{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "## This notebook shows some example gremlin queries using nodejs gremlin driver. Driver details are here: https://www.npmjs.com/package/gremlin. \n",
    "\n",
    "## You will use PixieDust extension that enables a Jupyter Notebook user to invoke Node.js commands.\n",
    "\n"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Install pixiedust_node"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "!pip install pixiedust_node"
   ],
   "outputs": [],
   "metadata": {
    "scrolled": true
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Import pixiedust_node"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "import pixiedust_node"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Install gremlin javascript driver"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "# install node packages\n",
    "npm.install('gremlin')\n",
    "npm.install('uuid')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node \n",
    "\n",
    "const { v4: uuidv4 } = require('uuid');\n",
    "const gremlin = require('gremlin');\n",
    "const traversal = gremlin.process.AnonymousTraversalSource.traversal;\n",
    "const DriverRemoteConnection = gremlin.driver.DriverRemoteConnection\n",
    "\n",
    "const { cardinality: { single } } = gremlin.process;\n",
    "const __ = gremlin.process.statics;\n",
    "const column = gremlin.process.column\n",
    "const direction = gremlin.process.direction\n",
    "const p = gremlin.process.P\n",
    "const textp = gremlin.process.TextP\n",
    "const pick = gremlin.process.pick\n",
    "const pop = gremlin.process.pop\n",
    "const order = gremlin.process.order\n",
    "const scope = gremlin.process.scope\n",
    "const t = gremlin.process.t\n",
    "\n",
    "const ClusterEndpoint = \"<ClusterEndpoint>\";\n",
    "const Port = \"Port\";\n",
    "\n",
    "const g = traversal().withRemote(new DriverRemoteConnection(`wss://${ClusterEndpoint}:${Port}/gremlin`));\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Create Single Vertex"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "var personId = uuidv4();\n",
    "\n",
    "try {\n",
    "    const queryPromise =  g.addV('person').property(t.id, personId)\n",
    "            .property('email','user@domain.com')\n",
    "            .property(single, 'firstname', 'firstname')\n",
    "            .property(single, 'lastname', 'lastname')\n",
    "            .next();\n",
    "    \n",
    "    queryPromise.then(data => {\n",
    "        console.log(data);\n",
    "    })\n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "var movieId = uuidv4();\n",
    "\n",
    "try {\n",
    "    const queryPromise =  g.addV('movie')\n",
    "            .property(t.id, movieId)\n",
    "            .property(single, 'title', 'movietitle')\n",
    "            .next();\n",
    "    \n",
    "    queryPromise.then(data => {\n",
    "        console.log(JSON.stringify(data));\n",
    "    })\n",
    "\n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Add edges between existing vertices"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "try {\n",
    "    const queryPromise =  g.addE(\"watched\")\n",
    "            .from_(__.V(personId)).to(__.V(movieId))\n",
    "            .next();\n",
    "    \n",
    "    queryPromise.then(data => {\n",
    "        console.log(data.value);\n",
    "    })\n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Add multiple vertices and edges"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "try {\n",
    "    const queryPromise =  g.addV('person').property(t.id, uuidv4())\n",
    "            .property('email', \"user@domain.com\")\n",
    "            .property(single, 'firstname', 'firstname')\n",
    "            .property(single, 'lastname', 'lastname')\n",
    "            .as(\"user\")\n",
    "            .addV('movie')\n",
    "            .property(t.id, uuidv4())\n",
    "            .property(single, 'title', 'movietitle')\n",
    "            .as(\"movie\")\n",
    "            .addE(\"watched\")\n",
    "            .from_('user').to('movie')\n",
    "            .next();\n",
    "    \n",
    "    queryPromise.then(data => {\n",
    "        console.log(data);\n",
    "    })\n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Read vertex and its attributes"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "try {\n",
    "    \n",
    "    const getPersonPromise= g.V().hasLabel(\"movie\").valueMap(true).limit(10).toList();\n",
    "    \n",
    "    console.log(\"\\n\");\n",
    "    console.log(\"id|label|title\");\n",
    "                \n",
    "    getPersonPromise.then(data => {\n",
    "        data.map(item => {\n",
    "            console.log(item.get(t.id) + \"|\" + item.get(t.label) + \"|\" + item.get(\"title\"))\n",
    "        });\n",
    "    });\n",
    "    \n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Read vertex connections"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "try {\n",
    "    \n",
    "    const getPersonPromise= g.V(personId).out(\"watched\").valueMap(true).limit(10).toList();\n",
    "    \n",
    "    getPersonPromise.then(data => {\n",
    "        data.forEach(item => {\n",
    "            console.log(item);\n",
    "        });\n",
    "    });\n",
    "    \n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "%%node\n",
    "\n",
    "function formatAndPrint(data){\n",
    "     console.log(data.get(\"personid\").padEnd(20,\" \") + data.get(\"movies\")[0].get(\"title\"));\n",
    "}\n",
    "\n",
    "try {\n",
    "    \n",
    "    const getPersonPromise = g.V(personId).project('personid','movies')\n",
    "                                            .by(\"email\").by(__.out(\"watched\").valueMap(\"title\").fold())\n",
    "                                            .limit(10).toList();\n",
    "    console.log(\"\\n\");\n",
    "    console.log(\"Email\".padEnd(20,\" \") + \"Title\".padEnd(20,\" \"));\n",
    "    console.log(\"\".padEnd(50,\"_\"));\n",
    "    \n",
    "    getPersonPromise.then(data => {\n",
    "        data.forEach(item => { \n",
    "            formatAndPrint(item);\n",
    "        });      \n",
    "    });  \n",
    "}\n",
    "catch(ex){\n",
    "    console.log(ex);\n",
    "}"
   ],
   "outputs": [],
   "metadata": {}
  }
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