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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "5a589865-2f6c-49bb-953c-f09e877cd512",
+ "metadata": {},
+ "source": [
+ "## Network Set up Between Instances"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "e8af1dc0-dbc0-4155-83a1-35b618996d16",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Successfully connected to CouchDB\n",
+ "{\"db_name\":\"photon\",\"purge_seq\":\"0-g1AAAABZeJzLYWBgYMpgTmEQSs4vTc5ISXIwNDfSMzTXM9AzyQHJ5bEASYYGIPUfCLISGfApTmRIqoeoygIA4GAYvA\",\"update_seq\":\"3-g1AAAACfeJzLYWBgYMpgTmEQSs4vTc5ISXIwNDfSMzTXM9AzyQHJ5bEASYYGIPUfCLIymBOZcoEC7IZGSaYGSclYNeIzL5EhqR5qECPYoGSjFOPUJAOsOrIAjHUpiw\",\"sizes\":{\"file\":770417,\"external\":726543,\"active\":726923},\"props\":{},\"doc_del_count\":0,\"doc_count\":1,\"disk_format_version\":8,\"compact_running\":false,\"cluster\":{\"q\":2,\"n\":3,\"w\":2,\"r\":2},\"instance_start_time\":\"0\"}\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import requests\n",
+ "\n",
+ "# replace with your CouchDB URL, database name, and credentials\n",
+ "couchdb_url = \"http://172.26.136.104:5987\"\n",
+ "database_name = \"photon\"\n",
+ "username = \"admin\"\n",
+ "password = \"admin\"\n",
+ "\n",
+ "response = requests.get(f\"{couchdb_url}/{database_name}\", auth=(username, password))\n",
+ "\n",
+ "# check that the request was successful\n",
+ "if response.status_code == 200:\n",
+ " print(\"Successfully connected to CouchDB\")\n",
+ "else:\n",
+ " print(\"Failed to connect to CouchDB:\", response.status_code)\n",
+ "\n",
+ "# print the first 500 characters of the response\n",
+ "print(response.text[:500])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "9389265b-6c95-423a-aa9e-d0e89bb66a91",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[nltk_data] Downloading package vader_lexicon to\n",
+ "[nltk_data] /home/jovyan/nltk_data...\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import json\n",
+ "import couchdb\n",
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import re\n",
+ "import nltk\n",
+ "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
+ "import emoji\n",
+ "from textblob import TextBlob\n",
+ "from fuzzywuzzy import process\n",
+ "import matplotlib.pyplot as plt\n",
+ "from wordcloud import WordCloud\n",
+ "\n",
+ "\n",
+ "nltk.download('vader_lexicon')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "5b0e64ab-1d17-42fa-b94d-a47f0073be17",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting couchdb\n",
+ " Downloading CouchDB-1.2-py2.py3-none-any.whl (67 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m68.0/68.0 kB\u001b[0m \u001b[31m199.9 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
+ "\u001b[?25hInstalling collected packages: couchdb\n",
+ "Successfully installed couchdb-1.2\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install couchdb"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "32ffa972-8225-45b7-9d08-90c223b029c9",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting cloudant\n",
+ " Downloading cloudant-2.15.0-py3-none-any.whl (80 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m80.5/80.5 kB\u001b[0m \u001b[31m220.9 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
+ "\u001b[?25hRequirement already satisfied: requests<3.0.0,>=2.7.0 in /opt/conda/lib/python3.10/site-packages (from cloudant) (2.29.0)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0,>=2.7.0->cloudant) (3.1.0)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0,>=2.7.0->cloudant) (3.4)\n",
+ "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0,>=2.7.0->cloudant) (1.26.15)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0,>=2.7.0->cloudant) (2023.5.7)\n",
+ "Installing collected packages: cloudant\n",
+ "Successfully installed cloudant-2.15.0\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install cloudant"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "5f685769-275e-4346-8180-9e16dc4ccbe9",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " location text\n",
+ "0 Melbourne, Victoria AshramGzb tdybsayudbysauaduyadbuadbyau\n",
+ "1 Melbourne, Victoria 1233123123123133123123123\n",
+ "2 Melbourne, Victoria @AshramGzb @narendramodi बिल्कुल सही कहा\n",
+ "3 Melbourne, Victoria @PM_Jordan DL Down3r´s hit inspirational song ...\n",
+ "4 Melbourne, Victoria @alcoholicsuide DL Down3r´s hit inspirational ...\n",
+ ".. ... ...\n",
+ "494 Melbourne, Victoria @redrobinhood123 Plays, just twitter just warn...\n",
+ "495 Melbourne, Victoria @ThaiSN30983779 🔥😜🔥\n",
+ "496 Melbourne, Victoria @embereon Will this do for you https://t.co/zV...\n",
+ "497 Melbourne, Victoria @PtUNfXAe99QsIIp @1990xiaoxiaoxia @aMeow0429 @...\n",
+ "498 Melbourne, Victoria @PtUNfXAe99QsIIp @aMeow0429 @1990xiaoxiaoxia @...\n",
+ "\n",
+ "[499 rows x 2 columns]\n"
+ ]
+ }
+ ],
+ "source": [
+ "from cloudant.client import CouchDB\n",
+ "import pandas as pd\n",
+ "\n",
+ "# Connect to CouchDB\n",
+ "client = CouchDB('admin', 'admin', url='http://172.26.136.104:5987', connect=True)\n",
+ "\n",
+ "# Access the 'twitter' database\n",
+ "db = client['twitter']\n",
+ "\n",
+ "# Get a list of all document IDs in the database\n",
+ "doc_ids = [doc['_id'] for doc in db]\n",
+ "\n",
+ "# Print the document IDs for debugging\n",
+ "#print(f\"Document IDs: {doc_ids}\")\n",
+ "\n",
+ "# Fetch each document by its ID and store the 'location' and 'text' fields in a DataFrame\n",
+ "data = []\n",
+ "for doc_id in doc_ids:\n",
+ " if not doc_id.startswith('_'): # Skip special documents\n",
+ " doc = db[doc_id]\n",
+ " location = doc.get('location')\n",
+ " text = doc.get('text')\n",
+ " if location and text: # Only include documents that have both fields\n",
+ " data.append({'location': location, 'text': text})\n",
+ "\n",
+ "df = pd.DataFrame(data)\n",
+ "\n",
+ "print(df)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "fd603603-ae6b-41f5-8cae-dd04957dbc28",
+ "metadata": {
+ "tags": []
+ },
+ "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>location</th>\n",
+ " <th>text</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
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+ "Empty DataFrame\n",
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+ "metadata": {},
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+ "source": [
+ "df.head()"
+ ]
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+ "display_name": "Python 3 (ipykernel)",
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+ "codemirror_mode": {
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