{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3e4eb758",
   "metadata": {},
   "source": [
    "## Hello World"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2460ecfc",
   "metadata": {},
   "source": [
    "In this demo notebook we will showcase a self-sovereign data scenario:\n",
    "\n",
    "- we will create a table in a shared data collection, that can be read by anyone in the network\n",
    "- mark some fields as personal information that is not to be shared\n",
    "- write a record\n",
    "- read it locally (and be able to see all fields)\n",
    "- read all records from a remote server\n",
    "   \n",
    "The default Weavechain node installation is preconfigured to support this scenario (by connecting to a public weave, having a *shared* data collection defined and mapped to a in-process SQLite instance and read rights for that collection already given)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e0dbccf",
   "metadata": {},
   "source": [
    "### 1. Create an API session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d96cfcaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"res\":\"ok\",\"data\":\"pong 1674668207181\"}\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from weaveapi.records import *\n",
    "from weaveapi.options import *\n",
    "from weaveapi.filter import *\n",
    "from weaveapi.weaveh import *\n",
    "\n",
    "WEAVE_CONFIG = \"config/demo_client_local.config\"\n",
    "nodeApi, session = connect_weave_api(WEAVE_CONFIG)\n",
    "\n",
    "scope = \"shared\"\n",
    "table = \"directory\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac907012",
   "metadata": {},
   "source": [
    "### 2. Create a local table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b4a5e29",
   "metadata": {},
   "source": [
    "- we drop the existing table if already existing and re-create it from scratch\n",
    "- a weavechain node can also connect to existing tables, reading their structure, but in this case we create it via the API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17b212cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'res': 'ok', 'target': {'operationType': 'CREATE_TABLE', 'organization': 'weavedemo', 'account': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg', 'scope': 'shared', 'table': 'directory'}}\n"
     ]
    }
   ],
   "source": [
    "layout = { \n",
    "    \"columns\": { \n",
    "        \"id\": { \"type\": \"LONG\", \"isIndexed\": True, \"isUnique\": True, \"isNullable\": False },\n",
    "        \"name_nickname\": { \"type\": \"STRING\" },\n",
    "        \"name_last\": { \"type\": \"STRING\" },\n",
    "        \"name_first\": { \"type\": \"STRING\" },\n",
    "        \"birthday\": { \"type\": \"STRING\" },\n",
    "        \"email_personal\": { \"type\": \"STRING\" },\n",
    "        \"phone_number\": { \"type\": \"STRING\" },\n",
    "        \"address_country\": { \"type\": \"STRING\" },\n",
    "        \"address_summary\": { \"type\": \"STRING\" },\n",
    "        \"address_timezone\": { \"type\": \"STRING\" },\n",
    "        \"linkedin_url\": { \"type\": \"STRING\" },\n",
    "        \"discord_username\": { \"type\": \"STRING\" },\n",
    "        \"telegram_username\": { \"type\": \"STRING\" },\n",
    "        \"ethereum_wallet_address\": { \"type\": \"STRING\" }\n",
    "    }, \n",
    "    \"idColumnIndex\": 0, \n",
    "    \"isLocal\": False,\n",
    "    \"applyReadTransformations\": True\n",
    "}\n",
    "\n",
    "nodeApi.dropTable(session, scope, table).get()\n",
    "reply = nodeApi.createTable(session, scope, table, CreateOptions(False, False, layout)).get()\n",
    "print(reply)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03d82eca",
   "metadata": {},
   "source": [
    "### 3. Mark some fields for erasure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "817c68c3",
   "metadata": {},
   "source": [
    "- the purpose is to protect certain fields when shared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "18be11b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'res': 'ok', 'target': {'operationType': 'UPDATE_LAYOUT', 'organization': 'weavedemo', 'account': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg', 'scope': 'shared', 'table': 'directory'}}\n"
     ]
    }
   ],
   "source": [
    "reply = nodeApi.getTableDefinition(session, scope, table).get()\n",
    "#print(reply)\n",
    "layout = json.loads(reply[\"data\"])[\"layout\"]\n",
    "layout[\"columns\"]\n",
    "\n",
    "newLayout = layout.copy()\n",
    "del newLayout[\"layout\"]\n",
    "del newLayout[\"indexes\"]\n",
    "del newLayout[\"columnNames\"]\n",
    "newLayout[\"columns\"] = { i[\"columnName\"]: i for i in layout[\"columns\"]}\n",
    "\n",
    "newLayout[\"columns\"][\"phone_number\"][\"readTransform\"] = \"ERASURE\"\n",
    "newLayout[\"columns\"][\"address_summary\"][\"readTransform\"] = \"ERASURE\"\n",
    "newLayout[\"columns\"][\"ethereum_wallet_address\"][\"readTransform\"] = \"ERASURE\"\n",
    "newLayout[\"columns\"][\"birthday\"][\"readTransform\"] = \"ERASURE\"\n",
    "\n",
    "reply = nodeApi.updateLayout(session, scope, table, newLayout).get()\n",
    "print(reply)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "256f11bb",
   "metadata": {},
   "source": [
    "### 4. Write a record in the local storage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ddea986d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'res': 'ok', 'target': {'operationType': 'WRITE', 'organization': 'weavedemo', 'account': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg', 'scope': 'shared', 'table': 'directory'}, 'data': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg,USr/yA9isOGMQ3/gNenSpZLi2VhwIP9x6UacGTkuBVc=,4YjeYJpUrcrpCf4oTEvuAspeJYiQYEy1AvTgbLsTo8UNzYbHKbNiV6jZihb7si5yc8MbXcr16kmGrieJgNW8s75e'}\n"
     ]
    }
   ],
   "source": [
    "records = Records(table, [ \n",
    "    [ 1, 'Nickname', 'Last Name', 'First name', '1980-01-01', 'email@gmail.com', '+40712345678', 'US', 'Secret', 'EST', 'https://www.linkedin.com/in/linkedin/', 'discord#1234', '@telegram', '0xwallet' ]\n",
    "])\n",
    "reply = nodeApi.write(session, scope, records, WRITE_DEFAULT).get()\n",
    "print(reply)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1c4be2c",
   "metadata": {},
   "source": [
    "### 5. Read the local record, from the local storage"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "996711b0",
   "metadata": {},
   "source": [
    "- since we read with the owner key and from the local node, we expect the records to have all fields visible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cb2dd661",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>id</th>\n",
       "      <th>name_nickname</th>\n",
       "      <th>name_last</th>\n",
       "      <th>name_first</th>\n",
       "      <th>birthday</th>\n",
       "      <th>email_personal</th>\n",
       "      <th>phone_number</th>\n",
       "      <th>address_country</th>\n",
       "      <th>address_summary</th>\n",
       "      <th>address_timezone</th>\n",
       "      <th>linkedin_url</th>\n",
       "      <th>discord_username</th>\n",
       "      <th>telegram_username</th>\n",
       "      <th>ethereum_wallet_address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Nickname</td>\n",
       "      <td>Last Name</td>\n",
       "      <td>First name</td>\n",
       "      <td>1980-01-01</td>\n",
       "      <td>email@gmail.com</td>\n",
       "      <td>+40712345678</td>\n",
       "      <td>US</td>\n",
       "      <td>Secret</td>\n",
       "      <td>EST</td>\n",
       "      <td>https://www.linkedin.com/in/linkedin/</td>\n",
       "      <td>discord#1234</td>\n",
       "      <td>@telegram</td>\n",
       "      <td>0xwallet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id name_nickname  name_last  name_first    birthday   email_personal  \\\n",
       "0   1      Nickname  Last Name  First name  1980-01-01  email@gmail.com   \n",
       "\n",
       "   phone_number address_country address_summary address_timezone  \\\n",
       "0  +40712345678              US          Secret              EST   \n",
       "\n",
       "                            linkedin_url discord_username telegram_username  \\\n",
       "0  https://www.linkedin.com/in/linkedin/     discord#1234         @telegram   \n",
       "\n",
       "  ethereum_wallet_address  \n",
       "0                0xwallet  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scope = \"shared\"\n",
    "table = \"directory\"\n",
    "\n",
    "reply = nodeApi.read(session, scope, table, None, READ_DEFAULT_NO_CHAIN).get()\n",
    "#print(reply)\n",
    "df = pd.DataFrame(reply[\"data\"])\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49d86941",
   "metadata": {},
   "source": [
    "### 5. Connect to proxy server"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6f52c82f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"res\":\"ok\",\"data\":\"pong 1674668209764\"}\n"
     ]
    }
   ],
   "source": [
    "WEAVE_CONFIG_REMOTE = \"config/demo_client_remote.config\"\n",
    "nodeApi2, session2 = connect_weave_api(WEAVE_CONFIG_REMOTE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9eb7b533",
   "metadata": {},
   "source": [
    "### 6. Read all shared records"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd6c037d",
   "metadata": {},
   "source": [
    "- we expect the records that we don't own to have certain fields erased for privacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5015c87f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>id</th>\n",
       "      <th>name_nickname</th>\n",
       "      <th>name_last</th>\n",
       "      <th>name_first</th>\n",
       "      <th>birthday</th>\n",
       "      <th>email_personal</th>\n",
       "      <th>phone_number</th>\n",
       "      <th>address_country</th>\n",
       "      <th>address_summary</th>\n",
       "      <th>address_timezone</th>\n",
       "      <th>linkedin_url</th>\n",
       "      <th>discord_username</th>\n",
       "      <th>telegram_username</th>\n",
       "      <th>ethereum_wallet_address</th>\n",
       "      <th>_nodeKey</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Nickname</td>\n",
       "      <td>Last Name</td>\n",
       "      <td>First name</td>\n",
       "      <td></td>\n",
       "      <td>email@gmail.com</td>\n",
       "      <td></td>\n",
       "      <td>US</td>\n",
       "      <td></td>\n",
       "      <td>EST</td>\n",
       "      <td>https://www.linkedin.com/in/linkedin/</td>\n",
       "      <td>discord#1234</td>\n",
       "      <td>@telegram</td>\n",
       "      <td></td>\n",
       "      <td>weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name_nickname  name_last  name_first birthday   email_personal  \\\n",
       "0  1.0      Nickname  Last Name  First name           email@gmail.com   \n",
       "\n",
       "  phone_number address_country address_summary address_timezone  \\\n",
       "0                           US                              EST   \n",
       "\n",
       "                            linkedin_url discord_username telegram_username  \\\n",
       "0  https://www.linkedin.com/in/linkedin/     discord#1234         @telegram   \n",
       "\n",
       "  ethereum_wallet_address                                           _nodeKey  \n",
       "0                          weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scope = \"shared\"\n",
    "table = \"directory\"\n",
    "\n",
    "reply = nodeApi2.read(session2, scope, table, None, READ_DEFAULT_MUX_NO_CHAIN).get()\n",
    "#print(reply)\n",
    "df = pd.DataFrame(reply[\"data\"].get(\"result\"))\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8200fb82",
   "metadata": {},
   "source": [
    "### 7. Check the local node for all operations on the shared data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9532baa7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>history</th>\n",
       "      <th>record</th>\n",
       "      <th>recordId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[{'account': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqW...</td>\n",
       "      <td>[1, Nickname, Last Name, First name, 1980-01-0...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             history  \\\n",
       "1  [{'account': 'weaveyh5R1ytoUCZnr3JjqMDfhUrXwqW...   \n",
       "\n",
       "                                              record recordId  \n",
       "1  [1, Nickname, Last Name, First name, 1980-01-0...        1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account</th>\n",
       "      <th>operation</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>ip</th>\n",
       "      <th>apiKey</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg</td>\n",
       "      <td>write</td>\n",
       "      <td>1674668207300999936</td>\n",
       "      <td>127.0.0.1</td>\n",
       "      <td>d2f86331322b497fb644e09862b681fdc2a9aa5180d0011c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg</td>\n",
       "      <td>read</td>\n",
       "      <td>1674668207315000064</td>\n",
       "      <td>127.0.0.1</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>weavexUTKAe7J5faqmiq94DXXWntyRBA8bPwmrUbCtebxWd3f</td>\n",
       "      <td>read</td>\n",
       "      <td>1674668211353999872</td>\n",
       "      <td>34.28.85.136</td>\n",
       "      <td>1e2f9e5e7c9f406081256bf5709dd1eae5ccf2e324469e1c</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             account operation  \\\n",
       "0  weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg     write   \n",
       "1  weaveyh5R1ytoUCZnr3JjqMDfhUrXwqWC2EWnZX3q7krKLPcg      read   \n",
       "2  weavexUTKAe7J5faqmiq94DXXWntyRBA8bPwmrUbCtebxWd3f      read   \n",
       "\n",
       "             timestamp            ip  \\\n",
       "0  1674668207300999936     127.0.0.1   \n",
       "1  1674668207315000064     127.0.0.1   \n",
       "2  1674668211353999872  34.28.85.136   \n",
       "\n",
       "                                             apiKey  \n",
       "0  d2f86331322b497fb644e09862b681fdc2a9aa5180d0011c  \n",
       "1  d2f86331322b497fb644e09862b681fdc2a9aa5180d0011c  \n",
       "2  1e2f9e5e7c9f406081256bf5709dd1eae5ccf2e324469e1c  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reply = nodeApi.history(session, scope, table, None, HISTORY_DEFAULT).get()\n",
    "#print(reply)\n",
    "df = pd.DataFrame(reply[\"data\"]).transpose()\n",
    "display(df)\n",
    "\n",
    "pd.DataFrame(df.iloc[0][\"history\"])"
   ]
  }
 ],
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