notebooks/tweepy_script.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Access the Twitter API using tweepy (see the provided \"Twitter Dev Account Setup Instructions\" for details on how to set up a free twitter dev account)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# http://www.tweepy.org/\n",
    "import tweepy\n",
    "\n",
    "# Replace the API_KEY and API_SECRET with your application's key and secret.\n",
    "API_KEY=\"Cuu4olIZR9Fhd5GHgXjoQ5Sjt\"\n",
    "API_SECRET=\"WBazSz07lENIw59oIxmw87hBQN7dRzAQAe4gwiySqrmVn4DCQA\"\n",
    "auth = tweepy.AppAuthHandler(API_KEY, API_SECRET)\n",
    "\n",
    "api = tweepy.API(auth, wait_on_rate_limit=True, wait_on_rate_limit_notify=True)\n",
    " \n",
    "if (not api):\n",
    "    print (\"Can't Authenticate\")\n",
    "    sys.exit(-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run the tweepy script to save tweets that include the desired search query to a json file on disk."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download 4-5% of each file IDs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filenames=['election-filter1.txt', 'election-filter2.txt', 'election-filter3.txt', 'election-filter4.txt',\n",
    "           'election-filter5.txt', 'election-filter6.txt'] \n",
    "    # 'first_debate.txt', 'election-day.txt', 'democratic-convention-filter.txt', 'republican-convention-filter.txt', \n",
    "    # 'second-debate.txt', 'third-debate.txt', 'vp-debate.txt'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import jsonpickle\n",
    "import os\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "ids_dir='non_troll_ids'\n",
    "save_dir='non_troll_twts'\n",
    "pct_from_file=0.05\n",
    "tweetsPerQry=100  # this is the max the API permits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On file: election-filter1.txt\n",
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    },
    {
     "name": "stderr",
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     "text": [
      "Rate limit reached. Sleeping for: 323\n"
     ]
    },
    {
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      "tweepError on iter 1000 of 1001\n",
      "On file: election-filter2.txt\n",
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      "Rate limit reached. Sleeping for: 329\n"
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    },
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      "tweepError on iter 1000 of 1001\n",
      "On file: election-filter3.txt\n",
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    },
    {
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     "output_type": "stream",
     "text": [
      "Rate limit reached. Sleeping for: 318\n"
     ]
    },
    {
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    },
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      "Rate limit reached. Sleeping for: 362\n"
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    },
    {
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      "tweepError on iter 1000 of 1001\n",
      "On file: election-filter4.txt\n",
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      "tweepError on iter 1000 of 1001\n",
      "On file: election-filter5.txt\n",
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      "tweepError on iter 1000 of 1001\n",
      "On file: election-filter6.txt\n",
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    },
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     "text": [
      "Rate limit reached. Sleeping for: 367\n"
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    },
    {
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Rate limit reached. Sleeping for: 391\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloaded 66399 tweets\n",
      "Downloaded 66471 tweets\n",
      "Downloaded 66529 tweets\n",
      "Downloaded 66593 tweets\n",
      "Downloaded 66664 tweets\n",
      "tweepError on iter 1000 of 1001\n"
     ]
    }
   ],
   "source": [
    "for f in filenames:\n",
    "    print('On file: {}'.format(f))\n",
    "    \n",
    "    with open(os.path.join(ids_dir, f), 'r') as id_file:\n",
    "        all_ids = id_file.read().splitlines()\n",
    "    \n",
    "    # select 5% randomly\n",
    "    # rand_ids = list(np.random.choice(all_ids, size=int(pct_from_file*len(all_ids))))\n",
    "    rand_ids = list(np.random.choice(all_ids, size=100000, replace=False))\n",
    "    \n",
    "    num_requests=int(len(rand_ids)/tweetsPerQry) + 1\n",
    "    out_file = f.replace('.txt', '')+'-tweets.json'\n",
    "    tweetCount = 0\n",
    "\n",
    "    # iterate over requests and write to file\n",
    "    # 900 requests per 15 mins => 60 requests per min => sleep 1 second\n",
    "    with open(os.path.join(save_dir, out_file), 'w') as out:    \n",
    "        for i in range(num_requests):\n",
    "            try:\n",
    "                new_tweets = api.statuses_lookup(rand_ids[i*tweetsPerQry:(i+1)*tweetsPerQry])\n",
    "                for tweet in new_tweets:\n",
    "                    out.write(jsonpickle.encode(tweet._json, unpicklable=False) + '\\n')\n",
    "                tweetCount += len(new_tweets)\n",
    "                print(\"Downloaded {0} tweets\".format(tweetCount))\n",
    "            except tweepy.TweepError:\n",
    "                print('tweepError on iter {} of {}'.format(i, num_requests))\n",
    "                continue\n",
    "            time.sleep(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "## QUERY-BASED\n",
    "\n",
    "# maxTweets = 10000000 # some arbitrary large number\n",
    "\n",
    "# fName = 'tweets.json' # we'll store the tweets in a text file.\n",
    "\n",
    "# # If results from a specific ID onwards are reqd, set since_id to that ID.\n",
    "# # else default to no lower limit, go as far back as API allows\n",
    "# sinceId = None\n",
    "\n",
    "# # If results only below a specific ID are, set max_id to that ID.\n",
    "# # else default to no upper limit, start from the most recent tweet matching the search query.\n",
    "# max_id = -1\n",
    "\n",
    "# tweetCount = 0\n",
    "# print(\"Downloading max {0} tweets\".format(maxTweets))\n",
    "# with open(fName, 'w') as f:\n",
    "#     while tweetCount < maxTweets:\n",
    "#         try:\n",
    "#             if (max_id <= 0):\n",
    "#                 if (not sinceId):\n",
    "#                     new_tweets = api.search(q=searchQuery, count=tweetsPerQry)\n",
    "#                 else:\n",
    "#                     new_tweets = api.search(q=searchQuery, count=tweetsPerQry,\n",
    "#                                             since_id=sinceId)\n",
    "#             else:\n",
    "#                 if (not sinceId):\n",
    "#                     new_tweets = api.search(q=searchQuery, count=tweetsPerQry,\n",
    "#                                             max_id=str(max_id - 1))\n",
    "#                 else:\n",
    "#                     new_tweets = api.search(q=searchQuery, count=tweetsPerQry,\n",
    "#                                             max_id=str(max_id - 1),\n",
    "#                                             since_id=sinceId)\n",
    "#             if not new_tweets:\n",
    "#                 print(\"No more tweets found\")\n",
    "#                 break\n",
    "#             for tweet in new_tweets:\n",
    "#                 f.write(jsonpickle.encode(tweet._json, unpicklable=False) +\n",
    "#                         '\\n')\n",
    "#             tweetCount += len(new_tweets)\n",
    "#             print(\"Downloaded {0} tweets\".format(tweetCount))\n",
    "#             max_id = new_tweets[-1].id\n",
    "#         except tweepy.TweepError as e:\n",
    "#             # Just exit if any error\n",
    "#             print(\"some error : \" + str(e))\n",
    "#             break\n",
    "\n",
    "# print (\"Downloaded {0} tweets, Saved to {1}\".format(tweetCount, fName))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
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