feat: add portfolio optimization and congress tracking (TDD)
Portfolio optimization (3 endpoints): - POST /portfolio/optimize - HRP optimal weights via scipy clustering - POST /portfolio/correlation - pairwise correlation matrix - POST /portfolio/risk-parity - inverse-volatility risk parity weights Congress tracking (2 endpoints): - GET /regulators/congress/trades - congress member stock trades - GET /regulators/congress/bills?query= - search congress bills Implementation: - portfolio_service.py: HRP with scipy fallback to inverse-vol - congress_service.py: multi-provider fallback pattern - 51 new tests (14 portfolio unit, 20 portfolio route, 12 congress unit, 7 congress route) - All 312 tests passing
This commit is contained in:
Yaojia Wang
68
congress_service.py
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68
congress_service.py
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@@ -0,0 +1,68 @@
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"""Congress trading data: member trades and bill search."""
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import asyncio
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import logging
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from typing import Any
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from openbb import obb
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from obb_utils import to_list
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logger = logging.getLogger(__name__)
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async def _try_obb_call(fn, *args, **kwargs) -> list[dict[str, Any]] | None:
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"""Attempt a single OBB call and return to_list result, or None on failure."""
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try:
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result = await asyncio.to_thread(fn, *args, **kwargs)
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return to_list(result)
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except Exception as exc:
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logger.debug("OBB call failed: %s", exc)
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return None
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def _get_congress_fn():
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"""Resolve the congress trading OBB function safely."""
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try:
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return obb.regulators.government_us.congress_trading
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except AttributeError:
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logger.debug("obb.regulators.government_us.congress_trading not available")
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return None
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async def get_congress_trades() -> list[dict[str, Any]]:
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"""Get recent US congress member stock trades.
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Returns an empty list if the data provider is unavailable.
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"""
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fn = _get_congress_fn()
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if fn is None:
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return []
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providers = ["quiverquant", "fmp"]
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for provider in providers:
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data = await _try_obb_call(fn, provider=provider)
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if data is not None:
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return data
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logger.warning("All congress trades providers failed")
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return []
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async def search_congress_bills(query: str) -> list[dict[str, Any]]:
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"""Search US congress bills by keyword.
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Returns an empty list if the data provider is unavailable.
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"""
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fn = _get_congress_fn()
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if fn is None:
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return []
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providers = ["quiverquant", "fmp"]
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for provider in providers:
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data = await _try_obb_call(fn, query, provider=provider)
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if data is not None:
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return data
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logger.warning("All congress bills providers failed for query: %s", query)
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return []
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2
main.py
2
main.py
@@ -37,6 +37,7 @@ from routes_sentiment import router as sentiment_router # noqa: E402
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from routes_shorts import router as shorts_router # noqa: E402
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from routes_surveys import router as surveys_router # noqa: E402
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from routes_technical import router as technical_router # noqa: E402
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from routes_portfolio import router as portfolio_router # noqa: E402
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logging.basicConfig(
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level=settings.log_level.upper(),
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@@ -81,6 +82,7 @@ app.include_router(fixed_income_router)
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app.include_router(economy_router)
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app.include_router(surveys_router)
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app.include_router(regulators_router)
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app.include_router(portfolio_router)
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@app.get("/health", response_model=dict[str, str])
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222
portfolio_service.py
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222
portfolio_service.py
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"""Portfolio optimization: HRP, correlation matrix, risk parity."""
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import asyncio
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import logging
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from typing import Any
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import numpy as np
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import pandas as pd
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from obb_utils import fetch_historical
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logger = logging.getLogger(__name__)
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async def fetch_historical_prices(symbols: list[str], days: int = 365) -> pd.DataFrame:
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"""Fetch closing prices for multiple symbols and return as a DataFrame.
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Columns are symbol names; rows are dates. Symbols with no data are skipped.
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"""
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tasks = [fetch_historical(sym, days=days) for sym in symbols]
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results = await asyncio.gather(*tasks)
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price_series: dict[str, pd.Series] = {}
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for sym, result in zip(symbols, results):
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if result is None or result.results is None:
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logger.warning("No historical data for %s, skipping", sym)
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continue
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rows = result.results
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if not rows:
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continue
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dates = []
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closes = []
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for row in rows:
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d = getattr(row, "date", None)
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c = getattr(row, "close", None)
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if d is not None and c is not None:
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dates.append(str(d))
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closes.append(float(c))
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if dates:
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price_series[sym] = pd.Series(closes, index=dates)
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if not price_series:
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return pd.DataFrame()
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df = pd.DataFrame(price_series)
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df = df.dropna(how="all")
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return df
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def _compute_returns(prices: pd.DataFrame) -> pd.DataFrame:
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"""Compute daily log returns from a price DataFrame."""
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return prices.pct_change().dropna()
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def _inverse_volatility_weights(returns: pd.DataFrame) -> dict[str, float]:
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"""Compute inverse-volatility weights."""
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vols = returns.std()
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inv_vols = 1.0 / vols
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weights = inv_vols / inv_vols.sum()
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return {sym: float(w) for sym, w in weights.items()}
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def _hrp_weights(returns: pd.DataFrame) -> dict[str, float]:
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"""Compute Hierarchical Risk Parity weights via scipy clustering.
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Falls back to inverse-volatility if scipy is unavailable.
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"""
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symbols = list(returns.columns)
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n = len(symbols)
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if n == 1:
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return {symbols[0]: 1.0}
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try:
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from scipy.cluster.hierarchy import linkage, leaves_list
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from scipy.spatial.distance import squareform
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corr = returns.corr().fillna(0).values
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# Convert correlation to distance: d = sqrt(0.5 * (1 - corr))
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dist = np.sqrt(np.clip(0.5 * (1 - corr), 0, 1))
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np.fill_diagonal(dist, 0.0)
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condensed = squareform(dist)
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link = linkage(condensed, method="single")
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order = leaves_list(link)
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sorted_symbols = [symbols[i] for i in order]
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except ImportError:
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logger.warning("scipy not available; using inverse-volatility for HRP")
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return _inverse_volatility_weights(returns)
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cov = returns.cov().values
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def _bisect_weights(items: list[str]) -> dict[str, float]:
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if len(items) == 1:
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return {items[0]: 1.0}
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mid = len(items) // 2
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left_items = items[:mid]
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right_items = items[mid:]
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left_idx = [sorted_symbols.index(s) for s in left_items]
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right_idx = [sorted_symbols.index(s) for s in right_items]
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def _cluster_var(idx: list[int]) -> float:
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sub_cov = cov[np.ix_(idx, idx)]
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w = np.ones(len(idx)) / len(idx)
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return float(w @ sub_cov @ w)
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v_left = _cluster_var(left_idx)
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v_right = _cluster_var(right_idx)
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total = v_left + v_right
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alpha = 1.0 - v_left / total if total > 0 else 0.5
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w_left = _bisect_weights(left_items)
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w_right = _bisect_weights(right_items)
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result = {}
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for sym, w in w_left.items():
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result[sym] = w * (1.0 - alpha)
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for sym, w in w_right.items():
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result[sym] = w * alpha
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return result
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raw = _bisect_weights(sorted_symbols)
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total = sum(raw.values())
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return {sym: float(w / total) for sym, w in raw.items()}
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async def optimize_hrp(symbols: list[str], days: int = 365) -> dict[str, Any]:
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"""Compute Hierarchical Risk Parity portfolio weights.
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Args:
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symbols: List of ticker symbols (1-50).
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days: Number of historical days to use.
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Returns:
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Dict with keys ``weights`` (symbol -> float) and ``method``.
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Raises:
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ValueError: If symbols is empty or no price data is available.
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"""
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if not symbols:
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raise ValueError("symbols must not be empty")
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prices = await fetch_historical_prices(symbols, days=days)
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if prices.empty:
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raise ValueError("No price data available for the given symbols")
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returns = _compute_returns(prices)
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weights = _hrp_weights(returns)
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return {"weights": weights, "method": "hrp"}
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async def compute_correlation(
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symbols: list[str], days: int = 365
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) -> dict[str, Any]:
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"""Compute correlation matrix for a list of symbols.
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Args:
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symbols: List of ticker symbols (1-50).
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days: Number of historical days to use.
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Returns:
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Dict with keys ``symbols`` (list) and ``matrix`` (list of lists).
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Raises:
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ValueError: If symbols is empty or no price data is available.
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"""
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if not symbols:
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raise ValueError("symbols must not be empty")
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prices = await fetch_historical_prices(symbols, days=days)
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if prices.empty:
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raise ValueError("No price data available for the given symbols")
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returns = _compute_returns(prices)
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available = list(returns.columns)
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corr = returns.corr().fillna(0)
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matrix = corr.values.tolist()
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return {"symbols": available, "matrix": matrix}
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async def compute_risk_parity(
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symbols: list[str], days: int = 365
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) -> dict[str, Any]:
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"""Compute equal risk contribution (inverse-volatility) weights.
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Args:
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symbols: List of ticker symbols (1-50).
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days: Number of historical days to use.
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Returns:
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Dict with keys ``weights``, ``risk_contributions``, and ``method``.
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Raises:
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ValueError: If symbols is empty or no price data is available.
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"""
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if not symbols:
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raise ValueError("symbols must not be empty")
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prices = await fetch_historical_prices(symbols, days=days)
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if prices.empty:
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raise ValueError("No price data available for the given symbols")
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returns = _compute_returns(prices)
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weights = _inverse_volatility_weights(returns)
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# Risk contributions: w_i * sigma_i / sum(w_j * sigma_j)
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vols = returns.std()
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weighted_risk = {sym: weights[sym] * float(vols[sym]) for sym in weights}
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total_risk = sum(weighted_risk.values())
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if total_risk > 0:
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risk_contributions = {sym: v / total_risk for sym, v in weighted_risk.items()}
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else:
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n = len(weights)
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risk_contributions = {sym: 1.0 / n for sym in weights}
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return {
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"weights": weights,
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"risk_contributions": risk_contributions,
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"method": "risk_parity",
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}
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54
routes_portfolio.py
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54
routes_portfolio.py
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@@ -0,0 +1,54 @@
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"""Routes for portfolio optimization (HRP, correlation, risk parity)."""
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel, Field
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from models import ApiResponse
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from route_utils import safe
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import portfolio_service
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router = APIRouter(prefix="/api/v1/portfolio")
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class PortfolioOptimizeRequest(BaseModel):
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symbols: list[str] = Field(..., min_length=1, max_length=50)
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days: int = Field(default=365, ge=1, le=3650)
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@router.post("/optimize", response_model=ApiResponse)
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@safe
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async def portfolio_optimize(request: PortfolioOptimizeRequest):
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"""Compute HRP optimal weights for a list of symbols."""
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try:
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result = await portfolio_service.optimize_hrp(
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request.symbols, days=request.days
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)
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except ValueError as exc:
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raise HTTPException(status_code=400, detail=str(exc))
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return ApiResponse(data=result)
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@router.post("/correlation", response_model=ApiResponse)
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@safe
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async def portfolio_correlation(request: PortfolioOptimizeRequest):
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"""Compute correlation matrix for a list of symbols."""
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try:
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result = await portfolio_service.compute_correlation(
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request.symbols, days=request.days
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)
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except ValueError as exc:
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raise HTTPException(status_code=400, detail=str(exc))
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return ApiResponse(data=result)
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@router.post("/risk-parity", response_model=ApiResponse)
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@safe
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async def portfolio_risk_parity(request: PortfolioOptimizeRequest):
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"""Compute equal risk contribution weights for a list of symbols."""
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try:
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result = await portfolio_service.compute_risk_parity(
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request.symbols, days=request.days
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)
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except ValueError as exc:
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raise HTTPException(status_code=400, detail=str(exc))
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return ApiResponse(data=result)
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@@ -1,10 +1,11 @@
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"""Routes for regulatory data (CFTC, SEC)."""
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"""Routes for regulatory data (CFTC, SEC, Congress)."""
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from fastapi import APIRouter, Path, Query
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from models import ApiResponse
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from route_utils import safe, validate_symbol
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import regulators_service
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import congress_service
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router = APIRouter(prefix="/api/v1/regulators")
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@@ -49,3 +50,22 @@ async def sec_cik_map(symbol: str = Path(..., min_length=1, max_length=20)):
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symbol = validate_symbol(symbol)
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data = await regulators_service.get_cik_map(symbol)
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return ApiResponse(data=data)
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# --- Congress Trading ---
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@router.get("/congress/trades", response_model=ApiResponse)
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@safe
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async def congress_trades():
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"""Recent US congress member stock trades."""
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data = await congress_service.get_congress_trades()
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return ApiResponse(data=data)
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@router.get("/congress/bills", response_model=ApiResponse)
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@safe
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async def congress_bills(query: str = Query(..., min_length=1, max_length=200)):
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"""Search US congress bills by keyword."""
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data = await congress_service.search_congress_bills(query)
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return ApiResponse(data=data)
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187
tests/test_congress_service.py
Normal file
187
tests/test_congress_service.py
Normal file
@@ -0,0 +1,187 @@
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"""Tests for congress trading service (TDD - RED phase first)."""
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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# --- get_congress_trades ---
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@pytest.mark.asyncio
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async def test_get_congress_trades_happy_path():
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"""Returns list of trade dicts when OBB call succeeds."""
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expected = [
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{
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"representative": "Nancy Pelosi",
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"ticker": "NVDA",
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"transaction_date": "2024-01-15",
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"transaction_type": "Purchase",
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"amount": "$1,000,001-$5,000,000",
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}
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]
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import congress_service
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mock_fn = MagicMock()
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with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
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patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=expected):
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result = await congress_service.get_congress_trades()
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assert isinstance(result, list)
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assert len(result) == 1
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assert result[0]["representative"] == "Nancy Pelosi"
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@pytest.mark.asyncio
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async def test_get_congress_trades_returns_empty_when_fn_not_available():
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"""Returns empty list when OBB congress function is not available."""
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import congress_service
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with patch.object(congress_service, "_get_congress_fn", return_value=None):
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result = await congress_service.get_congress_trades()
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assert result == []
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@pytest.mark.asyncio
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async def test_get_congress_trades_returns_empty_on_all_provider_failures():
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"""Returns empty list when all providers fail (_try_obb_call returns None)."""
|
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import congress_service
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mock_fn = MagicMock()
|
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with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
|
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patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=None):
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result = await congress_service.get_congress_trades()
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assert result == []
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@pytest.mark.asyncio
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async def test_get_congress_trades_empty_list_result():
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"""Returns empty list when _try_obb_call returns empty list."""
|
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import congress_service
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mock_fn = MagicMock()
|
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with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
|
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patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=[]):
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result = await congress_service.get_congress_trades()
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assert result == []
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# --- _get_congress_fn ---
|
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|
||||
def test_get_congress_fn_returns_none_when_attribute_missing():
|
||||
"""Returns None gracefully when obb.regulators.government_us is absent."""
|
||||
import congress_service
|
||||
|
||||
mock_obb = MagicMock(spec=[]) # spec with no attributes
|
||||
with patch.object(congress_service, "obb", mock_obb):
|
||||
result = congress_service._get_congress_fn()
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
def test_get_congress_fn_returns_callable_when_available():
|
||||
"""Returns the congress_trading callable when attribute exists."""
|
||||
import congress_service
|
||||
|
||||
mock_fn = MagicMock()
|
||||
mock_obb = MagicMock()
|
||||
mock_obb.regulators.government_us.congress_trading = mock_fn
|
||||
|
||||
with patch.object(congress_service, "obb", mock_obb):
|
||||
result = congress_service._get_congress_fn()
|
||||
|
||||
assert result is mock_fn
|
||||
|
||||
|
||||
# --- _try_obb_call ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_try_obb_call_returns_list_on_success():
|
||||
"""_try_obb_call converts OBBject result to list via to_list."""
|
||||
import congress_service
|
||||
|
||||
mock_result = MagicMock()
|
||||
expected = [{"ticker": "AAPL"}]
|
||||
|
||||
with patch.object(congress_service, "to_list", return_value=expected), \
|
||||
patch("congress_service.asyncio.to_thread", new_callable=AsyncMock, return_value=mock_result):
|
||||
result = await congress_service._try_obb_call(MagicMock())
|
||||
|
||||
assert result == expected
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_try_obb_call_returns_none_on_exception():
|
||||
"""_try_obb_call returns None when asyncio.to_thread raises."""
|
||||
import congress_service
|
||||
|
||||
with patch("congress_service.asyncio.to_thread", new_callable=AsyncMock, side_effect=Exception("fail")):
|
||||
result = await congress_service._try_obb_call(MagicMock())
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
# --- search_congress_bills ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_congress_bills_happy_path():
|
||||
"""Returns list of bill dicts when OBB call succeeds."""
|
||||
expected = [
|
||||
{"title": "Infrastructure Investment and Jobs Act", "bill_id": "HR3684"},
|
||||
{"title": "Inflation Reduction Act", "bill_id": "HR5376"},
|
||||
]
|
||||
|
||||
import congress_service
|
||||
|
||||
mock_fn = MagicMock()
|
||||
with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
|
||||
patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=expected):
|
||||
result = await congress_service.search_congress_bills("infrastructure")
|
||||
|
||||
assert isinstance(result, list)
|
||||
assert len(result) == 2
|
||||
assert result[0]["bill_id"] == "HR3684"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_congress_bills_returns_empty_when_fn_not_available():
|
||||
"""Returns empty list when OBB function is not available."""
|
||||
import congress_service
|
||||
|
||||
with patch.object(congress_service, "_get_congress_fn", return_value=None):
|
||||
result = await congress_service.search_congress_bills("taxes")
|
||||
|
||||
assert result == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_congress_bills_returns_empty_on_failure():
|
||||
"""Returns empty list when all providers fail."""
|
||||
import congress_service
|
||||
|
||||
mock_fn = MagicMock()
|
||||
with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
|
||||
patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=None):
|
||||
result = await congress_service.search_congress_bills("taxes")
|
||||
|
||||
assert result == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_congress_bills_empty_results():
|
||||
"""Returns empty list when _try_obb_call returns empty list."""
|
||||
import congress_service
|
||||
|
||||
mock_fn = MagicMock()
|
||||
with patch.object(congress_service, "_get_congress_fn", return_value=mock_fn), \
|
||||
patch.object(congress_service, "_try_obb_call", new_callable=AsyncMock, return_value=[]):
|
||||
result = await congress_service.search_congress_bills("nonexistent")
|
||||
|
||||
assert result == []
|
||||
263
tests/test_portfolio_service.py
Normal file
263
tests/test_portfolio_service.py
Normal file
@@ -0,0 +1,263 @@
|
||||
"""Tests for portfolio optimization service (TDD - RED phase first)."""
|
||||
|
||||
from unittest.mock import AsyncMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
# --- HRP Optimization ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_hrp_optimize_happy_path(mock_fetch):
|
||||
"""HRP returns weights that sum to ~1.0 for valid symbols."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{
|
||||
"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0],
|
||||
"MSFT": [300.0, 302.0, 298.0, 305.0, 307.0],
|
||||
"GOOGL": [2800.0, 2820.0, 2790.0, 2830.0, 2850.0],
|
||||
}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.optimize_hrp(
|
||||
["AAPL", "MSFT", "GOOGL"], days=365
|
||||
)
|
||||
|
||||
assert result["method"] == "hrp"
|
||||
assert set(result["weights"].keys()) == {"AAPL", "MSFT", "GOOGL"}
|
||||
total = sum(result["weights"].values())
|
||||
assert abs(total - 1.0) < 0.01
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_hrp_optimize_single_symbol(mock_fetch):
|
||||
"""Single symbol gets weight of 1.0."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0]}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.optimize_hrp(["AAPL"], days=365)
|
||||
|
||||
assert result["weights"]["AAPL"] == pytest.approx(1.0, abs=0.01)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_hrp_optimize_no_data_raises(mock_fetch):
|
||||
"""Raises ValueError when no price data is available."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame()
|
||||
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="No price data"):
|
||||
await portfolio_service.optimize_hrp(["AAPL", "MSFT"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_hrp_optimize_empty_symbols_raises():
|
||||
"""Raises ValueError for empty symbol list."""
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="symbols"):
|
||||
await portfolio_service.optimize_hrp([], days=365)
|
||||
|
||||
|
||||
# --- Correlation Matrix ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_correlation_matrix_happy_path(mock_fetch):
|
||||
"""Correlation matrix has 1.0 on diagonal and valid shape."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{
|
||||
"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0],
|
||||
"MSFT": [300.0, 302.0, 298.0, 305.0, 307.0],
|
||||
"GOOGL": [2800.0, 2820.0, 2790.0, 2830.0, 2850.0],
|
||||
}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.compute_correlation(
|
||||
["AAPL", "MSFT", "GOOGL"], days=365
|
||||
)
|
||||
|
||||
assert result["symbols"] == ["AAPL", "MSFT", "GOOGL"]
|
||||
matrix = result["matrix"]
|
||||
assert len(matrix) == 3
|
||||
assert len(matrix[0]) == 3
|
||||
# Diagonal should be 1.0
|
||||
for i in range(3):
|
||||
assert abs(matrix[i][i] - 1.0) < 0.01
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_correlation_matrix_two_symbols(mock_fetch):
|
||||
"""Two-symbol correlation is symmetric."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{
|
||||
"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0],
|
||||
"MSFT": [300.0, 302.0, 298.0, 305.0, 307.0],
|
||||
}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.compute_correlation(["AAPL", "MSFT"], days=365)
|
||||
|
||||
matrix = result["matrix"]
|
||||
# Symmetric: matrix[0][1] == matrix[1][0]
|
||||
assert abs(matrix[0][1] - matrix[1][0]) < 0.001
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_correlation_no_data_raises(mock_fetch):
|
||||
"""Raises ValueError when no data is returned."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame()
|
||||
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="No price data"):
|
||||
await portfolio_service.compute_correlation(["AAPL", "MSFT"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_correlation_empty_symbols_raises():
|
||||
"""Raises ValueError for empty symbol list."""
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="symbols"):
|
||||
await portfolio_service.compute_correlation([], days=365)
|
||||
|
||||
|
||||
# --- Risk Parity ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_risk_parity_happy_path(mock_fetch):
|
||||
"""Risk parity returns weights and risk_contributions summing to ~1.0."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{
|
||||
"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0],
|
||||
"MSFT": [300.0, 302.0, 298.0, 305.0, 307.0],
|
||||
"GOOGL": [2800.0, 2820.0, 2790.0, 2830.0, 2850.0],
|
||||
}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.compute_risk_parity(
|
||||
["AAPL", "MSFT", "GOOGL"], days=365
|
||||
)
|
||||
|
||||
assert result["method"] == "risk_parity"
|
||||
assert set(result["weights"].keys()) == {"AAPL", "MSFT", "GOOGL"}
|
||||
assert set(result["risk_contributions"].keys()) == {"AAPL", "MSFT", "GOOGL"}
|
||||
total_w = sum(result["weights"].values())
|
||||
assert abs(total_w - 1.0) < 0.01
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_risk_parity_single_symbol(mock_fetch):
|
||||
"""Single symbol gets weight 1.0 and risk_contribution 1.0."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame(
|
||||
{"AAPL": [150.0, 151.0, 149.0, 152.0, 153.0]}
|
||||
)
|
||||
|
||||
import portfolio_service
|
||||
|
||||
result = await portfolio_service.compute_risk_parity(["AAPL"], days=365)
|
||||
|
||||
assert result["weights"]["AAPL"] == pytest.approx(1.0, abs=0.01)
|
||||
assert result["risk_contributions"]["AAPL"] == pytest.approx(1.0, abs=0.01)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical_prices", new_callable=AsyncMock)
|
||||
async def test_risk_parity_no_data_raises(mock_fetch):
|
||||
"""Raises ValueError when no price data is available."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch.return_value = pd.DataFrame()
|
||||
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="No price data"):
|
||||
await portfolio_service.compute_risk_parity(["AAPL", "MSFT"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_risk_parity_empty_symbols_raises():
|
||||
"""Raises ValueError for empty symbol list."""
|
||||
import portfolio_service
|
||||
|
||||
with pytest.raises(ValueError, match="symbols"):
|
||||
await portfolio_service.compute_risk_parity([], days=365)
|
||||
|
||||
|
||||
# --- fetch_historical_prices helper ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical")
|
||||
async def test_fetch_historical_prices_returns_dataframe(mock_fetch_hist):
|
||||
"""fetch_historical_prices assembles a price DataFrame from OBBject results."""
|
||||
import pandas as pd
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
mock_result = MagicMock()
|
||||
mock_result.results = [
|
||||
MagicMock(date="2024-01-01", close=150.0),
|
||||
MagicMock(date="2024-01-02", close=151.0),
|
||||
]
|
||||
mock_fetch_hist.return_value = mock_result
|
||||
|
||||
import portfolio_service
|
||||
|
||||
df = await portfolio_service.fetch_historical_prices(["AAPL"], days=30)
|
||||
|
||||
assert isinstance(df, pd.DataFrame)
|
||||
assert "AAPL" in df.columns
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("portfolio_service.fetch_historical")
|
||||
async def test_fetch_historical_prices_skips_none(mock_fetch_hist):
|
||||
"""fetch_historical_prices returns empty DataFrame when all fetches fail."""
|
||||
import pandas as pd
|
||||
|
||||
mock_fetch_hist.return_value = None
|
||||
|
||||
import portfolio_service
|
||||
|
||||
df = await portfolio_service.fetch_historical_prices(["AAPL", "MSFT"], days=30)
|
||||
|
||||
assert isinstance(df, pd.DataFrame)
|
||||
assert df.empty
|
||||
98
tests/test_routes_congress.py
Normal file
98
tests/test_routes_congress.py
Normal file
@@ -0,0 +1,98 @@
|
||||
"""Tests for congress trading routes (TDD - RED phase first)."""
|
||||
|
||||
from unittest.mock import patch, AsyncMock
|
||||
|
||||
import pytest
|
||||
from httpx import AsyncClient, ASGITransport
|
||||
|
||||
from main import app
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def client():
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url="http://test") as c:
|
||||
yield c
|
||||
|
||||
|
||||
# --- GET /api/v1/regulators/congress/trades ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.get_congress_trades", new_callable=AsyncMock)
|
||||
async def test_congress_trades_happy_path(mock_fn, client):
|
||||
mock_fn.return_value = [
|
||||
{
|
||||
"representative": "Nancy Pelosi",
|
||||
"ticker": "NVDA",
|
||||
"transaction_date": "2024-01-15",
|
||||
"transaction_type": "Purchase",
|
||||
"amount": "$1,000,001-$5,000,000",
|
||||
}
|
||||
]
|
||||
resp = await client.get("/api/v1/regulators/congress/trades")
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["success"] is True
|
||||
assert len(data["data"]) == 1
|
||||
assert data["data"][0]["representative"] == "Nancy Pelosi"
|
||||
mock_fn.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.get_congress_trades", new_callable=AsyncMock)
|
||||
async def test_congress_trades_empty(mock_fn, client):
|
||||
mock_fn.return_value = []
|
||||
resp = await client.get("/api/v1/regulators/congress/trades")
|
||||
assert resp.status_code == 200
|
||||
assert resp.json()["data"] == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.get_congress_trades", new_callable=AsyncMock)
|
||||
async def test_congress_trades_service_error_returns_502(mock_fn, client):
|
||||
mock_fn.side_effect = RuntimeError("Data provider unavailable")
|
||||
resp = await client.get("/api/v1/regulators/congress/trades")
|
||||
assert resp.status_code == 502
|
||||
|
||||
|
||||
# --- GET /api/v1/regulators/congress/bills ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.search_congress_bills", new_callable=AsyncMock)
|
||||
async def test_congress_bills_happy_path(mock_fn, client):
|
||||
mock_fn.return_value = [
|
||||
{"title": "Infrastructure Investment and Jobs Act", "bill_id": "HR3684"},
|
||||
{"title": "Inflation Reduction Act", "bill_id": "HR5376"},
|
||||
]
|
||||
resp = await client.get("/api/v1/regulators/congress/bills?query=infrastructure")
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["success"] is True
|
||||
assert len(data["data"]) == 2
|
||||
assert data["data"][0]["bill_id"] == "HR3684"
|
||||
mock_fn.assert_called_once_with("infrastructure")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_congress_bills_missing_query(client):
|
||||
resp = await client.get("/api/v1/regulators/congress/bills")
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.search_congress_bills", new_callable=AsyncMock)
|
||||
async def test_congress_bills_empty(mock_fn, client):
|
||||
mock_fn.return_value = []
|
||||
resp = await client.get("/api/v1/regulators/congress/bills?query=nonexistent")
|
||||
assert resp.status_code == 200
|
||||
assert resp.json()["data"] == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_regulators.congress_service.search_congress_bills", new_callable=AsyncMock)
|
||||
async def test_congress_bills_service_error_returns_502(mock_fn, client):
|
||||
mock_fn.side_effect = RuntimeError("Congress API unavailable")
|
||||
resp = await client.get("/api/v1/regulators/congress/bills?query=tax")
|
||||
assert resp.status_code == 502
|
||||
225
tests/test_routes_portfolio.py
Normal file
225
tests/test_routes_portfolio.py
Normal file
@@ -0,0 +1,225 @@
|
||||
"""Tests for portfolio optimization routes (TDD - RED phase first)."""
|
||||
|
||||
from unittest.mock import patch, AsyncMock
|
||||
|
||||
import pytest
|
||||
from httpx import AsyncClient, ASGITransport
|
||||
|
||||
from main import app
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def client():
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url="http://test") as c:
|
||||
yield c
|
||||
|
||||
|
||||
# --- POST /api/v1/portfolio/optimize ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.optimize_hrp", new_callable=AsyncMock)
|
||||
async def test_portfolio_optimize_happy_path(mock_fn, client):
|
||||
mock_fn.return_value = {
|
||||
"weights": {"AAPL": 0.35, "MSFT": 0.32, "GOOGL": 0.33},
|
||||
"method": "hrp",
|
||||
}
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize",
|
||||
json={"symbols": ["AAPL", "MSFT", "GOOGL"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["success"] is True
|
||||
assert data["data"]["method"] == "hrp"
|
||||
assert "AAPL" in data["data"]["weights"]
|
||||
mock_fn.assert_called_once_with(["AAPL", "MSFT", "GOOGL"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_optimize_missing_symbols(client):
|
||||
resp = await client.post("/api/v1/portfolio/optimize", json={"days": 365})
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_optimize_empty_symbols(client):
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize", json={"symbols": [], "days": 365}
|
||||
)
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_optimize_too_many_symbols(client):
|
||||
symbols = [f"SYM{i}" for i in range(51)]
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize", json={"symbols": symbols, "days": 365}
|
||||
)
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.optimize_hrp", new_callable=AsyncMock)
|
||||
async def test_portfolio_optimize_service_error_returns_502(mock_fn, client):
|
||||
mock_fn.side_effect = RuntimeError("Computation failed")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 502
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.optimize_hrp", new_callable=AsyncMock)
|
||||
async def test_portfolio_optimize_value_error_returns_400(mock_fn, client):
|
||||
mock_fn.side_effect = ValueError("No price data available")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 400
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.optimize_hrp", new_callable=AsyncMock)
|
||||
async def test_portfolio_optimize_default_days(mock_fn, client):
|
||||
mock_fn.return_value = {"weights": {"AAPL": 1.0}, "method": "hrp"}
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/optimize", json={"symbols": ["AAPL"]}
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
mock_fn.assert_called_once_with(["AAPL"], days=365)
|
||||
|
||||
|
||||
# --- POST /api/v1/portfolio/correlation ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_correlation", new_callable=AsyncMock)
|
||||
async def test_portfolio_correlation_happy_path(mock_fn, client):
|
||||
mock_fn.return_value = {
|
||||
"symbols": ["AAPL", "MSFT"],
|
||||
"matrix": [[1.0, 0.85], [0.85, 1.0]],
|
||||
}
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/correlation",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["success"] is True
|
||||
assert data["data"]["symbols"] == ["AAPL", "MSFT"]
|
||||
assert data["data"]["matrix"][0][0] == pytest.approx(1.0)
|
||||
mock_fn.assert_called_once_with(["AAPL", "MSFT"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_correlation_missing_symbols(client):
|
||||
resp = await client.post("/api/v1/portfolio/correlation", json={"days": 365})
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_correlation_empty_symbols(client):
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/correlation", json={"symbols": [], "days": 365}
|
||||
)
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_correlation", new_callable=AsyncMock)
|
||||
async def test_portfolio_correlation_service_error_returns_502(mock_fn, client):
|
||||
mock_fn.side_effect = RuntimeError("Failed")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/correlation",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 502
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_correlation", new_callable=AsyncMock)
|
||||
async def test_portfolio_correlation_value_error_returns_400(mock_fn, client):
|
||||
mock_fn.side_effect = ValueError("No price data available")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/correlation",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 400
|
||||
|
||||
|
||||
# --- POST /api/v1/portfolio/risk-parity ---
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_risk_parity", new_callable=AsyncMock)
|
||||
async def test_portfolio_risk_parity_happy_path(mock_fn, client):
|
||||
mock_fn.return_value = {
|
||||
"weights": {"AAPL": 0.35, "MSFT": 0.33, "GOOGL": 0.32},
|
||||
"risk_contributions": {"AAPL": 0.34, "MSFT": 0.33, "GOOGL": 0.33},
|
||||
"method": "risk_parity",
|
||||
}
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/risk-parity",
|
||||
json={"symbols": ["AAPL", "MSFT", "GOOGL"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
data = resp.json()
|
||||
assert data["success"] is True
|
||||
assert data["data"]["method"] == "risk_parity"
|
||||
assert "risk_contributions" in data["data"]
|
||||
mock_fn.assert_called_once_with(["AAPL", "MSFT", "GOOGL"], days=365)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_risk_parity_missing_symbols(client):
|
||||
resp = await client.post("/api/v1/portfolio/risk-parity", json={"days": 365})
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_portfolio_risk_parity_empty_symbols(client):
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/risk-parity", json={"symbols": [], "days": 365}
|
||||
)
|
||||
assert resp.status_code == 422
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_risk_parity", new_callable=AsyncMock)
|
||||
async def test_portfolio_risk_parity_service_error_returns_502(mock_fn, client):
|
||||
mock_fn.side_effect = RuntimeError("Failed")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/risk-parity",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 502
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_risk_parity", new_callable=AsyncMock)
|
||||
async def test_portfolio_risk_parity_value_error_returns_400(mock_fn, client):
|
||||
mock_fn.side_effect = ValueError("No price data available")
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/risk-parity",
|
||||
json={"symbols": ["AAPL", "MSFT"], "days": 365},
|
||||
)
|
||||
assert resp.status_code == 400
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch("routes_portfolio.portfolio_service.compute_risk_parity", new_callable=AsyncMock)
|
||||
async def test_portfolio_risk_parity_default_days(mock_fn, client):
|
||||
mock_fn.return_value = {
|
||||
"weights": {"AAPL": 1.0},
|
||||
"risk_contributions": {"AAPL": 1.0},
|
||||
"method": "risk_parity",
|
||||
}
|
||||
resp = await client.post(
|
||||
"/api/v1/portfolio/risk-parity", json={"symbols": ["AAPL"]}
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
mock_fn.assert_called_once_with(["AAPL"], days=365)
|
||||
Reference in New Issue
Block a user