bf70ca3ac7
All 12 modules built per reviewed plan: - detector, state_machine (5-state phased FSM), canary, levels Phase B - notifier fanout (Discord + Telegram, bounded queue, retry, dead-letter) - audit (JSONL daily rotation), journal, report (weekly R-multiple PnL) - calibrate + labeler (Tk, lazy-imported), dryrun with acceptance gate - unified CLI: atm calibrate|label|dryrun|run|journal|report README + Phase 2 prop-firm TOS audit checklist included. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
"""Tests for atm.report."""
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from __future__ import annotations
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import pytest
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from atm.journal import TradeEntry
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from atm.report import iso_week, weekly_report
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WEEK = "2026-16"
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BASE_TS = "2026-04-14T10:00:00"
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def _trade(
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outcome: str,
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direction: str = "BUY",
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entry: float = 100.0,
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sl: float = 90.0,
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exit_: float | None = None,
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detected_ts: str | None = None,
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ts: str = BASE_TS,
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) -> TradeEntry:
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return TradeEntry(
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ts=ts,
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direction=direction,
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symbol="US30",
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entry=entry,
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sl=sl,
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tp1=None,
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tp2=None,
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exit=exit_,
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outcome=outcome,
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detected_ts=detected_ts,
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notes="",
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)
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def test_win_rate_and_pnl() -> None:
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"""5 synthetic trades: tp1 +2R, tp2 +3R, sl -1.5R, manual +2R, open excluded."""
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trades = [
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# tp1: BUY, entry=100, sl=90, exit=120 → R = (120-100)/(100-90) = +2.0
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_trade("tp1", exit_=120.0, detected_ts="2026-04-14T09:59:55"),
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# tp2: BUY, entry=100, sl=90, exit=130 → R = (130-100)/(100-90) = +3.0
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_trade("tp2", exit_=130.0),
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# sl: BUY, entry=100, sl=90, exit=85 → R = (85-100)/(100-90) = -1.5
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_trade("sl", exit_=85.0, detected_ts="2026-04-14T09:59:50"),
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# manual: SELL, entry=100, sl=110, exit=80 → R = (80-100)/(100-110) = +2.0
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_trade("manual", direction="SELL", sl=110.0, exit_=80.0),
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# open: excluded from counts
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_trade("open"),
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]
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report = weekly_report(trades, WEEK)
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assert report.week == WEEK
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assert report.n_trades == 4
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assert report.n_wins == 2
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assert report.n_losses == 2
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assert report.win_rate == pytest.approx(0.5)
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assert report.pnl_r == pytest.approx(5.5)
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# slippage: trade[0]=5s, trade[2]=10s → avg=7.5s
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assert report.avg_slippage == pytest.approx(7.5)
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def test_iso_week() -> None:
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assert iso_week("2026-04-14T10:00:00") == "2026-16"
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assert iso_week("2026-01-01T00:00:00") == "2026-01"
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def test_empty_week() -> None:
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report = weekly_report([], WEEK)
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assert report.n_trades == 0
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assert report.n_wins == 0
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assert report.n_losses == 0
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assert report.win_rate == 0.0
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assert report.pnl_r == 0.0
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assert report.avg_slippage is None
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