kingchenc
677ea37402
Stacked on #315 (the native Binance REST fetcher). Retarget to `main` once #315 merges. Migrates the runnable examples off third-party data-I/O packages onto Wickra's native data layer (`CandleReader`, `Resampler`, `BinanceFeed`, `fetch_*klines`). ## Third-party packages removed (the zero-dep selling point) - **Node**: `ws` (live feed → BinanceFeed) — dropped from package.json + lockfile - **Go**: `github.com/coder/websocket` — dropped from go.mod / go.sum (`go mod tidy`) - **Java**: `jackson-databind` (live feed + REST fetch) — dropped from pom.xml - **R**: `jsonlite` + `websocket` + `later` — dropped from the README notes Each language's CSV loading now goes through `CandleReader`, manual resampling through `Resampler`, the live feed through `BinanceFeed`, and (Java/R) the REST download through the native fetcher. ## Verification Ran the offline examples per language against the bundled data — backtest and multi_timeframe produce identical output across Python / Node / Go / Java / R (e.g. ATR(14) last 345.1010; 1h→5m resamples to 240 bars, →15m to 80 bars). C# / C / WASM (stdlib-only, no third-party deps to remove) follow in this branch. Note: the streaming `strategy_*` examples have pre-existing candle-indicator runtime bugs (CI only syntax-smokes them); the CSV migration preserves their shape and leaves those bugs for a separate fix.
195 lines
7.3 KiB
HTML
195 lines
7.3 KiB
HTML
<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<title>Wickra WASM — MACD + ADX trend filter</title>
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<style>
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body { font-family: ui-sans-serif, system-ui, sans-serif; max-width: 760px; margin: 2rem auto; padding: 0 1rem; color: #1d1d1d; }
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h1 { margin-bottom: .25rem; }
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.meta { color: #666; margin-top: 0; }
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table { border-collapse: collapse; width: 100%; margin-top: 1rem; font-variant-numeric: tabular-nums; }
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th, td { border: 1px solid #ddd; padding: .5rem .75rem; text-align: right; }
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th:first-child, td:first-child { text-align: left; }
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th { background: #fafafa; }
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code { background: #f4f4f4; padding: .1rem .25rem; border-radius: .2rem; font-size: .9em; }
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label { display: inline-block; margin-right: .5rem; }
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button { padding: .5rem 1rem; }
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#status { margin-top: 1rem; color: #666; }
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.note { margin-top: 1rem; color: #888; font-size: .9em; }
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</style>
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</head>
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<body>
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<h1>Wickra WASM — MACD + ADX trend filter</h1>
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<p class="meta">
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Long-only trend follower: enters on a MACD(12,26,9) histogram crossover up
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while ADX(14) > 20, exits on the opposite crossover, 0.1% fees. The
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browser counterpart of <code>examples/python/strategy_macd_adx.py</code>,
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<code>examples/node/strategy_macd_adx.js</code> and the Rust
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<code>strategy_macd_adx.rs</code> — same loop, same summary.
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</p>
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<p>
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<label>Dataset: <input type="text" id="path" value="../data/btcusdt-1h.csv" size="40" /></label>
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<button id="go" disabled>Run strategy</button>
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</p>
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<p id="status">Loading WASM module…</p>
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<table id="results" hidden>
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<thead><tr><th>Metric</th><th>Value</th></tr></thead>
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<tbody></tbody>
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</table>
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<p class="note" id="disclaimer" hidden>
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NOTE: Educational example — fees, slippage, funding costs and tax effects
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are simplified or omitted. Past performance is not indicative of future
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results.
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</p>
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<script type="module">
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import init, {
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CandleReader, version, installPanicHook, MACD, ADX } from "../../bindings/wasm/pkg/wickra_wasm.js";
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const FEE = 0.001;
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const ADX_FLOOR = 20.0;
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function parseCsv(text) {
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// Native CandleReader: header validation, BOM/whitespace tolerance. No
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// manual CSV parsing.
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const candles = new CandleReader(text).read();
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const cols = { timestamp: [], open: [], high: [], low: [], close: [], volume: [] };
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for (const c of candles) {
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cols.timestamp.push(c.timestamp);
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cols.open.push(c.open);
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cols.high.push(c.high);
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cols.low.push(c.low);
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cols.close.push(c.close);
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cols.volume.push(c.volume);
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}
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return cols;
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}
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function signed(value, digits) {
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return (value >= 0 ? "+" : "") + value.toFixed(digits);
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}
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function runStrategy(cols) {
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const n = cols.close.length;
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const macd = new MACD(12, 26, 9);
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const adx = new ADX(14);
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let inPosition = false;
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let entryPrice = 0.0;
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const closedTrades = [];
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let equity = 1.0;
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const equityCurve = [];
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let prevHistSign = null;
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for (let i = 0; i < n; i++) {
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const price = cols.close[i];
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const macdOut = macd.update(price);
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const adxOut = adx.update(cols.high[i], cols.low[i], price);
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const mtm = inPosition ? equity * (price / entryPrice) : equity;
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equityCurve.push(mtm);
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if (macdOut == null || adxOut == null) continue;
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const histSign = macdOut.histogram > 0.0;
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const crossUp = prevHistSign === false && histSign;
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const crossDown = prevHistSign === true && !histSign;
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prevHistSign = histSign;
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if (!inPosition && crossUp && adxOut.adx > ADX_FLOOR) {
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entryPrice = price;
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equity *= 1.0 - FEE;
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inPosition = true;
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} else if (inPosition && crossDown) {
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const tradeRet = price / entryPrice - 1.0;
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closedTrades.push(tradeRet);
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equity *= (1.0 + tradeRet) * (1.0 - FEE);
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inPosition = false;
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}
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}
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if (inPosition) {
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const tradeRet = cols.close[n - 1] / entryPrice - 1.0;
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closedTrades.push(tradeRet);
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equity *= (1.0 + tradeRet) * (1.0 - FEE);
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}
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return summarise("MACD + ADX Trend Filter (1h, BTCUSDT)", cols.close[0], cols.close[n - 1], n, closedTrades, equity, equityCurve);
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}
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function summarise(name, firstPrice, lastPrice, bars, closedTrades, finalEquity, equityCurve) {
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const buyHold = lastPrice / firstPrice;
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const stratReturn = finalEquity - 1.0;
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const bhReturn = buyHold - 1.0;
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const wins = closedTrades.filter((r) => r > 0).length;
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const losses = closedTrades.filter((r) => r < 0).length;
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const best = closedTrades.length ? Math.max(...closedTrades) : 0.0;
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const worst = closedTrades.length ? Math.min(...closedTrades) : 0.0;
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const nT = closedTrades.length;
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const meanRet = nT ? closedTrades.reduce((a, r) => a + r, 0) / nT : 0.0;
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const varRet = nT > 1 ? closedTrades.reduce((a, r) => a + (r - meanRet) ** 2, 0) / (nT - 1) : 0.0;
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const stddev = Math.sqrt(varRet);
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const sharpe = varRet > 0 ? meanRet / stddev : 0.0;
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let peak = equityCurve.length ? equityCurve[0] : 1.0;
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let maxDd = 0.0;
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for (const eq of equityCurve) {
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if (eq > peak) peak = eq;
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const dd = (peak - eq) / peak;
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if (dd > maxDd) maxDd = dd;
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}
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return [
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["Strategy", name],
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["Bars", String(bars)],
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["Trades", `${nT} (W${wins} / L${losses})`],
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["Strategy return", `${signed(stratReturn * 100, 2)}%`],
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["Buy & Hold return", `${signed(bhReturn * 100, 2)}%`],
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["Excess over BH", `${signed((stratReturn - bhReturn) * 100, 2)}%`],
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["Max drawdown", `${(maxDd * 100).toFixed(2)}%`],
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["Per-trade Sharpe", `${sharpe.toFixed(2)} (mean ${signed(meanRet, 4)}, stddev ${stddev.toFixed(4)})`],
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["Best / worst trade", `${signed(best * 100, 2)}% / ${signed(worst * 100, 2)}%`],
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];
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}
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function render(rows) {
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const tbody = document.querySelector("#results tbody");
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tbody.innerHTML = "";
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for (const [k, v] of rows) {
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const tr = document.createElement("tr");
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tr.innerHTML = `<td>${k}</td><td>${v}</td>`;
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tbody.appendChild(tr);
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}
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document.getElementById("results").hidden = false;
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document.getElementById("disclaimer").hidden = false;
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}
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async function run() {
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const path = document.getElementById("path").value;
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const status = document.getElementById("status");
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status.textContent = `Fetching ${path}…`;
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try {
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const resp = await fetch(path);
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if (!resp.ok) throw new Error(`HTTP ${resp.status} for ${path}`);
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const cols = parseCsv(await resp.text());
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status.textContent = `Running MACD + ADX over ${cols.close.length} bars…`;
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await new Promise((r) => setTimeout(r, 0));
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render(runStrategy(cols));
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status.textContent = `Done — ${cols.close.length} bars.`;
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} catch (err) {
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status.textContent = `error: ${err.message || err}`;
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}
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}
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document.getElementById("go").onclick = run;
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init().then(() => {
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installPanicHook();
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document.getElementById("go").disabled = false;
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document.getElementById("status").textContent = `Ready — wickra ${version()}. Click "Run strategy".`;
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});
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</script>
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</body>
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</html>
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