Database_2_Mongodb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1c8a34bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pymongo in c:\\users\\naman jain\\anaconda3\\lib\\site-packages (3.12.1)\n"
     ]
    }
   ],
   "source": [
    "!python -m pip install pymongo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2cd69bfa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pymongo[srv] in c:\\users\\naman jain\\anaconda3\\lib\\site-packages (3.12.1)\n",
      "Requirement already satisfied: dnspython<3.0.0,>=1.16.0 in c:\\users\\naman jain\\anaconda3\\lib\\site-packages (from pymongo[srv]) (2.1.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pymongo[srv] # for cloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ba7470b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymongo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9b84fbcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# connection string to mongo atlas with userid and password"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0ac9c1e6",
   "metadata": {},
   "outputs": [
    {
     "ename": "ConfigurationError",
     "evalue": "The DNS operation timed out after 21.107285261154175 seconds",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTimeout\u001b[0m                                   Traceback (most recent call last)",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\srv_resolver.py:88\u001b[0m, in \u001b[0;36m_SrvResolver._resolve_uri\u001b[1;34m(self, encapsulate_errors)\u001b[0m\n\u001b[0;32m     87\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m---> 88\u001b[0m     results \u001b[38;5;241m=\u001b[39m \u001b[43m_resolve\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_mongodb._tcp.\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__fqdn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mSRV\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m     89\u001b[0m \u001b[43m                       \u001b[49m\u001b[43mlifetime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__connect_timeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     90\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\srv_resolver.py:46\u001b[0m, in \u001b[0;36m_resolve\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(resolver, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mresolve\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m     45\u001b[0m     \u001b[38;5;66;03m# dnspython >= 2\u001b[39;00m\n\u001b[1;32m---> 46\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mresolver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresolve\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\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[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     47\u001b[0m \u001b[38;5;66;03m# dnspython 1.X\u001b[39;00m\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\dns\\resolver.py:1305\u001b[0m, in \u001b[0;36mresolve\u001b[1;34m(qname, rdtype, rdclass, tcp, source, raise_on_no_answer, source_port, lifetime, search)\u001b[0m\n\u001b[0;32m   1296\u001b[0m \u001b[38;5;124;03m\"\"\"Query nameservers to find the answer to the question.\u001b[39;00m\n\u001b[0;32m   1297\u001b[0m \n\u001b[0;32m   1298\u001b[0m \u001b[38;5;124;03mThis is a convenience function that uses the default resolver\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1302\u001b[0m \u001b[38;5;124;03mparameters.\u001b[39;00m\n\u001b[0;32m   1303\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m-> 1305\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mget_default_resolver\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresolve\u001b[49m\u001b[43m(\u001b[49m\u001b[43mqname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrdclass\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtcp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msource\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1306\u001b[0m \u001b[43m                                      \u001b[49m\u001b[43mraise_on_no_answer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msource_port\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1307\u001b[0m \u001b[43m                                      \u001b[49m\u001b[43mlifetime\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msearch\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\dns\\resolver.py:1176\u001b[0m, in \u001b[0;36mResolver.resolve\u001b[1;34m(self, qname, rdtype, rdclass, tcp, source, raise_on_no_answer, source_port, lifetime, search)\u001b[0m\n\u001b[0;32m   1175\u001b[0m     time\u001b[38;5;241m.\u001b[39msleep(backoff)\n\u001b[1;32m-> 1176\u001b[0m timeout \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_compute_timeout\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstart\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlifetime\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1177\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\dns\\resolver.py:997\u001b[0m, in \u001b[0;36mBaseResolver._compute_timeout\u001b[1;34m(self, start, lifetime)\u001b[0m\n\u001b[0;32m    996\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m duration \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m lifetime:\n\u001b[1;32m--> 997\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m Timeout(timeout\u001b[38;5;241m=\u001b[39mduration)\n\u001b[0;32m    998\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mmin\u001b[39m(lifetime \u001b[38;5;241m-\u001b[39m duration, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimeout)\n",
      "\u001b[1;31mTimeout\u001b[0m: The DNS operation timed out after 21.107285261154175 seconds",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mConfigurationError\u001b[0m                        Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[17], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m client_c \u001b[38;5;241m=\u001b[39m \u001b[43mpymongo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mMongoClient\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmongodb+srv://mydb:1234@cluster0.2htkknx.mongodb.net/?retryWrites=true&w=majority\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      2\u001b[0m db \u001b[38;5;241m=\u001b[39m client_c\u001b[38;5;241m.\u001b[39mtest\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\mongo_client.py:670\u001b[0m, in \u001b[0;36mMongoClient.__init__\u001b[1;34m(self, host, port, document_class, tz_aware, connect, type_registry, **kwargs)\u001b[0m\n\u001b[0;32m    667\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m timeout \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    668\u001b[0m     timeout \u001b[38;5;241m=\u001b[39m common\u001b[38;5;241m.\u001b[39mvalidate_timeout_or_none_or_zero(\n\u001b[0;32m    669\u001b[0m         keyword_opts\u001b[38;5;241m.\u001b[39mcased_key(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconnecttimeoutms\u001b[39m\u001b[38;5;124m\"\u001b[39m), timeout)\n\u001b[1;32m--> 670\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43muri_parser\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_uri\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    671\u001b[0m \u001b[43m    \u001b[49m\u001b[43mentity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalidate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwarn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnormalize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    672\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconnect_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    673\u001b[0m seeds\u001b[38;5;241m.\u001b[39mupdate(res[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnodelist\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m    674\u001b[0m username \u001b[38;5;241m=\u001b[39m res[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124musername\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;129;01mor\u001b[39;00m username\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\uri_parser.py:524\u001b[0m, in \u001b[0;36mparse_uri\u001b[1;34m(uri, default_port, validate, warn, normalize, connect_timeout)\u001b[0m\n\u001b[0;32m    522\u001b[0m connect_timeout \u001b[38;5;241m=\u001b[39m connect_timeout \u001b[38;5;129;01mor\u001b[39;00m options\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconnectTimeoutMS\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    523\u001b[0m dns_resolver \u001b[38;5;241m=\u001b[39m _SrvResolver(fqdn, connect_timeout\u001b[38;5;241m=\u001b[39mconnect_timeout)\n\u001b[1;32m--> 524\u001b[0m nodes \u001b[38;5;241m=\u001b[39m \u001b[43mdns_resolver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_hosts\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    525\u001b[0m dns_options \u001b[38;5;241m=\u001b[39m dns_resolver\u001b[38;5;241m.\u001b[39mget_options()\n\u001b[0;32m    526\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dns_options:\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\srv_resolver.py:118\u001b[0m, in \u001b[0;36m_SrvResolver.get_hosts\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    117\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_hosts\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m--> 118\u001b[0m     _, nodes \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_srv_response_and_hosts\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[0;32m    119\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m nodes\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\srv_resolver.py:99\u001b[0m, in \u001b[0;36m_SrvResolver._get_srv_response_and_hosts\u001b[1;34m(self, encapsulate_errors)\u001b[0m\n\u001b[0;32m     98\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_srv_response_and_hosts\u001b[39m(\u001b[38;5;28mself\u001b[39m, encapsulate_errors):\n\u001b[1;32m---> 99\u001b[0m     results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_resolve_uri\u001b[49m\u001b[43m(\u001b[49m\u001b[43mencapsulate_errors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    101\u001b[0m     \u001b[38;5;66;03m# Construct address tuples\u001b[39;00m\n\u001b[0;32m    102\u001b[0m     nodes \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m    103\u001b[0m         (maybe_decode(res\u001b[38;5;241m.\u001b[39mtarget\u001b[38;5;241m.\u001b[39mto_text(omit_final_dot\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)), res\u001b[38;5;241m.\u001b[39mport)\n\u001b[0;32m    104\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m res \u001b[38;5;129;01min\u001b[39;00m results]\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pymongo\\srv_resolver.py:95\u001b[0m, in \u001b[0;36m_SrvResolver._resolve_uri\u001b[1;34m(self, encapsulate_errors)\u001b[0m\n\u001b[0;32m     93\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m     94\u001b[0m     \u001b[38;5;66;03m# Else, raise all errors as ConfigurationError.\u001b[39;00m\n\u001b[1;32m---> 95\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m ConfigurationError(\u001b[38;5;28mstr\u001b[39m(exc))\n\u001b[0;32m     96\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m results\n",
      "\u001b[1;31mConfigurationError\u001b[0m: The DNS operation timed out after 21.107285261154175 seconds"
     ]
    }
   ],
   "source": [
    "client_c = pymongo.MongoClient(\"mongodb+srv://mydb:1234@cluster0.2htkknx.mongodb.net/?retryWrites=true&w=majority\")\n",
    "db = client_c.test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a9c650be",
   "metadata": {},
   "outputs": [],
   "source": [
    "# connecting to local mongodb atlas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f1facc10",
   "metadata": {},
   "outputs": [],
   "source": [
    "default_url = \"mongodb://localhost:27017/\"\n",
    "db_name=\"Student1\"\n",
    "\n",
    "# Establishing a connection to the database\n",
    "client=pymongo.MongoClient(default_url)\n",
    "\n",
    "# creating a database\n",
    "dataBase = client[db_name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "897be0fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a0042e5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'Student1')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataBase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3fe8770a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Students', 'admin', 'config', 'local']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client.list_database_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1f50ef98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# record"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e9119ebc",
   "metadata": {},
   "outputs": [],
   "source": [
    "record ={\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\"\n",
    "\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "04dbd2cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bfa79eb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "coll_name=\"studentdetails\"\n",
    "collection=dataBase[coll_name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f8d7f299",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Collection(Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'Student1'), 'studentdetails')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "01d633b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.InsertOneResult at 0x22bb14059c0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collection.insert_one(record)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b6640364",
   "metadata": {},
   "outputs": [],
   "source": [
    "record1 ={\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"company\":\"MSIL\"\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b662b668",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.InsertOneResult at 0x22bb09b9240>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collection.insert_one(record1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d33dc396",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.InsertOneResult at 0x22bb140c940>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record2 ={\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"learning\":[\"Python\",\"Sql\",\"DBMS\"]\n",
    "}\n",
    "\n",
    "collection.insert_one(record2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ff8e6aa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.InsertOneResult at 0x22bb0a29cc0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record3 ={\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"learning\":[\"Python\",\"Sql\",\"DBMS\"],\n",
    "    \"record_dict\":{\"name\":\"Preeti\",\"mail_id\": \"naman@gmail.com\"}\n",
    "}\n",
    "\n",
    "collection.insert_one(record3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a711eb31",
   "metadata": {},
   "outputs": [],
   "source": [
    "# inserting multiple records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5ae59530",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_records=[\n",
    "    \n",
    "    {\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"learning\":[\"Python\",\"Sql\",\"DBMS\"],\n",
    "    \"record_dict\":{\"name\":\"Preeti\",\"mail_id\": \"naman@gmail.com\"}\n",
    "},\n",
    "    \n",
    "    {\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"learning\":[\"Python\",\"Sql\",\"DBMS\"]\n",
    "},\n",
    "    \n",
    "    {\n",
    "    \"studentname\":\"naman\",\n",
    "    \"studentrollno\":40,\n",
    "    \"class\":\"graduated\",\n",
    "    \"company\":\"MSIL\"\n",
    "}    \n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "029ecc83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.InsertManyResult at 0x22bb098cdc0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collection.insert_many(list_of_records)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a1918132",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dumping the entire json file into mongodb database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3fdf6a2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Querying data using find method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "78a51d59",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_record = collection.find_one()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7e5a1a4d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n"
     ]
    }
   ],
   "source": [
    "print(first_record)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c3a14aa6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pymongo.cursor.Cursor object at 0x0000022BB1138CD0>\n"
     ]
    }
   ],
   "source": [
    "all_records=collection.find()\n",
    "print(all_records)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "13244c1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'),\n",
       " 'studentname': 'naman',\n",
       " 'studentrollno': 40,\n",
       " 'class': 'graduated'}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(all_records)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "6ef22052",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f37b34ed5726bb57a5a'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5f'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n"
     ]
    }
   ],
   "source": [
    "for i in all_records:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "033a9aa7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# filter out or query data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "20afac85",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0f37b34ed5726bb57a5a'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5f'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n"
     ]
    }
   ],
   "source": [
    "query={\"company\":\"MSIL\"}\n",
    "records=collection.find(query)\n",
    "for i in records:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "283a8bce",
   "metadata": {},
   "outputs": [],
   "source": [
    "query1={\"studentname\":\"preeti\"}\n",
    "records=collection.find(query1)\n",
    "for i in records:\n",
    "    print(i)               # no data with studentname == preeti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "86e0c26f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f37b34ed5726bb57a5a'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5f'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n"
     ]
    }
   ],
   "source": [
    "for i in collection.find({\"studentrollno\":{\"$gt\":30}}):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "af5d8eed",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in collection.find({\"studentrollno\":{\"$gt\":40}}):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "eb0b1e2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# delete the data from database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "332ba0d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.DeleteResult at 0x22bb1931f00>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query_to_delete={\"company\":\"MSIL\"}\n",
    "collection.delete_one(query_to_delete)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "603b44a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5f'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'company': 'MSIL'}\n"
     ]
    }
   ],
   "source": [
    "for i in collection.find():\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8e4ed841",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.DeleteResult at 0x22bb1879e80>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collection.delete_many(query_to_delete)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8eaebc49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n"
     ]
    }
   ],
   "source": [
    "for i in collection.find():\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "4fee3df4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# update"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "6b769379",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n"
     ]
    }
   ],
   "source": [
    "records_ = collection.find({},{\"learning\",\"class\"})\n",
    "for i in records_:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "f1064f62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n"
     ]
    }
   ],
   "source": [
    "records_ = collection.find()\n",
    "for i in records_:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "7f53eccf",
   "metadata": {},
   "outputs": [],
   "source": [
    "present_data = {\"studentname\":\"naman\"}\n",
    "new_data={\"$set\":{\"studentname\":\"Naman Jain\"}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "224e91b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'_id': ObjectId('63dc0ebfb34ed5726bb57a59'), 'studentname': 'Naman Jain', 'studentrollno': 40, 'class': 'graduated'}\n",
      "{'_id': ObjectId('63dc0f7eb34ed5726bb57a5b'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n",
      "{'_id': ObjectId('63dc103bb34ed5726bb57a5c'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5d'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS'], 'record_dict': {'name': 'Preeti', 'mail_id': 'naman@gmail.com'}}\n",
      "{'_id': ObjectId('63dc125cb34ed5726bb57a5e'), 'studentname': 'naman', 'studentrollno': 40, 'class': 'graduated', 'learning': ['Python', 'Sql', 'DBMS']}\n"
     ]
    }
   ],
   "source": [
    "collection.update_one(present_data,new_data)\n",
    "\n",
    "for i in collection.find():\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86087a00",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b94fe112",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f01b1ab",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a6dd6a02",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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