Fetches 10-Year Historical Stock Prices from Nasdaq and saves them as CSV

10y_historical_prices_nasdaq.py

import requests
import bs4 as bs
import csv
import re

def historical_prices(symbol:str):
    url = "https://www.nasdaq.com/symbol/{0}/historical".format(symbol)
    headers = {'content-type' : 'application/json'}
    data = "10y|false|{0}".format(symbol)
    resp = requests.post(url, data=data, headers=headers)
    soup = bs.BeautifulSoup(resp.text, 'lxml')
    historical_container = soup.find("div", {"id" : "quotes_content_left_pnlAJAX"})
    table = historical_container.find("table")
    historical_prices = []
    for row in table.findAll('tr')[2:]:
        date = re.sub(r"[\n\t\s]*", "", row.findAll('td')[0].text)
        price_open = re.sub(r"[\n\t\s]*", "", row.findAll('td')[1].text)
        price_high = re.sub(r"[\n\t\s]*", "", row.findAll('td')[2].text)
        price_low = re.sub(r"[\n\t\s]*", "", row.findAll('td')[3].text)
        price_close = re.sub(r"[\n\t\s]*", "", row.findAll('td')[4].text)
        volume = re.sub(r"[\n\t\s]*", "", row.findAll('td')[5].text)
        historical_prices.append((date,price_open,price_high,price_low,price_close,volume))

    # Save to CSV
    file_name = "{0}_10y.csv".format(symbol)
    with open(file_name, 'w') as csv_file:
        writer = csv.writer(csv_file)
        writer.writerow(['date', 'open', 'high', 'low', 'close', 'volume'])
        for row in historical_prices:
           writer.writerow(row)

    return historical_prices


def main():
    prices = historical_prices('aapl')
    

if  __name__ =='__main__':
	main()