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from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import csv
import time
import glob
import os
import pandas as pd
import re, os.path

from pathlib import Path

  
# Open Chrome


#options=webdriver.ChromeOptions();

#prefs={"download.default_directory":"C:/DumpStack.log.tmpUsers/apskaita3/Desktop/Nasdaq_file"}

#options.add_experimental_option("prefs",prefs)


driver = webdriver.Chrome("C:/Users/Žymantas/Desktop/Nasdaq_file/chromedriver.exe")
driver.minimize_window()
#driver.set_window_size(-10000000,-1000000000)
# Open URL
driver.get(
    'http://www.nasdaqomxnordic.com/aktier/microsite?Instrument=VSE28424&name=Apranga&ISIN=LT0000102337')
  
# Enter text
#driver.find_element_by_id('textbox').send_keys("Hello world")
  
# Generate Text File
#driver.find_element_by_id('createTxt').click()
  
# Click on Download Button
driver.find_element_by_id('exportIntradayTradesCSV').click()

time.sleep(5)

driver.close()


#with open('C:/Users/apskaita3/Downloads/share_export.csv', mode ='r') as file:
   
 # csvFile = csv.reader(file)
 
  #for lines in csvFile:
   #   print(lines)

#all_files = glob.glob('C:/Users/apskaita3/Downloads/share_export.csv') #give path to your desired file path
#latest_csv = max(all_files, key=os.path.getctime)
#print(latest_csv)


folder_path = r'C:/Users/Žymantas/Downloads'
file_type = '\*csv'
files = glob.glob(folder_path + file_type)
max_file = max(files, key=os.path.getctime)

df = pd.read_csv(max_file,  sep=';',skiprows=1)







df2= pd.read_csv('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv',sep=';',skiprows=1)        


   

df3=df2.append(df,ignore_index=True)
df3 = df3[~df3.index.duplicated()]
#df3= df.sort_values(by=['Execution Time']
#df3.columns = df3.columns.str.replace(' ', '')
#print(df3.columns)
#print(df3.iloc[:, 1])
df3.sort_values(by=['Execution Time'], inplace=True, ascending=False)
#print(df3.columns.tolist())
df3.to_csv('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv', index=False)
#df3.reset_index(drop=True, inplace=True)


#df=pd.read_csv('C:/Users/apskaita3/Downloads/f1.csv',index_col=0)
#a=df.to_csv('C:/Users/apskaita3/Desktop/Nasdaq_file/share_export.csv')
#b=pd.read_csv(io.StringIO(a.to_csv(index=False)))
#df.to_csv('C:/Users/apskaita3/Desktop/Nasdaq_file/share_export.csv')
#df.to_csv('C:/Users/apskaita3/Desktop/Nasdaq_file/share_export.csv', mode='a', index=False, header=False)






#print(df)


#with open(max_file, 'r') as file:
#    reader = csv.reader(file)


#file.close()






#path='C:/Users/apskaita3/Desktop/Nasdaq_file/'+ max_file





#df = pd.read_csv(max_file,sep=';')
#df.to_csv('C:/Users/apskaita3/Desktop/Nasdaq_file/share_export.csv')
#file = open(max_file)
#csvreader = csv.reader(file)


#header = []
#header = next(csvreader)
#header

#rows = []
#for row in csvreader:
#        rows.append(row)
#rows


#pattern = "share_export"
#mypath = "C:/Users/apskaita3/Downloads"
#for root, dirs, files in os.walk(mypath):
  #  for file in filter(lambda x: re.match(pattern, x), files):
  #      os.remove(os.path.join(root, file))


#df2 = pd.read_csv('C:/Users/apskaita3/Desktop/Nasdaq_file/share_export.csv')


#modTimesinceEpoc = os.path.getmtime('C:/Users/apskaita3/Downloads/share_export(13).csv')
# Convert seconds since epoch to readable timestamp
#modificationTime = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(modTimesinceEpoc))
#print("Last Modified Time : ", modificationTime )