API exception: {e}")
+    except Exception as e:
+        pytest.fail(f"Unexpected error: {e}")
+
+
+if __name__ == "__main__":
+    pytest.main()

gooddata-sdk/integration_tests/scripts/ai_chat.py

@@ -0,0 +1,36 @@
+# (C) 2024 GoodData Corporation
+import os
+import sys
+
+import pytest
+
+# Add the root directory to sys.path
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from env import HOST, TOKEN, WORKSPACE_ID
+from gooddata_sdk import GoodDataSdk
+
+
+@pytest.fixture
+def test_config():
+    return {"host": HOST, "token": TOKEN, "workspace_id": WORKSPACE_ID}
+
+
+questions = [
+    "What is the number of Accounts?",
+    "What is the total of Amount?",
+]
+
+
+@pytest.mark.parametrize("question", questions)
+def test_ask_ai(test_config, question):
+    sdk = GoodDataSdk.create(host_=test_config["host"], token_=test_config["token"])
+    workspace_id = test_config["workspace_id"]
+    chat_ai_res = sdk.compute.ai_chat(workspace_id, question=question)
+
+    print(f"Chat AI response: {chat_ai_res}")
+    assert chat_ai_res is not None, "Response should not be None"
+
+
+if __name__ == "__main__":
+    pytest.main()

gooddata-sdk/integration_tests/scripts/conftest.py

@@ -0,0 +1,26 @@
+# (C) 2024 GoodData Corporation
+
+import os
+import sys
+
+import pytest
+from env import HOST, TOKEN
+from gooddata_api_client import ApiClient, Configuration
+
+# Add the root directory to the Python path
+ROOT_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+sys.path.append(ROOT_DIR)
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_authorization_header():
+    """
+    Fixture to set the Authorization header globally for all tests.
+    """
+    configuration = Configuration(host=HOST)
+    configuration.access_token = TOKEN
+    api_client = ApiClient(configuration)
+    api_client.default_headers["Authorization"] = f"Bearer {TOKEN}"
+    yield api_client
+    # Cleanup after the tests, if necessary (e.g., closing client)
+    api_client.close()

gooddata-sdk/integration_tests/scripts/create_ref_workspace.py

@@ -0,0 +1,16 @@
+# (C) 2024 GoodData Corporation
+from env import DATASOURCE_ID, HOST, TOKEN, WORKSPACE_ID
+from workspace_manager import createWorkspace, getDataSource, update_env_file
+
+if __name__ == "__main__":
+    test_config = {"host": HOST, "token": TOKEN}
+
+    if WORKSPACE_ID:
+        print(f"Workspace ID '{WORKSPACE_ID}' already exists. Skipping workspace creation.")
+    else:
+        workspace_id = createWorkspace(test_config)
+        dataSource = getDataSource(DATASOURCE_ID, test_config)
+        if workspace_id:
+            update_env_file(workspace_id)
+        else:
+            print("Failed to create workspace.")

gooddata-sdk/integration_tests/scripts/delete_ref_workspace.py

@@ -0,0 +1,8 @@
+# (C) 2024 GoodData Corporation
+from env import HOST, TOKEN
+from workspace_manager import deleteWorkspace
+
+if __name__ == "__main__":
+    test_config = {"host": HOST, "token": TOKEN}
+
+    deleteWorkspace(test_config)

gooddata-sdk/integration_tests/scripts/utils.py

@@ -0,0 +1,30 @@
+# (C) 2024 GoodData Corporation
+import json
+
+
+def load_json(file_path):
+    """Load a JSON file and return its contents."""
+    with open(file_path) as file:  # Removed the "r" as it's the default mode
+        return json.load(file)
+
+
+def normalize_metrics(metrics, exclude_keys=None):
+    """
+    Normalize keys in the metrics list to camelCase, excluding specified keys.
+
+    :param metrics: List of dictionaries with metric data.
+    :param exclude_keys: List of keys to exclude from normalization.
+    :return: List of normalized metric dictionaries.
+    """
+    if exclude_keys is None:
+        exclude_keys = []
+
+    def snake_to_camel(snake_str):
+        components = snake_str.split("_")
+        return components[0] + "".join(x.title() for x in components[1:])
+
+    return [
+        {snake_to_camel(key): value for key, value in metric.items() if key not in exclude_keys}
+        for metric in metrics
+        if isinstance(metric, dict)
+    ]