Built-in Plugins

1// Example: Use built-in SMA in a custom indicator2import { sma } from '@quatick/indicators/sma';3import { ema } from '@quatick/indicators/ema';4import { rsi } from '@quatick/indicators/rsi';56export function calculate(bars: BarData[], params: any) {7  const closes = bars.map(b => b.close);8  9  const sma20 = sma(closes, 20);10  const ema50 = ema(closes, 50);11  const rsi14 = rsi(closes, 14);12  13  // Your custom logic combining multiple indicators14  return bars.map((bar, i) => ({15    time: bar.time,16    value: sma20[i] > ema50[i] && rsi14[i] < 30 ? 1 : 0,17  }));18}

1# In Python strategies, compute indicators using pandas:2import pandas as pd3import numpy as np45def initialize(bars_data):6    df = pd.DataFrame(bars_data)7    8    # Trend9    df['sma_20'] = df['close'].rolling(20).mean()10    df['ema_50'] = df['close'].ewm(span=50).mean()11    12    # Momentum13    df['rsi'] = compute_rsi(df['close'], 14)14    15    # Volatility16    df['bb_upper'], df['bb_middle'], df['bb_lower'], _, _ = compute_bollinger(df['close'])17    18    # Volume19    df['obv'] = (np.sign(df['close'].diff()) * df['volume']).cumsum()20    21    return df

1// Inheritance chain:2// BasePlugin → BaseIndicator → YourIndicator3// BasePlugin → BaseOverlay  → YourOverlay45// BasePlugin provides:6// - Plugin registration and lifecycle7// - Parameter management8// - Theme integration9// - Event handling1011// BaseIndicator adds:12// - calculate() execution on bar updates13// - Output rendering (LINE, HISTOGRAM, etc.)14// - Pane management (overlay or separate)15// - Y-axis scaling1617// BaseOverlay adds:18// - render() on canvas19// - Hit testing and interaction20// - Drag/resize handling21// - Serialization