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from selenium import webdriver | |
from selenium.webdriver.chrome.options import Options | |
from selenium.webdriver.support.ui import WebDriverWait | |
from selenium.webdriver.support import expected_conditions as EC | |
from selenium.webdriver.common.by import By | |
from time import sleep | |
import pandas as pd | |
def get_currencies(currencies, start, end, export_csv=False): | |
frames = [] | |
for currency in currencies: | |
while True: | |
try: | |
# Opening the connection and grabbing the page | |
my_url = f'https://br.investing.com/currencies/usd-{currency.lower()}-historical-data' | |
option = Options() | |
option.headless = False | |
driver = webdriver.Chrome(options=option) | |
driver.get(my_url) | |
driver.maximize_window() | |
# Clicking on the date button | |
date_button = WebDriverWait(driver, 20).until( | |
EC.element_to_be_clickable((By.XPATH, "/html/body/div[5]/section/div[8]/div[3]/div/div[2]/span"))) | |
date_button.click() | |
# Sending the start date | |
start_bar = WebDriverWait(driver, 20).until( | |
EC.element_to_be_clickable((By.XPATH, "/html/body/div[7]/div[1]/input[1]"))) | |
start_bar.clear() | |
start_bar.send_keys(start) | |
# Sending the end date | |
end_bar = WebDriverWait(driver, 20).until( | |
EC.element_to_be_clickable((By.XPATH, "/html/body/div[7]/div[1]/input[2]"))) | |
end_bar.clear() | |
end_bar.send_keys(end) | |
# Clicking on the apply button | |
apply = WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, "/html/body/div[7]/div[5]/a"))) | |
apply.click() | |
sleep(5) | |
# Getting the tables on the page and quiting | |
dataframes = pd.read_html(driver.page_source) | |
driver.quit() | |
print(f'{currency} scraped.') | |
break | |
except: | |
driver.quit() | |
print(f'Failed to scrape {currency}. Trying again in 30 seconds.') | |
sleep(30) | |
continue | |
# Selecting the correct table | |
for dataframe in dataframes: | |
if dataframe.columns.tolist() == ['Date', 'Price', 'Open', 'High', 'Low', 'Change%']: | |
df = dataframe | |
break | |
frames.append(df) | |
# Exporting the .csv file | |
if export_csv: | |
df.to_csv('currency.csv', index=False) | |
print(f'{currency}.csv exported.') | |
return frames |
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