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import pandas as pd
import pytest
import TerraFin.data.factory as factory_module
import TerraFin.data.providers.market.market_indicator as market_indicator_module
from TerraFin.data import DataFactory
from TerraFin.data.contracts import HistoryChunk
from TerraFin.data.contracts.dataframes import TimeSeriesDataFrame
def _assert_timeseries_contract(df: TimeSeriesDataFrame) -> None:
assert isinstance(df, TimeSeriesDataFrame)
if df.empty:
# Empty is an accepted fallback contract.
return
assert "time" in df.columns
assert "close" in df.columns
assert pd.api.types.is_datetime64_any_dtype(df["time"])
assert df["time"].is_monotonic_increasing
assert not df["time"].duplicated().any()
def test_timeseries_dataframe_normalizes_index_based_data() -> None:
raw = pd.DataFrame(
{"Close": [1.0, 1.1, 1.2]},
index=["2024-01-03", "2024-01-01", "2024-01-01"], # duplicate time included intentionally
)
df = TimeSeriesDataFrame(raw)
_assert_timeseries_contract(df)
assert list(df.columns) == ["time", "close"]
assert len(df) == 2
def test_chart_output_methods_are_marked() -> None:
chart_methods = {
name
for name, method in inspect.getmembers(DataFactory, predicate=inspect.isfunction)
if getattr(method, "__chart_output__", False)
}
assert chart_methods == {"get", "get_fred_data", "get_economic_data", "get_market_data"}
def test_get_market_data_contract_stubbed(monkeypatch) -> None:
def _stub_market_data(_name: str) -> TimeSeriesDataFrame:
return TimeSeriesDataFrame(pd.DataFrame({"Close": [100.0, 101.5, 103.0]}, index=["2026-01-01", "2026-01-02", "2026-01-03"]))
monkeypatch.setattr(factory_module, "get_market_data", _stub_market_data)
factory = DataFactory()
df = factory.get_market_data("S&P 500")
_assert_timeseries_contract(df)
def test_get_fred_data_contract_stubbed(monkeypatch) -> None:
def _stub_fred_data(_name: str) -> TimeSeriesDataFrame:
return TimeSeriesDataFrame(pd.DataFrame({"Close": [2.5, 2.6, 2.7]}, index=["2026-01-01", "2026-01-02", "2026-01-03"]))
monkeypatch.setattr(factory_module, "get_fred_data", _stub_fred_data)
factory = DataFactory()
df = factory.get_fred_data("T10Y2Y")
_assert_timeseries_contract(df)
def test_get_economic_data_contract_stubbed(monkeypatch) -> None:
def _stub_economic_data(_name: str) -> TimeSeriesDataFrame:
return TimeSeriesDataFrame(pd.DataFrame({"Close": [1.0, 0.9, 0.8]}, index=["2026-01-01", "2026-01-02", "2026-01-03"]))
monkeypatch.setattr(factory_module, "get_economic_indicator", _stub_economic_data)
factory = DataFactory()
df = factory.get_economic_data("Term Spread")
_assert_timeseries_contract(df)
def test_get_recent_history_contract_stubbed(monkeypatch) -> None:
def _stub_recent(_ticker: str, *, period: str = "3y", force_refresh: bool = False) -> HistoryChunk:
_ = force_refresh
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": ["2024-01-01", "2025-01-01", "2026-01-01"],
"close": [100.0, 120.0, 140.0],
}
)
)
return HistoryChunk(
frame=frame,
loaded_start="2024-01-01",
loaded_end="2026-01-01",
requested_period=period,
is_complete=False,
has_older=True,
source_version="test",
)
monkeypatch.setattr(factory_module, "get_yf_recent_history", _stub_recent)
chunk = DataFactory().get_recent_history("AAPL", period="3y")
_assert_timeseries_contract(chunk.frame)
assert chunk.loaded_start == "2024-01-01"
assert chunk.loaded_end == "2026-01-01"
assert chunk.has_older is True
assert chunk.requested_period == "3y"
def test_get_recent_history_force_refresh_propagates_upstream_failure(monkeypatch) -> None:
"""``force_refresh=True`` is the freshness-verification lever — if
the upstream fetch fails the caller must learn about it, not get a
silently-stale fallback."""
def _exploding_recent(_ticker: str, *, period: str = "3y", force_refresh: bool = False) -> HistoryChunk:
_ = period, force_refresh
raise RuntimeError("upstream blew up")
monkeypatch.setattr(factory_module, "get_yf_recent_history", _exploding_recent)
with pytest.raises(RuntimeError, match="upstream blew up"):
DataFactory().get_recent_history("AAPL", period="3y", force_refresh=True)
def test_get_recent_history_default_swallows_upstream_failure(monkeypatch) -> None:
"""Default ``force_refresh=False`` keeps the graceful-degradation
behavior — upstream errors are logged and the factory falls back to
its own ``self.get(name)``-based slice."""
def _exploding_recent(_ticker: str, *, period: str = "3y", force_refresh: bool = False) -> HistoryChunk:
_ = period, force_refresh
raise RuntimeError("upstream blew up")
def _stub_get(_self, _name: str) -> TimeSeriesDataFrame:
return TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.to_datetime(["2024-01-01", "2024-01-02", "2024-01-03"]),
"close": [10.0, 11.0, 12.0],
}
)
)
monkeypatch.setattr(factory_module, "get_yf_recent_history", _exploding_recent)
monkeypatch.setattr(DataFactory, "get", _stub_get)
chunk = DataFactory().get_recent_history("AAPL", period="3y")
# Fallback path returned a chunk rather than raising.
assert chunk.source_version == "factory-fallback"
assert not chunk.frame.empty
def test_get_full_history_backfill_contract_stubbed(monkeypatch) -> None:
def _stub_backfill(_ticker: str, *, loaded_start: str | None = None) -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": ["2021-01-01", "2022-01-01", "2023-01-01"],
"close": [80.0, 90.0, 95.0],
}
)
)
return HistoryChunk(
frame=frame,
loaded_start="2021-01-01",
loaded_end="2026-01-01",
requested_period=None,
is_complete=True,
has_older=False,
source_version="test",
)
monkeypatch.setattr(factory_module, "get_yf_full_history_backfill", _stub_backfill)
chunk = DataFactory().get_full_history_backfill("AAPL", loaded_start="2024-01-01")
_assert_timeseries_contract(chunk.frame)
assert chunk.loaded_start == "2021-01-01"
assert chunk.loaded_end == "2026-01-01"
assert chunk.is_complete is True
def test_get_recent_history_uses_custom_market_indicator_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["Vol Regime"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_recent(_key: str, *, period: str = "3y") -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.date_range("2023-01-01", periods=5, freq="D"),
"close": [10.0, 15.0, 25.0, 45.0, 85.0],
}
),
name="Vol Regime",
chart_meta={"zones": market_indicator_module.VOL_REGIME_ZONES},
)
return HistoryChunk(
frame=frame,
loaded_start="2023-01-01",
loaded_end="2023-01-05",
requested_period=period,
is_complete=False,
has_older=True,
source_version="custom-recent",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_recent_history", _stub_recent)
chunk = DataFactory().get_recent_history("Vol Regime", period="3y")
assert chunk.source_version == "custom-recent"
assert chunk.frame.name == "Vol Regime"
assert chunk.frame.chart_meta["zones"] == market_indicator_module.VOL_REGIME_ZONES
assert chunk.has_older is True
def test_get_full_history_backfill_uses_custom_market_indicator_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["VVIX/VIX Ratio"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_backfill(_key: str, *, loaded_start: str | None = None) -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.date_range("2021-01-01", periods=3, freq="D"),
"close": [4.9, 5.1, 5.3],
}
),
name="VVIX/VIX Ratio",
)
return HistoryChunk(
frame=frame,
loaded_start="2021-01-01",
loaded_end="2026-01-01",
requested_period=None,
is_complete=True,
has_older=False,
source_version="custom-full",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_full_history_backfill", _stub_backfill)
chunk = DataFactory().get_full_history_backfill("VVIX/VIX Ratio", loaded_start="2024-01-01")
assert chunk.source_version == "custom-full"
assert chunk.frame.name == "VVIX/VIX Ratio"
assert chunk.loaded_start == "2021-01-01"
assert chunk.is_complete is True
def test_get_recent_history_uses_fear_greed_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["Fear & Greed"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_recent(_key: str, *, period: str = "3y") -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.date_range("2024-01-01", periods=3, freq="D"),
"close": [25.0, 45.0, 65.0],
}
),
name="Fear & Greed",
)
return HistoryChunk(
frame=frame,
loaded_start="2024-01-01",
loaded_end="2024-01-03",
requested_period=period,
is_complete=False,
has_older=True,
source_version="fear-greed-recent",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_recent_history", _stub_recent)
chunk = DataFactory().get_recent_history("Fear & Greed", period="3y")
assert chunk.source_version == "fear-greed-recent"
assert chunk.frame.name == "Fear & Greed"
assert chunk.has_older is True
def test_get_recent_history_uses_cape_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["CAPE"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_recent(_key: str, *, period: str = "3y") -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.to_datetime(["2024-01-01", "2025-01-01", "2026-01-01"]),
"close": [28.5, 31.2, 33.1],
}
),
name="CAPE",
)
return HistoryChunk(
frame=frame,
loaded_start="2024-01-01",
loaded_end="2026-01-01",
requested_period=period,
is_complete=False,
has_older=True,
source_version="cape-recent",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_recent_history", _stub_recent)
chunk = DataFactory().get_recent_history("CAPE", period="3y")
assert chunk.source_version == "cape-recent"
assert chunk.frame.name == "CAPE"
assert chunk.has_older is True
def test_get_recent_history_uses_net_breadth_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["Net Breadth"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_recent(_key: str, *, period: str = "3y") -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.to_datetime(["2024-01-01", "2024-01-02", "2024-01-03"]),
"close": [-12.0, 4.5, 16.2],
}
),
name="Net Breadth",
)
return HistoryChunk(
frame=frame,
loaded_start="2024-01-01",
loaded_end="2024-01-03",
requested_period=period,
is_complete=False,
has_older=True,
source_version="net-breadth-recent",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_recent_history", _stub_recent)
chunk = DataFactory().get_recent_history("Net Breadth", period="3y")
assert chunk.source_version == "net-breadth-recent"
assert chunk.frame.name == "Net Breadth"
assert chunk.has_older is True
def test_get_recent_history_uses_economic_indicator_for_rrp(monkeypatch) -> None:
def _forbid_recent_history(_ticker: str, *, period: str = "3y") -> HistoryChunk:
_ = period
raise AssertionError("yfinance recent-history loader should not run for economic indicators")
def _stub_economic_indicator(name: str) -> TimeSeriesDataFrame:
assert name == "RRP"
return TimeSeriesDataFrame(pd.DataFrame(
{
"Close": [2.0, 4.0, 6.0, 8.0],
},
index=["2020-01-01", "2022-01-01", "2024-01-01", "2026-01-01"],
))
monkeypatch.setattr(factory_module, "get_yf_recent_history", _forbid_recent_history)
monkeypatch.setattr(factory_module, "get_economic_indicator", _stub_economic_indicator)
chunk = DataFactory().get_recent_history("RRP", period="3y")
assert chunk.frame.name == "RRP"
assert chunk.loaded_start == "2024-01-01"
assert chunk.loaded_end == "2026-01-01"
assert chunk.has_older is True
assert chunk.requested_period == "3y"
assert chunk.frame["close"].tolist() == [6.0, 8.0]
def test_get_full_history_backfill_uses_trailing_forward_pe_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["Trailing-Forward P/E Spread"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_backfill(_key: str, *, loaded_start: str | None = None) -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.to_datetime(["2022-01-01", "2023-01-01", "2024-01-01"]),
"close": [1.1, 0.8, 0.5],
}
),
name="Trailing-Forward P/E Spread",
)
return HistoryChunk(
frame=frame,
loaded_start="2022-01-01",
loaded_end="2024-01-01",
requested_period=None,
is_complete=True,
has_older=False,
source_version="pe-spread-full",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_full_history_backfill", _stub_backfill)
chunk = DataFactory().get_full_history_backfill("Trailing-Forward P/E Spread", loaded_start="2025-01-01")
assert chunk.source_version == "pe-spread-full"
assert chunk.frame.name == "Trailing-Forward P/E Spread"
assert chunk.is_complete is True
def test_get_full_history_backfill_uses_economic_indicator_for_rrp(monkeypatch) -> None:
def _forbid_full_history(_ticker: str, *, loaded_start: str | None = None) -> HistoryChunk:
_ = loaded_start
raise AssertionError("yfinance full-history loader should not run for economic indicators")
def _stub_economic_indicator(name: str) -> TimeSeriesDataFrame:
assert name == "RRP"
return TimeSeriesDataFrame(pd.DataFrame(
{
"Close": [2.0, 4.0, 6.0, 8.0],
},
index=["2020-01-01", "2022-01-01", "2024-01-01", "2026-01-01"],
))
monkeypatch.setattr(factory_module, "get_yf_full_history_backfill", _forbid_full_history)
monkeypatch.setattr(factory_module, "get_economic_indicator", _stub_economic_indicator)
chunk = DataFactory().get_full_history_backfill("RRP", loaded_start="2024-01-01")
assert chunk.frame.name == "RRP"
assert chunk.loaded_start == "2020-01-01"
assert chunk.loaded_end == "2026-01-01"
assert chunk.is_complete is True
assert chunk.frame["close"].tolist() == [2.0, 4.0]
def test_get_full_history_backfill_uses_net_breadth_progressive_hook(monkeypatch) -> None:
indicator = factory_module.MARKET_INDICATOR_REGISTRY["Net Breadth"]
def _forbid_fallback(_key: str):
raise AssertionError("fallback market-data loader should not run")
def _stub_backfill(_key: str, *, loaded_start: str | None = None) -> HistoryChunk:
frame = TimeSeriesDataFrame(
pd.DataFrame(
{
"time": pd.to_datetime(["2023-01-01", "2023-01-02", "2023-01-03"]),
"close": [-18.0, -6.0, 9.0],
}
),
name="Net Breadth",
)
return HistoryChunk(
frame=frame,
loaded_start="2023-01-01",
loaded_end="2023-01-03",
requested_period=None,
is_complete=True,
has_older=False,
source_version="net-breadth-full",
)
monkeypatch.setattr(indicator, "get_data", _forbid_fallback)
monkeypatch.setattr(indicator, "get_full_history_backfill", _stub_backfill)
chunk = DataFactory().get_full_history_backfill("Net Breadth", loaded_start="2025-01-01")
assert chunk.source_version == "net-breadth-full"
assert chunk.frame.name == "Net Breadth"
assert chunk.is_complete is True
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