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feat: expand screeners and stabilize interactive feedback

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leefer
2026-07-28 22:47:50 +08:00
parent f4b2d7152a
commit 1cc80583b3
22 changed files with 2707 additions and 509 deletions
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tests/test_curated_screener.py
+248 -3
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@@ -1,26 +1,78 @@
import sqlite3
import tempfile
import unittest
from datetime import datetime, timedelta
from pathlib import Path
from database import ReviewDatabase
from screener import (
ADVANCED_CURATED_STRATEGIES,
CURATED_STRATEGIES,
FACTOR_FIELDS,
FACTOR_GROUPS,
ScreenerEngine,
_broken_reversal_metrics,
_risk_flags,
_rsi,
_quarter_periods,
)
from server import automatic_screener_jobs
class CuratedScreenerTests(unittest.TestCase):
def test_first_batch_contains_ten_distinct_curated_strategies(self):
self.assertEqual(10, len(CURATED_STRATEGIES))
self.assertEqual(10, len({item["name"] for item in CURATED_STRATEGIES}))
def test_curated_library_contains_original_and_advanced_strategies(self):
self.assertEqual(13, len(ADVANCED_CURATED_STRATEGIES))
self.assertEqual(23, len(CURATED_STRATEGIES))
self.assertEqual(23, len({item["name"] for item in CURATED_STRATEGIES}))
self.assertTrue(
{"行业动量轮动", "主力资金行业流入"}.issubset(
{item["name"] for item in CURATED_STRATEGIES}
)
)
self.assertTrue(
all(item["formula"]["meta"]["library"] == "curated" for item in CURATED_STRATEGIES)
)
def test_every_curated_strategy_explains_environment_and_failure_risk(self):
for strategy in CURATED_STRATEGIES:
meta = strategy["formula"]["meta"]
self.assertTrue(meta.get("suitable_environment"), strategy["name"])
self.assertTrue(meta.get("failure_risk"), strategy["name"])
self.assertNotIn("emotion_gate", meta, strategy["name"])
def test_automatic_curated_jobs_are_not_filtered_by_market_regime(self):
strategies = [
{
"name": "阶段策略",
"regimes": ["retreat"],
"formula": {"meta": {"library": "stage"}},
},
*CURATED_STRATEGIES,
]
for regime in ("ice", "repair", "fermentation", "climax", "divergence", "retreat"):
jobs = automatic_screener_jobs(strategies, regime)
curated_names = {
job["strategy"]["name"] for job in jobs if job["mode"] == "curated"
}
self.assertEqual(
{strategy["name"] for strategy in CURATED_STRATEGIES},
curated_names,
regime,
)
def test_curated_risk_flags_do_not_reintroduce_regime_gating(self):
row = {
"pct_chg": 0,
"return_10d": 0,
"volatility_10d": 0,
"amount_billion": 5,
}
self.assertIn("市场处于退潮阶段，策略可能选择空仓", _risk_flags(row, "retreat"))
self.assertNotIn(
"市场处于退潮阶段，策略可能选择空仓",
_risk_flags(row, "retreat", include_regime_risk=False),
)
def test_every_curated_formula_uses_supported_factors(self):
with tempfile.TemporaryDirectory() as root:
database = ReviewDatabase(Path(root) / "review.db")
@@ -56,6 +108,15 @@ class CuratedScreenerTests(unittest.TestCase):
connection.close()
self.assertTrue({"pe_ttm", "pb", "ps_ttm", "dv_ttm"}.issubset(indicator_columns))
self.assertIn("fundamental_indicators", tables)
self.assertIn("benchmark_bars", tables)
def test_advanced_strategies_declare_history_and_backtest_contracts(self):
for strategy in ADVANCED_CURATED_STRATEGIES:
meta = strategy["formula"]["meta"]
self.assertGreaterEqual(meta["history_days"], 80, strategy["name"])
self.assertGreaterEqual(meta["backtest_days"], 1, strategy["name"])
self.assertGreater(meta["take_profit"], 0, strategy["name"])
self.assertLess(meta["stop_loss"], 0, strategy["name"])
def test_quarter_periods_stop_at_selected_date(self):
periods = _quarter_periods("20260722", 5)
@@ -98,6 +159,10 @@ class CuratedScreenerTests(unittest.TestCase):
for index in range(100)
],
)
connection.executemany(
"INSERT INTO benchmark_bars (trade_date, ts_code, close) VALUES (?, ?, ?)",
[(f"2026{index + 1:04d}", "000300.SH", 4000 + index) for index in range(60)],
)
health = database.factor_health_summary("20260722")
self.assertTrue(health["market"])
@@ -105,10 +170,190 @@ class CuratedScreenerTests(unittest.TestCase):
self.assertTrue(health["valuation"])
self.assertTrue(health["fundamental"])
self.assertTrue(health["dividend_history"])
self.assertTrue(health["benchmark"])
self.assertEqual(health["valuation_rows"], 1)
self.assertEqual(health["fundamental_rows"], 100)
self.assertEqual(health["dividend_years"], 5)
def test_moneyflow_health_requires_the_latest_five_market_dates(self):
with tempfile.TemporaryDirectory() as root:
database = ReviewDatabase(Path(root) / "review.db")
dates = [f"202607{day:02d}" for day in range(20, 25)]
database.upsert_daily_bars([
{
"trade_date": trade_date, "ts_code": "600000.SH",
"open": 10, "high": 10.2, "low": 9.8, "close": 10,
"pct_chg": 0, "vol": 1000, "amount": 100000,
}
for trade_date in dates
])
database.upsert_moneyflow([
{"trade_date": "20260105", "ts_code": "600000.SH", "net_mf_amount": 10}
] * 5)
self.assertFalse(database.factor_health_summary(dates[-1])["moneyflow_history"])
database.upsert_moneyflow([
{"trade_date": trade_date, "ts_code": "600000.SH", "net_mf_amount": 10}
for trade_date in dates
])
health = database.factor_health_summary(dates[-1])
self.assertTrue(health["moneyflow_history"])
self.assertEqual(health["moneyflow_dates"], 5)
def test_technical_helpers_detect_rsi_and_daily_reversal_path(self):
self.assertLess(_rsi([10, 9, 8, 7, 6, 5, 4], 6), 1)
rows = [
{"close": 10, "high": 10, "vol": 100},
{"close": 11, "high": 11, "vol": 120},
{"close": 12, "high": 12, "vol": 130},
{"close": 11.2, "high": 11.8, "vol": 100},
{"close": 12.5, "high": 12.5, "vol": 140},
]
metrics = _broken_reversal_metrics(
rows, [False, True, True, False, True], "600000", "示例"
)
self.assertEqual(metrics["signal"], 1)
self.assertEqual(metrics["days"], 1)
def test_factor_builder_generates_long_window_and_benchmark_factors(self):
with tempfile.TemporaryDirectory() as root:
database = ReviewDatabase(Path(root) / "review.db")
database.upsert_stock_master([
{
"ts_code": "600000.SH", "name": "趋势样本", "industry": "银行",
"market": "主板", "list_date": "20000101",
}
])
dates = []
cursor = datetime(2025, 6, 1)
while len(dates) < 260:
if cursor.weekday() < 5:
dates.append(cursor.strftime("%Y%m%d"))
cursor += timedelta(days=1)
bars = []
benchmarks = []
indicators = []
for index, trade_date in enumerate(dates):
close = 10 + index * 0.05
bars.append({
"trade_date": trade_date, "ts_code": "600000.SH",
"open": close - 0.02, "high": close + 0.08, "low": close - 0.08,
"close": close, "pct_chg": 0.25, "vol": 1000 + index,
"amount": 200000,
})
benchmarks.append({
"trade_date": trade_date, "ts_code": "000300.SH",
"close": 4000 + index, "pct_chg": 0.02,
})
if index >= 250:
indicators.append({
"trade_date": trade_date, "ts_code": "600000.SH",
"turnover_rate": 2, "volume_ratio": 1,
})
database.upsert_daily_bars(bars)
database.upsert_benchmark_bars(benchmarks)
database.upsert_daily_indicators(indicators)
factors, actual_date = ScreenerEngine(database).build_factors(
dates[-1], history_days=260
)
self.assertEqual(actual_date, dates[-1])
self.assertEqual(len(factors), 1)
factor = factors[0]
self.assertEqual(factor["ma_bull_alignment"], 1)
self.assertEqual(factor["rs_high_120"], 1)
self.assertGreater(factor["momentum_60_5"], 0)
self.assertEqual(factor["momentum_60_5_rank"], 0)
def test_factor_builder_generates_sector_momentum_and_five_day_flow(self):
with tempfile.TemporaryDirectory() as root:
database = ReviewDatabase(Path(root) / "review.db")
stocks = [
("600001.SH", "动量样本", "电子", 0.16, 180),
("600002.SH", "对照样本", "银行", 0.02, -40),
]
database.upsert_stock_master([
{
"ts_code": code, "name": name, "industry": industry,
"market": "主板", "list_date": "20000101",
}
for code, name, industry, _, _ in stocks
])
dates = []
cursor = datetime(2026, 4, 1)
while len(dates) < 80:
if cursor.weekday() < 5:
dates.append(cursor.strftime("%Y%m%d"))
cursor += timedelta(days=1)
bars = []
for index, trade_date in enumerate(dates):
for code, _, _, slope, _ in stocks:
close = 10 + index * slope
bars.append({
"trade_date": trade_date, "ts_code": code,
"open": close - 0.03, "high": close + 0.08,
"low": close - 0.08, "close": close,
"pct_chg": slope, "vol": 1000 + index,
"amount": 300000,
})
database.upsert_daily_bars(bars)
database.upsert_daily_indicators([
{
"trade_date": dates[-1], "ts_code": code,
"turnover_rate": 2, "volume_ratio": 1,
"circ_mv": 1000000, "total_mv": 1500000,
}
for code, *_ in stocks
])
database.upsert_moneyflow([
{
"trade_date": trade_date, "ts_code": code,
"net_mf_amount": daily_flow,
}
for trade_date in dates[-5:]
for code, _, _, _, daily_flow in stocks
])
factors, _ = ScreenerEngine(database).build_factors(
dates[-1], history_days=80
)
by_code = {item["ts_code"]: item for item in factors}
leader = by_code["600001.SH"]
laggard = by_code["600002.SH"]
self.assertGreater(leader["return_20d"], laggard["return_20d"])
self.assertEqual(leader["sector_momentum_rank"], 1)
self.assertEqual(laggard["sector_momentum_rank"], 0)
self.assertGreater(leader["net_flow_5d_million"], 0)
self.assertLess(laggard["net_flow_5d_million"], 0)
self.assertEqual(leader["sector_flow_rank"], 1)
def test_screen_reports_signal_health(self):
with tempfile.TemporaryDirectory() as root:
database = ReviewDatabase(Path(root) / "review.db")
engine = ScreenerEngine(database)
formula = {
"universe": {"exclude_st": True, "listed_days_min": 0},
"filters": [{"field": "pct_chg", "op": ">", "value": 0}],
"score": [{"field": "amount_billion", "weight": 1, "direction": "desc"}],
"limit": 5,
"min_score": 0,
}
result = engine.screen(
0, "20260724", formula, "repair", "健康检查", False,
mode="curated",
prepared_factors=[{
"ts_code": "600000.SH", "code": "600000", "name": "浦发银行",
"sector": "银行", "listed_days": 1000, "pct_chg": 1,
"amount_billion": 5, "price": 10, "return_5d": 1,
"volume_ratio_5d": 1, "sector_strength": 50,
}],
prepared_date="20260724",
)
health = result["meta"]["health"]
self.assertEqual(health["status"], "normal")
self.assertEqual(health["signal_count"], 1)
self.assertEqual(health["coverage"], 100)
if __name__ == "__main__":
unittest.main()