ap_rva_reader.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# twitter\n",
    "# api key zhwCkCeGpNOWQWKsxyzBOa40R\n",
    "# secret bmmlaFsTIfdKLBzdqAcPawysXKATBacOSoWh37LK4V0QURQPxT\n",
    "# bearer AAAAAAAAAAAAAAAAAAAAAL0mHAEAAAAAznnM6K4lw5npEXNbiLrA%2B5m78W4%3DSKpNKovgHYbjQVT54KSnmbJJilZufD7GKIjmTZ5CCSySEJtkxO\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import os\n",
    "import json\n",
    "import GetOldTweets3 as got\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "userid = 'AP_Richmond'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweetCriteria = got.manager.TweetCriteria().setUsername(userid)\\\n",
    "                                           .setSince('2015-01-01')\n",
    "tweets = got.manager.TweetManager.getTweets(tweetCriteria)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1304"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tweets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\"id\":[t.id for t in tweets], \"date\":[t.date for t in tweets], \"text\":[t.text for t in tweets]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "# readable truncated date\n",
    "df['dt'] = df.date.dt.strftime(\"%Y-%m-%d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1304, 4)"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Mold Spore'] = df.text.str.replace(',','').str.extract('Mold Spore-? ([0-9]+)', re.IGNORECASE)\n",
    "df['Tree Pollen'] = df.text.str.replace(',','').str.extract('Tree Pollen-? ([0-9,]+)', re.IGNORECASE)\n",
    "df['Grass Pollen'] = df.text.str.replace(',','').str.extract('Grass Pollen-? ([0-9,]+)', re.IGNORECASE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop tweets with no allergen counts\n",
    "df = df[~(df['Mold Spore'].isnull().values & df['Tree Pollen'].isnull().values & df['Grass Pollen'].isnull().values)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(886, 7)"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.fillna(0)\n",
    "df['Mold Spore'] = df['Mold Spore'].astype('int')\n",
    "df['Tree Pollen'] = df['Tree Pollen'].astype('int')\n",
    "df['Grass Pollen'] = df['Grass Pollen'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('date',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_json('allergy_tweets_2015_20200824.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .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>id</th>\n",
       "      <th>text</th>\n",
       "      <th>dt</th>\n",
       "      <th>mold</th>\n",
       "      <th>tree</th>\n",
       "      <th>grass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-06 17:11:12</th>\n",
       "      <td>1291421577049976832</td>\n",
       "      <td>8/6/20 Mold Spore- 9,756 Moderate</td>\n",
       "      <td>2020-08-06</td>\n",
       "      <td>9756</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-05 15:51:04</th>\n",
       "      <td>1291039023578976256</td>\n",
       "      <td>8/5/20 Mold Spore- 9,180 Moderate</td>\n",
       "      <td>2020-08-05</td>\n",
       "      <td>9180</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-04 16:07:21</th>\n",
       "      <td>1290680734643101696</td>\n",
       "      <td>8/4/2020 Mold Spore- 2,520 Low</td>\n",
       "      <td>2020-08-04</td>\n",
       "      <td>2520</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03 17:37:43</th>\n",
       "      <td>1290341089178787840</td>\n",
       "      <td>8/3/2020 Mold Spore- 4,770 Low</td>\n",
       "      <td>2020-08-03</td>\n",
       "      <td>4770</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-29 15:50:06</th>\n",
       "      <td>1288502064558026752</td>\n",
       "      <td>7/29/20 Mold Spore- 6,180 Low</td>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>6180</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-03 16:52:35</th>\n",
       "      <td>584035778273157120</td>\n",
       "      <td>4/2/15 Tree Pollen- 306 High Mold Spore- 4,500...</td>\n",
       "      <td>2015-04-03</td>\n",
       "      <td>4500</td>\n",
       "      <td>306</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-02 16:38:29</th>\n",
       "      <td>583669843418882048</td>\n",
       "      <td>4/2/15 Tree Pollen- 108 High Mold Spore- 2,250...</td>\n",
       "      <td>2015-04-02</td>\n",
       "      <td>2250</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-01 16:29:59</th>\n",
       "      <td>583305315707457536</td>\n",
       "      <td>4/1/15 Tree Pollen- 327 High Mold Spore- 4,050...</td>\n",
       "      <td>2015-04-01</td>\n",
       "      <td>4050</td>\n",
       "      <td>327</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31 21:28:40</th>\n",
       "      <td>583018094609731584</td>\n",
       "      <td>3/31/15 Tree Pollen- 50 Moderate Mold Spore- 1...</td>\n",
       "      <td>2015-03-31</td>\n",
       "      <td>1800</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-30 20:34:53</th>\n",
       "      <td>582642171477647360</td>\n",
       "      <td>3/30/15 Pollen machine back in place with a ne...</td>\n",
       "      <td>2015-03-30</td>\n",
       "      <td>1530</td>\n",
       "      <td>162</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>886 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      id  \\\n",
       "2020-08-06 17:11:12  1291421577049976832   \n",
       "2020-08-05 15:51:04  1291039023578976256   \n",
       "2020-08-04 16:07:21  1290680734643101696   \n",
       "2020-08-03 17:37:43  1290341089178787840   \n",
       "2020-07-29 15:50:06  1288502064558026752   \n",
       "...                                  ...   \n",
       "2015-04-03 16:52:35   584035778273157120   \n",
       "2015-04-02 16:38:29   583669843418882048   \n",
       "2015-04-01 16:29:59   583305315707457536   \n",
       "2015-03-31 21:28:40   583018094609731584   \n",
       "2015-03-30 20:34:53   582642171477647360   \n",
       "\n",
       "                                                                  text  \\\n",
       "2020-08-06 17:11:12                  8/6/20 Mold Spore- 9,756 Moderate   \n",
       "2020-08-05 15:51:04                  8/5/20 Mold Spore- 9,180 Moderate   \n",
       "2020-08-04 16:07:21                     8/4/2020 Mold Spore- 2,520 Low   \n",
       "2020-08-03 17:37:43                     8/3/2020 Mold Spore- 4,770 Low   \n",
       "2020-07-29 15:50:06                      7/29/20 Mold Spore- 6,180 Low   \n",
       "...                                                                ...   \n",
       "2015-04-03 16:52:35  4/2/15 Tree Pollen- 306 High Mold Spore- 4,500...   \n",
       "2015-04-02 16:38:29  4/2/15 Tree Pollen- 108 High Mold Spore- 2,250...   \n",
       "2015-04-01 16:29:59  4/1/15 Tree Pollen- 327 High Mold Spore- 4,050...   \n",
       "2015-03-31 21:28:40  3/31/15 Tree Pollen- 50 Moderate Mold Spore- 1...   \n",
       "2015-03-30 20:34:53  3/30/15 Pollen machine back in place with a ne...   \n",
       "\n",
       "                             dt  mold  tree  grass  \n",
       "2020-08-06 17:11:12  2020-08-06  9756     0      0  \n",
       "2020-08-05 15:51:04  2020-08-05  9180     0      0  \n",
       "2020-08-04 16:07:21  2020-08-04  2520     0      0  \n",
       "2020-08-03 17:37:43  2020-08-03  4770     0      0  \n",
       "2020-07-29 15:50:06  2020-07-29  6180     0      0  \n",
       "...                         ...   ...   ...    ...  \n",
       "2015-04-03 16:52:35  2015-04-03  4500   306      0  \n",
       "2015-04-02 16:38:29  2015-04-02  2250   108      0  \n",
       "2015-04-01 16:29:59  2015-04-01  4050   327      0  \n",
       "2015-03-31 21:28:40  2015-03-31  1800    50      0  \n",
       "2015-03-30 20:34:53  2015-03-30  1530   162      0  \n",
       "\n",
       "[886 rows x 6 columns]"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_json('allergy_tweets_2015_20200824.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create figure and plot space\n",
    "fig, axs = plt.subplots(3,figsize=(16, 8))\n",
    "\n",
    "# Add x-axis and y-axis\n",
    "axs[0].plot(df.index.values, df['Mold Spore'], color='purple')\n",
    "axs[0].set_title('Mold Spore')\n",
    "\n",
    "axs[1].plot(df.index.values, df['Tree Pollen'], color='brown')\n",
    "axs[1].set_title('Tree Pollen')\n",
    "\n",
    "axs[2].plot(df.index.values, df['Grass Pollen'], color='green')\n",
    "axs[2].set_title('Grass Pollen')\n",
    "\n",
    "plt.suptitle('Richmond VA Allergen Counts (Allergy Partners of Richmond)')\n",
    "\n",
    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "plt.show()\n",
    "#y=['Mold Spore','Tree Pollen','Grass Pollen'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.tseries.offsets import DateOffset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['id', 'text', 'dt', 'mold', 'tree', 'grass']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "mold17 = df.loc['2017']['mold'].reset_index()\n",
    "mold17['date'] = mold17.date + DateOffset(years=1)\n",
    "mold17.columns = ['date','mold17']\n",
    "\n",
    "mold16 = df.loc['2016']['mold'].reset_index()\n",
    "mold16['date'] = mold16.date + DateOffset(years=2)\n",
    "mold16.columns = ['date','mold16']\n",
    "\n",
    "mold15 = df.loc['2015']['mold'].reset_index()\n",
    "mold15['date'] = mold15.date + DateOffset(years=3)\n",
    "mold15.columns = ['date','mold15']\n",
    "\n",
    "mold18 = df.loc['2018']['mold'].reset_index()\n",
    "mold18.columns = ['date','mold18']\n",
    "\n",
    "mold19 = df.loc['2019']['mold'].reset_index()\n",
    "mold19['date'] = mold19.date + DateOffset(years=-1)\n",
    "mold19.columns = ['date','mold19']\n",
    "\n",
    "mold20 = df.loc['2020']['mold'].reset_index()\n",
    "mold20['date'] = mold20.date + DateOffset(years=-2)\n",
    "mold20.columns = ['date','mold20']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1152 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create figure and plot space\n",
    "fig, ax = plt.subplots(6, figsize=(10, 16), sharey=True, sharex=True)\n",
    "\n",
    "# Add x-axis and y-axis\n",
    "ax[0].plot(mold15.date, mold15.mold15)\n",
    "ax[1].plot(mold16.date, mold16.mold16)\n",
    "ax[2].plot(mold17.date, mold17.mold17)\n",
    "ax[3].plot(mold18.date, mold18.mold18)\n",
    "ax[4].plot(mold19.date, mold19.mold19)\n",
    "ax[5].plot(mold20.date, mold20.mold20)\n",
    "\n",
    "#plt.suptitle('Richmond VA Allergen Counts (Allergy Partners of Richmond)')\n",
    "\n",
    "#fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "plt.show()\n",
    "#y=['Mold Spore','Tree Pollen','Grass Pollen'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd1993c09d0>"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.plot(x='date', y=['mold18', 'mold17', 'mold16', 'mold15'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def auth():\n",
    "    return 'AAAAAAAAAAAAAAAAAAAAAL0mHAEAAAAAznnM6K4lw5npEXNbiLrA%2B5m78W4%3DSKpNKovgHYbjQVT54KSnmbJJilZufD7GKIjmTZ5CCSySEJtkxO'\n",
    "    #return os.environ.get(\"BEARER_TOKEN\")\n",
    "\n",
    "def create_url():\n",
    "    query = \"from:{} -is:retweet\".format(userid)\n",
    "    # Tweet fields are adjustable.\n",
    "    # Options include:\n",
    "    # attachments, author_id, context_annotations,\n",
    "    # conversation_id, created_at, entities, geo, id,\n",
    "    # in_reply_to_user_id, lang, non_public_metrics, organic_metrics,\n",
    "    # possibly_sensitive, promoted_metrics, public_metrics, referenced_tweets,\n",
    "    # source, text, and withheld\n",
    "    tweet_fields = \"tweet.fields=author_id\"\n",
    "    url = \"https://api.twitter.com/2/tweets/search/recent?query={}&{}&start_time=2019-08-24T02:28:39Z\".format(\n",
    "        query, tweet_fields\n",
    "    )\n",
    "    return url\n",
    "\n",
    "def create_headers(bearer_token):\n",
    "    headers = {\"Authorization\": \"Bearer {}\".format(bearer_token)}\n",
    "    return headers\n",
    "\n",
    "\n",
    "def connect_to_endpoint(url, headers):\n",
    "    response = requests.request(\"GET\", url, headers=headers)\n",
    "    print(response.status_code)\n",
    "    if response.status_code != 200:\n",
    "        raise Exception(response.status_code, response.text)\n",
    "    return response.json()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "400\n"
     ]
    },
    {
     "ename": "Exception",
     "evalue": "(400, '{\"errors\":[{\"parameters\":{\"start_time\":[\"2019-08-24T02:28Z\"]},\"message\":\"Invalid \\'start_time\\':\\'2019-08-24T02:28Z\\'. \\'start_time\\' must be on or after 2020-08-17T02:57Z\"}],\"title\":\"Invalid Request\",\"detail\":\"One or more parameters to your request was invalid.\",\"type\":\"https://api.twitter.com/2/problems/invalid-request\"}')",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-18-3391f108738f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_url\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mheaders\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_headers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbearer_token\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mjson_response\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconnect_to_endpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_response\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort_keys\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-17-4a9721d83c98>\u001b[0m in \u001b[0;36mconnect_to_endpoint\u001b[0;34m(url, headers)\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m200\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 29\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     30\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mException\u001b[0m: (400, '{\"errors\":[{\"parameters\":{\"start_time\":[\"2019-08-24T02:28Z\"]},\"message\":\"Invalid \\'start_time\\':\\'2019-08-24T02:28Z\\'. \\'start_time\\' must be on or after 2020-08-17T02:57Z\"}],\"title\":\"Invalid Request\",\"detail\":\"One or more parameters to your request was invalid.\",\"type\":\"https://api.twitter.com/2/problems/invalid-request\"}')"
     ]
    }
   ],
   "source": [
    "#https://api.twitter.com/2/tweets/search/recent?query=from:TwitterDev\n",
    "bearer_token = auth()\n",
    "url = create_url()\n",
    "headers = create_headers(bearer_token)\n",
    "json_response = connect_to_endpoint(url, headers)\n",
    "print(json.dumps(json_response, indent=4, sort_keys=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_rules(headers, bearer_token):\n",
    "    response = requests.get(\n",
    "        \"https://api.twitter.com/2/tweets/search/stream/rules\", headers=headers\n",
    "    )\n",
    "    if response.status_code != 200:\n",
    "        raise Exception(\n",
    "            \"Cannot get rules (HTTP {}): {}\".format(response.status_code, response.text)\n",
    "        )\n",
    "    print(json.dumps(response.json()))\n",
    "    return response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def set_rules(headers, bearer_token):\n",
    "    # You can adjust the rules if needed\n",
    "    sample_rules = [\n",
    "        {\"value\": \"from:{} -is:retweet\".format(userid), \"tag\": \"from ap_rva\"}\n",
    "    ]\n",
    "    payload = {\"add\": sample_rules}\n",
    "    response = requests.post(\n",
    "        \"https://api.twitter.com/2/tweets/search/stream/rules\",\n",
    "        headers=headers,\n",
    "        json=payload,\n",
    "    )\n",
    "    if response.status_code != 201:\n",
    "        raise Exception(\n",
    "            \"Cannot add rules (HTTP {}): {}\".format(response.status_code, response.text)\n",
    "        )\n",
    "    print(json.dumps(response.json()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_stream(headers, set, bearer_token):\n",
    "    response = requests.get(\n",
    "        \"https://api.twitter.com/2/tweets/search/stream\", headers=headers, stream=True,\n",
    "    )\n",
    "    print(response.status_code)\n",
    "    if response.status_code != 200:\n",
    "        raise Exception(\n",
    "            \"Cannot delete rules (HTTP {}): {}\".format(\n",
    "                response.status_code, response.text\n",
    "            )\n",
    "        )\n",
    "    for response_line in response.iter_lines():\n",
    "        if response_line:\n",
    "            json_response = json.loads(response_line)\n",
    "            print(json.dumps(json_response, indent=4, sort_keys=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"meta\": {\"sent\": \"2020-08-24T02:53:27.011Z\"}}\n",
      "{\"data\": [{\"value\": \"from:AP_Richmond -is:retweet\", \"tag\": \"from ap_rva\", \"id\": \"1297728699215818754\"}], \"meta\": {\"sent\": \"2020-08-24T02:53:28.034Z\", \"summary\": {\"created\": 1, \"not_created\": 0, \"valid\": 1, \"invalid\": 0}}}\n",
      "200\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-16-53dff61cf216>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mrules\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_rules\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbearer_token\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset_rules\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbearer_token\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mget_stream\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbearer_token\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-11-f4b9eab7fdfd>\u001b[0m in \u001b[0;36mget_stream\u001b[0;34m(headers, set, bearer_token)\u001b[0m\n\u001b[1;32m     10\u001b[0m             )\n\u001b[1;32m     11\u001b[0m         )\n\u001b[0;32m---> 12\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mresponse_line\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miter_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     13\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresponse_line\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m             \u001b[0mjson_response\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse_line\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/site-packages/requests/models.py\u001b[0m in \u001b[0;36miter_lines\u001b[0;34m(self, chunk_size, decode_unicode, delimiter)\u001b[0m\n\u001b[1;32m    793\u001b[0m         \u001b[0mpending\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    794\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 795\u001b[0;31m         \u001b[0;32mfor\u001b[0m \u001b[0mchunk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miter_content\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunk_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchunk_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecode_unicode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_unicode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    796\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    797\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpending\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/site-packages/requests/models.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m()\u001b[0m\n\u001b[1;32m    749\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'stream'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    750\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 751\u001b[0;31m                     \u001b[0;32mfor\u001b[0m \u001b[0mchunk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstream\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunk_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecode_content\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    752\u001b[0m                         \u001b[0;32myield\u001b[0m \u001b[0mchunk\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    753\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mProtocolError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/site-packages/urllib3/response.py\u001b[0m in \u001b[0;36mstream\u001b[0;34m(self, amt, decode_content)\u001b[0m\n\u001b[1;32m    570\u001b[0m         \"\"\"\n\u001b[1;32m    571\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchunked\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupports_chunked_reads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 572\u001b[0;31m             \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_chunked\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mamt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecode_content\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_content\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    573\u001b[0m                 \u001b[0;32myield\u001b[0m \u001b[0mline\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    574\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/site-packages/urllib3/response.py\u001b[0m in \u001b[0;36mread_chunked\u001b[0;34m(self, amt, decode_content)\u001b[0m\n\u001b[1;32m    762\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    763\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 764\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_chunk_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    765\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchunk_left\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    766\u001b[0m                     \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/site-packages/urllib3/response.py\u001b[0m in \u001b[0;36m_update_chunk_length\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    692\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchunk_left\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    693\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 694\u001b[0;31m         \u001b[0mline\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreadline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    695\u001b[0m         \u001b[0mline\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mline\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mb\";\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    696\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/socket.py\u001b[0m in \u001b[0;36mreadinto\u001b[0;34m(self, b)\u001b[0m\n\u001b[1;32m    667\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    668\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 669\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    670\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    671\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_timeout_occurred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/ssl.py\u001b[0m in \u001b[0;36mrecv_into\u001b[0;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[1;32m   1239\u001b[0m                   \u001b[0;34m\"non-zero flags not allowed in calls to recv_into() on %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1240\u001b[0m                   self.__class__)\n\u001b[0;32m-> 1241\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1242\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1243\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python38/lib/python3.8/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m   1097\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1098\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mbuffer\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1099\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1100\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1101\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "bearer_token = auth() #os.environ.get(\"BEARER_TOKEN\")\n",
    "headers = create_headers(bearer_token)\n",
    "rules = get_rules(headers, bearer_token)\n",
    "set = set_rules(headers, bearer_token)\n",
    "get_stream(headers, set, bearer_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Authorization': 'Bearer None'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "headers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
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