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converted version to just run and download output (On Colab)
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‎README.md

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@@ -13,9 +13,9 @@ By using selenium and pytesseract ocr module we can scrap any Text Captcha Human
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Used Pandas for managing data in tabular format.
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Here i provided source codes for scrapping data for analytics.
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Here i provided source codes for scrapping data and further used for analytics.
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### youtube :
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### youtube (version 1) :
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2020
https://youtu.be/2nPUuaq4RRI (gturesults.in)
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‎gturesults.in/README.md

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# Note :
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# Result-Data-Analyzer
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To run this in your system
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## How to run :
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1> you have to install tesseract-ocr in your system
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1) Open notebook file in colab
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2) Hit CTRL+F9 (Run All)
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3) Resume run using CTRL+F10 (Run After) (After Runtime Restart)
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4) Download output file
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2> you have to download your browser's driver file
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#### Scrap, Analyze & Enjoy!
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here i use chrome browser in incognito mode so i downloaded chromedriver.exe
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the driver is version specific
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you have to define path for this driverfile in program
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#### Thank You!

‎gturesults.in/g.xlsx

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‎gturesults.in/out.xlsx

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‎gturesults.in/result_data_analyzer_gtu_results.ipynb

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"private_outputs": true,
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"provenance": [],
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"collapsed_sections": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"install selenium\n",
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"and\n",
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"chrome driver (also define path)"
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],
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"metadata": {
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"id": "-lYAwjJwe4Oa"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!pip install selenium\n",
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"!apt-get update # to update ubuntu to correctly run apt install\n",
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"!apt install chromium-chromedriver\n",
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"!cp /usr/lib/chromium-browser/chromedriver /usr/bin\n",
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"import sys\n",
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"sys.path.insert(0,'/usr/lib/chromium-browser/chromedriver')"
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],
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"metadata": {
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"id": "rjyqtRrYewxu"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"install tesseract"
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],
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"metadata": {
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"id": "FFYAh381exh4"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!sudo apt install tesseract-ocr\n",
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"!pip install pytesseract"
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],
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"metadata": {
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"id": "2_AwFU5SQ5lT"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"restart runtime"
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],
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"metadata": {
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"id": "MBT77b1SBIWq"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"import os\n",
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"os.kill(os.getpid(), 9)\n",
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"#-----------OR-----------\n",
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"# quit()\n",
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"#-----------OR-----------\n",
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"# exit()"
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],
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"metadata": {
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"id": "LQu1QserAnKc"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"import dependancies"
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],
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"metadata": {
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"id": "QQovnVXAfNbx"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"from selenium import webdriver\n",
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"from selenium.webdriver.common.by import By\n",
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"from selenium.webdriver.common.keys import Keys\n",
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"from selenium.webdriver.support.select import Select\n",
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"from selenium.webdriver.chrome.service import Service\n",
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"\n",
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"import cv2\n",
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"from PIL import Image, ImageCms, ImageFilter\n",
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"import pytesseract\n",
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"\n",
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"import pandas as pd\n",
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"import warnings\n",
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"warnings.filterwarnings('ignore')"
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],
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"metadata": {
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"id": "RhvflwoJfMZZ"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"helper functions"
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],
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"metadata": {
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"id": "T2jcfxOqfdvk"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"def step1():\n",
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" # open webpage\n",
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" driver.get(URL)\n",
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"\n",
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" # save captcha\n",
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" imdata = driver.find_element(By.ID,\"imgCaptcha\")\n",
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" with open(path, 'wb') as file:\n",
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" file.write(imdata.screenshot_as_png)\n",
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"\n",
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"def step2():\n",
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" # convert to inverted mask and save img_temp\n",
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" im = cv2.imread(path)\n",
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" gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)\n",
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" thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]\n",
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" horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25, 1))\n",
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" Mask = cv2.morphologyEx(thresh, cv2.MORPH_OPEN,horizontal_kernel, iterations=2)\n",
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" #Mask = cv2.bitwise_not(Mask)\n",
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" cv2.imwrite(\"old.png\", Mask)\n",
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"\n",
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" # open img_temp and reinvert mask\n",
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" img = Image.open(\"old.png\")\n",
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" img = img.convert(\"RGBA\")\n",
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" datas = img.getdata()\n",
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" newData = []\n",
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" for item in datas:\n",
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" if item[0] == 0 and item[1] == 0 and item[2] == 0:\n",
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" newData.append((255, 255, 255, 0))\n",
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" else:\n",
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" newData.append(item)\n",
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" img.putdata(newData)\n",
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"\n",
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" # paste mask on img and save new_temp_img\n",
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" background = Image.open(path)\n",
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" background = background.convert(\"RGBA\")\n",
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" background.paste(img,mask=img)\n",
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" background.save(\"new.png\",\"PNG\")\n",
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"\n",
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"def step3(im): # solve captcha\n",
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" im = Image.open(im) # open last saved img\n",
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" im = im.crop((5,5,115,35)) # crop it\n",
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" # conver image to extractable form elements (deffer captcha styles)\n",
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" rgb = ImageCms.createProfile(colorSpace='sRGB')\n",
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" lab = ImageCms.createProfile(colorSpace='LAB')\n",
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" transform = ImageCms.buildTransform(inputProfile=rgb, outputProfile=lab, inMode='RGB', outMode='LAB')\n",
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" lab_im = ImageCms.applyTransform(im=im, transform=transform)\n",
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" l, a, b = lab_im.split()\n",
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" im=l # select an element which is most extractable\n",
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" im = im.filter(ImageFilter.MinFilter(3)) # filter it\n",
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" result = pytesseract.image_to_string(im) # send it to ocr and save results to a variable\n",
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" l=[]\n",
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" l.append(result.strip())\n",
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" if l[0]==\" \" or l[0]==\"\" : # if result will be empty then it will do above steps again untill it gets the result\n",
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" step1()\n",
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" step2()\n",
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" l[0]=step3(\"new.png\")\n",
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" return l[0] # return final result (maybe right or wrong)\n",
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"\n",
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"def step4(enroll,ans): # return data\n",
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" # site automation \n",
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" sel = Select (driver.find_element(By.ID,\"ddlbatch\")) # focus on select element\n",
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" sel.select_by_value(exam) # select element by giving id (specific for a exam)\n",
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" enr = driver.find_element(By.ID,\"txtenroll\") # get enrollment no. text box\n",
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" captex = driver.find_element(By.ID,\"CodeNumberTextBox\") # get captcha text box\n",
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" enr.send_keys(enroll) # send (type) given enrollment number to text box\n",
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" captex.send_keys(ans) # send (type) extracted captcha text to text box\n",
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" captex.send_keys(Keys.RETURN) # return (ENTER)\n",
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"\n",
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" ere = driver.find_element(By.ID,\"lblmsg\").text\n",
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" if ere == \"ERROR: Incorrect captcha code, try again.\" : \n",
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" return \"err\"\n",
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" if ere == \"Your request count is reached to maximum limit, Please try again later.\" : \n",
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" return \"reqover\"\n",
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" if ere == \"Oppssss! Data not available.\" : \n",
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" return \"nodata\"\n",
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"\n",
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" name = driver.find_element(By.ID,\"lblName\").text\n",
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" sess = driver.find_element(By.ID,\"lblSession\").text\n",
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" dd = driver.find_element(By.ID,\"lblDeclaredOn\").text\n",
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" bra = driver.find_element(By.ID,\"lblBranchName\").text\n",
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" cs = driver.find_element(By.ID,\"lblExamName\").text\n",
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" csb = driver.find_element(By.ID,\"lblCUPBack\").text\n",
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" tb = driver.find_element(By.ID,\"lblTotalBack\").text\n",
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" spi = driver.find_element(By.ID,\"lblSPI\").text\n",
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" cpi = driver.find_element(By.ID,\"lblCPI\").text\n",
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" cgpa = driver.find_element(By.ID,\"lblCGPA\").text\n",
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" cp = driver.find_element(By.ID,\"pt100Curr\").text\n",
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" cup = driver.find_element(By.ID,\"pt100Cuml\").text\n",
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" return [enroll,name,sess,cs,dd,bra,int(csb),int(tb),float(spi),float(cpi),float(cgpa),int(cp),int(cup),ere]\n",
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"\n",
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"def loop():\n",
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" # just a loop through different enrollment numbers\n",
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" global counter\n",
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" mynewlist = []\n",
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" for i in mylist :\n",
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" enroll = \"{}\".format(i)\n",
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" step1()\n",
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" step2()\n",
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" ans=step3(\"new.png\")\n",
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" nr=step4(enroll,ans)\n",
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" if nr == \"err\" :\n",
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" mynewlist.append(enroll)\n",
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" elif nr == \"reqover\" :\n",
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" print(\"Change the SERVER!\")\n",
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" break\n",
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" elif nr == \"nodata\" :\n",
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" df.loc[len(df)] = [enroll,\"nodata\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\",\"-\"]\n",
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" counter += 1\n",
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" print(f\"{counter}/{tc} {int(counter*100/tc)}%\")\n",
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" else :\n",
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" df.loc[len(df)] = nr\n",
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" counter += 1\n",
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" print(f\"{counter}/{tc} {int(counter*100/tc)}%\")\n",
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" return mynewlist"
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],
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"metadata": {
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"id": "t9H8OdFrRLBY"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"main function"
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],
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"metadata": {
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"id": "5QIu2udZgKKq"
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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": null,
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"metadata": {
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"id": "E_BfboOxLMJd"
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},
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"outputs": [],
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"source": [
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"try:\n",
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"\t# initiate webdriver and configure options\n",
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"\tchrome_options = webdriver.ChromeOptions()\n",
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"\tchrome_options.add_argument('--headless')\n",
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"\tchrome_options.add_argument('--no-sandbox')\n",
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"\tchrome_options.add_argument('--disable-dev-shm-usage')\n",
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"\tchrome_options.add_argument(\"--incognito\")\n",
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"\n",
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"\tser = Service(\"chromedriver\")\n",
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"\tdriver = webdriver.Chrome(service=ser,options=chrome_options)\n",
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"\n",
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"\t# define url and filename for download captcha_temp\n",
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"\tURL = \"https://www.gturesults.in/\"\n",
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"\texam = \"3361$S2022$2022-08-25$current$0\"\n",
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"\tpath=\"cap.jpg\"\n",
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" \n",
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"\t# create empty dataframe for filling output data with same labels that input file has\n",
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"\tdf = pd.read_json('{\"Enrollment No.\":{},\"Name\":{},\"Session\":{},\"Exam\":{},\"Declared On\":{},\"Branch\":{},\"Current Sem. Backlog\":{},\"Total Backlog\":{},\"SPI\":{},\"CPI\":{},\"CGPA\":{},\"Current Points\":{},\"Cumulative points\":{},\"Message\":{}}')\n",
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"\n",
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"\tmylist = range(190280111001,190280111010+1) # give range of enrollment no. (here i given our batch's range)\n",
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"\t\n",
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"\tcounter = 0\n",
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"\ttc = len(mylist)\n",
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" \n",
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"\t# main driver programm\n",
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"\t# loop runs untill all data has scraped if any server error not happens\n",
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"\twhile 1:\n",
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"\t\tmynewlist=loop()\n",
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"\t\tif len(mynewlist) != 0:\n",
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"\t\t\tmylist = mynewlist\n",
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"\t\telse:\n",
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"\t\t\tbreak\n",
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"\n",
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"\t# save dataframe to excel file\n",
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"\tdf.to_excel(\"out.xlsx\")\n",
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"\n",
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"finally:\n",
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"\tdriver.close() # close the window\n",
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"\tdriver.quit() # stop the driver\n",
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"\t# remove unnecessary files\n",
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"\timport os\n",
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"\tos.remove(\"cap.jpg\")\n",
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"\tos.remove(\"old.png\")\n",
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"\tos.remove(\"new.png\")"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"👈 download <font color='yellow'>out.xlsx</font> from left side bar by double clicking it"
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],
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"metadata": {
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"id": "qgkULANw3ZQ2"
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}
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}
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]
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}

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