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)
#print(df)
#df0=pd.read_csv('C:/Users/Žymantas/Downloads/share_export.csv', sep=';',skiprows=1)
#df2= pd.read_csv('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv',sep=';',skiprows=1)
#print(df2)
#df2_1= pd.read_csv('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv',sep=';',skiprows=1)
#f2_2= pd.read_csv('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv',sep=';',skiprows=1)
new_file = open(max_file, 'r')
next(new_file)
with open('C:/Users/Žymantas/Desktop/Nasdaq_file/share_export.csv', 'a') as f2:
f2.write(new_file.read().replace(";",","))
new_file.close()
#df3=df2.append(df0, ignore_index=True)
#df3 = df0.append(df2_1, ignore_index=True).append(df2_2, ignore_index=True)
#df3=df2.append(df0,ignore_index=True)
#df3 = df3[~df3.index.duplicated()]
#df3= df3.sort_values(by=['Execution Time'])
#df3.drop_duplicates()
#print(df0.head())
#print(df2.head())
#print(df0)
#print(df2)
#print(df3.tail())
#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', sep=';',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 )