twitterapp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tweepy import API\n",
    "from tweepy import Cursor\n",
    "from tweepy.streaming import StreamListener\n",
    "from tweepy import OAuthHandler\n",
    "from tweepy import Stream\n",
    "from Tweepy_API import config\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Authenticator\n",
    "class TwitterAuthenticator():\n",
    "    def authenticate_twitter(self):\n",
    "        auth = OAuthHandler(config.API_KEY, config.API_SECRET_KEY)\n",
    "        auth.set_access_token(config.ACCESS_TOKEN, config.ACCESS_TOKEN_SECRET)\n",
    "        return auth     \n",
    "\n",
    "\n",
    "# Streamer\n",
    "class TwitterStreamer():\n",
    "    \"\"\"\n",
    "    class for streaming and processing live tweets\n",
    "    \"\"\"\n",
    "    def __init__(self):\n",
    "        self.twitter_auth = TwitterAuthenticator()\n",
    "        \n",
    "    def stream_tweets(self, hashtags_list):\n",
    "        # Handles twitter authentication and connection to twitter streamer API\n",
    "        listener = TwitterListener()\n",
    "        auth = self.twitter_auth.authenticate_twitter()\n",
    "        stream = Stream(auth, listener)\n",
    "        stream.filter(track=hashtags_list, is_async=True)\n",
    "        \n",
    "\n",
    "# Streamer Listener\n",
    "class TwitterListener(StreamListener):\n",
    "    \"\"\"\n",
    "    Basic listener class that prints to cmd\n",
    "    \"\"\"\n",
    "    def on_data(self, data):\n",
    "        print(data)\n",
    "        return True\n",
    "    \n",
    "    def on_error(self, status):\n",
    "        # Return False in case rate limit occurs\n",
    "        if status==402:\n",
    "            return False\n",
    "        print(status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Client\n",
    "class TwitterClient():\n",
    "    def __init__(self, twitter_user=None):\n",
    "        self.auth = TwitterAuthenticator().authenticate_twitter()\n",
    "        self.twitter_client = API(self.auth)\n",
    "        self.twitter_user  =twitter_user\n",
    "    \n",
    "    def get_tweets(self, num_tweets):\n",
    "        tweets = []\n",
    "        for tweet in Cursor(self.twitter_client.user_timeline, id=self.twitter_user).items(num_tweets):\n",
    "            tweets.append(tweet)\n",
    "        return tweets\n",
    "    \n",
    "    def get_frds(self, num_frds):\n",
    "        frds = []\n",
    "        for tweet in Cursor(self.twitter_client.friends, id=self.twitter_user).items(num_frds):\n",
    "            frds.append(tweet)\n",
    "        return frds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TweetAnalysizer():\n",
    "    \n",
    "    def tweets2df(self, tweets):\n",
    "        df = pd.DataFrame(data = [tweet.text for tweet in tweets], columns=[\"Tweets\"])\n",
    "        df[\"id\"] = np.array([tweet.id for tweet in tweets])\n",
    "        df[\"geo\"] = np.array([tweet.geo for tweet in tweets])\n",
    "        df[\"date\"] = np.array([tweet.created_at for tweet in tweets])\n",
    "        df[\"likes\"] = np.array([tweet.favorite_count for tweet in tweets])\n",
    "        \n",
    "        return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# hashtags_list = [\"nvidia\"]\n",
    "# twitter_streamer = TwitterStreamer()\n",
    "# tweets = twitter_streamer.stream_tweets(hashtags_list)\n",
    "\n",
    "twitter_client = TwitterClient(\"realdonaldtrump\")\n",
    "tweets = twitter_client.get_tweets(10)\n",
    "\n",
    "df = TweetAnalysizer().tweets2df(tweets)\n",
    "df\n",
    "# Time Series\n",
    "time_likes = pd.Series(data=df[\"likes\"].values, index=df[\"date\"])\n",
    "time_likes.plot(color=\"b\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "query=\"#nvidia\"\n",
    "\n",
    "auth = TwitterAuthenticator().authenticate_twitter()\n",
    "twitter_api = API(auth)\n",
    "\n",
    "\n",
    "tweets = Cursor(twitter_api.search, q=query, lang=\"en\").items(200)\n",
    "for i,tweet in enumerate(tweets):\n",
    "    print(i,tweet.text)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweets = twitter_api.search(q=query, lang=\"en\",count=150)\n",
    "for i,tweet in enumerate(tweets):\n",
    "    print(i,tweet.text)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Date</th>\n",
       "      <th>Tweet</th>\n",
       "      <th>Geo</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Retweets</th>\n",
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       "      <td>1301203944593649667</td>\n",
       "      <td>2020-09-02 17:02:50</td>\n",
       "      <td>RT @NVIDIADRIVE: Watch NVIDIA founder and CEO ...</td>\n",
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       "      <td>2020-09-02 15:38:57</td>\n",
       "      <td>RT @NVIDIACreators: Turn any room into a home ...</td>\n",
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       "      <td>2020-09-02 14:54:04</td>\n",
       "      <td>RT @NVIDIADRIVE: With the next-gen MBUX #AI co...</td>\n",
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       "      <td>2020-09-01 18:28:49</td>\n",
       "      <td>RT @NVIDIAGeForce: New RT Cores. \\nNew Tensor ...</td>\n",
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       "      <td>2020-09-01 18:19:17</td>\n",
       "      <td>GeForce RTX 30 Series GPUs, powered by our sec...</td>\n",
       "      <td>None</td>\n",
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       "      <td>170</td>\n",
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      ],
      "text/plain": [
       "                    Id                Date  \\\n",
       "0  1301203944593649667 2020-09-02 17:02:50   \n",
       "1  1301182835546439684 2020-09-02 15:38:57   \n",
       "2  1301171539488858113 2020-09-02 14:54:04   \n",
       "3  1300863197440663552 2020-09-01 18:28:49   \n",
       "4  1300860795723669505 2020-09-01 18:19:17   \n",
       "\n",
       "                                               Tweet   Geo  Likes  Retweets  \n",
       "0  RT @NVIDIADRIVE: Watch NVIDIA founder and CEO ...  None      0        43  \n",
       "1  RT @NVIDIACreators: Turn any room into a home ...  None      0        95  \n",
       "2  RT @NVIDIADRIVE: With the next-gen MBUX #AI co...  None      0        78  \n",
       "3  RT @NVIDIAGeForce: New RT Cores. \\nNew Tensor ...  None      0     10547  \n",
       "4  GeForce RTX 30 Series GPUs, powered by our sec...  None    833       170  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from Tweepy_API.TwitterClient import TwitterClient\n",
    "\n",
    "client = TwitterClient(\"nvidia\").getTweets(5)\n",
    "df = client.getTweetDataFrame()\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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