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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "203ae436",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# filename: strat_backtestingpy_sma_showcase.ipynb\n",
+    "\n",
+    "# --- 1. Imports and Setup ---\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import pandas_ta as ta\n",
+    "import talib\n",
+    "import tulipy as ti\n",
+    "from backtesting import Backtest, Strategy\n",
+    "from backtesting.lib import crossover\n",
+    "from backtesting.test import EURUSD\n",
+    "\n",
+    "# --- 2. Load the Sample Data ---\n",
+    "print(\"Loading built-in EURUSD sample data...\")\n",
+    "data = EURUSD.copy()\n",
+    "print(\"Data loaded successfully.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fff685c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- Example 1: Using TA-Lib ---\n",
+    "print(\"\\n--- Showcase: TA-Lib ---\")\n",
+    "\n",
+    "def SMA(array, n):\n",
+    "    \"\"\"Helper function to wrap talib.SMA for use with self.I\"\"\"\n",
+    "    return talib.SMA(array, n)\n",
+    "\n",
+    "class SmaCrossTaLib(Strategy):\n",
+    "    fast_period = 10\n",
+    "    slow_period = 40\n",
+    "\n",
+    "    def init(self):\n",
+    "        self.fast_sma = self.I(SMA, self.data.Close, self.fast_period)\n",
+    "        self.slow_sma = self.I(SMA, self.data.Close, self.slow_period)\n",
+    "\n",
+    "    def next(self):\n",
+    "        if crossover(self.fast_sma, self.slow_sma):\n",
+    "            self.buy()\n",
+    "        elif crossover(self.slow_sma, self.fast_sma):\n",
+    "            self.position.close()\n",
+    "\n",
+    "bt = Backtest(data, SmaCrossTaLib, cash=10000, commission=.002)\n",
+    "stats = bt.run()\n",
+    "print(stats)\n",
+    "bt.plot(resample=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1c8df83",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- Example 2: Using pandas-ta ---\n",
+    "print(\"\\n--- Showcase: pandas-ta ---\")\n",
+    "\n",
+    "class SmaCrossPandasTa(Strategy):\n",
+    "    fast_period = 10\n",
+    "    slow_period = 40\n",
+    "\n",
+    "    def init(self):\n",
+    "        self.fast_sma = self.I(ta.sma, pd.Series(self.data.Close), length=self.fast_period)\n",
+    "        self.slow_sma = self.I(ta.sma, pd.Series(self.data.Close), length=self.slow_period)\n",
+    "\n",
+    "    def next(self):\n",
+    "        if crossover(self.fast_sma, self.slow_sma):\n",
+    "            self.buy()\n",
+    "        elif crossover(self.slow_sma, self.fast_sma):\n",
+    "            self.position.close()\n",
+    "\n",
+    "bt = Backtest(data, SmaCrossPandasTa, cash=10000, commission=.002)\n",
+    "stats = bt.run()\n",
+    "print(stats)\n",
+    "bt.plot(resample=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3368601a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- Example 3: Using a Custom Python Function ---\n",
+    "print(\"\\n--- Showcase: Custom Function ---\")\n",
+    "\n",
+    "def my_sma_func(price_series, n):\n",
+    "    return price_series.rolling(n).mean()\n",
+    "\n",
+    "class SmaCrossCustom(Strategy):\n",
+    "    fast_period = 10\n",
+    "    slow_period = 40\n",
+    "\n",
+    "    def init(self):\n",
+    "        self.fast_sma = self.I(my_sma_func, pd.Series(self.data.Close), self.fast_period)\n",
+    "        self.slow_sma = self.I(my_sma_func, pd.Series(self.data.Close), self.slow_period)\n",
+    "\n",
+    "    def next(self):\n",
+    "        if crossover(self.fast_sma, self.slow_sma):\n",
+    "            self.buy()\n",
+    "        elif crossover(self.slow_sma, self.fast_sma):\n",
+    "            self.position.close()\n",
+    "\n",
+    "bt = Backtest(data, SmaCrossCustom, cash=10000, commission=.002)\n",
+    "stats = bt.run()\n",
+    "print(stats)\n",
+    "bt.plot(resample=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2121bebf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- Example 4: Using tulipy ---\n",
+    "print(\"\\n--- Showcase: tulipy ---\")\n",
+    "\n",
+    "def tulip_sma(price_array, period):\n",
+    "    result = ti.sma(price_array, period=period)\n",
+    "    pad_size = len(price_array) - len(result)\n",
+    "    return np.concatenate([np.full(pad_size, np.nan), result])\n",
+    "\n",
+    "class SmaCrossTulip(Strategy):\n",
+    "    fast_period = 10\n",
+    "    slow_period = 40\n",
+    "\n",
+    "    def init(self):\n",
+    "        self.fast_sma = self.I(tulip_sma, self.data.Close, self.fast_period)\n",
+    "        self.slow_sma = self.I(tulip_sma, self.data.Close, self.slow_period)\n",
+    "\n",
+    "    def next(self):\n",
+    "        if crossover(self.fast_sma, self.slow_sma):\n",
+    "            self.buy()\n",
+    "        elif crossover(self.slow_sma, self.fast_sma):\n",
+    "            self.position.close()\n",
+    "\n",
+    "bt = Backtest(data, SmaCrossTulip, cash=10000, commission=.002)\n",
+    "stats = bt.run()\n",
+    "print(stats)\n",
+    "bt.plot(resample=False)"
+   ]
+  }
+ ],
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+   "display_name": "strategy-optimizer_env_bck",
+   "language": "python",
+   "name": "python3"
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+   "file_extension": ".py",
+   "mimetype": "text/x-python",
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+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
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