feat: add scanner tests, global demo key in conftest, remove 48 inline key patches
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
This commit is contained in:
copilot-swe-agent[bot]
parent
4155b1754b
commit
9174ebe763
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@ -4,18 +4,40 @@ import os
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import pytest
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_DEMO_KEY = "demo"
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def pytest_configure(config):
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config.addinivalue_line("markers", "integration: tests that hit real external APIs")
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config.addinivalue_line("markers", "slow: tests that take a long time to run")
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@pytest.fixture(autouse=True)
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def _set_alpha_vantage_demo_key(monkeypatch):
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"""Ensure ALPHA_VANTAGE_API_KEY is always set to 'demo' unless the test
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overrides it. This means no test needs its own patch.dict for the key."""
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if not os.environ.get("ALPHA_VANTAGE_API_KEY"):
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monkeypatch.setenv("ALPHA_VANTAGE_API_KEY", _DEMO_KEY)
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@pytest.fixture
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def av_api_key():
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"""Return the Alpha Vantage API key or skip the test."""
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key = os.environ.get("ALPHA_VANTAGE_API_KEY")
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if not key:
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pytest.skip("ALPHA_VANTAGE_API_KEY not set")
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return key
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"""Return the Alpha Vantage API key ('demo' by default).
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Skips the test automatically when the Alpha Vantage API endpoint is not
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reachable (e.g. sandboxed CI without outbound network access).
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"""
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import socket
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try:
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socket.setdefaulttimeout(3)
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socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect(
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("www.alphavantage.co", 443)
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)
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except (socket.error, OSError):
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pytest.skip("Alpha Vantage API not reachable — skipping live API test")
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return os.environ.get("ALPHA_VANTAGE_API_KEY", _DEMO_KEY)
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@pytest.fixture
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@ -57,14 +57,13 @@ class TestMakeApiRequestErrors:
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def test_timeout_raises_timeout_error(self):
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"""A timeout should raise ThirdPartyTimeoutError."""
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with patch.dict(os.environ, {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(ThirdPartyTimeoutError):
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# Use an impossibly short timeout
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_make_api_request(
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"TIME_SERIES_DAILY",
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{"symbol": "IBM"},
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timeout=0.001,
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)
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with pytest.raises(ThirdPartyTimeoutError):
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# Use an impossibly short timeout
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_make_api_request(
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"TIME_SERIES_DAILY",
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{"symbol": "IBM"},
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timeout=0.001,
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)
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def test_valid_request_succeeds(self, av_api_key):
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"""A valid request with a real key should return data."""
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@ -97,9 +97,8 @@ class TestMakeApiRequest:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(CSV_DAILY_ADJUSTED)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = _make_api_request("TIME_SERIES_DAILY_ADJUSTED",
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{"symbol": "AAPL", "datatype": "csv"})
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result = _make_api_request("TIME_SERIES_DAILY_ADJUSTED",
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{"symbol": "AAPL", "datatype": "csv"})
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assert "timestamp" in result
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assert "186.00" in result
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@ -112,9 +111,8 @@ class TestMakeApiRequest:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(AlphaVantageRateLimitError):
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_make_api_request("TIME_SERIES_DAILY_ADJUSTED", {"symbol": "AAPL"})
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with pytest.raises(AlphaVantageRateLimitError):
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_make_api_request("TIME_SERIES_DAILY_ADJUSTED", {"symbol": "AAPL"})
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def test_raises_api_key_error_for_invalid_api_key(self):
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"""An 'Invalid API key' Information response raises an API-key-related error.
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@ -145,9 +143,8 @@ class TestMakeApiRequest:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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side_effect=TimeoutError("connection timed out")):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(TimeoutError):
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_make_api_request("OVERVIEW", {"symbol": "AAPL"})
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with pytest.raises(TimeoutError):
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_make_api_request("OVERVIEW", {"symbol": "AAPL"})
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def test_http_error_propagates_on_non_200_status(self):
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"""HTTP 4xx/5xx responses raise an error.
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@ -164,9 +161,8 @@ class TestMakeApiRequest:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=bad_resp):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(Exception):
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_make_api_request("OVERVIEW", {"symbol": "AAPL"})
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with pytest.raises(Exception):
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_make_api_request("OVERVIEW", {"symbol": "AAPL"})
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# ---------------------------------------------------------------------------
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@ -259,8 +255,7 @@ class TestAlphaVantageGetStock:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(CSV_DAILY_ADJUSTED)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_stock("AAPL", "2024-01-01", "2024-01-05")
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result = get_stock("AAPL", "2024-01-01", "2024-01-05")
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assert isinstance(result, str)
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@ -276,8 +271,7 @@ class TestAlphaVantageGetStock:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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side_effect=capture_request):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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get_stock("AAPL", "2020-01-01", "2020-01-05")
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get_stock("AAPL", "2020-01-01", "2020-01-05")
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assert captured_params.get("outputsize") == "full"
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@ -287,9 +281,8 @@ class TestAlphaVantageGetStock:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(AlphaVantageRateLimitError):
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get_stock("AAPL", "2024-01-01", "2024-01-05")
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with pytest.raises(AlphaVantageRateLimitError):
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get_stock("AAPL", "2024-01-01", "2024-01-05")
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# ---------------------------------------------------------------------------
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@ -305,8 +298,7 @@ class TestAlphaVantageGetFundamentals:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(OVERVIEW_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_fundamentals("AAPL")
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result = get_fundamentals("AAPL")
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assert "Apple Inc" in result
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assert "TECHNOLOGY" in result
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@ -317,9 +309,8 @@ class TestAlphaVantageGetFundamentals:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(AlphaVantageRateLimitError):
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get_fundamentals("AAPL")
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with pytest.raises(AlphaVantageRateLimitError):
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get_fundamentals("AAPL")
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class TestAlphaVantageGetBalanceSheet:
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@ -329,8 +320,7 @@ class TestAlphaVantageGetBalanceSheet:
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payload = json.dumps({"symbol": "AAPL", "annualReports": [], "quarterlyReports": []})
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(payload)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_balance_sheet("AAPL")
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result = get_balance_sheet("AAPL")
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assert "AAPL" in result
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@ -342,8 +332,7 @@ class TestAlphaVantageGetCashflow:
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payload = json.dumps({"symbol": "AAPL", "annualReports": [], "quarterlyReports": []})
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(payload)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_cashflow("AAPL")
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result = get_cashflow("AAPL")
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assert "AAPL" in result
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@ -355,8 +344,7 @@ class TestAlphaVantageGetIncomeStatement:
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payload = json.dumps({"symbol": "AAPL", "annualReports": [], "quarterlyReports": []})
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(payload)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_income_statement("AAPL")
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result = get_income_statement("AAPL")
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assert "AAPL" in result
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@ -397,8 +385,7 @@ class TestAlphaVantageGetNews:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(NEWS_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_news("AAPL", "2024-01-01", "2024-01-05")
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result = get_news("AAPL", "2024-01-01", "2024-01-05")
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assert "Apple Hits Record High" in result
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@ -408,9 +395,8 @@ class TestAlphaVantageGetNews:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(AlphaVantageRateLimitError):
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get_news("AAPL", "2024-01-01", "2024-01-05")
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with pytest.raises(AlphaVantageRateLimitError):
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get_news("AAPL", "2024-01-01", "2024-01-05")
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class TestAlphaVantageGetGlobalNews:
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@ -419,8 +405,7 @@ class TestAlphaVantageGetGlobalNews:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(NEWS_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_global_news("2024-01-15", look_back_days=7)
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result = get_global_news("2024-01-15", look_back_days=7)
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assert isinstance(result, str)
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@ -436,8 +421,7 @@ class TestAlphaVantageGetGlobalNews:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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side_effect=capture):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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get_global_news("2024-01-15", look_back_days=7)
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get_global_news("2024-01-15", look_back_days=7)
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# time_from should be 7 days before 2024-01-15 → 2024-01-08
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assert "20240108T0000" in captured_params.get("time_from", "")
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@ -449,8 +433,7 @@ class TestAlphaVantageGetInsiderTransactions:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(INSIDER_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_insider_transactions("AAPL")
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result = get_insider_transactions("AAPL")
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assert "Tim Cook" in result
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@ -460,9 +443,8 @@ class TestAlphaVantageGetInsiderTransactions:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with pytest.raises(AlphaVantageRateLimitError):
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get_insider_transactions("AAPL")
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with pytest.raises(AlphaVantageRateLimitError):
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get_insider_transactions("AAPL")
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# ---------------------------------------------------------------------------
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@ -477,10 +459,9 @@ class TestAlphaVantageGetIndicator:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(CSV_RSI)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_indicator(
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"AAPL", "rsi", "2024-01-05", look_back_days=5
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)
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result = get_indicator(
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"AAPL", "rsi", "2024-01-05", look_back_days=5
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)
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assert isinstance(result, str)
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assert "RSI" in result.upper()
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@ -490,10 +471,9 @@ class TestAlphaVantageGetIndicator:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(CSV_SMA)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_indicator(
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"AAPL", "close_50_sma", "2024-01-05", look_back_days=5
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)
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result = get_indicator(
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"AAPL", "close_50_sma", "2024-01-05", look_back_days=5
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)
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assert isinstance(result, str)
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assert "SMA" in result.upper()
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@ -510,8 +490,7 @@ class TestAlphaVantageGetIndicator:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_response(RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_indicator("AAPL", "rsi", "2024-01-05", look_back_days=5)
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result = get_indicator("AAPL", "rsi", "2024-01-05", look_back_days=5)
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assert "Error" in result or "rate limit" in result.lower()
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@ -519,8 +498,7 @@ class TestAlphaVantageGetIndicator:
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"""VWMA is not directly available; a descriptive message is returned."""
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from tradingagents.dataflows.alpha_vantage_indicator import get_indicator
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = get_indicator("AAPL", "vwma", "2024-01-05", look_back_days=5)
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result = get_indicator("AAPL", "vwma", "2024-01-05", look_back_days=5)
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assert "VWMA" in result
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assert "not directly available" in result.lower() or "Volume Weighted" in result
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@ -100,8 +100,7 @@ class TestRouteToVendor:
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with patch("tradingagents.dataflows.interface.get_config", return_value=patched_config):
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_av_response(_OHLCV_CSV_AV)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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result = route_to_vendor("get_stock_data", "AAPL", "2024-01-04", "2024-01-05")
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result = route_to_vendor("get_stock_data", "AAPL", "2024-01-04", "2024-01-05")
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assert isinstance(result, str)
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@ -124,13 +123,12 @@ class TestRouteToVendor:
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# AV returns a rate-limit response
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_av_response(_RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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# yfinance is the fallback
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with patch("tradingagents.dataflows.y_finance.yf.Ticker",
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return_value=mock_ticker):
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result = route_to_vendor(
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"get_stock_data", "AAPL", "2024-01-04", "2024-01-05"
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)
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# yfinance is the fallback
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with patch("tradingagents.dataflows.y_finance.yf.Ticker",
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return_value=mock_ticker):
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result = route_to_vendor(
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"get_stock_data", "AAPL", "2024-01-04", "2024-01-05"
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)
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assert isinstance(result, str)
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assert "AAPL" in result
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@ -150,13 +148,12 @@ class TestRouteToVendor:
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with patch("tradingagents.dataflows.interface.get_config", return_value=patched_config):
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
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return_value=_mock_av_response(_RATE_LIMIT_JSON)):
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with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
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with patch(
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"tradingagents.dataflows.y_finance.yf.Ticker",
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side_effect=ConnectionError("network unavailable"),
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):
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with pytest.raises(RuntimeError, match="No available vendor"):
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route_to_vendor("get_stock_data", "AAPL", "2024-01-04", "2024-01-05")
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with patch(
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"tradingagents.dataflows.y_finance.yf.Ticker",
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side_effect=ConnectionError("network unavailable"),
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):
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with pytest.raises(RuntimeError, match="No available vendor"):
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route_to_vendor("get_stock_data", "AAPL", "2024-01-04", "2024-01-05")
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def test_unknown_method_raises_value_error(self):
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from tradingagents.dataflows.interface import route_to_vendor
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@ -195,8 +192,7 @@ class TestFullPipeline:
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with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
|
||||
return_value=_mock_av_response(_OHLCV_CSV_AV)):
|
||||
with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
result = get_stock("AAPL", "2024-01-04", "2024-01-05")
|
||||
result = get_stock("AAPL", "2024-01-04", "2024-01-05")
|
||||
|
||||
assert isinstance(result, str)
|
||||
# pandas may reformat "185.00" → "185.0"; check for the numeric value
|
||||
|
|
@ -230,8 +226,7 @@ class TestFullPipeline:
|
|||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
|
||||
return_value=_mock_av_response(_OVERVIEW_JSON)):
|
||||
with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
result = get_fundamentals("AAPL")
|
||||
result = get_fundamentals("AAPL")
|
||||
|
||||
assert "Apple Inc" in result
|
||||
assert "TECHNOLOGY" in result
|
||||
|
|
@ -262,8 +257,7 @@ class TestFullPipeline:
|
|||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
|
||||
return_value=_mock_av_response(_NEWS_JSON)):
|
||||
with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
result = get_news("AAPL", "2024-01-01", "2024-01-05")
|
||||
result = get_news("AAPL", "2024-01-01", "2024-01-05")
|
||||
|
||||
assert "Apple Hits Record High" in result
|
||||
|
||||
|
|
@ -288,8 +282,7 @@ class TestFullPipeline:
|
|||
# --- Step 2: Alpha Vantage fundamentals ---
|
||||
with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
|
||||
return_value=_mock_av_response(_OVERVIEW_JSON)):
|
||||
with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
fundamentals = get_fundamentals("AAPL")
|
||||
fundamentals = get_fundamentals("AAPL")
|
||||
|
||||
# --- Assertions ---
|
||||
assert isinstance(price_data, str)
|
||||
|
|
@ -330,9 +323,8 @@ class TestFullPipeline:
|
|||
# Alpha Vantage rate-limits
|
||||
with patch("tradingagents.dataflows.alpha_vantage_common.requests.get",
|
||||
return_value=_mock_av_response(_RATE_LIMIT_JSON)):
|
||||
with patch.dict("os.environ", {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
with pytest.raises(AlphaVantageRateLimitError):
|
||||
get_fundamentals("AAPL")
|
||||
with pytest.raises(AlphaVantageRateLimitError):
|
||||
get_fundamentals("AAPL")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
|
|
|
|||
|
|
@ -83,33 +83,29 @@ class TestAlphaVantageFailoverRaise:
|
|||
|
||||
def test_sector_perf_raises_on_total_failure(self):
|
||||
"""When every GLOBAL_QUOTE call fails, the function should raise."""
|
||||
with patch.dict(os.environ, {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
with pytest.raises(AlphaVantageError, match="All .* sector queries failed"):
|
||||
get_sector_performance_alpha_vantage()
|
||||
with pytest.raises(AlphaVantageError, match="All .* sector queries failed"):
|
||||
get_sector_performance_alpha_vantage()
|
||||
|
||||
def test_industry_perf_raises_on_total_failure(self):
|
||||
"""When every ticker quote fails, the function should raise."""
|
||||
with patch.dict(os.environ, {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
with pytest.raises(AlphaVantageError, match="All .* ticker queries failed"):
|
||||
get_industry_performance_alpha_vantage("technology")
|
||||
with pytest.raises(AlphaVantageError, match="All .* ticker queries failed"):
|
||||
get_industry_performance_alpha_vantage("technology")
|
||||
|
||||
|
||||
class TestRouteToVendorFallback:
|
||||
"""Verify route_to_vendor falls back from AV to yfinance."""
|
||||
|
||||
def test_sector_perf_falls_back_to_yfinance(self):
|
||||
with patch.dict(os.environ, {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
result = route_to_vendor("get_sector_performance")
|
||||
# Should get yfinance data (no "Alpha Vantage" in header)
|
||||
assert "Sector Performance Overview" in result
|
||||
# Should have actual percentage data, not all errors
|
||||
assert "Error:" not in result or result.count("Error:") < 3
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
result = route_to_vendor("get_sector_performance")
|
||||
# Should get yfinance data (no "Alpha Vantage" in header)
|
||||
assert "Sector Performance Overview" in result
|
||||
# Should have actual percentage data, not all errors
|
||||
assert "Error:" not in result or result.count("Error:") < 3
|
||||
|
||||
def test_industry_perf_falls_back_to_yfinance(self):
|
||||
with patch.dict(os.environ, {"ALPHA_VANTAGE_API_KEY": "demo"}):
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
result = route_to_vendor("get_industry_performance", "technology")
|
||||
assert "Industry Performance" in result
|
||||
# Should contain real ticker symbols
|
||||
assert "N/A" not in result or result.count("N/A") < 5
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
result = route_to_vendor("get_industry_performance", "technology")
|
||||
assert "Industry Performance" in result
|
||||
# Should contain real ticker symbols
|
||||
assert "N/A" not in result or result.count("N/A") < 5
|
||||
|
|
|
|||
|
|
@ -0,0 +1,729 @@
|
|||
"""Offline mocked tests for the market-wide scanner layer.
|
||||
|
||||
Covers both yfinance and Alpha Vantage scanner functions, plus the
|
||||
route_to_vendor scanner routing. All external calls are mocked so
|
||||
these tests run without a network connection or API key.
|
||||
"""
|
||||
|
||||
import json
|
||||
import pandas as pd
|
||||
import pytest
|
||||
from datetime import date, datetime
|
||||
from unittest.mock import patch, MagicMock
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Helpers — mock data factories
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _av_response(payload: dict | str) -> MagicMock:
|
||||
"""Build a mock requests.Response wrapping a JSON dict or raw string."""
|
||||
resp = MagicMock()
|
||||
resp.status_code = 200
|
||||
resp.text = json.dumps(payload) if isinstance(payload, dict) else payload
|
||||
resp.raise_for_status = MagicMock()
|
||||
return resp
|
||||
|
||||
|
||||
def _global_quote(symbol: str, price: float = 480.0, change: float = 2.5,
|
||||
change_pct: str = "0.52%") -> dict:
|
||||
return {
|
||||
"Global Quote": {
|
||||
"01. symbol": symbol,
|
||||
"05. price": str(price),
|
||||
"09. change": str(change),
|
||||
"10. change percent": change_pct,
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
def _time_series_daily(symbol: str) -> dict:
|
||||
"""Return a minimal TIME_SERIES_DAILY JSON payload."""
|
||||
return {
|
||||
"Meta Data": {"2. Symbol": symbol},
|
||||
"Time Series (Daily)": {
|
||||
"2024-01-08": {"4. close": "482.00"},
|
||||
"2024-01-05": {"4. close": "480.00"},
|
||||
"2024-01-04": {"4. close": "475.00"},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
_TOP_GAINERS_LOSERS = {
|
||||
"top_gainers": [
|
||||
{"ticker": "NVDA", "price": "620.00", "change_percentage": "5.10%", "volume": "45000000"},
|
||||
{"ticker": "AMD", "price": "175.00", "change_percentage": "3.20%", "volume": "32000000"},
|
||||
],
|
||||
"top_losers": [
|
||||
{"ticker": "INTC", "price": "31.00", "change_percentage": "-4.50%", "volume": "28000000"},
|
||||
],
|
||||
"most_actively_traded": [
|
||||
{"ticker": "TSLA", "price": "240.00", "change_percentage": "1.80%", "volume": "90000000"},
|
||||
],
|
||||
}
|
||||
|
||||
_NEWS_SENTIMENT = {
|
||||
"feed": [
|
||||
{
|
||||
"title": "AI Stocks Rally on Positive Earnings",
|
||||
"summary": "Tech stocks continued their upward climb.",
|
||||
"source": "Reuters",
|
||||
"url": "https://example.com/news/1",
|
||||
"time_published": "20240108T130000",
|
||||
"overall_sentiment_score": 0.35,
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# yfinance scanner — get_market_movers_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestYfinanceScannerMarketMovers:
|
||||
"""Offline tests for get_market_movers_yfinance."""
|
||||
|
||||
def _screener_data(self, category: str = "day_gainers") -> dict:
|
||||
return {
|
||||
"quotes": [
|
||||
{
|
||||
"symbol": "NVDA",
|
||||
"shortName": "NVIDIA Corp",
|
||||
"regularMarketPrice": 620.00,
|
||||
"regularMarketChangePercent": 5.10,
|
||||
"regularMarketVolume": 45_000_000,
|
||||
"marketCap": 1_500_000_000_000,
|
||||
},
|
||||
{
|
||||
"symbol": "AMD",
|
||||
"shortName": "Advanced Micro Devices",
|
||||
"regularMarketPrice": 175.00,
|
||||
"regularMarketChangePercent": 3.20,
|
||||
"regularMarketVolume": 32_000_000,
|
||||
"marketCap": 280_000_000_000,
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
def test_returns_markdown_table_for_day_gainers(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_movers_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
return_value=self._screener_data()):
|
||||
result = get_market_movers_yfinance("day_gainers")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Market Movers" in result
|
||||
assert "NVDA" in result
|
||||
assert "5.10%" in result
|
||||
assert "|" in result # markdown table
|
||||
|
||||
def test_returns_markdown_table_for_day_losers(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_movers_yfinance
|
||||
|
||||
data = {"quotes": [{"symbol": "INTC", "shortName": "Intel", "regularMarketPrice": 31.00,
|
||||
"regularMarketChangePercent": -4.5, "regularMarketVolume": 28_000_000,
|
||||
"marketCap": 130_000_000_000}]}
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
return_value=data):
|
||||
result = get_market_movers_yfinance("day_losers")
|
||||
|
||||
assert "Market Movers" in result
|
||||
assert "INTC" in result
|
||||
|
||||
def test_invalid_category_returns_error_string(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_movers_yfinance
|
||||
|
||||
result = get_market_movers_yfinance("not_a_category")
|
||||
assert "Invalid category" in result
|
||||
|
||||
def test_empty_quotes_returns_no_data_message(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_movers_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
return_value={"quotes": []}):
|
||||
result = get_market_movers_yfinance("day_gainers")
|
||||
|
||||
assert "No quotes found" in result
|
||||
|
||||
def test_api_error_returns_error_string(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_movers_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
side_effect=Exception("network failure")):
|
||||
result = get_market_movers_yfinance("day_gainers")
|
||||
|
||||
assert "Error" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# yfinance scanner — get_market_indices_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestYfinanceScannerMarketIndices:
|
||||
"""Offline tests for get_market_indices_yfinance."""
|
||||
|
||||
def _make_multi_etf_df(self) -> pd.DataFrame:
|
||||
"""Build a minimal multi-ticker Close DataFrame as yf.download returns."""
|
||||
symbols = ["^GSPC", "^DJI", "^IXIC", "^VIX", "^RUT"]
|
||||
idx = pd.date_range("2024-01-04", periods=3, freq="B", tz="UTC")
|
||||
closes = pd.DataFrame(
|
||||
{s: [4800.0 + i * 10, 4810.0 + i * 10, 4820.0 + i * 10] for i, s in enumerate(symbols)},
|
||||
index=idx,
|
||||
)
|
||||
return pd.DataFrame({"Close": closes})
|
||||
|
||||
def test_returns_markdown_table_with_indices(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_indices_yfinance
|
||||
|
||||
# Multi-symbol download returns a MultiIndex DataFrame
|
||||
symbols = ["^GSPC", "^DJI", "^IXIC", "^VIX", "^RUT"]
|
||||
idx = pd.date_range("2024-01-04", periods=5, freq="B")
|
||||
close_data = {s: [4800.0 + i for i in range(5)] for s in symbols}
|
||||
# yf.download with multiple symbols returns DataFrame with MultiIndex columns
|
||||
multi_df = pd.DataFrame(close_data, index=idx)
|
||||
multi_df.columns = pd.MultiIndex.from_product([["Close"], symbols])
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download",
|
||||
return_value=multi_df):
|
||||
result = get_market_indices_yfinance()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Market Indices" in result or "Index" in result.split("\n")[0]
|
||||
|
||||
def test_returns_string_on_download_error(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_market_indices_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download",
|
||||
side_effect=Exception("network error")):
|
||||
result = get_market_indices_yfinance()
|
||||
|
||||
assert isinstance(result, str)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# yfinance scanner — get_sector_performance_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestYfinanceScannerSectorPerformance:
|
||||
"""Offline tests for get_sector_performance_yfinance."""
|
||||
|
||||
def _make_sector_df(self) -> pd.DataFrame:
|
||||
"""Multi-symbol ETF DataFrame covering 6 months of daily closes."""
|
||||
etfs = ["XLK", "XLV", "XLF", "XLE", "XLY", "XLP", "XLI", "XLB", "XLRE", "XLU", "XLC"]
|
||||
# 130 trading days ~ 6 months
|
||||
idx = pd.date_range("2023-07-01", periods=130, freq="B")
|
||||
data = {e: [100.0 + i * 0.01 for i in range(130)] for e in etfs}
|
||||
df = pd.DataFrame(data, index=idx)
|
||||
df.columns = pd.MultiIndex.from_product([["Close"], etfs])
|
||||
return df
|
||||
|
||||
def test_returns_sector_performance_table(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_sector_performance_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download",
|
||||
return_value=self._make_sector_df()):
|
||||
result = get_sector_performance_yfinance()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Sector Performance Overview" in result
|
||||
assert "|" in result
|
||||
|
||||
def test_contains_all_sectors(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_sector_performance_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download",
|
||||
return_value=self._make_sector_df()):
|
||||
result = get_sector_performance_yfinance()
|
||||
|
||||
# 11 GICS sectors should all appear
|
||||
for sector in ["Technology", "Healthcare", "Financials", "Energy"]:
|
||||
assert sector in result
|
||||
|
||||
def test_download_error_returns_error_string(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_sector_performance_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download",
|
||||
side_effect=Exception("connection refused")):
|
||||
result = get_sector_performance_yfinance()
|
||||
|
||||
assert "Error" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# yfinance scanner — get_industry_performance_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestYfinanceScannerIndustryPerformance:
|
||||
"""Offline tests for get_industry_performance_yfinance."""
|
||||
|
||||
def _mock_sector_with_companies(self) -> MagicMock:
|
||||
top_companies = pd.DataFrame(
|
||||
{
|
||||
"name": ["Apple Inc.", "Microsoft Corp", "NVIDIA Corp"],
|
||||
"rating": [4.5, 4.8, 4.2],
|
||||
"market weight": [0.072, 0.065, 0.051],
|
||||
},
|
||||
index=pd.Index(["AAPL", "MSFT", "NVDA"], name="symbol"),
|
||||
)
|
||||
mock_sector = MagicMock()
|
||||
mock_sector.top_companies = top_companies
|
||||
return mock_sector
|
||||
|
||||
def test_returns_industry_table_for_valid_sector(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_industry_performance_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Sector",
|
||||
return_value=self._mock_sector_with_companies()):
|
||||
result = get_industry_performance_yfinance("technology")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Industry Performance" in result
|
||||
assert "AAPL" in result
|
||||
assert "Apple Inc." in result
|
||||
|
||||
def test_empty_top_companies_returns_no_data_message(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_industry_performance_yfinance
|
||||
|
||||
mock_sector = MagicMock()
|
||||
mock_sector.top_companies = pd.DataFrame()
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Sector",
|
||||
return_value=mock_sector):
|
||||
result = get_industry_performance_yfinance("technology")
|
||||
|
||||
assert "No industry data found" in result
|
||||
|
||||
def test_none_top_companies_returns_no_data_message(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_industry_performance_yfinance
|
||||
|
||||
mock_sector = MagicMock()
|
||||
mock_sector.top_companies = None
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Sector",
|
||||
return_value=mock_sector):
|
||||
result = get_industry_performance_yfinance("healthcare")
|
||||
|
||||
assert "No industry data found" in result
|
||||
|
||||
def test_sector_error_returns_error_string(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_industry_performance_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Sector",
|
||||
side_effect=Exception("yfinance unavailable")):
|
||||
result = get_industry_performance_yfinance("technology")
|
||||
|
||||
assert "Error" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# yfinance scanner — get_topic_news_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestYfinanceScannerTopicNews:
|
||||
"""Offline tests for get_topic_news_yfinance."""
|
||||
|
||||
def _mock_search(self, title: str = "AI Revolution in Tech") -> MagicMock:
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [
|
||||
{
|
||||
"title": title,
|
||||
"publisher": "TechCrunch",
|
||||
"link": "https://techcrunch.com/story",
|
||||
"summary": "Artificial intelligence is transforming the industry.",
|
||||
}
|
||||
]
|
||||
return mock_search
|
||||
|
||||
def test_returns_formatted_news_for_topic(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_topic_news_yfinance
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Search",
|
||||
return_value=self._mock_search()):
|
||||
result = get_topic_news_yfinance("artificial intelligence")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "AI Revolution in Tech" in result
|
||||
assert "News for Topic" in result
|
||||
|
||||
def test_no_results_returns_no_news_message(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_topic_news_yfinance
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = []
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Search",
|
||||
return_value=mock_search):
|
||||
result = get_topic_news_yfinance("obscure_topic")
|
||||
|
||||
assert "No news found" in result
|
||||
|
||||
def test_handles_nested_content_structure(self):
|
||||
from tradingagents.dataflows.yfinance_scanner import get_topic_news_yfinance
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [
|
||||
{
|
||||
"content": {
|
||||
"title": "Semiconductor Demand Surges",
|
||||
"summary": "Chip makers report record orders.",
|
||||
"provider": {"displayName": "Bloomberg"},
|
||||
"canonicalUrl": {"url": "https://bloomberg.com/chips"},
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Search",
|
||||
return_value=mock_search):
|
||||
result = get_topic_news_yfinance("semiconductors")
|
||||
|
||||
assert "Semiconductor Demand Surges" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alpha Vantage scanner — get_market_movers_alpha_vantage
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAVScannerMarketMovers:
|
||||
"""Offline mocked tests for get_market_movers_alpha_vantage."""
|
||||
|
||||
def test_day_gainers_returns_markdown_table(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_movers_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
return_value=json.dumps(_TOP_GAINERS_LOSERS)):
|
||||
result = get_market_movers_alpha_vantage("day_gainers")
|
||||
|
||||
assert "Market Movers" in result
|
||||
assert "NVDA" in result
|
||||
assert "5.10%" in result
|
||||
assert "|" in result
|
||||
|
||||
def test_day_losers_returns_markdown_table(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_movers_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
return_value=json.dumps(_TOP_GAINERS_LOSERS)):
|
||||
result = get_market_movers_alpha_vantage("day_losers")
|
||||
|
||||
assert "INTC" in result
|
||||
|
||||
def test_most_actives_returns_markdown_table(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_movers_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
return_value=json.dumps(_TOP_GAINERS_LOSERS)):
|
||||
result = get_market_movers_alpha_vantage("most_actives")
|
||||
|
||||
assert "TSLA" in result
|
||||
|
||||
def test_invalid_category_raises_value_error(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_movers_alpha_vantage
|
||||
|
||||
with pytest.raises(ValueError, match="Invalid category"):
|
||||
get_market_movers_alpha_vantage("not_valid")
|
||||
|
||||
def test_rate_limit_error_propagates(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_movers_alpha_vantage
|
||||
from tradingagents.dataflows.alpha_vantage_common import RateLimitError
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=RateLimitError("rate limited")):
|
||||
with pytest.raises(RateLimitError):
|
||||
get_market_movers_alpha_vantage("day_gainers")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alpha Vantage scanner — get_market_indices_alpha_vantage
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAVScannerMarketIndices:
|
||||
"""Offline mocked tests for get_market_indices_alpha_vantage."""
|
||||
|
||||
def test_returns_markdown_table_with_index_names(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_indices_alpha_vantage
|
||||
|
||||
def fake_request(function_name, params, **kwargs):
|
||||
symbol = params.get("symbol", "SPY")
|
||||
return json.dumps(_global_quote(symbol))
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=fake_request):
|
||||
result = get_market_indices_alpha_vantage()
|
||||
|
||||
assert "Market Indices" in result
|
||||
assert "|" in result
|
||||
assert any(name in result for name in ["S&P 500", "Dow Jones", "NASDAQ"])
|
||||
|
||||
def test_all_proxies_appear_in_output(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_market_indices_alpha_vantage
|
||||
|
||||
def fake_request(function_name, params, **kwargs):
|
||||
return json.dumps(_global_quote(params.get("symbol", "SPY")))
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=fake_request):
|
||||
result = get_market_indices_alpha_vantage()
|
||||
|
||||
# All 4 ETF proxies should appear
|
||||
for proxy in ["SPY", "DIA", "QQQ", "IWM"]:
|
||||
assert proxy in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alpha Vantage scanner — get_sector_performance_alpha_vantage
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAVScannerSectorPerformance:
|
||||
"""Offline mocked tests for get_sector_performance_alpha_vantage."""
|
||||
|
||||
def _make_fake_request(self):
|
||||
"""Return a side_effect function handling both GLOBAL_QUOTE and TIME_SERIES_DAILY."""
|
||||
def fake(function_name, params, **kwargs):
|
||||
if function_name == "GLOBAL_QUOTE":
|
||||
symbol = params.get("symbol", "XLK")
|
||||
return json.dumps(_global_quote(symbol))
|
||||
elif function_name == "TIME_SERIES_DAILY":
|
||||
symbol = params.get("symbol", "XLK")
|
||||
return json.dumps(_time_series_daily(symbol))
|
||||
return json.dumps({})
|
||||
return fake
|
||||
|
||||
def test_returns_sector_table_with_percentages(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_sector_performance_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=self._make_fake_request()):
|
||||
result = get_sector_performance_alpha_vantage()
|
||||
|
||||
assert "Sector Performance Overview" in result
|
||||
assert "|" in result
|
||||
|
||||
def test_all_eleven_sectors_in_output(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_sector_performance_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=self._make_fake_request()):
|
||||
result = get_sector_performance_alpha_vantage()
|
||||
|
||||
for sector in ["Technology", "Healthcare", "Financials", "Energy"]:
|
||||
assert sector in result
|
||||
|
||||
def test_all_errors_raises_alpha_vantage_error(self):
|
||||
"""If ALL sector ETF requests fail, AlphaVantageError is raised for fallback."""
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_sector_performance_alpha_vantage
|
||||
from tradingagents.dataflows.alpha_vantage_common import AlphaVantageError, RateLimitError
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=RateLimitError("rate limited")):
|
||||
with pytest.raises(AlphaVantageError):
|
||||
get_sector_performance_alpha_vantage()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alpha Vantage scanner — get_industry_performance_alpha_vantage
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAVScannerIndustryPerformance:
|
||||
"""Offline mocked tests for get_industry_performance_alpha_vantage."""
|
||||
|
||||
def test_returns_table_for_technology_sector(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_industry_performance_alpha_vantage
|
||||
|
||||
def fake_request(function_name, params, **kwargs):
|
||||
symbol = params.get("symbol", "AAPL")
|
||||
return json.dumps(_global_quote(symbol, price=185.0, change_pct="+1.20%"))
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=fake_request):
|
||||
result = get_industry_performance_alpha_vantage("technology")
|
||||
|
||||
assert "Industry Performance" in result
|
||||
assert "|" in result
|
||||
assert any(t in result for t in ["AAPL", "MSFT", "NVDA"])
|
||||
|
||||
def test_invalid_sector_raises_value_error(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_industry_performance_alpha_vantage
|
||||
|
||||
with pytest.raises(ValueError, match="Unknown sector"):
|
||||
get_industry_performance_alpha_vantage("not_a_real_sector")
|
||||
|
||||
def test_sorted_by_change_percent_descending(self):
|
||||
"""Results should be sorted by change % descending."""
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_industry_performance_alpha_vantage
|
||||
|
||||
# Alternate high/low changes to verify sort order
|
||||
prices = {"AAPL": ("180.00", "+5.00%"), "MSFT": ("380.00", "+1.00%"),
|
||||
"NVDA": ("620.00", "+8.00%"), "GOOGL": ("140.00", "+2.50%"),
|
||||
"META": ("350.00", "+3.10%"), "AVGO": ("850.00", "+0.50%"),
|
||||
"ADBE": ("550.00", "+4.20%"), "CRM": ("275.00", "+1.80%"),
|
||||
"AMD": ("170.00", "+6.30%"), "INTC": ("31.00", "-2.10%")}
|
||||
|
||||
def fake_request(function_name, params, **kwargs):
|
||||
symbol = params.get("symbol", "AAPL")
|
||||
p, c = prices.get(symbol, ("100.00", "0.00%"))
|
||||
return json.dumps({
|
||||
"Global Quote": {"01. symbol": symbol, "05. price": p,
|
||||
"09. change": "1.00", "10. change percent": c}
|
||||
})
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=fake_request):
|
||||
result = get_industry_performance_alpha_vantage("technology")
|
||||
|
||||
# NVDA (+8%) should appear before INTC (-2.1%)
|
||||
nvda_pos = result.find("NVDA")
|
||||
intc_pos = result.find("INTC")
|
||||
assert nvda_pos != -1 and intc_pos != -1
|
||||
assert nvda_pos < intc_pos
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alpha Vantage scanner — get_topic_news_alpha_vantage
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAVScannerTopicNews:
|
||||
"""Offline mocked tests for get_topic_news_alpha_vantage."""
|
||||
|
||||
def test_returns_news_articles_for_known_topic(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_topic_news_alpha_vantage
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
return_value=json.dumps(_NEWS_SENTIMENT)):
|
||||
result = get_topic_news_alpha_vantage("market", limit=5)
|
||||
|
||||
assert "News for Topic" in result
|
||||
assert "AI Stocks Rally on Positive Earnings" in result
|
||||
|
||||
def test_known_topic_is_mapped_to_av_value(self):
|
||||
"""Topic strings like 'market' are remapped to AV-specific topic keys."""
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_topic_news_alpha_vantage
|
||||
|
||||
captured = {}
|
||||
|
||||
def capture_request(function_name, params, **kwargs):
|
||||
captured.update(params)
|
||||
return json.dumps(_NEWS_SENTIMENT)
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=capture_request):
|
||||
get_topic_news_alpha_vantage("market", limit=5)
|
||||
|
||||
# "market" maps to "financial_markets" in _TOPIC_MAP
|
||||
assert captured.get("topics") == "financial_markets"
|
||||
|
||||
def test_unknown_topic_passed_through(self):
|
||||
"""Topics not in the map are forwarded to the API as-is."""
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_topic_news_alpha_vantage
|
||||
|
||||
captured = {}
|
||||
|
||||
def capture_request(function_name, params, **kwargs):
|
||||
captured.update(params)
|
||||
return json.dumps(_NEWS_SENTIMENT)
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=capture_request):
|
||||
get_topic_news_alpha_vantage("custom_topic", limit=3)
|
||||
|
||||
assert captured.get("topics") == "custom_topic"
|
||||
|
||||
def test_empty_feed_returns_no_articles_message(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_topic_news_alpha_vantage
|
||||
|
||||
empty = {"feed": []}
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
return_value=json.dumps(empty)):
|
||||
result = get_topic_news_alpha_vantage("earnings", limit=5)
|
||||
|
||||
assert "No articles" in result
|
||||
|
||||
def test_rate_limit_error_propagates(self):
|
||||
from tradingagents.dataflows.alpha_vantage_scanner import get_topic_news_alpha_vantage
|
||||
from tradingagents.dataflows.alpha_vantage_common import RateLimitError
|
||||
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=RateLimitError("rate limited")):
|
||||
with pytest.raises(RateLimitError):
|
||||
get_topic_news_alpha_vantage("technology")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Scanner routing — route_to_vendor for scanner methods
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestScannerRouting:
|
||||
"""End-to-end routing tests for scanner_data methods via route_to_vendor."""
|
||||
|
||||
def test_get_market_movers_routes_to_yfinance_by_default(self):
|
||||
"""Default config uses yfinance for scanner_data."""
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
|
||||
screener_data = {
|
||||
"quotes": [{"symbol": "NVDA", "shortName": "NVIDIA", "regularMarketPrice": 620.0,
|
||||
"regularMarketChangePercent": 5.1, "regularMarketVolume": 45_000_000,
|
||||
"marketCap": 1_500_000_000_000}]
|
||||
}
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
return_value=screener_data):
|
||||
result = route_to_vendor("get_market_movers", "day_gainers")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "NVDA" in result
|
||||
|
||||
def test_get_sector_performance_routes_to_yfinance_by_default(self):
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
|
||||
etfs = ["XLK", "XLV", "XLF", "XLE", "XLY", "XLP", "XLI", "XLB", "XLRE", "XLU", "XLC"]
|
||||
idx = pd.date_range("2023-07-01", periods=130, freq="B")
|
||||
close_data = {e: [100.0 + i * 0.01 for i in range(130)] for e in etfs}
|
||||
df = pd.DataFrame(close_data, index=idx)
|
||||
df.columns = pd.MultiIndex.from_product([["Close"], etfs])
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.download", return_value=df):
|
||||
result = route_to_vendor("get_sector_performance")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Sector Performance Overview" in result
|
||||
|
||||
def test_get_market_movers_falls_back_to_yfinance_when_av_fails(self):
|
||||
"""When AV scanner raises AlphaVantageError, fallback to yfinance is used."""
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
from tradingagents.dataflows.config import get_config
|
||||
from tradingagents.dataflows.alpha_vantage_common import AlphaVantageError
|
||||
|
||||
original_config = get_config()
|
||||
patched_config = {
|
||||
**original_config,
|
||||
"data_vendors": {**original_config.get("data_vendors", {}), "scanner_data": "alpha_vantage"},
|
||||
}
|
||||
|
||||
screener_data = {
|
||||
"quotes": [{"symbol": "AMD", "shortName": "AMD", "regularMarketPrice": 175.0,
|
||||
"regularMarketChangePercent": 3.2, "regularMarketVolume": 32_000_000,
|
||||
"marketCap": 280_000_000_000}]
|
||||
}
|
||||
|
||||
with patch("tradingagents.dataflows.interface.get_config", return_value=patched_config):
|
||||
# AV market movers raises → fallback to yfinance
|
||||
with patch("tradingagents.dataflows.alpha_vantage_scanner._rate_limited_request",
|
||||
side_effect=AlphaVantageError("rate limited")):
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.screener.screen",
|
||||
return_value=screener_data):
|
||||
result = route_to_vendor("get_market_movers", "day_gainers")
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "AMD" in result
|
||||
|
||||
def test_get_topic_news_routes_correctly(self):
|
||||
from tradingagents.dataflows.interface import route_to_vendor
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [{"title": "Fed Signals Rate Cut", "publisher": "Reuters",
|
||||
"link": "https://example.com", "summary": "Fed news."}]
|
||||
|
||||
with patch("tradingagents.dataflows.yfinance_scanner.yf.Search",
|
||||
return_value=mock_search):
|
||||
result = route_to_vendor("get_topic_news", "economy")
|
||||
|
||||
assert isinstance(result, str)
|
||||
|
|
@ -403,3 +403,165 @@ class TestGetInsiderTransactions:
|
|||
result = get_insider_transactions("AAPL")
|
||||
|
||||
assert "Error" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# get_stock_stats_indicators_window
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestGetStockStatsIndicatorsWindow:
|
||||
"""Tests for get_stock_stats_indicators_window (technical indicators)."""
|
||||
|
||||
def _bulk_rsi_data(self):
|
||||
"""Return a realistic dict of date→rsi_value as _get_stock_stats_bulk would."""
|
||||
return {
|
||||
"2024-01-08": "62.34",
|
||||
"2024-01-07": "N/A", # weekend
|
||||
"2024-01-06": "N/A", # weekend
|
||||
"2024-01-05": "59.12",
|
||||
"2024-01-04": "55.67",
|
||||
"2024-01-03": "50.00",
|
||||
}
|
||||
|
||||
def test_returns_formatted_indicator_string(self):
|
||||
"""Success path: returns a multi-line string with dates and RSI values."""
|
||||
from tradingagents.dataflows.y_finance import get_stock_stats_indicators_window
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.y_finance._get_stock_stats_bulk",
|
||||
return_value=self._bulk_rsi_data(),
|
||||
):
|
||||
result = get_stock_stats_indicators_window("AAPL", "rsi", "2024-01-08", 5)
|
||||
|
||||
assert "rsi" in result
|
||||
assert "2024-01-08" in result
|
||||
assert "62.34" in result
|
||||
|
||||
def test_includes_indicator_description(self):
|
||||
"""The returned string includes the indicator description / usage notes."""
|
||||
from tradingagents.dataflows.y_finance import get_stock_stats_indicators_window
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.y_finance._get_stock_stats_bulk",
|
||||
return_value=self._bulk_rsi_data(),
|
||||
):
|
||||
result = get_stock_stats_indicators_window("AAPL", "rsi", "2024-01-08", 5)
|
||||
|
||||
# Every supported indicator has a description string
|
||||
assert "RSI" in result or "momentum" in result.lower()
|
||||
|
||||
def test_unsupported_indicator_raises_value_error(self):
|
||||
"""Requesting an unsupported indicator raises ValueError before any network call."""
|
||||
from tradingagents.dataflows.y_finance import get_stock_stats_indicators_window
|
||||
|
||||
with pytest.raises(ValueError, match="not supported"):
|
||||
get_stock_stats_indicators_window("AAPL", "unknown_indicator", "2024-01-08", 5)
|
||||
|
||||
def test_bulk_exception_triggers_fallback(self):
|
||||
"""If _get_stock_stats_bulk raises, the function falls back gracefully."""
|
||||
from tradingagents.dataflows.y_finance import get_stock_stats_indicators_window
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.y_finance._get_stock_stats_bulk",
|
||||
side_effect=Exception("stockstats unavailable"),
|
||||
):
|
||||
with patch(
|
||||
"tradingagents.dataflows.y_finance.get_stockstats_indicator",
|
||||
return_value="45.00",
|
||||
):
|
||||
result = get_stock_stats_indicators_window("AAPL", "rsi", "2024-01-08", 3)
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "rsi" in result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# get_global_news_yfinance
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestGetGlobalNewsYfinance:
|
||||
"""Tests for get_global_news_yfinance."""
|
||||
|
||||
def _mock_search_with_article(self):
|
||||
"""Return a mock yf.Search object with one flat-structured news article."""
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [
|
||||
{
|
||||
"title": "Fed Holds Rates Steady",
|
||||
"publisher": "Reuters",
|
||||
"link": "https://example.com/fed",
|
||||
"summary": "The Federal Reserve decided to hold interest rates.",
|
||||
}
|
||||
]
|
||||
return mock_search
|
||||
|
||||
def test_returns_string_with_articles(self):
|
||||
"""When yfinance Search returns articles, a formatted string is returned."""
|
||||
from tradingagents.dataflows.yfinance_news import get_global_news_yfinance
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.yfinance_news.yf.Search",
|
||||
return_value=self._mock_search_with_article(),
|
||||
):
|
||||
result = get_global_news_yfinance("2024-01-15", look_back_days=7)
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "Fed Holds Rates Steady" in result
|
||||
|
||||
def test_no_news_returns_fallback_message(self):
|
||||
"""When no articles are found, a 'no news found' message is returned."""
|
||||
from tradingagents.dataflows.yfinance_news import get_global_news_yfinance
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = []
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.yfinance_news.yf.Search",
|
||||
return_value=mock_search,
|
||||
):
|
||||
result = get_global_news_yfinance("2024-01-15")
|
||||
|
||||
assert "No global news found" in result
|
||||
|
||||
def test_handles_nested_content_structure(self):
|
||||
"""Articles with nested 'content' key are parsed correctly."""
|
||||
from tradingagents.dataflows.yfinance_news import get_global_news_yfinance
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [
|
||||
{
|
||||
"content": {
|
||||
"title": "Inflation Report Beats Expectations",
|
||||
"summary": "CPI data came in below forecasts.",
|
||||
"provider": {"displayName": "Bloomberg"},
|
||||
"canonicalUrl": {"url": "https://bloomberg.com/story"},
|
||||
"pubDate": "2024-01-15T10:00:00Z",
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.yfinance_news.yf.Search",
|
||||
return_value=mock_search,
|
||||
):
|
||||
result = get_global_news_yfinance("2024-01-15", look_back_days=3)
|
||||
|
||||
assert "Inflation Report Beats Expectations" in result
|
||||
|
||||
def test_deduplicates_articles_across_queries(self):
|
||||
"""Duplicate titles from multiple search queries appear only once."""
|
||||
from tradingagents.dataflows.yfinance_news import get_global_news_yfinance
|
||||
|
||||
same_article = {"title": "Market Rally Continues", "publisher": "AP", "link": ""}
|
||||
|
||||
mock_search = MagicMock()
|
||||
mock_search.news = [same_article]
|
||||
|
||||
with patch(
|
||||
"tradingagents.dataflows.yfinance_news.yf.Search",
|
||||
return_value=mock_search,
|
||||
):
|
||||
result = get_global_news_yfinance("2024-01-15", look_back_days=7, limit=5)
|
||||
|
||||
# Title should appear exactly once despite multiple search queries
|
||||
assert result.count("Market Rally Continues") == 1
|
||||
|
|
|
|||
Loading…
Reference in New Issue