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+ {
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {},
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+ "source": [
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+ "> Notebook to download data using twitter's API"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import tweepy\n",
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+ "import os\n",
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+ "import csv\n",
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+ "import pandas as pd"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "# Saved the API Keys in the environment variables\n",
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+ "consumer_key = os.getenv(\"TWITTER_CONSUMER_KEY\")\n",
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+ "consumer_secret = os.getenv(\"TWITTER_CONSUMER_SECRET\")\n",
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+ "access_token = os.getenv(\"TWITTER_ACCESS_TOKEN\")\n",
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+ "access_token_secret = os.getenv(\"TWITTER_ACCESS_TOKEN_SECRET\")\n",
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+ "bearer_token = os.getenv(\"BEARER_TOKEN\")"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import requests\n",
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+ "import json\n",
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+ "from requests_oauthlib import OAuth1\n",
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+ "import urllib\n",
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+ "\n",
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+ "\n",
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+ "auth = OAuth1(consumer_key, consumer_secret, access_token, access_token_secret)"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 4,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "https://api.twitter.com/2/tweets/search/recent?query=%23AppleVisionPro-is:retweets&tweet.fields=author_id,created_at&max_results=10000\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "def create_url():\n",
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+ " query = urllib.parse.quote(\"#AppleVisionPro\") + \"-is:retweets\"\n",
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+ " tweet_fields = \"tweet.fields=author_id,created_at\"\n",
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+ " max_results = \"max_results=10000\"\n",
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+ " url = \"https://api.twitter.com/2/tweets/search/recent?query={}&{}&{}\".format(\n",
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+ " query, tweet_fields, max_results\n",
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+ " )\n",
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+ " print(url)\n",
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+ " return url\n",
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+ "\n",
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+ "\n",
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+ "def connect_to_endpoint(url):\n",
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+ " headers = {\n",
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+ " \"Authorization\": \"Bearer \" + bearer_token,\n",
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+ " \"Content-Type\": \"application/json\",\n",
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+ " }\n",
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+ " response = requests.get(url, headers=headers, auth=auth)\n",
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+ " # print(response)\n",
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+ " return response.json()\n",
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+ "\n",
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+ "\n",
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+ "def main():\n",
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+ " url = create_url()\n",
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+ " json_response = connect_to_endpoint(url)\n",
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+ " # Create a DataFrame from the JSON response\n",
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+ " df = pd.json_normalize(json_response)\n",
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+ " # Save the DataFrame as a Parquet file\n",
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+ " df.to_parquet(\"avp_tweets.parquet.gzip\", compression=\"gzip\")\n",
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+ "\n",
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+ "\n",
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+ "if __name__ == \"__main__\":\n",
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+ " main()"
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "Python 3",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.10.13"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 2
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+ }