{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "# Movies dataset\n",
    "\n",
    "This notebook loads a small movie-domain graph into both `NetworkXGraph` and\n",
    "`Neo4jGraph`.\n",
    "\n",
    "Dataset notes:\n",
    "- movie nodes with title and IMDb id\n",
    "- genre nodes linked with `IN_GENRE`\n",
    "- source is a public sample API, with a bundled fallback for offline use"
   ],
   "id": "32dd24794d06ada8"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import importlib.util\n",
    "\n",
    "# Comprovació de presència del paquet\n",
    "package_to_check = 'drm'\n",
    "spec = importlib.util.find_spec(package_to_check)\n",
    "\n",
    "if spec is None:\n",
    "    print(f'⚠️ {package_to_check} no està instal·lat. Iniciant instal·lació...')\n",
    "    %pip install -q --upgrade drm-tools\n",
    "    print(\"✅ Instal·lació completada. L'estat del kernel PODRIA requerir un reinici.\")\n",
    "else:\n",
    "    print(f'✅ {package_to_check} ja està present al sistema. Saltant instal·lació.')\n"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "import os\n",
    "\n",
    "from drm import Neo4jGraph, NetworkXGraph\n",
    "from drm.exemples import load_movies_sample\n",
    "\n",
    "\n",
    "def neo4j_config(default_target=\"DEV\"):\n",
    "    target = os.environ.get(\"NEO4J_TARGET\", default_target).upper()\n",
    "    prefix = f\"NEO4J_{target}_\"\n",
    "    return {\n",
    "        \"target\": target,\n",
    "        \"url\": os.environ.get(f\"{prefix}URL\", os.environ.get(\"NEO4J_URL\", \"bolt://localhost:7687\")),\n",
    "        \"user\": os.environ.get(f\"{prefix}USER\", os.environ.get(\"NEO4J_USER\", \"neo4j\")),\n",
    "        \"password\": os.environ.get(f\"{prefix}PASSWORD\", os.environ.get(\"NEO4J_PASSWORD\", \"secret\")),\n",
    "        \"database\": os.environ.get(f\"{prefix}DATABASE\", os.environ.get(\"NEO4J_DATABASE\", \"neo4j\")),\n",
    "    }"
   ],
   "id": "23fd05f52c2f1764"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## NetworkXGraph",
   "id": "30e059e774c65fe6"
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "nx_graph = NetworkXGraph()\n# load_movies_sample works with both NetworkXGraph (in-memory) and Neo4jGraph (persistent)\nnx_stats = load_movies_sample(nx_graph, limit=25)\nprint(\"NetworkX stats:\", nx_stats)\nnx_graph.close()",
   "id": "ddbdf9a1eec3d9c3"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## Neo4jGraph",
   "id": "b9a46c6da226f5a2"
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "cfg = neo4j_config()\n",
    "print(\"Using Neo4j target:\", cfg[\"target\"])\n",
    "neo4j_graph = Neo4jGraph(\n",
    "    url=cfg[\"url\"],\n",
    "    user=cfg[\"user\"],\n",
    "    password=cfg[\"password\"],\n",
    "    database=cfg[\"database\"],\n",
    ")\n",
    "try:\n",
    "    neo4j_stats = load_movies_sample(neo4j_graph, limit=25)\n",
    "    print(\"Neo4j stats:\", neo4j_stats)\n",
    "finally:\n",
    "    neo4j_graph.close()\n"
   ],
   "id": "99d65580fda5ec65"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (drm-tool)",
   "language": "python",
   "name": "drm-tool"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}