{
 "cells": [
  {
   "cell_type": "code",
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   "id": "b05aa740",
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ EASI tools loaded successfully (with Gateway support)\n"
     ]
    },
    {
     "data": {
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      "application/vnd.holoviews_load.v0+json": ""
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     "output_type": "stream",
     "text": [
      "======================================================================\n",
      "📦 ODC Module with Cognito Authentication Loaded\n",
      "======================================================================\n",
      "\n",
      "💡 Quick Start:\n",
      "   1. setup_cognito_auth('train_files/crediential.txt')\n",
      "   2. Use datacube normally with authenticated S3 access\n",
      "\n",
      "📚 Functions:\n",
      "   - setup_cognito_auth()    : Setup Cognito authentication\n",
      "   - get_cognito_auth()      : Get authenticator instance\n",
      "   - print_auth_status()     : Show auth status\n",
      "   - auto_setup()            : Auto-setup if credentials exist\n",
      "======================================================================\n",
      "\n",
      "✅ Module loaded with Cognito authentication support\n",
      "CPU times: user 529 ms, sys: 10.3 ms, total: 540 ms\n",
      "Wall time: 531 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "%matplotlib inline\n",
    "\n",
    "import importlib\n",
    "import sys\n",
    "sys.path.insert(0, '/media/x79/2A7D-FAA0/remote-sensing')\n",
    "\n",
    "# Import ODC module with Cognito authentication\n",
    "import new_import_ODC_cognito  \n",
    "importlib.reload(new_import_ODC_cognito)\n",
    "\n",
    "from new_import_ODC_cognito import *\n",
    "\n",
    "print(\"✅ Module loaded with Cognito authentication support\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6abb2be1",
   "metadata": {},
   "source": [
    "# 🔐 Cognito Authentication for ODC\n",
    "\n",
    "## Overview / Tổng quan\n",
    "\n",
    "Notebook này sử dụng **AWS Cognito authentication** để truy cập S3 và Open Data Cube (ODC).\n",
    "\n",
    "### Luồng xác thực:\n",
    "```\n",
    "Cognito Tokens → AWS Credentials → S3/ODC Access\n",
    "```\n",
    "\n",
    "### Lợi ích:\n",
    "- ✅ **Bảo mật cao hơn**: Identity-based authentication\n",
    "- ✅ **Thông tin user**: Username, email, groups\n",
    "- ✅ **Token auto-expire**: Tăng cường bảo mật\n",
    "- ✅ **Quản lý quyền tốt**: Group-based permissions\n",
    "\n",
    "### Credentials file:\n",
    "```\n",
    "/media/x79/2A7D-FAA0/remote-sensing/train_files/crediential.txt\n",
    "```\n",
    "\n",
    "---\n",
    "\n",
    "**📚 Docs**: `COGNITO_GUIDE.md`, `S3_ACCESS_GUIDE.md`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b794d005",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🔐 Step 1: Cognito Authentication Setup\n",
      "----------------------------------------------------------------------\n",
      "🔐 Setting up Cognito authentication...\n",
      "✓ AWS credentials loaded from file\n",
      "✓ Cognito tokens loaded successfully\n",
      "\n",
      "📋 Token Information:\n",
      "\n",
      "=== Cognito Token Information ===\n",
      "\n",
      "User Information:\n",
      "  Username: hienm2523001\n",
      "  Name: Hien Phan\n",
      "  Email: hienm2523001@gstudent.ctu.edu.vn\n",
      "  Groups: default-group, allocation:R-19244:CSIRO and Vietnam partners\n",
      "  Token expires: 2026-03-05 04:52:38\n",
      "  Time remaining: 6h 25m\n",
      "\n",
      "=== Getting AWS Credentials from Cognito ===\n",
      "⚠ No Identity Pool ID provided\n",
      "⚠ Using existing AWS credentials (already exchanged from Cognito)...\n",
      "✓ Using AWS credentials loaded from file\n",
      "✓ AWS credentials set in environment\n",
      "\n",
      "🌐 Configuring datacube S3 access...\n",
      "\n",
      "✅ Cognito authentication setup complete!\n",
      "✅ Ready to use datacube with S3 access\n",
      "\n",
      "\n",
      "✅ Authentication successful!\n",
      "   Ready to access S3 buckets with authenticated credentials\n",
      "\n",
      "======================================================================\n",
      "🚀 Step 2: Dask + Datacube Initialization\n",
      "----------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/x79/miniconda3/envs/env_01/lib/python3.10/site-packages/distributed/node.py:188: UserWarning: Port 8787 is already in use.\n",
      "Perhaps you already have a cluster running?\n",
      "Hosting the HTTP server on port 38781 instead\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "ename": "OperationalError",
     "evalue": "(psycopg2.OperationalError) connection to server at \"v2-db-easi-asia-eks.cluster-ro-czyydvizywt5.ap-southeast-1.rds.amazonaws.com\" (10.0.22.166), port 5432 failed: Connection timed out\n\tIs the server running on that host and accepting TCP/IP connections?\n\n(Background on this error at: https://sqlalche.me/e/14/e3q8)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:3371\u001b[0m, in \u001b[0;36mEngine._wrap_pool_connect\u001b[0;34m(self, fn, connection)\u001b[0m\n\u001b[1;32m   3370\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3371\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3372\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m dialect\u001b[38;5;241m.\u001b[39mdbapi\u001b[38;5;241m.\u001b[39mError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:327\u001b[0m, in \u001b[0;36mPool.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    320\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Return a DBAPI connection from the pool.\u001b[39;00m\n\u001b[1;32m    321\u001b[0m \n\u001b[1;32m    322\u001b[0m \u001b[38;5;124;03mThe connection is instrumented such that when its\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    325\u001b[0m \n\u001b[1;32m    326\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 327\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_ConnectionFairy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_checkout\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:894\u001b[0m, in \u001b[0;36m_ConnectionFairy._checkout\u001b[0;34m(cls, pool, threadconns, fairy)\u001b[0m\n\u001b[1;32m    893\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m fairy:\n\u001b[0;32m--> 894\u001b[0m     fairy \u001b[38;5;241m=\u001b[39m \u001b[43m_ConnectionRecord\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheckout\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpool\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    896\u001b[0m     fairy\u001b[38;5;241m.\u001b[39m_pool \u001b[38;5;241m=\u001b[39m pool\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:493\u001b[0m, in \u001b[0;36m_ConnectionRecord.checkout\u001b[0;34m(cls, pool)\u001b[0m\n\u001b[1;32m    491\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    492\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mcheckout\u001b[39m(\u001b[38;5;28mcls\u001b[39m, pool):\n\u001b[0;32m--> 493\u001b[0m     rec \u001b[38;5;241m=\u001b[39m \u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_get\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    494\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/impl.py:145\u001b[0m, in \u001b[0;36mQueuePool._do_get\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    144\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m--> 145\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m util\u001b[38;5;241m.\u001b[39msafe_reraise():\n\u001b[1;32m    146\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dec_overflow()\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/langhelpers.py:70\u001b[0m, in \u001b[0;36msafe_reraise.__exit__\u001b[0;34m(self, type_, value, traceback)\u001b[0m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwarn_only:\n\u001b[0;32m---> 70\u001b[0m         \u001b[43mcompat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     71\u001b[0m \u001b[43m            \u001b[49m\u001b[43mexc_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     72\u001b[0m \u001b[43m            \u001b[49m\u001b[43mwith_traceback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexc_tb\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     73\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/compat.py:211\u001b[0m, in \u001b[0;36mraise_\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exception\n\u001b[1;32m    212\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    213\u001b[0m     \u001b[38;5;66;03m# credit to\u001b[39;00m\n\u001b[1;32m    214\u001b[0m     \u001b[38;5;66;03m# https://cosmicpercolator.com/2016/01/13/exception-leaks-in-python-2-and-3/\u001b[39;00m\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;66;03m# as the __traceback__ object creates a cycle\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/impl.py:143\u001b[0m, in \u001b[0;36mQueuePool._do_get\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    142\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 143\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_connection\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    144\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:273\u001b[0m, in \u001b[0;36mPool._create_connection\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    271\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Called by subclasses to create a new ConnectionRecord.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_ConnectionRecord\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:388\u001b[0m, in \u001b[0;36m_ConnectionRecord.__init__\u001b[0;34m(self, pool, connect)\u001b[0m\n\u001b[1;32m    387\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m connect:\n\u001b[0;32m--> 388\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__connect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    389\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfinalize_callback \u001b[38;5;241m=\u001b[39m deque()\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:690\u001b[0m, in \u001b[0;36m_ConnectionRecord.__connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    689\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m--> 690\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m util\u001b[38;5;241m.\u001b[39msafe_reraise():\n\u001b[1;32m    691\u001b[0m         pool\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError on connect(): \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, e)\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/langhelpers.py:70\u001b[0m, in \u001b[0;36msafe_reraise.__exit__\u001b[0;34m(self, type_, value, traceback)\u001b[0m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwarn_only:\n\u001b[0;32m---> 70\u001b[0m         \u001b[43mcompat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     71\u001b[0m \u001b[43m            \u001b[49m\u001b[43mexc_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     72\u001b[0m \u001b[43m            \u001b[49m\u001b[43mwith_traceback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexc_tb\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     73\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/compat.py:211\u001b[0m, in \u001b[0;36mraise_\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exception\n\u001b[1;32m    212\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    213\u001b[0m     \u001b[38;5;66;03m# credit to\u001b[39;00m\n\u001b[1;32m    214\u001b[0m     \u001b[38;5;66;03m# https://cosmicpercolator.com/2016/01/13/exception-leaks-in-python-2-and-3/\u001b[39;00m\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;66;03m# as the __traceback__ object creates a cycle\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:686\u001b[0m, in \u001b[0;36m_ConnectionRecord.__connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    685\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstarttime \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 686\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdbapi_connection \u001b[38;5;241m=\u001b[39m connection \u001b[38;5;241m=\u001b[39m \u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_invoke_creator\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    687\u001b[0m pool\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreated new connection \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, connection)\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/create.py:574\u001b[0m, in \u001b[0;36mcreate_engine.<locals>.connect\u001b[0;34m(connection_record)\u001b[0m\n\u001b[1;32m    573\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m connection\n\u001b[0;32m--> 574\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdialect\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcparams\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/default.py:598\u001b[0m, in \u001b[0;36mDefaultDialect.connect\u001b[0;34m(self, *cargs, **cparams)\u001b[0m\n\u001b[1;32m    596\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39mcargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcparams):\n\u001b[1;32m    597\u001b[0m     \u001b[38;5;66;03m# inherits the docstring from interfaces.Dialect.connect\u001b[39;00m\n\u001b[0;32m--> 598\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdbapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcparams\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/psycopg2/__init__.py:122\u001b[0m, in \u001b[0;36mconnect\u001b[0;34m(dsn, connection_factory, cursor_factory, **kwargs)\u001b[0m\n\u001b[1;32m    121\u001b[0m dsn \u001b[38;5;241m=\u001b[39m _ext\u001b[38;5;241m.\u001b[39mmake_dsn(dsn, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 122\u001b[0m conn \u001b[38;5;241m=\u001b[39m \u001b[43m_connect\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdsn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconnection_factory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconnection_factory\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwasync\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    123\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cursor_factory \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[0;31mOperationalError\u001b[0m: connection to server at \"v2-db-easi-asia-eks.cluster-ro-czyydvizywt5.ap-southeast-1.rds.amazonaws.com\" (10.0.22.166), port 5432 failed: Connection timed out\n\tIs the server running on that host and accepting TCP/IP connections?\n",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 24\u001b[0m\n\u001b[1;32m     21\u001b[0m cluster, client \u001b[38;5;241m=\u001b[39m notebook_utils\u001b[38;5;241m.\u001b[39minitialize_dask(use_gateway\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, workers\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m4\u001b[39m)\n\u001b[1;32m     23\u001b[0m \u001b[38;5;66;03m# Khai báo Datacube\u001b[39;00m\n\u001b[0;32m---> 24\u001b[0m dc \u001b[38;5;241m=\u001b[39m \u001b[43mdatacube\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDatacube\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     26\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m✅ Dask + Datacube + S3 (Cognito authenticated) ready!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m   Dask dashboard: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mclient\u001b[38;5;241m.\u001b[39mdashboard_link\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/api/core.py:87\u001b[0m, in \u001b[0;36mDatacube.__init__\u001b[0;34m(self, index, config, app, env, validate_connection)\u001b[0m\n\u001b[1;32m     84\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m config\n\u001b[1;32m     86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m index \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 87\u001b[0m     index \u001b[38;5;241m=\u001b[39m \u001b[43mindex_connect\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnormalise_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     88\u001b[0m \u001b[43m                          \u001b[49m\u001b[43mapplication_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     89\u001b[0m \u001b[43m                          \u001b[49m\u001b[43mvalidate_connection\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalidate_connection\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     91\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mindex \u001b[38;5;241m=\u001b[39m index\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/index/_api.py:45\u001b[0m, in \u001b[0;36mindex_connect\u001b[0;34m(local_config, application_name, validate_connection)\u001b[0m\n\u001b[1;32m     38\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m index_driver:\n\u001b[1;32m     39\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m     40\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo index driver found for \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m available: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (\n\u001b[1;32m     41\u001b[0m             driver_name, \u001b[38;5;28mlen\u001b[39m(index_drivers()), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(index_drivers())\n\u001b[1;32m     42\u001b[0m         )\n\u001b[1;32m     43\u001b[0m     )\n\u001b[0;32m---> 45\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mindex_driver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect_to_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlocal_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     46\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43mapplication_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapplication_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     47\u001b[0m \u001b[43m                                     \u001b[49m\u001b[43mvalidate_connection\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalidate_connection\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/index/postgres/index.py:166\u001b[0m, in \u001b[0;36mDefaultIndexDriver.connect_to_index\u001b[0;34m(config, application_name, validate_connection)\u001b[0m\n\u001b[1;32m    164\u001b[0m \u001b[38;5;129m@staticmethod\u001b[39m\n\u001b[1;32m    165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mconnect_to_index\u001b[39m(config, application_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, validate_connection\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[0;32m--> 166\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mIndex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mapplication_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalidate_connection\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/index/postgres/index.py:77\u001b[0m, in \u001b[0;36mIndex.from_config\u001b[0;34m(cls, config, application_name, validate_connection)\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m     76\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mfrom_config\u001b[39m(\u001b[38;5;28mcls\u001b[39m, config, application_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, validate_connection\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[0;32m---> 77\u001b[0m     db \u001b[38;5;241m=\u001b[39m \u001b[43mPostgresDb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mapplication_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapplication_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     78\u001b[0m \u001b[43m                                \u001b[49m\u001b[43mvalidate_connection\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalidate_connection\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     79\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(db)\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/drivers/postgres/_connections.py:75\u001b[0m, in \u001b[0;36mPostgresDb.from_config\u001b[0;34m(cls, config, application_name, validate_connection)\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m     72\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mfrom_config\u001b[39m(\u001b[38;5;28mcls\u001b[39m, config, application_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, validate_connection\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m     73\u001b[0m     app_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_app_name(application_name)\n\u001b[0;32m---> 75\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mPostgresDb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     76\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_hostname\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     77\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_database\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     78\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_username\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDEFAULT_DB_USER\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     79\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_password\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     80\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_port\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDEFAULT_DB_PORT\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     81\u001b[0m \u001b[43m        \u001b[49m\u001b[43mapplication_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapp_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     82\u001b[0m \u001b[43m        \u001b[49m\u001b[43mvalidate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalidate_connection\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     83\u001b[0m \u001b[43m        \u001b[49m\u001b[43miam_rds_auth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mbool\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdb_iam_authentication\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDEFAULT_IAM_AUTH\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     84\u001b[0m \u001b[43m        \u001b[49m\u001b[43miam_rds_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdb_iam_timeout\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDEFAULT_IAM_TIMEOUT\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     85\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpool_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdb_connection_timeout\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m60\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     86\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;66;43;03m# pass config?\u001b[39;49;00m\n\u001b[1;32m     87\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/drivers/postgres/_connections.py:107\u001b[0m, in \u001b[0;36mPostgresDb.create\u001b[0;34m(cls, hostname, database, username, password, port, application_name, validate, iam_rds_auth, iam_rds_timeout, pool_timeout)\u001b[0m\n\u001b[1;32m     96\u001b[0m engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_create_engine(\n\u001b[1;32m     97\u001b[0m     mk_url(\n\u001b[1;32m     98\u001b[0m         \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpostgresql\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    104\u001b[0m     iam_rds_timeout\u001b[38;5;241m=\u001b[39miam_rds_timeout,\n\u001b[1;32m    105\u001b[0m     pool_timeout\u001b[38;5;241m=\u001b[39mpool_timeout)\n\u001b[1;32m    106\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m validate:\n\u001b[0;32m--> 107\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[43m_core\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdatabase_exists\u001b[49m\u001b[43m(\u001b[49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m    108\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m IndexSetupError(\u001b[38;5;124m'\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mNo DB schema exists. Have you run init?\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;132;01m{init_command}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    109\u001b[0m             init_command\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatacube system init\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    110\u001b[0m         ))\n\u001b[1;32m    112\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _core\u001b[38;5;241m.\u001b[39mschema_is_latest(engine):\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/drivers/postgres/_core.py:152\u001b[0m, in \u001b[0;36mdatabase_exists\u001b[0;34m(engine)\u001b[0m\n\u001b[1;32m    148\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mdatabase_exists\u001b[39m(engine):\n\u001b[1;32m    149\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    150\u001b[0m \u001b[38;5;124;03m    Have they init'd this database?\u001b[39;00m\n\u001b[1;32m    151\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 152\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhas_schema\u001b[49m\u001b[43m(\u001b[49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/datacube/drivers/postgres/_core.py:237\u001b[0m, in \u001b[0;36mhas_schema\u001b[0;34m(engine)\u001b[0m\n\u001b[1;32m    236\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mhas_schema\u001b[39m(engine):\n\u001b[0;32m--> 237\u001b[0m     inspector \u001b[38;5;241m=\u001b[39m \u001b[43minspect\u001b[49m\u001b[43m(\u001b[49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    238\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m SCHEMA_NAME \u001b[38;5;129;01min\u001b[39;00m inspector\u001b[38;5;241m.\u001b[39mget_schema_names()\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/inspection.py:64\u001b[0m, in \u001b[0;36minspect\u001b[0;34m(subject, raiseerr)\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m reg \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m     63\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m subject\n\u001b[0;32m---> 64\u001b[0m ret \u001b[38;5;241m=\u001b[39m \u001b[43mreg\u001b[49m\u001b[43m(\u001b[49m\u001b[43msubject\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     65\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ret \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m     66\u001b[0m     \u001b[38;5;28;01mbreak\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/reflection.py:182\u001b[0m, in \u001b[0;36mInspector._engine_insp\u001b[0;34m(bind)\u001b[0m\n\u001b[1;32m    180\u001b[0m \u001b[38;5;129m@inspection\u001b[39m\u001b[38;5;241m.\u001b[39m_inspects(Engine)\n\u001b[1;32m    181\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_engine_insp\u001b[39m(bind):\n\u001b[0;32m--> 182\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mInspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_construct\u001b[49m\u001b[43m(\u001b[49m\u001b[43mInspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_init_engine\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbind\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/reflection.py:117\u001b[0m, in \u001b[0;36mInspector._construct\u001b[0;34m(cls, init, bind)\u001b[0m\n\u001b[1;32m    114\u001b[0m     \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m bind\u001b[38;5;241m.\u001b[39mdialect\u001b[38;5;241m.\u001b[39minspector\n\u001b[1;32m    116\u001b[0m \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__new__\u001b[39m(\u001b[38;5;28mcls\u001b[39m)\n\u001b[0;32m--> 117\u001b[0m \u001b[43minit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbind\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/reflection.py:128\u001b[0m, in \u001b[0;36mInspector._init_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_init_engine\u001b[39m(\u001b[38;5;28mself\u001b[39m, engine):\n\u001b[1;32m    127\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbind \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mengine \u001b[38;5;241m=\u001b[39m engine\n\u001b[0;32m--> 128\u001b[0m     \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mclose()\n\u001b[1;32m    129\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_op_context_requires_connect \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    130\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdialect \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mengine\u001b[38;5;241m.\u001b[39mdialect\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:3325\u001b[0m, in \u001b[0;36mEngine.connect\u001b[0;34m(self, close_with_result)\u001b[0m\n\u001b[1;32m   3310\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m, close_with_result\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m   3311\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return a new :class:`_engine.Connection` object.\u001b[39;00m\n\u001b[1;32m   3312\u001b[0m \n\u001b[1;32m   3313\u001b[0m \u001b[38;5;124;03m    The :class:`_engine.Connection` object is a facade that uses a DBAPI\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   3322\u001b[0m \n\u001b[1;32m   3323\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m-> 3325\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_connection_cls\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclose_with_result\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclose_with_result\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:96\u001b[0m, in \u001b[0;36mConnection.__init__\u001b[0;34m(self, engine, connection, close_with_result, _branch_from, _execution_options, _dispatch, _has_events, _allow_revalidate)\u001b[0m\n\u001b[1;32m     91\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_has_events \u001b[38;5;241m=\u001b[39m _branch_from\u001b[38;5;241m.\u001b[39m_has_events\n\u001b[1;32m     92\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     93\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dbapi_connection \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m     94\u001b[0m         connection\n\u001b[1;32m     95\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m connection \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m---> 96\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_connection\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     97\u001b[0m     )\n\u001b[1;32m     99\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transaction \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_nested_transaction \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    100\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__savepoint_seq \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:3404\u001b[0m, in \u001b[0;36mEngine.raw_connection\u001b[0;34m(self, _connection)\u001b[0m\n\u001b[1;32m   3382\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mraw_connection\u001b[39m(\u001b[38;5;28mself\u001b[39m, _connection\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m   3383\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return a \"raw\" DBAPI connection from the connection pool.\u001b[39;00m\n\u001b[1;32m   3384\u001b[0m \n\u001b[1;32m   3385\u001b[0m \u001b[38;5;124;03m    The returned object is a proxied version of the DBAPI\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   3402\u001b[0m \n\u001b[1;32m   3403\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m-> 3404\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_wrap_pool_connect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_connection\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:3374\u001b[0m, in \u001b[0;36mEngine._wrap_pool_connect\u001b[0;34m(self, fn, connection)\u001b[0m\n\u001b[1;32m   3372\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m dialect\u001b[38;5;241m.\u001b[39mdbapi\u001b[38;5;241m.\u001b[39mError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m   3373\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m connection \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 3374\u001b[0m         \u001b[43mConnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle_dbapi_exception_noconnection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3375\u001b[0m \u001b[43m            \u001b[49m\u001b[43me\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdialect\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\n\u001b[1;32m   3376\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3377\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   3378\u001b[0m         util\u001b[38;5;241m.\u001b[39mraise_(\n\u001b[1;32m   3379\u001b[0m             sys\u001b[38;5;241m.\u001b[39mexc_info()[\u001b[38;5;241m1\u001b[39m], with_traceback\u001b[38;5;241m=\u001b[39msys\u001b[38;5;241m.\u001b[39mexc_info()[\u001b[38;5;241m2\u001b[39m]\n\u001b[1;32m   3380\u001b[0m         )\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:2208\u001b[0m, in \u001b[0;36mConnection._handle_dbapi_exception_noconnection\u001b[0;34m(cls, e, dialect, engine)\u001b[0m\n\u001b[1;32m   2206\u001b[0m     util\u001b[38;5;241m.\u001b[39mraise_(newraise, with_traceback\u001b[38;5;241m=\u001b[39mexc_info[\u001b[38;5;241m2\u001b[39m], from_\u001b[38;5;241m=\u001b[39me)\n\u001b[1;32m   2207\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m should_wrap:\n\u001b[0;32m-> 2208\u001b[0m     \u001b[43mutil\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   2209\u001b[0m \u001b[43m        \u001b[49m\u001b[43msqlalchemy_exception\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwith_traceback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexc_info\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrom_\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43me\u001b[49m\n\u001b[1;32m   2210\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2211\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   2212\u001b[0m     util\u001b[38;5;241m.\u001b[39mraise_(exc_info[\u001b[38;5;241m1\u001b[39m], with_traceback\u001b[38;5;241m=\u001b[39mexc_info[\u001b[38;5;241m2\u001b[39m])\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/compat.py:211\u001b[0m, in \u001b[0;36mraise_\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    208\u001b[0m     exception\u001b[38;5;241m.\u001b[39m__cause__ \u001b[38;5;241m=\u001b[39m replace_context\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exception\n\u001b[1;32m    212\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    213\u001b[0m     \u001b[38;5;66;03m# credit to\u001b[39;00m\n\u001b[1;32m    214\u001b[0m     \u001b[38;5;66;03m# https://cosmicpercolator.com/2016/01/13/exception-leaks-in-python-2-and-3/\u001b[39;00m\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;66;03m# as the __traceback__ object creates a cycle\u001b[39;00m\n\u001b[1;32m    216\u001b[0m     \u001b[38;5;28;01mdel\u001b[39;00m exception, replace_context, from_, with_traceback\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/base.py:3371\u001b[0m, in \u001b[0;36mEngine._wrap_pool_connect\u001b[0;34m(self, fn, connection)\u001b[0m\n\u001b[1;32m   3369\u001b[0m dialect \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdialect\n\u001b[1;32m   3370\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3371\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3372\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m dialect\u001b[38;5;241m.\u001b[39mdbapi\u001b[38;5;241m.\u001b[39mError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m   3373\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m connection \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:327\u001b[0m, in \u001b[0;36mPool.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    319\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m    320\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return a DBAPI connection from the pool.\u001b[39;00m\n\u001b[1;32m    321\u001b[0m \n\u001b[1;32m    322\u001b[0m \u001b[38;5;124;03m    The connection is instrumented such that when its\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    325\u001b[0m \n\u001b[1;32m    326\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 327\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_ConnectionFairy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_checkout\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:894\u001b[0m, in \u001b[0;36m_ConnectionFairy._checkout\u001b[0;34m(cls, pool, threadconns, fairy)\u001b[0m\n\u001b[1;32m    891\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    892\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_checkout\u001b[39m(\u001b[38;5;28mcls\u001b[39m, pool, threadconns\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, fairy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    893\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m fairy:\n\u001b[0;32m--> 894\u001b[0m         fairy \u001b[38;5;241m=\u001b[39m \u001b[43m_ConnectionRecord\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheckout\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpool\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    896\u001b[0m         fairy\u001b[38;5;241m.\u001b[39m_pool \u001b[38;5;241m=\u001b[39m pool\n\u001b[1;32m    897\u001b[0m         fairy\u001b[38;5;241m.\u001b[39m_counter \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:493\u001b[0m, in \u001b[0;36m_ConnectionRecord.checkout\u001b[0;34m(cls, pool)\u001b[0m\n\u001b[1;32m    491\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    492\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mcheckout\u001b[39m(\u001b[38;5;28mcls\u001b[39m, pool):\n\u001b[0;32m--> 493\u001b[0m     rec \u001b[38;5;241m=\u001b[39m \u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_get\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    494\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    495\u001b[0m         dbapi_connection \u001b[38;5;241m=\u001b[39m rec\u001b[38;5;241m.\u001b[39mget_connection()\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/impl.py:145\u001b[0m, in \u001b[0;36mQueuePool._do_get\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    143\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_create_connection()\n\u001b[1;32m    144\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m--> 145\u001b[0m         \u001b[38;5;28;01mwith\u001b[39;00m util\u001b[38;5;241m.\u001b[39msafe_reraise():\n\u001b[1;32m    146\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dec_overflow()\n\u001b[1;32m    147\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/langhelpers.py:70\u001b[0m, in \u001b[0;36msafe_reraise.__exit__\u001b[0;34m(self, type_, value, traceback)\u001b[0m\n\u001b[1;32m     68\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m  \u001b[38;5;66;03m# remove potential circular references\u001b[39;00m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwarn_only:\n\u001b[0;32m---> 70\u001b[0m         \u001b[43mcompat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     71\u001b[0m \u001b[43m            \u001b[49m\u001b[43mexc_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     72\u001b[0m \u001b[43m            \u001b[49m\u001b[43mwith_traceback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexc_tb\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     73\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     75\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m compat\u001b[38;5;241m.\u001b[39mpy3k \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info[\u001b[38;5;241m1\u001b[39m]:\n\u001b[1;32m     76\u001b[0m         \u001b[38;5;66;03m# emulate Py3K's behavior of telling us when an exception\u001b[39;00m\n\u001b[1;32m     77\u001b[0m         \u001b[38;5;66;03m# occurs in an exception handler.\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/compat.py:211\u001b[0m, in \u001b[0;36mraise_\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    208\u001b[0m     exception\u001b[38;5;241m.\u001b[39m__cause__ \u001b[38;5;241m=\u001b[39m replace_context\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exception\n\u001b[1;32m    212\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    213\u001b[0m     \u001b[38;5;66;03m# credit to\u001b[39;00m\n\u001b[1;32m    214\u001b[0m     \u001b[38;5;66;03m# https://cosmicpercolator.com/2016/01/13/exception-leaks-in-python-2-and-3/\u001b[39;00m\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;66;03m# as the __traceback__ object creates a cycle\u001b[39;00m\n\u001b[1;32m    216\u001b[0m     \u001b[38;5;28;01mdel\u001b[39;00m exception, replace_context, from_, with_traceback\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/impl.py:143\u001b[0m, in \u001b[0;36mQueuePool._do_get\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    141\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_inc_overflow():\n\u001b[1;32m    142\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 143\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_connection\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    144\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m    145\u001b[0m         \u001b[38;5;28;01mwith\u001b[39;00m util\u001b[38;5;241m.\u001b[39msafe_reraise():\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:273\u001b[0m, in \u001b[0;36mPool._create_connection\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    270\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_create_connection\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m    271\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Called by subclasses to create a new ConnectionRecord.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 273\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_ConnectionRecord\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:388\u001b[0m, in \u001b[0;36m_ConnectionRecord.__init__\u001b[0;34m(self, pool, connect)\u001b[0m\n\u001b[1;32m    386\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__pool \u001b[38;5;241m=\u001b[39m pool\n\u001b[1;32m    387\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m connect:\n\u001b[0;32m--> 388\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__connect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    389\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfinalize_callback \u001b[38;5;241m=\u001b[39m deque()\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:690\u001b[0m, in \u001b[0;36m_ConnectionRecord.__connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    688\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfresh \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    689\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m--> 690\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m util\u001b[38;5;241m.\u001b[39msafe_reraise():\n\u001b[1;32m    691\u001b[0m         pool\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError on connect(): \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, e)\n\u001b[1;32m    692\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    693\u001b[0m     \u001b[38;5;66;03m# in SQLAlchemy 1.4 the first_connect event is not used by\u001b[39;00m\n\u001b[1;32m    694\u001b[0m     \u001b[38;5;66;03m# the engine, so this will usually not be set\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/langhelpers.py:70\u001b[0m, in \u001b[0;36msafe_reraise.__exit__\u001b[0;34m(self, type_, value, traceback)\u001b[0m\n\u001b[1;32m     68\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m  \u001b[38;5;66;03m# remove potential circular references\u001b[39;00m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwarn_only:\n\u001b[0;32m---> 70\u001b[0m         \u001b[43mcompat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     71\u001b[0m \u001b[43m            \u001b[49m\u001b[43mexc_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     72\u001b[0m \u001b[43m            \u001b[49m\u001b[43mwith_traceback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexc_tb\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     73\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     75\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m compat\u001b[38;5;241m.\u001b[39mpy3k \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exc_info[\u001b[38;5;241m1\u001b[39m]:\n\u001b[1;32m     76\u001b[0m         \u001b[38;5;66;03m# emulate Py3K's behavior of telling us when an exception\u001b[39;00m\n\u001b[1;32m     77\u001b[0m         \u001b[38;5;66;03m# occurs in an exception handler.\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/util/compat.py:211\u001b[0m, in \u001b[0;36mraise_\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m    208\u001b[0m     exception\u001b[38;5;241m.\u001b[39m__cause__ \u001b[38;5;241m=\u001b[39m replace_context\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exception\n\u001b[1;32m    212\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m    213\u001b[0m     \u001b[38;5;66;03m# credit to\u001b[39;00m\n\u001b[1;32m    214\u001b[0m     \u001b[38;5;66;03m# https://cosmicpercolator.com/2016/01/13/exception-leaks-in-python-2-and-3/\u001b[39;00m\n\u001b[1;32m    215\u001b[0m     \u001b[38;5;66;03m# as the __traceback__ object creates a cycle\u001b[39;00m\n\u001b[1;32m    216\u001b[0m     \u001b[38;5;28;01mdel\u001b[39;00m exception, replace_context, from_, with_traceback\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/pool/base.py:686\u001b[0m, in \u001b[0;36m_ConnectionRecord.__connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    684\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    685\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstarttime \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 686\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdbapi_connection \u001b[38;5;241m=\u001b[39m connection \u001b[38;5;241m=\u001b[39m \u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_invoke_creator\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    687\u001b[0m     pool\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreated new connection \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, connection)\n\u001b[1;32m    688\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfresh \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/create.py:574\u001b[0m, in \u001b[0;36mcreate_engine.<locals>.connect\u001b[0;34m(connection_record)\u001b[0m\n\u001b[1;32m    572\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m connection \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    573\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m connection\n\u001b[0;32m--> 574\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdialect\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcparams\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/sqlalchemy/engine/default.py:598\u001b[0m, in \u001b[0;36mDefaultDialect.connect\u001b[0;34m(self, *cargs, **cparams)\u001b[0m\n\u001b[1;32m    596\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39mcargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcparams):\n\u001b[1;32m    597\u001b[0m     \u001b[38;5;66;03m# inherits the docstring from interfaces.Dialect.connect\u001b[39;00m\n\u001b[0;32m--> 598\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdbapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcparams\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/env_01/lib/python3.10/site-packages/psycopg2/__init__.py:122\u001b[0m, in \u001b[0;36mconnect\u001b[0;34m(dsn, connection_factory, cursor_factory, **kwargs)\u001b[0m\n\u001b[1;32m    119\u001b[0m     kwasync[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124masync_\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124masync_\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    121\u001b[0m dsn \u001b[38;5;241m=\u001b[39m _ext\u001b[38;5;241m.\u001b[39mmake_dsn(dsn, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 122\u001b[0m conn \u001b[38;5;241m=\u001b[39m \u001b[43m_connect\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdsn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconnection_factory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconnection_factory\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwasync\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    123\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cursor_factory \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    124\u001b[0m     conn\u001b[38;5;241m.\u001b[39mcursor_factory \u001b[38;5;241m=\u001b[39m cursor_factory\n",
      "\u001b[0;31mOperationalError\u001b[0m: (psycopg2.OperationalError) connection to server at \"v2-db-easi-asia-eks.cluster-ro-czyydvizywt5.ap-southeast-1.rds.amazonaws.com\" (10.0.22.166), port 5432 failed: Connection timed out\n\tIs the server running on that host and accepting TCP/IP connections?\n\n(Background on this error at: https://sqlalche.me/e/14/e3q8)"
     ]
    }
   ],
   "source": [
    "# ══════════════════════════════════════════════════════════════════════════════\n",
    "# SETUP COGNITO AUTHENTICATION\n",
    "# ══════════════════════════════════════════════════════════════════════════════\n",
    "print(\"🔐 Step 1: Cognito Authentication Setup\")\n",
    "print(\"-\" * 70)\n",
    "\n",
    "# Setup Cognito authentication for S3 access\n",
    "auth = setup_cognito_auth('/media/x79/2A7D-FAA0/remote-sensing/train_files/crediential.txt')\n",
    "\n",
    "if auth:\n",
    "    print(\"\\n✅ Authentication successful!\")\n",
    "    print(\"   Ready to access S3 buckets with authenticated credentials\")\n",
    "else:\n",
    "    print(\"\\n⚠ Authentication failed - falling back to unsigned access\")\n",
    "\n",
    "print(\"\\n\" + \"=\" * 70)\n",
    "print(\"🚀 Step 2: Dask + Datacube Initialization\")\n",
    "print(\"-\" * 70)\n",
    "\n",
    "# Khởi tạo Dask + Datacube (use_gateway=False for local execution)\n",
    "cluster, client = notebook_utils.initialize_dask(use_gateway=False, workers=4)\n",
    "\n",
    "# Khai báo Datacube\n",
    "dc = datacube.Datacube()\n",
    "\n",
    "print(\"\\n✅ Dask + Datacube + S3 (Cognito authenticated) ready!\")\n",
    "print(f\"   Dask dashboard: {client.dashboard_link}\")\n",
    "print(\"=\" * 70)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5bc42a3c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common native CRS: EPSG:32648\n",
      "No datasets require offset correction\n",
      "The valid_data_mask and scale (no offset) have been applied to the reflectance bands\n",
      "✅ Sentinel-2 raw: FrozenMappingWarningOnValuesAccess({'time': 151, 'y': 8874, 'x': 9902})\n"
     ]
    }
   ],
   "source": [
    "# Cấu hình vùng và thời gian\n",
    "date_range    = (\"2022-09-01\", \"2023-10-01\")\n",
    "longtitude_range = (105.5, 106.4)\n",
    "latitude_range   = (9.2, 10.0)\n",
    "\n",
    "# Tải dữ liệu Sentinel-2\n",
    "data_sen2 = load_data(\n",
    "    dc=dc,\n",
    "    date_range=date_range,\n",
    "    longtitude_range=longtitude_range,\n",
    "    latitude_range=latitude_range,\n",
    ")\n",
    "print(f\"✅ Sentinel-2 raw: {data_sen2.dims}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ef51e7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bits</th>\n",
       "      <th>values</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>qa</th>\n",
       "      <td>[0, 1, 2, 3, 4, 5, 6, 7]</td>\n",
       "      <td>{'0': 'no data', '1': 'saturated or defective'...</td>\n",
       "      <td>Sen2Cor Scene Classification</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        bits  \\\n",
       "qa  [0, 1, 2, 3, 4, 5, 6, 7]   \n",
       "\n",
       "                                               values  \\\n",
       "qa  {'0': 'no data', '1': 'saturated or defective'...   \n",
       "\n",
       "                     description  \n",
       "qa  Sen2Cor Scene Classification  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'0': 'no data',\n",
       " '1': 'saturated or defective',\n",
       " '2': 'dark area pixels',\n",
       " '3': 'cloud shadows',\n",
       " '4': 'vegetation',\n",
       " '5': 'bare soils',\n",
       " '6': 'water',\n",
       " '7': 'unclassified',\n",
       " '8': 'cloud medium probability',\n",
       " '9': 'cloud high probability',\n",
       " '10': 'thin cirrus',\n",
       " '11': 'snow or ice'}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "ValueError",
     "evalue": "No `satellite_mission` was provided. Please specify either 'ls' or 's2' to ensure the \nfunction calculates indices using the correct spectral bands.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Tiền xử lý Sentinel-2: cloud mask + NDVI + resampling\u001b[39;00m\n\u001b[1;32m      2\u001b[0m data_clean \u001b[38;5;241m=\u001b[39m mask_clean(data_sen2)\n\u001b[0;32m----> 3\u001b[0m data_ndvi  \u001b[38;5;241m=\u001b[39m \u001b[43mcalculate_indices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata_clean\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mNDVI\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      4\u001b[0m data_fill  \u001b[38;5;241m=\u001b[39m fill_nan(data_ndvi)\n\u001b[1;32m      5\u001b[0m data_sen2_monthly \u001b[38;5;241m=\u001b[39m data_fill\u001b[38;5;241m.\u001b[39mresample(time\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m1MS\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mmean()\u001b[38;5;241m.\u001b[39mcompute()\n",
      "File \u001b[0;32m~/remote-sensing/deafrica_tools/bandindices.py:374\u001b[0m, in \u001b[0;36mcalculate_indices\u001b[0;34m(ds, index, collection, satellite_mission, custom_varname, normalise, drop, deep_copy)\u001b[0m\n\u001b[1;32m    368\u001b[0m \u001b[38;5;66;03m# Rename bands to a consistent format if depending on what satellite mission\u001b[39;00m\n\u001b[1;32m    369\u001b[0m \u001b[38;5;66;03m# is specified in `satellite_mission`. This allows the same index calculations\u001b[39;00m\n\u001b[1;32m    370\u001b[0m \u001b[38;5;66;03m# to be applied to all satellite missions. If no satellite mission was provided,\u001b[39;00m\n\u001b[1;32m    371\u001b[0m \u001b[38;5;66;03m# raise an exception.\u001b[39;00m\n\u001b[1;32m    372\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m satellite_mission \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 374\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    375\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo `satellite_mission` was provided. Please specify \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    376\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124meither \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mls\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m or \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124ms2\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to ensure the \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mfunction \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    377\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcalculates indices using the correct spectral \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    378\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbands.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    379\u001b[0m     )\n\u001b[1;32m    381\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m satellite_mission \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mls\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    382\u001b[0m     sr_max \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.0\u001b[39m\n",
      "\u001b[0;31mValueError\u001b[0m: No `satellite_mission` was provided. Please specify either 'ls' or 's2' to ensure the \nfunction calculates indices using the correct spectral bands."
     ]
    }
   ],
   "source": [
    "# Tiền xử lý Sentinel-2: cloud mask + NDVI + resampling\n",
    "data_clean = mask_clean(data_sen2)\n",
    "data_ndvi  = calculate_indices(data_clean, index=\"NDVI\", satellite_mission=\"s2\")\n",
    "data_fill  = fill_nan(data_ndvi)\n",
    "data_sen2_monthly = data_fill.resample(time=\"1MS\").mean().compute()\n",
    "print(f\"✅ S2 monthly shape: {data_sen2_monthly.dims}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0da4f86d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tải Sentinel-1 (SAR VV/VH)\n",
    "data_sen1 = load_data_sen1(\n",
    "    dc=dc,\n",
    "    date_range=date_range,\n",
    "    longtitude_range=longtitude_range,\n",
    "    latitude_range=latitude_range,\n",
    ")\n",
    "data_sen1_monthly = calculate_average(data_sen1, [\"VV\", \"VH\"], resample=\"1MS\").compute()\n",
    "print(f\"✅ S1 monthly shape: {data_sen1_monthly.dims}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "412b3716",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Ánh xạ nhãn lớp đất\n",
    "label_mapping = {\n",
    "    \"Lua tom\": \"0\", \"Lua\": \"1\", \"CHN\": \"2\", \"CLN\": \"3\",\n",
    "    \"TS\": \"4\", \"Song\": \"5\", \"Dat xay dung\": \"6\", \"Rung\": \"7\",\n",
    "}\n",
    "\n",
    "# Tải và ghép dữ liệu train từ S1 + S2\n",
    "train_data = load_train_data(label_mapping=label_mapping)\n",
    "X, y = get_data_sen1_and_sen2(train_data, data_sen2_monthly, data_sen1_monthly)\n",
    "\n",
    "# Chia tập train / val / test\n",
    "X_train, X_val, X_test, y_train, y_val, y_test = split_train_data(X, y, test_size=0.2, val_size=0.1)\n",
    "\n",
    "X_train_np = np.array(X_train, dtype=np.float32)\n",
    "X_val_np   = np.array(X_val,   dtype=np.float32)\n",
    "X_test_np  = np.array(X_test,  dtype=np.float32)\n",
    "y_train_np = np.array(y_train, dtype=np.int64)\n",
    "y_val_np   = np.array(y_val,   dtype=np.int64)\n",
    "y_test_np  = np.array(y_test,  dtype=np.int64)\n",
    "\n",
    "# Gộp train + val cho sklearn\n",
    "X_fit = np.concatenate([X_train_np, X_val_np], axis=0)\n",
    "y_fit = np.concatenate([y_train_np, y_val_np], axis=0)\n",
    "\n",
    "print(f\"✅ X_fit: {X_fit.shape}  |  X_test: {X_test_np.shape}\")\n",
    "print(f\"   Classes: {sorted(set(y_fit.tolist()))}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84a8a1d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "# ── Xây dựng và train mô hình Decision Tree ─────────────────────────────────\n",
    "model = DecisionTreeClassifier(\n",
    "    max_depth=30,\n",
    "    min_samples_leaf=2,\n",
    "    min_samples_split=5,\n",
    "    class_weight=\"balanced\",\n",
    "    random_state=42,\n",
    ")\n",
    "\n",
    "print(\"🚀 Training Decision Tree...\")\n",
    "model.fit(X_fit, y_fit)\n",
    "\n",
    "val_acc = model.score(X_val_np, y_val_np)\n",
    "print(f\"✅ Training hoàn tất!  Depth: {model.get_depth()}  \"\n",
    "      f\"Leaves: {model.get_n_leaves()}  Val accuracy: {val_acc:.4f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8248d748",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "# ═══════════════════════════════════════════════════════════════════════════════\n",
    "# PHÂN TÍCH ĐIỂM HỘI TỤ — Decision Tree\n",
    "# Phương pháp: quét max_depth từ 1→50 và theo dõi train/val accuracy\n",
    "# Điểm hội tụ = độ sâu tại đó val_acc đạt cực đại rồi bắt đầu giảm (overfitting)\n",
    "# ═══════════════════════════════════════════════════════════════════════════════\n",
    "DEPTH_RANGE = list(range(1, 51))\n",
    "THRESHOLD   = 0.001    # cải thiện val_acc < 0.1% → coi là hội tụ\n",
    "\n",
    "train_accs_d, val_accs_d = [], []\n",
    "print(\"🔍 Phân tích hội tụ theo max_depth ...\")\n",
    "for d in DEPTH_RANGE:\n",
    "    m = DecisionTreeClassifier(\n",
    "        min_samples_leaf=2, min_samples_split=5,\n",
    "        class_weight=\"balanced\", random_state=42, max_depth=d,\n",
    "    )\n",
    "    m.fit(X_fit, y_fit)\n",
    "    train_accs_d.append(m.score(X_fit,    y_fit))\n",
    "    val_accs_d.append(  m.score(X_val_np, y_val_np))\n",
    "\n",
    "train_accs_d = np.array(train_accs_d)\n",
    "val_accs_d   = np.array(val_accs_d)\n",
    "improvements = np.diff(val_accs_d)\n",
    "\n",
    "# ── Tìm điểm hội tụ ───────────────────────────────────────────────────────────\n",
    "best_depth      = DEPTH_RANGE[int(np.argmax(val_accs_d))]\n",
    "best_val_acc    = float(np.max(val_accs_d))\n",
    "\n",
    "# Điểm hội tụ sớm: lần đầu cải thiện < threshold\n",
    "conv_depth = None\n",
    "for i, imp in enumerate(improvements):\n",
    "    if abs(imp) < THRESHOLD:\n",
    "        conv_depth = DEPTH_RANGE[i + 1]\n",
    "        break\n",
    "\n",
    "# Điểm overfit: val_acc bắt đầu giảm so với peak\n",
    "overfit_depth = None\n",
    "peak_idx = int(np.argmax(val_accs_d))\n",
    "for i in range(peak_idx + 1, len(val_accs_d)):\n",
    "    if val_accs_d[i] < best_val_acc - 0.005:   # giảm > 0.5%\n",
    "        overfit_depth = DEPTH_RANGE[i]\n",
    "        break\n",
    "\n",
    "# Khoảng cách train-val (generalization gap)\n",
    "gap = train_accs_d - val_accs_d\n",
    "\n",
    "# ── Vẽ đồ thị ─────────────────────────────────────────────────────────────────\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "# --- Trái: accuracy curves ---\n",
    "axes[0].plot(DEPTH_RANGE, train_accs_d, \"b-o\", markersize=3, label=\"Train\")\n",
    "axes[0].plot(DEPTH_RANGE, val_accs_d,   \"g-o\", markersize=3, label=\"Val\")\n",
    "axes[0].axvline(x=best_depth, color=\"red\", linestyle=\"--\", linewidth=1.5,\n",
    "                label=f\"Best depth={best_depth} ({best_val_acc*100:.2f}%)\")\n",
    "if conv_depth:\n",
    "    axes[0].axvline(x=conv_depth, color=\"orange\", linestyle=\":\", linewidth=1.5,\n",
    "                    label=f\"Hội tụ depth={conv_depth}\")\n",
    "if overfit_depth:\n",
    "    axes[0].axvline(x=overfit_depth, color=\"purple\", linestyle=\"-.\", linewidth=1.5,\n",
    "                    label=f\"Overfit depth={overfit_depth}\")\n",
    "axes[0].set_xlabel(\"max_depth\")\n",
    "axes[0].set_ylabel(\"Accuracy\")\n",
    "axes[0].set_title(\"Train / Val Accuracy vs max_depth\")\n",
    "axes[0].legend(fontsize=8)\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# --- Giữa: marginal improvement ---\n",
    "axes[1].bar(DEPTH_RANGE[1:], improvements * 100,\n",
    "            color=[\"green\" if v > 0 else \"red\" for v in improvements], alpha=0.7)\n",
    "axes[1].axhline(y=0, color=\"black\", linewidth=0.8)\n",
    "axes[1].axhline(y=THRESHOLD * 100, color=\"orange\", linestyle=\"--\",\n",
    "                label=f\"Threshold={THRESHOLD*100:.2f}%\")\n",
    "if conv_depth:\n",
    "    axes[1].axvline(x=conv_depth, color=\"orange\", linestyle=\":\", linewidth=1.5,\n",
    "                    label=f\"Hội tụ depth={conv_depth}\")\n",
    "axes[1].set_xlabel(\"max_depth\")\n",
    "axes[1].set_ylabel(\"ΔVal Accuracy (%)\")\n",
    "axes[1].set_title(\"Marginal Val Improvement per Depth Step\")\n",
    "axes[1].legend(fontsize=8)\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "# --- Phải: generalization gap ---\n",
    "axes[2].fill_between(DEPTH_RANGE, gap * 100, alpha=0.5, color=\"tomato\", label=\"Gap = Train − Val\")\n",
    "axes[2].plot(DEPTH_RANGE, gap * 100, \"r-o\", markersize=3)\n",
    "if best_depth:\n",
    "    axes[2].axvline(x=best_depth, color=\"red\", linestyle=\"--\", linewidth=1.5,\n",
    "                    label=f\"Best depth={best_depth}\")\n",
    "axes[2].set_xlabel(\"max_depth\")\n",
    "axes[2].set_ylabel(\"Gap (%)\")\n",
    "axes[2].set_title(\"Generalization Gap (Overfitting Risk)\")\n",
    "axes[2].legend(fontsize=8)\n",
    "axes[2].grid(True, alpha=0.3)\n",
    "\n",
    "plt.suptitle(\"Decision Tree — Convergence Analysis\", fontsize=13, fontweight=\"bold\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# ── Tổng kết ──────────────────────────────────────────────────────────────────\n",
    "print(f\"\\n{'═'*58}\")\n",
    "print(f\"  Độ sâu TỐI ƯU (best val acc) : max_depth = {best_depth}  ({best_val_acc*100:.4f}%)\")\n",
    "if conv_depth:\n",
    "    print(f\"  Điểm HỘI TỤ (Δacc < {THRESHOLD*100:.1f}%)  : max_depth = {conv_depth}\")\n",
    "if overfit_depth:\n",
    "    print(f\"  Điểm OVERFIT bắt đầu         : max_depth ≥ {overfit_depth}\")\n",
    "    print(f\"  → Nên dùng max_depth ≤ {best_depth} để tránh overfit\")\n",
    "print(f\"{'═'*58}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5660e2ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# ── Đánh giá trên tập test ─────────────────────────────────────────────────────\n",
    "y_pred = model.predict(X_test_np)\n",
    "\n",
    "acc = accuracy_score(y_test_np, y_pred)\n",
    "print(f\"Test Accuracy : {acc:.4f} ({acc*100:.2f}%)\\n\")\n",
    "print(classification_report(y_test_np, y_pred, digits=4))\n",
    "\n",
    "# ── Feature importance ──────────────────────────────────────────────────────────\n",
    "feat_imp = model.feature_importances_\n",
    "idx = feat_imp.argsort()[::-1][:20]\n",
    "plt.figure(figsize=(12, 4))\n",
    "plt.bar(range(len(idx)), feat_imp[idx])\n",
    "plt.xticks(range(len(idx)), idx, rotation=45)\n",
    "plt.title(\"Top-20 Feature Importances\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# ── Confusion matrix ────────────────────────────────────────────────────────────\n",
    "class_names = list(label_mapping.keys())\n",
    "cm = confusion_matrix(y_test_np, y_pred)\n",
    "plt.figure(figsize=(9, 7))\n",
    "sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Greens\",\n",
    "            xticklabels=class_names, yticklabels=class_names)\n",
    "plt.xlabel(\"Predicted\")\n",
    "plt.ylabel(\"Actual\")\n",
    "plt.title(\"Confusion Matrix — Decision Tree\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e416c2aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib, json\n",
    "from datetime import datetime\n",
    "\n",
    "# ── Lưu mô hình ────────────────────────────────────────────────────────────────\n",
    "model_path = \"model_decision_tree_land_use.joblib\"\n",
    "joblib.dump(model, model_path)\n",
    "print(f\"✅ Model saved → {model_path}\")\n",
    "\n",
    "# ── Lưu thông tin mô hình ──────────────────────────────────────────────────────\n",
    "info = {\n",
    "    \"model_type\": \"DecisionTree\",\n",
    "    \"max_depth\": model.get_depth(),\n",
    "    \"n_leaves\": model.get_n_leaves(),\n",
    "    \"class_weight\": \"balanced\",\n",
    "    \"n_features\": int(X_fit.shape[1]),\n",
    "    \"label_mapping\": label_mapping,\n",
    "    \"test_accuracy\": float(acc),\n",
    "    \"train_samples\": int(len(X_fit)),\n",
    "    \"test_samples\": int(len(X_test_np)),\n",
    "    \"saved_at\": datetime.now().isoformat(),\n",
    "}\n",
    "info_path = \"model_decision_tree_land_use_info.json\"\n",
    "with open(info_path, \"w\") as f:\n",
    "    json.dump(info, f, indent=2, ensure_ascii=False)\n",
    "print(f\"✅ Info saved  → {info_path}\")\n",
    "print(json.dumps(info, indent=2, ensure_ascii=False))\n",
    "\n",
    "# ── Đóng kết nối Dask ──────────────────────────────────────────────────────────\n",
    "try:\n",
    "    client.close()\n",
    "    cluster.close()\n",
    "    print(\"✅ Dask cluster closed.\")\n",
    "except Exception:\n",
    "    pass\n"
   ]
  }
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