Hsinchu_Hackthon.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tkinter import *\n",
    "#Creating main window\n",
    "\n",
    "\n",
    "def Input_Box():\n",
    "    root = Tk()\n",
    "    # creating a top window\n",
    "    master_2 = Toplevel(root)\n",
    "\n",
    "    #Textboxes\n",
    "    user_name = Entry(master_2)\n",
    "    user_name.grid(row = 1, column = 2)\n",
    "    pwd = Entry(master_2)\n",
    "    pwd.grid(row = 2, column = 2)\n",
    "\n",
    "    label_un = Label(master_2, text = \"Username\")\n",
    "    label_un.grid(row = 1, column = 1)\n",
    "    label_pwd = Label(master_2, text = \"Password\")\n",
    "    label_pwd.grid(row = 2, column = 1)\n",
    "\n",
    "    get_button = Button(master_2, text = \"Confirm\", command = lambda: getname(user_name))\n",
    "    get_button.grid(row=3, column = 1)3\n",
    "    master_2.mainloop() \n",
    "    \n",
    "    \n",
    "    #call_button = Button(root, text='Enter Usrnm and pwd', command = Input_Box)\n",
    "    #call_button.pack()\n",
    "    \n",
    "def getname(user_name):\n",
    "    input = user_name.get()\n",
    "    print(\"!!!!!: %s\"%input)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<__main__.GUI at 0x1a3619f128>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tkinter import *\n",
    "\n",
    "class GUI(object):\n",
    "    def changeLabel(self):\n",
    "        text = \"You have entered \" + self.someName.get()\n",
    "        self.labelText.set(text)\n",
    "        self.someName.delete(0, END)\n",
    "        self.someName.insert(0, \"You've clicked!\")            \n",
    "    def processed_text(self):\n",
    "        if  self.someName.get() is None:\n",
    "            return \"\"\n",
    "        else:\n",
    "            text = re.sub('[\\n\\r]', ' ',  self.someName.get())\n",
    "            return text\n",
    "    def __init__(self):\n",
    "        app = Tk()\n",
    "        app.title(\"GUI Test\")\n",
    "        app.geometry('450x300')\n",
    "\n",
    "        self.labelText = StringVar()\n",
    "        self.labelText.set(\"Click when ready\")\n",
    "        label1 = Label(app, textvariable=self.labelText, height=4)\n",
    "        label1.pack()\n",
    "\n",
    "        userInput = StringVar(None)\n",
    "        self.someName = Entry(app, textvariable=userInput)\n",
    "        self.someName.pack()\n",
    "\n",
    "        button1 = Button(app, text=\"Click Here\", width=20,command=self.changeLabel)\n",
    "        button1.pack(side='bottom',padx=15,pady=15)\n",
    "        text = self.processed_text\n",
    "        print\n",
    "        app.mainloop()\n",
    "\n",
    "GUI() #calling the class to run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://www.instagram.com/ping7446/\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:azure.storage.common.storageclient:Client-Request-ID=89d869d4-d258-11e7-bb7b-6c4008956dc6 Outgoing request: Method=PUT, Path=/mycontainer, Query={'restype': 'container', 'timeout': None}, Headers={'x-ms-blob-public-access': 'container', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '89d869d4-d258-11e7-bb7b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:56 GMT', 'Authorization': 'SharedKey storage19960311:BXUQDMEG/FzDxwzxxwLXajfR8v59MEx9XSQHr2FEq/M='}.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len: 3\n",
      "Sentence 1  : 今天我的工作是幫忙拍攝 || Score 0.720436\n",
      "Sentence 2  : 他們要提供給報紙刊登 || Score 0.033009\n",
      "Sentence 3  : 很開心自己也能幫的上忙 || Score 0.665949\n",
      "Average : 0.47\n",
      "---------------------------------------------\n",
      "len: 5\n",
      "Sentence 1  : 亞歷山大 || Score 0.479501\n",
      "Sentence 2  : 今天下午是亞歷體能訓練測驗 || Score 0.031049\n",
      "Sentence 3  : 亞歷爸也是工作人員之幫忙 || Score 0.437414\n",
      "Sentence 4  : 很棒的體驗 || Score 0.827937\n",
      "Sentence 5  : 我跟阿弟就負責加油 || Score 0.831982\n",
      "Average : 0.52\n",
      "---------------------------------------------\n",
      "len: 5\n",
      "Sentence 1  : 父子 || Score 0.909091\n",
      "Sentence 2  : 認真挑選菜單中 || Score 0.807464\n",
      "Average : 0.86\n",
      "---------------------------------------------\n",
      "len: 3\n",
      "Sentence 1  : 再忙也要好好吃頓飯 || Score 0.293135\n",
      "Average : 0.29\n",
      "---------------------------------------------\n",
      "len: 3\n",
      "Sentence 1  : 安德里 || Score 0.500000\n",
      "Sentence 2  : 你在看我嗎 || Score 0.348244\n",
      "Sentence 3  : 我也在看你 || Score 0.587521\n",
      "Average : 0.48\n",
      "---------------------------------------------\n",
      "len: 12\n",
      "Sentence 1  : 安德里 || Score 0.500000\n",
      "Sentence 2  : 帶阿弟來吃午飯 || Score 0.735570\n",
      "Sentence 3  : 剛剛去跟油漆師傅說 || Score 0.119624\n",
      "Sentence 4  : 我明天再決定 || Score 0.330888\n",
      "Sentence 5  : 今天晚上跟老公討論下 || Score 0.480260\n",
      "Sentence 6  : 當媽也是很擔心 || Score 0.600590\n",
      "Sentence 7  : 顏色會影響到孩子 || Score 0.645451\n",
      "Sentence 8  : 哪怕點點 || Score 0.468750\n",
      "Sentence 9  : 以前完全不知道這個 || Score 0.115280\n",
      "Sentence 10  : 看到大家回應 || Score 0.286063\n",
      "Sentence 11  : 對我來說都是寶貴建議 || Score 0.485561\n",
      "Sentence 12  : 謝謝你們分享 || Score 0.664579\n",
      "Average : 0.45\n",
      "---------------------------------------------\n",
      "len: 5\n",
      "Sentence 1  : 請問你們有看過這個根據嗎 || Score 0.006648\n",
      "Sentence 3  : 因為我沒經驗不知道 || Score 0.008746\n",
      "Sentence 5  : 很感謝這位網友的好意建議 || Score 0.972282\n",
      "Average : 0.33\n",
      "---------------------------------------------\n",
      "len: 5\n",
      "Sentence 1  : 去年聖誕節 || Score 0.174211\n",
      "Sentence 2  : 有買過這個好吃 || Score 0.081786\n",
      "Sentence 3  : 今天再買來吃 || Score 0.397695\n",
      "Sentence 4  : 聖誕節賣場都是滿滿各種巧克力販賣中 || Score 0.221895\n",
      "Sentence 5  : 非常吸引人 || Score 0.738633\n",
      "Average : 0.32\n",
      "---------------------------------------------\n",
      "len: 8\n",
      "Sentence 1  : 安德里 || Score 0.500000\n",
      "Sentence 2  : 陪我等哥哥上游泳課 || Score 0.980858\n",
      "Sentence 3  : 阿弟跑來找我 || Score 0.344300\n",
      "Sentence 4  : 要我抱他 || Score 0.782178\n",
      "Sentence 5  : 我才抱下 || Score 0.477955\n",
      "Sentence 6  : 阿弟就睡著 || Score 0.230542\n",
      "Sentence 7  : 辛苦了 || Score 0.820000\n",
      "Sentence 8  : 今天的行程都是陪我等哥哥 || Score 0.949241\n",
      "Average : 0.64\n",
      "---------------------------------------------\n",
      "len: 6\n",
      "Sentence 1  : 明天要決定孩子房間面牆的油漆顏色 || Score 0.086305\n",
      "Sentence 2  : 亞歷藍色 || Score 0.212710\n",
      "Sentence 3  : 阿弟綠色 || Score 0.473767\n",
      "Sentence 4  : 只是光這兩種 || Score 0.241431\n",
      "Sentence 5  : 就分很多種深淺顏色 || Score 0.747578\n",
      "Sentence 6  : 很怕明天我選不好 || Score 0.107126\n",
      "Average : 0.31\n",
      "---------------------------------------------\n",
      "len: 8\n",
      "Sentence 1  : 安德里 || Score 0.500000\n",
      "Sentence 2  : 我吃午飯阿弟吃點心 || Score 0.281921\n",
      "Sentence 3  : 我忙到現在吃午飯 || Score 0.706337\n",
      "Sentence 4  : 放心阿弟有吃午飯 || Score 0.620700\n",
      "Sentence 5  : 現在已經下午 || Score 0.387144\n",
      "Sentence 6  : 趕緊吃吃 || Score 0.829446\n",
      "Sentence 7  : 等等接亞歷下課 || Score 0.138602\n",
      "Sentence 8  : 五點阿弟上體能課程 || Score 0.107218\n",
      "Average : 0.45\n",
      "---------------------------------------------\n",
      "len: 5\n",
      "Sentence 1  : 安德里母子 || Score 0.908285\n",
      "Sentence 2  : 今天阿弟跟著我到處跑 || Score 0.456282\n",
      "Sentence 3  : 忙碌但是很開心 || Score 0.823838\n",
      "Average : 0.73\n",
      "---------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:azure.storage.common.storageclient:Client-Request-ID=89d869d4-d258-11e7-bb7b-6c4008956dc6 Receiving Response: Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d36-001e-0086-3f65-66d999000000, HTTP Status Code=409, Message=The specified container already exists., Headers={'x-ms-blob-public-access': 'container', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '89d869d4-d258-11e7-bb7b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:56 GMT', 'Authorization': 'SharedKey storage19960311:BXUQDMEG/FzDxwzxxwLXajfR8v59MEx9XSQHr2FEq/M='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=89d869d4-d258-11e7-bb7b-6c4008956dc6 Operation failed: checking if the operation should be retried. Current retry count=0, Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d36-001e-0086-3f65-66d999000000, HTTP status code=409, Exception=The specified container already exists.<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ContainerAlreadyExists</Code><Message>The specified container already exists.RequestId:4cb16d36-001e-0086-3f65-66d999000000Time:2017-11-26T03:18:57.1668011Z</Message></Error>.\n",
      "ERROR:azure.storage.common.storageclient:Client-Request-ID=89d869d4-d258-11e7-bb7b-6c4008956dc6 Retry policy did not allow for a retry: Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d36-001e-0086-3f65-66d999000000, HTTP status code=409, Exception=The specified container already exists.<?xml version=\"1.0\" encoding=\"utf-8\"?><Error><Code>ContainerAlreadyExists</Code><Message>The specified container already exists.RequestId:4cb16d36-001e-0086-3f65-66d999000000Time:2017-11-26T03:18:57.1668011Z</Message></Error>.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=89f89706-d258-11e7-876b-6c4008956dc6 Outgoing request: Method=PUT, Path=/mycontainer/imagehappy.txt, Query={'timeout': None}, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '858', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '89f89706-d258-11e7-876b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:Mp8VkemTOOCApIdxxFUoUEiQHbgca/j/i8BBRltTlAQ='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=89f89706-d258-11e7-876b-6c4008956dc6 Receiving Response: Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d44-001e-0086-4365-66d999000000, HTTP Status Code=201, Message=Created, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '858', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '89f89706-d258-11e7-876b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:Mp8VkemTOOCApIdxxFUoUEiQHbgca/j/i8BBRltTlAQ='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a01a362-d258-11e7-957b-6c4008956dc6 Outgoing request: Method=PUT, Path=/mycontainer/imagesad.txt, Query={'timeout': None}, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '429', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a01a362-d258-11e7-957b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:NrAN49dXs85SsgahHVRjLlb+yNko4xYhDvsPEO5qD9g='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a01a362-d258-11e7-957b-6c4008956dc6 Receiving Response: Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d5a-001e-0086-4b65-66d999000000, HTTP Status Code=201, Message=Created, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '429', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a01a362-d258-11e7-957b-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:NrAN49dXs85SsgahHVRjLlb+yNko4xYhDvsPEO5qD9g='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a0c5b4a-d258-11e7-9f19-6c4008956dc6 Outgoing request: Method=PUT, Path=/mycontainer/scorehappy.txt, Query={'timeout': None}, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '40', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a0c5b4a-d258-11e7-9f19-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:mG8XUMuk2RA5TM4GdD9+lvhjgmwtTmgSpbkioIHXafU='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a0c5b4a-d258-11e7-9f19-6c4008956dc6 Receiving Response: Server-Timestamp=Sun, 26 Nov 2017 03:18:56 GMT, Server-Request-ID=4cb16d5c-001e-0086-4c65-66d999000000, HTTP Status Code=201, Message=Created, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '40', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a0c5b4a-d258-11e7-9f19-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:mG8XUMuk2RA5TM4GdD9+lvhjgmwtTmgSpbkioIHXafU='}.\n",
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a141c36-d258-11e7-938a-6c4008956dc6 Outgoing request: Method=PUT, Path=/mycontainer/scoresad.txt, Query={'timeout': None}, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '20', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a141c36-d258-11e7-938a-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:/KM8s6oe0Z/siOspwtqt1wy1cTd5xOSX4CwJ0UmPUrk='}.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:azure.storage.common.storageclient:Client-Request-ID=8a141c36-d258-11e7-938a-6c4008956dc6 Receiving Response: Server-Timestamp=Sun, 26 Nov 2017 03:18:57 GMT, Server-Request-ID=4cb16d5e-001e-0086-4d65-66d999000000, HTTP Status Code=201, Message=Created, Headers={'x-ms-blob-type': 'BlockBlob', 'x-ms-lease-id': None, 'If-Modified-Since': None, 'If-Unmodified-Since': None, 'If-Match': None, 'If-None-Match': None, 'x-ms-blob-cache-control': None, 'x-ms-blob-content-type': 'application/TXT', 'x-ms-blob-content-disposition': None, 'x-ms-blob-content-md5': None, 'x-ms-blob-content-encoding': None, 'x-ms-blob-content-language': None, 'Content-Length': '20', 'x-ms-version': '2017-04-17', 'User-Agent': 'Azure-Storage/0.37.1-0.37.1 (Python CPython 3.6.3; Darwin 16.7.0)', 'x-ms-client-request-id': '8a141c36-d258-11e7-938a-6c4008956dc6', 'x-ms-date': 'Sun, 26 Nov 2017 03:18:57 GMT', 'Authorization': 'SharedKey storage19960311:/KM8s6oe0Z/siOspwtqt1wy1cTd5xOSX4CwJ0UmPUrk='}.\n",
      "ERROR:root:Error extracting Query Id, exiting\n"
     ]
    },
    {
     "ename": "SystemExit",
     "evalue": "1",
     "output_type": "error",
     "traceback": [
      "An exception has occurred, use %tb to see the full traceback.\n",
      "\u001b[0;31mSystemExit\u001b[0m\u001b[0;31m:\u001b[0m 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/helen/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2870: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n",
      "  warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "from json import JSONDecodeError\n",
    "import bs4\n",
    "import requests\n",
    "import re\n",
    "import logging as log\n",
    "from abc import ABCMeta, abstractmethod\n",
    "import sys\n",
    "import numpy as np\n",
    "from textblob import TextBlob\n",
    "from snownlp import SnowNLP\n",
    "from azure.storage.blob import BlockBlobService\n",
    "from azure.storage.blob import PublicAccess\n",
    "from azure.storage.blob import ContentSettings\n",
    "from math import pow\n",
    "from easygui import *\n",
    "\n",
    "tArray = []\n",
    "iArray = []\n",
    "class InstagramUser:\n",
    "    def __init__(self, user_id, username=None, bio=None, followers_count=None, following_count=None, is_private=False):\n",
    "        \"\"\"\n",
    "        A class to represent an Instagram User\n",
    "        :param user_id: User ID of instagram user\n",
    "        :param username: Username of Instagram user\n",
    "        :param bio: Bio text for user\n",
    "        :param followers_count: Number of followers\n",
    "        :param following_count: Number of people following\n",
    "        :param is_private: Boolean to indicate if account is private or not\n",
    "        \"\"\"\n",
    "        self.id = user_id\n",
    "        self.username = username\n",
    "        self.bio = bio\n",
    "        self.followers_count = followers_count\n",
    "        self.following_count = following_count\n",
    "        self.is_private = is_private\n",
    "\n",
    "\n",
    "class InstagramPost:\n",
    "    def __init__(self, post_id, code, user=None, caption=\"\", display_src=None, is_video=False, created_at=None):\n",
    "        \"\"\"\n",
    "        A class to represent a post on Instagram\n",
    "        :param post_id: ID of the post\n",
    "        :param code: Code of the post\n",
    "        :param user: A user object representing the owner of the post\n",
    "        :param caption: The caption/text of the post\n",
    "        :param display_src: The URL of the image of the post\n",
    "        :param is_video: A boolean value indicating it's a video\n",
    "        :param created_at: The time it was created\n",
    "        \"\"\"\n",
    "        self.post_id = post_id\n",
    "        self.code = code\n",
    "        self.caption = caption\n",
    "        self.user = user\n",
    "        self.display_src = display_src\n",
    "        self.is_video = is_video\n",
    "        self.created_at = created_at\n",
    "\n",
    "    def processed_text(self):\n",
    "        \"\"\"\n",
    "        Processes a caption to remove newlines in it.\n",
    "        :return:\n",
    "        \"\"\"\n",
    "        if self.caption is None:\n",
    "            return \"\"\n",
    "        else:\n",
    "            text = re.sub('[\\n\\r]', ' ', self.caption)\n",
    "            return text\n",
    "    def processed_image(self):\n",
    "        \"\"\"\n",
    "        Processes a caption to remove newlines in it.\n",
    "        :return:\n",
    "        \"\"\"\n",
    "        if self.display_src is None:\n",
    "            return \"\"\n",
    "        else:\n",
    "            image = re.sub('[\\n\\r]', ' ', self.display_src)\n",
    "            return image\n",
    "\n",
    "    def hashtags(self):\n",
    "        \"\"\"\n",
    "        Simple hashtag extractor to return the hastags in the post\n",
    "        :return:\n",
    "        \"\"\"\n",
    "        hashtags = []\n",
    "        if self.caption is None:\n",
    "            return hashtags\n",
    "        else:\n",
    "            for tag in re.findall(\"#[a-zA-Z0-9]+\", self.caption):\n",
    "                hashtags.append(tag)\n",
    "            return hashtags\n",
    "\n",
    "\n",
    "class HashTagSearch(metaclass=ABCMeta):\n",
    "    instagram_root = \"https://www.instagram.com\"\n",
    "\n",
    "    def __init__(self, ):\n",
    "        \"\"\"\n",
    "        This class performs a search on Instagrams hashtag search engine, and extracts posts for that given hashtag.\n",
    "        There are some limitations, as this does not extract all occurrences of the hash tag.\n",
    "        Instead, it extracts the most recent uses of the tag.\n",
    "        \"\"\"\n",
    "        super().__init__()\n",
    "\n",
    "    def extract_recent_tag(self, tag):\n",
    "        \"\"\"\n",
    "        Extracts Instagram posts for a given hashtag\n",
    "        :param tag: Hashtag to extract\n",
    "        \"\"\"\n",
    "        \n",
    "        url_string = \"https://www.instagram.com/%s/\"%tag\n",
    "        print(url_string)\n",
    "        response = bs4.BeautifulSoup(requests.get(url_string).text, \"html.parser\")\n",
    "        ##print(\"!!!!... Response: %s\"%response)\n",
    "        potential_query_ids = self.get_query_id(response)\n",
    "        shared_data = self.extract_shared_data(response)\n",
    "        ##print(\"@@@....share data :%s\"% shared_data)\n",
    "        media = shared_data['entry_data']['ProfilePage'][0]['user']['media']\n",
    "        #print(\"@@@..... media\"%media)\n",
    "        posts = []\n",
    "        for node in media['nodes']:\n",
    "            ##print(\"!!!!.....NODE %s\"%node);\n",
    "            post = self.extract_recent_instagram_post(node)\n",
    "            posts.append(post)\n",
    "        self.save_results(posts)\n",
    "\n",
    "        end_cursor = media['page_info']['end_cursor']\n",
    "\n",
    "        # figure out valid queryId\n",
    "        success = False\n",
    "        for potential_id in potential_query_ids:\n",
    "            url = \"https://www.instagram.com/graphql/query/?query_id=%s&tag_name=%s&first=12&after=%s\" % (\n",
    "                potential_id, tag, end_cursor)\n",
    "            try:\n",
    "                data = requests.get(url).json()\n",
    "                if 'hashtag' not in data['data']:\n",
    "                    # empty response, skip\n",
    "                    continue\n",
    "                query_id = potential_id\n",
    "                success = True\n",
    "                break\n",
    "            except JSONDecodeError as de:\n",
    "                # no valid JSON retured, most likely wrong query_id resulting in 'Oops, an error occurred.'\n",
    "                pass\n",
    "        if not success:\n",
    "            log.error(\"Error extracting Query Id, exiting\")\n",
    "            sys.exit(1)\n",
    "\n",
    "        while end_cursor is not None:\n",
    "            url = \"https://www.instagram.com/graphql/query/?query_id=%s&tag_name=%s&first=12&after=%s\" % (\n",
    "            query_id, tag, end_cursor)\n",
    "            data = json.loads(requests.get(url).text)\n",
    "            end_cursor = data['data']['hashtag']['edge_hashtag_to_media']['page_info']['end_cursor']\n",
    "            posts = []\n",
    "            for node in data['data']['hashtag']['edge_hashtag_to_media']['edges']:\n",
    "                posts.append(self.extract_recent_query_instagram_post(node['node']))\n",
    "            self.save_results(posts)\n",
    "\n",
    "\n",
    "    @staticmethod\n",
    "    def extract_shared_data(doc):\n",
    "        for script_tag in doc.find_all(\"script\"):\n",
    "            if script_tag.text.startswith(\"window._sharedData =\"):\n",
    "                shared_data = re.sub(\"^window\\._sharedData = \", \"\", script_tag.text)\n",
    "                shared_data = re.sub(\";$\", \"\", shared_data)\n",
    "                shared_data = json.loads(shared_data)\n",
    "                return shared_data\n",
    "\n",
    "    @staticmethod\n",
    "    def extract_recent_instagram_post(node):\n",
    "        return InstagramPost(\n",
    "            post_id=node['id'],\n",
    "            code=node['code'],\n",
    "            user=InstagramUser(user_id=node['owner']['id']),\n",
    "            caption=node['caption'] if 'caption' in node else None,\n",
    "            display_src=node['display_src'],\n",
    "            is_video=node['is_video'],\n",
    "            created_at=node['date']\n",
    "        )\n",
    "\n",
    "    @staticmethod\n",
    "    def extract_recent_query_instagram_post(node):\n",
    "        return InstagramPost(\n",
    "            post_id=node['id'],\n",
    "            code=node['shortcode'],\n",
    "            user=InstagramUser(user_id=node['owner']['id']),\n",
    "            caption=node['edge_media_to_caption']['edges'][0]['node']['text']\n",
    "            if len(node['edge_media_to_caption']['edges']) > 0 else None,\n",
    "            display_src=node['display_url'],\n",
    "            is_video=node['is_video'],\n",
    "            created_at=node['taken_at_timestamp']\n",
    "        )\n",
    "\n",
    "    @staticmethod\n",
    "    def extract_owner_details(owner):\n",
    "        \"\"\"\n",
    "        Extracts the details of a user object.\n",
    "        :param owner: Instagrams JSON user object\n",
    "        :return: An Instagram User object\n",
    "        \"\"\"\n",
    "        username = None\n",
    "        if \"username\" in owner:\n",
    "            username = owner[\"username\"]\n",
    "        is_private = False\n",
    "        if \"is_private\" in owner:\n",
    "            is_private = is_private\n",
    "        user = InstagramUser(owner['id'], username=username, is_private=is_private)\n",
    "        return user\n",
    "\n",
    "    def get_query_id(self, doc):\n",
    "        query_ids = []\n",
    "        for script in doc.find_all(\"script\"):\n",
    "            if script.has_attr(\"src\") and \"en_US_Commons\" in script['src']:\n",
    "                text = requests.get(\"%s%s\" % (self.instagram_root, script['src'])).text\n",
    "                for query_id in re.findall(\"(?<=queryId:\\\")[0-9]{17,17}\", text):\n",
    "                    query_ids.append(query_id)\n",
    "        return query_ids\n",
    "\n",
    "    @abstractmethod\n",
    "    def save_results(self, instagram_results):\n",
    "        \"\"\"\n",
    "        Implement yourself to work out what to do with each extract batch of posts\n",
    "        :param instagram_results: A list of Instagram Posts\n",
    "        \"\"\"\n",
    "\n",
    "\n",
    "class HashTagSearchExample(HashTagSearch):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.total_posts = 0\n",
    "\n",
    "    def save_results(self, instagram_results):\n",
    "        super().save_results(instagram_results)\n",
    "        #print(instagram_results)\n",
    "        for i, post in enumerate(instagram_results):\n",
    "            self.total_posts += 1\n",
    "            #print(\"%i - %s\" % (self.total_posts, post.processed_text()))\n",
    "            #print(\"%s\"% (post.processed_image()))\n",
    "            tArray.append(post.processed_text())\n",
    "            iArray.append(post.processed_image())\n",
    "        #print (iArray)\n",
    "        #print (tArray)\n",
    "        a = []\n",
    "        average_sad = []\n",
    "        average_happy = []\n",
    "        image_sad = []\n",
    "        image_happy = []\n",
    "        j=0\n",
    "        \n",
    "        for text in tArray:\n",
    "            n_text = text.split(\" \")\n",
    "            a = []\n",
    "            new_text = \"\"\n",
    "            count=0\n",
    "            total=0\n",
    "            print(\"len: %i\"%len(n_text))  \n",
    "            for i in range(0,len(n_text)):\n",
    "                new_text = \"\"\n",
    "                for ch in n_text[i]:\n",
    "                    if ord(ch) > 0x4e00 and ord(ch) < 0x9fff:\n",
    "                        new_text+=ch\n",
    "                a.append(new_text)\n",
    "                if n_text[i] == ''or new_text=='':\n",
    "                    continue\n",
    "                else :\n",
    "                    s =''.join(a[i])\n",
    "                    s = SnowNLP(s)\n",
    "                    s1 = SnowNLP(s.sentences[0])\n",
    "                    count+=s1.sentiments\n",
    "                    print(\"Sentence %i  : %s || Score %f\"% (len(a) , a[i], s1.sentiments))\n",
    "                    total = total+1\n",
    "            #print(\"total=%i\"%total)\n",
    "            if total==0:\n",
    "                avv=0.5\n",
    "            else:\n",
    "                avv = count/total\n",
    "            if avv>=0.4:\n",
    "                average_happy.append(avv)\n",
    "                image_happy.append(iArray[tArray.index(text)])\n",
    "            else:\n",
    "                average_sad.append(avv)\n",
    "                #print(\"aaaaa%s\"%iArray[tArray.index(text)])\n",
    "                image_sad.append(iArray[tArray.index(text)])\n",
    "            #average.append(round(count/len(n_text),2))\n",
    "            print(\"Average : %.2f\"%avv)\n",
    "            \n",
    "            print(\"---------------------------------------------\")\n",
    "        np.savetxt('image_happy.txt', image_happy, fmt='%s')\n",
    "        np.savetxt('image_sad.txt', image_sad, fmt='%s')\n",
    "        np.savetxt('score_happy.txt', average_happy, fmt='%.2f')\n",
    "        np.savetxt('score_sad.txt', average_sad, fmt='%.2f')\n",
    "        block_blob_service = BlockBlobService(account_name='storage19960311', account_key='/VwwrK4FVgSFaweKkOv4TTX/2ymEzcnSIhfx6jTRBK9S7xzOIPXMMi4DVT8CytzoP+YkQhdmXUcj7QS1JBtXUg==')\n",
    "        block_blob_service.create_container('mycontainer', public_access=PublicAccess.Container)\n",
    "        block_blob_service.create_blob_from_path(\n",
    "            'mycontainer',\n",
    "            'imagehappy.txt',\n",
    "            'image_happy.txt',\n",
    "            content_settings=ContentSettings(content_type='application/TXT')\n",
    "            )\n",
    "        block_blob_service.create_blob_from_path(\n",
    "            'mycontainer',\n",
    "            'imagesad.txt',\n",
    "            'image_sad.txt',\n",
    "            content_settings=ContentSettings(content_type='application/TXT')\n",
    "            )\n",
    "        block_blob_service.create_blob_from_path(\n",
    "            'mycontainer',\n",
    "            'scorehappy.txt',\n",
    "            'score_happy.txt',\n",
    "            content_settings=ContentSettings(content_type='application/TXT')\n",
    "            )\n",
    "        block_blob_service.create_blob_from_path(\n",
    "            'mycontainer',\n",
    "            'scoresad.txt',\n",
    "            'score_sad.txt',\n",
    "            content_settings=ContentSettings(content_type='application/TXT')\n",
    "            )\n",
    "\n",
    "\n",
    "        \n",
    "if __name__ == '__main__':\n",
    "    \n",
    "    log.basicConfig(level=log.INFO)\n",
    "    title = \"Hackthon DEMO\"\n",
    "\n",
    "    #msgbox displays the string you give as an argument and gives the user an OK\n",
    "    #button.\n",
    "    #msgbox(\"Welcome to the demo GUI!\", title)\n",
    "\n",
    "    #You can specify the text of the OK button using the ok_button parameter.\n",
    "    #msgbox(\"Are you read for some UI magic?\", title, ok_button=\"I'm ready!\")\n",
    "    band = enterbox(\"Please Enter Your IG Account?\", title)\n",
    "    #print (\"%s\"%band)\n",
    "    HashTagSearchExample().extract_recent_tag(band)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from easygui import *\n",
    "title = \"GUI DEMO\"\n",
    "\n",
    "#msgbox displays the string you give as an argument and gives the user an OK\n",
    "#button.\n",
    "msgbox(\"Welcome to the demo GUI!\", title)\n",
    "\n",
    "#You can specify the text of the OK button using the ok_button parameter.\n",
    "msgbox(\"Are you read for some UI magic?\", title, ok_button=\"I'm ready!\")\n",
    "band = enterbox(\"What's your name?\", title)\n",
    "print (\"%s\"%band)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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