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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Notebook to download data using twitter's API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tweepy\n",
    "import os\n",
    "import csv\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saved the API Keys in the environment variables\n",
    "consumer_key = os.getenv(\"TWITTER_CONSUMER_KEY\")\n",
    "consumer_secret = os.getenv(\"TWITTER_CONSUMER_SECRET\")\n",
    "access_token = os.getenv(\"TWITTER_ACCESS_TOKEN\")\n",
    "access_token_secret = os.getenv(\"TWITTER_ACCESS_TOKEN_SECRET\")\n",
    "bearer_token = os.getenv(\"BEARER_TOKEN\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "from requests_oauthlib import OAuth1\n",
    "import urllib\n",
    "\n",
    "\n",
    "auth = OAuth1(consumer_key, consumer_secret, access_token, access_token_secret)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://api.twitter.com/2/tweets/search/recent?query=%23AppleVisionPro-is:retweets&tweet.fields=author_id,created_at&max_results=10000\n"
     ]
    }
   ],
   "source": [
    "def create_url():\n",
    "    query = urllib.parse.quote(\"#AppleVisionPro\") + \"-is:retweets\"\n",
    "    tweet_fields = \"tweet.fields=author_id,created_at\"\n",
    "    max_results = \"max_results=10000\"\n",
    "    url = \"https://api.twitter.com/2/tweets/search/recent?query={}&{}&{}\".format(\n",
    "        query, tweet_fields, max_results\n",
    "    )\n",
    "    print(url)\n",
    "    return url\n",
    "\n",
    "\n",
    "def connect_to_endpoint(url):\n",
    "    headers = {\n",
    "        \"Authorization\": \"Bearer \" + bearer_token,\n",
    "        \"Content-Type\": \"application/json\",\n",
    "    }\n",
    "    response = requests.get(url, headers=headers, auth=auth)\n",
    "    # print(response)\n",
    "    return response.json()\n",
    "\n",
    "\n",
    "def main():\n",
    "    url = create_url()\n",
    "    json_response = connect_to_endpoint(url)\n",
    "    # Create a DataFrame from the JSON response\n",
    "    df = pd.json_normalize(json_response)\n",
    "    # Save the DataFrame as a Parquet file\n",
    "    df.to_parquet(\"avp_tweets.parquet.gzip\", compression=\"gzip\")\n",
    "\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  }
 ],
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