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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e838ff21",
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "\n",
    "\n",
    "def csv_to_tag_lists(csv_path: str) -> dict:\n",
    "    read_tags = []\n",
    "    write_tags = []\n",
    "\n",
    "    def to_float(val):\n",
    "        try:\n",
    "            return float(str(val).strip())\n",
    "        except Exception:\n",
    "            return None\n",
    "\n",
    "    with open(csv_path, newline='', encoding='utf-8') as f:\n",
    "        reader = csv.DictReader(f)\n",
    "        for row in reader:\n",
    "            # Basic normalization\n",
    "            op = (row.get('operation') or '').strip()\n",
    "\n",
    "            if op == 'READ':\n",
    "                # Build common tag payload with required mappings\n",
    "                tag = {\n",
    "                    'server_id': '1',\n",
    "                    'tag_address': row.get('opc_tag'),\n",
    "                    'tag_name': row.get('name'),\n",
    "                    'data_range': [to_float(row.get('min_value')), to_float(row.get('max_value'))],\n",
    "                    'aggr_func': row.get('aggregation_func').lower(),\n",
    "                    # keep other fields with their original names\n",
    "                    'frequency': row.get('frequency'),\n",
    "                    'local': row.get('local'),\n",
    "                    'area': row.get('area'),\n",
    "                    'description': row.get('description'),\n",
    "                }\n",
    "\n",
    "                read_tags.append(tag)\n",
    "\n",
    "            else:\n",
    "                tag = {\n",
    "                    'server_id': '1',\n",
    "                    'addr': row.get('opc_tag'),\n",
    "                    'tag_name': row.get('name'),\n",
    "                    'local': row.get('local'),\n",
    "                    'area': row.get('area'),\n",
    "                    'description': row.get('description'),\n",
    "                }\n",
    "\n",
    "            if op == 'WRITE_PREDICTION':\n",
    "                tag['type'] = 'prediction'\n",
    "                write_tags.append(tag)\n",
    "            elif op == 'WRITE_CONFIDENCE':\n",
    "                tag['type'] = 'confidence'\n",
    "                write_tags.append(tag)\n",
    "            # ignore any other operation values silently\n",
    "\n",
    "    return {'read_tags': read_tags, 'write_tags': write_tags}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4621cd43",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "file_names = ['Courier - Página1.csv']\n",
    "\n",
    "for file_name in file_names:\n",
    "    write_file = file_name.replace('.csv', '.json')\n",
    "\n",
    "    with open(write_file, 'w', encoding='utf-8') as f:\n",
    "        json.dump(csv_to_tag_lists(file_name), f, indent=2, ensure_ascii=False)"
   ]
  }
 ],
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