dekun
cee641ba5d
Aggregate four-account trades via hub_ai module and /api/hub/trades/today; store sessions in JSON; default OpenAI config matches instances. Co-authored-by: Cursor <cursoragent@cursor.com>
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
"""hub_trades_lib 单元测试。"""
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from __future__ import annotations
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import sqlite3
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import unittest
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from hub_trades_lib import fetch_trades_for_trading_day, summarize_trades, trading_day_from_dt
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from datetime import datetime
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class HubTradesLibTest(unittest.TestCase):
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def test_trading_day_reset(self):
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dt = datetime(2026, 6, 6, 7, 30, 0)
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self.assertEqual(trading_day_from_dt(dt, 8), "2026-06-05")
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dt2 = datetime(2026, 6, 6, 8, 0, 0)
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self.assertEqual(trading_day_from_dt(dt2, 8), "2026-06-06")
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def test_fetch_and_summarize(self):
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conn = sqlite3.connect(":memory:")
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conn.row_factory = sqlite3.Row
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conn.execute(
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"""CREATE TABLE trade_records (
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symbol TEXT, exchange_symbol TEXT, direction TEXT, result TEXT,
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pnl_amount REAL, closed_at TEXT, opened_at TEXT, session_date TEXT,
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monitor_type TEXT, actual_rr REAL, planned_rr REAL, trade_style TEXT, entry_reason TEXT
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)"""
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)
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conn.execute(
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"INSERT INTO trade_records VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)",
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(
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"ONDO/USDT",
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"ONDO/USDT:USDT",
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"short",
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"止损",
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-0.5,
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"2026-06-06 10:00:00",
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"2026-06-06 09:00:00",
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"2026-06-06",
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"趋势回调",
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None,
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None,
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"trend",
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"",
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),
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)
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conn.commit()
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rows = fetch_trades_for_trading_day(conn, "2026-06-06")
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self.assertEqual(len(rows), 1)
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stats = summarize_trades(rows)
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self.assertEqual(stats["closed_count"], 1)
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self.assertEqual(stats["loss_count"], 1)
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self.assertAlmostEqual(stats["total_pnl_u"], -0.5)
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conn.close()
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if __name__ == "__main__":
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unittest.main()
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