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enhancing backtesting functionality

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This commit is contained in:
moen0
2026-04-23 23:21:03 +02:00
parent 768511e90d
commit e6e0f6f79c
5 changed files with 98 additions and 49 deletions
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backend/api/routes.py
+5 -1
View File
@@ -10,7 +10,7 @@ from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, Field
from indicators.sessions import set_timezone
BACKEND_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if BACKEND_DIR not in sys.path:
sys.path.insert(0, BACKEND_DIR)
@@ -524,6 +524,10 @@ def get_backtest(
max_consecutive_losses: int = 0,
):
dataset_id = _resolve_dataset(dataset)
if "MT5" in dataset.upper():
set_timezone("mt5")
else:
set_timezone("est")
candles = _get_candles_for_timeframe(dataset_id, timeframe)
strategy = _build_strategy(
backend/data/model.py
-2
View File
@@ -28,5 +28,3 @@ class Trade:
exit_price: float
pnl: float
r_multiple: float = 0.0
partial_tp_taken: bool = False
partial_tp_realized_pnl: float = 0.0
backend/indicators/sessions.py
+24 -6
View File
@@ -1,5 +1,6 @@
from datetime import time
# EST sessions (for histdata CSVs)
SESSIONS_EST = {
"asian": (time(19, 0), time(3, 0)),
"london": (time(2, 0), time(5, 0)),
@@ -8,25 +9,42 @@ SESSIONS_EST = {
"london_ny_overlap": (time(8, 0), time(10, 0)),
}
# UTC+2 sessions (for MetaTrader exported CSVs)
SESSIONS_MT5 = {
"asian": (time(2, 0), time(10, 0)),
"london": (time(9, 0), time(12, 0)),
"new_york": (time(14, 0), time(17, 0)),
"london_close": (time(17, 0), time(19, 0)),
"london_ny_overlap": (time(15, 0), time(17, 0)),
}
# Active session map (switch based on data source)
_active_sessions = SESSIONS_EST
def set_timezone(tz="est"):
global _active_sessions
if tz.lower() in ("mt5", "utc+2", "server"):
_active_sessions = SESSIONS_MT5
else:
_active_sessions = SESSIONS_EST
def in_session(candle_time, session_name):
if session_name == "all":
return True
if session_name not in SESSIONS_EST:
if session_name not in _active_sessions:
return True
t = candle_time.time()
start, end = SESSIONS_EST[session_name]
start, end = _active_sessions[session_name]
if start > end:
return t >= start or t < end
return start <= t < end
def get_session(candle_time):
for name in SESSIONS_EST:
if name == "all":
continue
for name in _active_sessions:
if in_session(candle_time, name):
return name
return "off_hours"
frontend/src/components/BacktestingTab.jsx
+69 -13
View File
@@ -39,6 +39,8 @@ const DAYS = [
const STARTING_BALANCE = 10000;
const PRESETS_KEY = 'nq_backtest_presets';
const RESULT_HISTORY_KEY = 'nq_backtest_recent_results';
const RESULT_HISTORY_LIMIT = 10;
const DEFAULT_PRESET_NAME = 'Manual';
function formatMoney(v) {
return v.toLocaleString('en-US', { minimumFractionDigits: 2, maximumFractionDigits: 2 });
@@ -81,15 +83,14 @@ function savePresets(presets) {
function loadRecentResults() {
try {
const parsed = JSON.parse(localStorage.getItem(RESULT_HISTORY_KEY) || '[]');
return Array.isArray(parsed) ? parsed.slice(0,
5) : [];
return Array.isArray(parsed) ? parsed.slice(0, RESULT_HISTORY_LIMIT) : [];
} catch {
return [];
}
}
function saveRecentResults(results) {
localStorage.setItem(RESULT_HISTORY_KEY, JSON.stringify(results.slice(0, 5)));
localStorage.setItem(RESULT_HISTORY_KEY, JSON.stringify(results.slice(0, RESULT_HISTORY_LIMIT)));
}
function NumberInput({ label, value, onChange, min, max, step = 1 }) {
@@ -195,6 +196,7 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
// Presets
const [presets, setPresets] = useState(loadPresets);
const [presetName, setPresetName] = useState('');
const [activePresetName, setActivePresetName] = useState(DEFAULT_PRESET_NAME);
const [showPresets, setShowPresets] = useState(false);
const [recentResults, setRecentResults] = useState(loadRecentResults);
@@ -243,12 +245,16 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
const updated = { ...presets, [name]: getSettings() };
setPresets(updated);
savePresets(updated);
setActivePresetName(name);
setPresetName('');
};
const handleLoadPreset = (name) => {
const preset = presets[name];
if (preset) applySettings(preset);
if (preset) {
applySettings(preset);
setActivePresetName(name);
}
setShowPresets(false);
};
@@ -257,6 +263,41 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
delete updated[name];
setPresets(updated);
savePresets(updated);
if (activePresetName === name) {
setActivePresetName(DEFAULT_PRESET_NAME);
}
};
const exportRunParameters = (run) => {
const exportPayload = {
exportedAt: new Date().toISOString(),
runId: run.id,
presetName: run.presetName || DEFAULT_PRESET_NAME,
parameters: run.settings || {
timeframe: run.timeframe,
riskReward: run.riskReward,
},
queryParameters: run.queryParameters || null,
summary: {
dataset: run.dataset,
timeframe: run.timeframe,
riskReward: run.riskReward,
totalPnl: run.totalPnl,
winRate: run.winRate,
totalTrades: run.totalTrades,
},
};
const blob = new Blob([JSON.stringify(exportPayload, null, 2)], { type: 'application/json' });
const url = URL.createObjectURL(blob);
const anchor = document.createElement('a');
const safePreset = (run.presetName || DEFAULT_PRESET_NAME).replace(/[^a-z0-9_-]/gi, '_');
anchor.href = url;
anchor.download = `backtest-params-${run.dataset || 'dataset'}-${safePreset}-${run.id}.json`;
document.body.appendChild(anchor);
anchor.click();
document.body.removeChild(anchor);
URL.revokeObjectURL(url);
};
const toggleDay = (day) => {
@@ -426,18 +467,25 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
onBacktestComplete?.(backtestData);
if (backtestData?.stats) {
const snapshotSettings = {
...getSettings(),
dayFilter: [...dayFilter],
};
const snapshot = {
id: `${Date.now()}-${Math.random().toString(36).slice(2, 8)}`,
runAt: new Date().toISOString(),
dataset: selectedDataset,
presetName: activePresetName,
timeframe,
riskReward,
settings: snapshotSettings,
queryParameters: Object.fromEntries(params.entries()),
totalPnl: Number(backtestData.stats.total_pnl ?? 0),
winRate: Number(backtestData.stats.win_rate ?? 0),
totalTrades: Number(backtestData.stats.total_trades ?? 0),
};
setRecentResults((prev) => {
const next = [snapshot, ...prev].slice(0, 5);
const next = [snapshot, ...prev].slice(0, RESULT_HISTORY_LIMIT);
saveRecentResults(next);
return next;
});
@@ -463,7 +511,7 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
requireFvgObConfluence, asianSweepOnly, dayFilter,
useBreakEven, beTriggerRr,
usePartialTp, partialTpRr, partialTpPercent,
maxDailyLoss, maxConsecutiveLosses, onBacktestComplete,
maxDailyLoss, maxConsecutiveLosses, onBacktestComplete, activePresetName,
]);
const runMonteCarlo = useCallback(async () => {
@@ -796,22 +844,30 @@ export function BacktestingTab({ datasets = [], selectedDataset, onDatasetChange
<p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-1">Results</p>
<h2 className="text-[20px] font-semibold tracking-tight">Backtest Summary</h2>
<p className="text-[12px] text-[#737373] font-mono mt-2">CSV: {selectedDataset}</p>
<p className="text-[12px] text-[#737373] font-mono mt-1">Preset: {activePresetName}</p>
</div>
<div className="mb-6 border border-[#1a1a1a] bg-black/30 p-4">
<p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-3">Last 5 Runs</p>
<p className="text-[11px] text-[#525252] font-mono uppercase tracking-widest mb-3">Last {RESULT_HISTORY_LIMIT} Runs</p>
{recentResults.length === 0 ? (
<p className="text-[12px] text-[#737373] font-mono">No previous runs saved yet.</p>
) : (
<div className="space-y-2">
{recentResults.map((run) => (
<div key={run.id} className="grid grid-cols-2 md:grid-cols-6 gap-2 text-[12px] font-mono border border-[#1a1a1a] bg-black/40 px-3 py-2">
<div key={run.id} className="grid grid-cols-2 md:grid-cols-8 gap-2 text-[12px] font-mono border border-[#1a1a1a] bg-black/40 px-3 py-2 items-center">
<span className="text-[#a3a3a3]">{new Date(run.runAt).toLocaleString()}</span>
<span className="text-[#fafafa]">{run.dataset}</span>
<span className="text-[#a3a3a3]">{run.timeframe}m</span>
<span className={run.totalPnl >= 0 ? 'text-[#10b981]' : 'text-[#ef4444]'}>${formatMoney(run.totalPnl)}</span>
<span className="text-[#60a5fa]">{run.winRate.toFixed(1)}%</span>
<span className="text-[#fafafa]">{run.totalTrades} trades</span>
<span className="text-[#fafafa]">{run.dataset || 'Unknown CSV'}</span>
<span className="text-[#a3a3a3]">{run.timeframe ?? '-'}m</span>
<span className="text-[#a78bfa]">{run.presetName || DEFAULT_PRESET_NAME}</span>
<span className={(run.totalPnl ?? 0) >= 0 ? 'text-[#10b981]' : 'text-[#ef4444]'}>${formatMoney(Number(run.totalPnl ?? 0))}</span>
<span className="text-[#60a5fa]">{Number(run.winRate ?? 0).toFixed(1)}%</span>
<span className="text-[#fafafa]">{Number(run.totalTrades ?? 0)} trades</span>
<button
onClick={() => exportRunParameters(run)}
className="px-2 py-1 text-[11px] border border-[#262626] text-[#d4d4d8] hover:text-[#fafafa] hover:border-[#404040] transition-colors"
>
Export
</button>
</div>
))}
</div>
frontend/src/components/OptimizerTab.jsx
-27
View File
@@ -100,9 +100,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
const [asianSweepOnlyModes, setAsianSweepOnlyModes] = useState('true,false');
const [useBreakEvenModes, setUseBreakEvenModes] = useState('false,true');
const [beTriggerRrValues, setBeTriggerRrValues] = useState('1.0,1.5,2.0');
const [usePartialTpModes, setUsePartialTpModes] = useState('false,true');
const [partialTpRrValues, setPartialTpRrValues] = useState('1.0,1.5,2.0');
const [partialTpPercentValues, setPartialTpPercentValues] = useState('50');
const [loading, setLoading] = useState(false);
const [progressPct, setProgressPct] = useState(0);
@@ -158,9 +155,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asianSweepOnly: params.asian_sweep_only === true || params.asian_sweep_only === 'true',
useBreakEven: params.use_break_even === true || params.use_break_even === 'true',
beTriggerRr: Number(params.be_trigger_rr ?? 1.0),
usePartialTp: params.use_partial_tp === true || params.use_partial_tp === 'true',
partialTpRr: Number(params.partial_tp_rr ?? 1.0),
partialTpPercent: Number(params.partial_tp_percent ?? 50),
dayFilter: [0, 1, 2, 3, 4],
maxDailyLoss: 0,
maxConsecutiveLosses: 0,
@@ -250,9 +244,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
* count(asianSweepOnlyModes)
* count(useBreakEvenModes)
* count(beTriggerRrValues)
* count(usePartialTpModes)
* count(partialTpRrValues)
* count(partialTpPercentValues)
* Math.max(1, sweepFactor || boolCount);
}, [
sessions,
@@ -271,9 +262,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asianSweepOnlyModes,
useBreakEvenModes,
beTriggerRrValues,
usePartialTpModes,
partialTpRrValues,
partialTpPercentValues,
]);
const mcPnlHistogram = useMemo(() => {
@@ -358,9 +346,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asian_sweep_only_modes: parseBoolList(asianSweepOnlyModes, [true, false]),
use_break_even_modes: parseBoolList(useBreakEvenModes, [false, true]),
be_trigger_rr_values: parseFloatList(beTriggerRrValues, [1.0, 1.5, 2.0]),
use_partial_tp_modes: parseBoolList(usePartialTpModes, [false, true]),
partial_tp_rr_values: parseFloatList(partialTpRrValues, [1.0, 1.5, 2.0]),
partial_tp_percent_values: parseFloatList(partialTpPercentValues, [50]),
};
const seedValue = comboSamplingSeed.trim();
if (seedValue) {
@@ -481,9 +466,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asianSweepOnlyModes,
useBreakEvenModes,
beTriggerRrValues,
usePartialTpModes,
partialTpRrValues,
partialTpPercentValues,
activateTopResult,
]);
@@ -523,9 +505,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asian_sweep_only: String(targetParams.asian_sweep_only ?? false),
use_break_even: String(targetParams.use_break_even ?? false),
be_trigger_rr: String(targetParams.be_trigger_rr ?? 1.0),
use_partial_tp: String(targetParams.use_partial_tp ?? false),
partial_tp_rr: String(targetParams.partial_tp_rr ?? 1.0),
partial_tp_percent: String(targetParams.partial_tp_percent ?? 50),
runs: String(mcRuns),
shuffle_trades: String(mcShuffleTrades),
pnl_variation_pct: String(mcVariationPct),
@@ -663,9 +642,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
asian_sweep_only: p.asianSweepOnly,
use_break_even: p.useBreakEven,
be_trigger_rr: p.beTriggerRr,
use_partial_tp: p.usePartialTp,
partial_tp_rr: p.partialTpRr,
partial_tp_percent: p.partialTpPercent,
},
timeframe: p.timeframe,
riskReward: p.riskReward,
@@ -790,9 +766,6 @@ export function OptimizerTab({ datasets = [], selectedDataset, onDatasetChange,
<TextListInput label="Asian Sweep Only" value={asianSweepOnlyModes} onChange={setAsianSweepOnlyModes} placeholder="true,false" />
<TextListInput label="Use Break-Even" value={useBreakEvenModes} onChange={setUseBreakEvenModes} placeholder="false,true" />
<TextListInput label="BE Trigger RR" value={beTriggerRrValues} onChange={setBeTriggerRrValues} placeholder="1.0,1.5,2.0" />
<TextListInput label="Use Partial TP" value={usePartialTpModes} onChange={setUsePartialTpModes} placeholder="false,true" />
<TextListInput label="Partial TP RR" value={partialTpRrValues} onChange={setPartialTpRrValues} placeholder="1.0,1.5,2.0" />
<TextListInput label="Partial TP %" value={partialTpPercentValues} onChange={setPartialTpPercentValues} placeholder="50" />
</div>
<div className="mt-6 border border-[#1a1a1a] bg-black/40 p-4">