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feat: EOD aggregation with market filter (issue #86)
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- Add market parameter to aggregate_daily_from_trades() for per-market L6 aggregation
- Store market-scoped keys (total_pnl_KR, win_rate_US, etc.) in L6/L5/L4 layers
- Hook aggregate_daily_from_trades() into market close detection in run()
- Update tests for market-scoped context keys

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
agentson
2026-02-10 04:23:49 +09:00
parent 3cdd10783b
commit 78021d4695
3 changed files with 144 additions and 60 deletions
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56
tests/test_context.py
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@@ -161,7 +161,7 @@ class TestContextAggregator:
self, aggregator: ContextAggregator, db_conn: sqlite3.Connection
) -> None:
"""Test aggregating daily metrics from trades."""
date = "2026-02-04"
date = datetime.now(UTC).date().isoformat()
# Create sample trades
log_trade(db_conn, "005930", "BUY", 85, "Good signal", quantity=10, price=70000, pnl=500)
@@ -175,36 +175,44 @@ class TestContextAggregator:
db_conn.commit()
# Aggregate
aggregator.aggregate_daily_from_trades(date)
aggregator.aggregate_daily_from_trades(date, market="KR")
# Verify L6 contexts
store = aggregator.store
assert store.get_context(ContextLayer.L6_DAILY, date, "trade_count") == 3
assert store.get_context(ContextLayer.L6_DAILY, date, "buys") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "sells") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "holds") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "total_pnl") == 2000.0
assert store.get_context(ContextLayer.L6_DAILY, date, "unique_stocks") == 3
assert store.get_context(ContextLayer.L6_DAILY, date, "trade_count_KR") == 3
assert store.get_context(ContextLayer.L6_DAILY, date, "buys_KR") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "sells_KR") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "holds_KR") == 1
assert store.get_context(ContextLayer.L6_DAILY, date, "total_pnl_KR") == 2000.0
assert store.get_context(ContextLayer.L6_DAILY, date, "unique_stocks_KR") == 3
# 2 wins, 0 losses
assert store.get_context(ContextLayer.L6_DAILY, date, "win_rate") == 100.0
assert store.get_context(ContextLayer.L6_DAILY, date, "win_rate_KR") == 100.0
def test_aggregate_weekly_from_daily(self, aggregator: ContextAggregator) -> None:
"""Test aggregating weekly metrics from daily."""
week = "2026-W06"
# Set daily contexts
aggregator.store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "total_pnl", 100.0)
aggregator.store.set_context(ContextLayer.L6_DAILY, "2026-02-03", "total_pnl", 200.0)
aggregator.store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "avg_confidence", 80.0)
aggregator.store.set_context(ContextLayer.L6_DAILY, "2026-02-03", "avg_confidence", 85.0)
aggregator.store.set_context(
ContextLayer.L6_DAILY, "2026-02-02", "total_pnl_KR", 100.0
)
aggregator.store.set_context(
ContextLayer.L6_DAILY, "2026-02-03", "total_pnl_KR", 200.0
)
aggregator.store.set_context(
ContextLayer.L6_DAILY, "2026-02-02", "avg_confidence_KR", 80.0
)
aggregator.store.set_context(
ContextLayer.L6_DAILY, "2026-02-03", "avg_confidence_KR", 85.0
)
# Aggregate
aggregator.aggregate_weekly_from_daily(week)
# Verify L5 contexts
store = aggregator.store
weekly_pnl = store.get_context(ContextLayer.L5_WEEKLY, week, "weekly_pnl")
avg_conf = store.get_context(ContextLayer.L5_WEEKLY, week, "avg_confidence")
weekly_pnl = store.get_context(ContextLayer.L5_WEEKLY, week, "weekly_pnl_KR")
avg_conf = store.get_context(ContextLayer.L5_WEEKLY, week, "avg_confidence_KR")
assert weekly_pnl == 300.0
assert avg_conf == 82.5
@@ -214,9 +222,15 @@ class TestContextAggregator:
month = "2026-02"
# Set weekly contexts
aggregator.store.set_context(ContextLayer.L5_WEEKLY, "2026-W05", "weekly_pnl", 100.0)
aggregator.store.set_context(ContextLayer.L5_WEEKLY, "2026-W06", "weekly_pnl", 200.0)
aggregator.store.set_context(ContextLayer.L5_WEEKLY, "2026-W07", "weekly_pnl", 150.0)
aggregator.store.set_context(
ContextLayer.L5_WEEKLY, "2026-W05", "weekly_pnl_KR", 100.0
)
aggregator.store.set_context(
ContextLayer.L5_WEEKLY, "2026-W06", "weekly_pnl_KR", 200.0
)
aggregator.store.set_context(
ContextLayer.L5_WEEKLY, "2026-W07", "weekly_pnl_KR", 150.0
)
# Aggregate
aggregator.aggregate_monthly_from_weekly(month)
@@ -285,7 +299,7 @@ class TestContextAggregator:
self, aggregator: ContextAggregator, db_conn: sqlite3.Connection
) -> None:
"""Test running all aggregations from L7 to L1."""
date = "2026-02-04"
date = datetime.now(UTC).date().isoformat()
# Create sample trades
log_trade(db_conn, "005930", "BUY", 85, "Good signal", quantity=10, price=70000, pnl=1000)
@@ -299,12 +313,12 @@ class TestContextAggregator:
# Verify data exists in each layer
store = aggregator.store
assert store.get_context(ContextLayer.L6_DAILY, date, "total_pnl") == 1000.0
assert store.get_context(ContextLayer.L6_DAILY, date, "total_pnl_KR") == 1000.0
from datetime import date as date_cls
trade_date = date_cls.fromisoformat(date)
iso_year, iso_week, _ = trade_date.isocalendar()
trade_week = f"{iso_year}-W{iso_week:02d}"
assert store.get_context(ContextLayer.L5_WEEKLY, trade_week, "weekly_pnl") is not None
assert store.get_context(ContextLayer.L5_WEEKLY, trade_week, "weekly_pnl_KR") is not None
trade_month = f"{trade_date.year}-{trade_date.month:02d}"
trade_quarter = f"{trade_date.year}-Q{(trade_date.month - 1) // 3 + 1}"
trade_year = str(trade_date.year)