#!pip install selenium
import time
import csv
import datetime
import argparse
import os
import numpy
#!pip install selenium
from selenium import webdriver
import pandas as pd;
output_final_final=pd.DataFrame()

# modules neccesary for web-automation.
options = webdriver.ChromeOptions()
options.add_argument('--ignore-certificate-errors')
options.add_argument("--test-type")
## path where you store your chromedriver 
driver = webdriver.Chrome()  # Optional argument, if not specified will search path.
## website you would like to complte auto scrape
## Link to download the webdriver -- chrome : https://chromedriver.storage.googleapis.com/index.html?path=75.0.3770.90/
## You may modify the webdriver or omit it depends on the system  and (or) the browser.


# Interaction with user for text entering and searching section
driver.get('https://www.bop.gov/inmateloc/')
driver.find_element_by_xpath('//*[@id="ui-id-1"]/span').click()
## text entering on wesbite for searching
text_area_first = driver.find_element_by_id('inmNameFirst');
print('Enter First Name for Search:')
first_name = input()
text_area_first.send_keys(first_name)
print('\n First Name Collected, then Please Enter the Last Name: ')
last_name = input()
text_area_last=driver.find_element_by_id('inmNameLast')
text_area_last.send_keys(last_name)
print('\n Please Enter the Age if if known, heat \'Enter\' to skip: ')
Age = input()
text_area_age=driver.find_element_by_id('inmAge')
text_area_age.send_keys(Age)
print('\n Enter the ID if it known, heat \'Enter\' if not sure: ')
ID = input()
text_area_mid=driver.find_element_by_id('inmNameMid')
text_area_mid.send_keys(ID)


# Automation and Scraping section
print ('\n\n Is this correct information you would like to search?')
print ('\n            <',first_name,last_name,Age,ID,'>          \n')
print ('Please enter yes/no: \n')
start_check = input()
if start_check == 'yes':
    time.sleep(2)
    driver.find_element_by_xpath('//*[@id="searchNameButton"]').click()
    print('Start searching for the information in database, please wait ...')
    item = driver.find_element_by_xpath('//*[@id="inmateTable"]')
    driver.execute_script("arguments[0].click();", item)
    time.sleep(3)
    for table in driver.find_elements_by_xpath('//*[@id="inmateTable"]/tbody'):
        data = [item.text for item in table.find_elements_by_xpath(".//*[self::td or self::th]")]
    time.sleep(2)
    driver.quit() # automatically close the website. 
    if len(data)<8:
        print ("\n No information found, do you want to try one more time?")        
        print('\n Pleaese enter Y/N for your answer: ')
        re_run = input()
        print('Re-run the cell manually for this time: ')
    else:
        print("\n Data Scraping Successful, please run next cell.")
else:
    driver.refresh()
    print('Enter again: \n')
    print('First Name:')
    first_name = input()
    print('\n Last Name: ')
    last_name = input()
    driver.find_element_by_xpath('//*[@id="searchNameButton"]').click()
    print('Start searching for the information in database, please wait ...')
    item = driver.find_element_by_xpath('//*[@id="inmateTable"]')
    driver.execute_script("arguments[0].click();", item)
    for table in driver.find_elements_by_xpath('//*[@id="inmateTable"]/tbody'):
        data = [item.text for item in table.find_elements_by_xpath(".//*[self::td or self::th]")]
    time.sleep(2)
    driver.quit()
    if len(data)<8:
        print ("\n No information found, do you want to try one more time?")        
        print('\n Pleaese enter Y/N for your answer: ')
        re_run = input()
        print('Re-run the cell manually for this time: ')
    else:
        print("\n Data Scraping Successful, please run next cell.")
 
 
#Data Preprocessing and storage
n=7
final = [data[i * n:(i + 1) * n] for i in range((len(data) + n - 1) // n )]  
output_final=pd.DataFrame(final)
output_final.columns=['Name','Register Number','Age','Race','Gender','Release Date','Status']
print(output_final.head(3))
time.sleep(2)
print('\nData Cleansing Successful.')
## save to the path you would choose.
export1_csv =output_final.to_csv ('extracted_data.csv', index = None, header=True)
print("Cleaned Data Saved.")