Yahoo_fin question: how does one export all stock tickers to a csv file

[Larz60+]

For NASDAQ
ftp.nasdaqtrader.com
hover over product login and choose Market Data, daily list.
You will need to set up an account

You can get historical data from yahoo finance,
here's an app most of this is from Maik Rosenheinrich blog.
I only added class info:

MaikFetchStockData.py

# Note original code by: 
# Modified (slightly) by Larz60+, made into a class that cam be imported
# also added command line usage: python MaikFetchStockData.py symbol
# if run from command line without symbol, will ask for one
# returns a tab delimited csv file.
# you can also supply start and end dates, and reporting interval

import requests                  # [handles the http interactions](http://docs.python-requests.org/en/master/) 
from bs4 import BeautifulSoup    # beautiful soup handles the html to text conversion and more
import re                        # regular expressions are necessary for finding the crumb (more on crumbs later)
from datetime import datetime    # string to datetime object conversion
from time import mktime          # mktime transforms datetime objects to unix timestamps
import sys


class MaikFetchStockData:
    def __init__(self):
        pass

    def _get_crumbs_and_cookies(self, stock):
        """
        The first function calls the website of a selected stock and collects the cookies and crumb.
        We reuse the headers in the subsequent function to mimic the same browser.

        get crumb and cookies for historical data csv download from yahoo finance
        
        parameters: stock - short-handle identifier of the company 
        
        returns a tuple of header, crumb and cookie
        """
        
        # url = 'https://finance.yahoo.com/quote/{}/history'.format(stock)
        url = f"https://finance.yahoo.com/quote/{stock}/history"
        with requests.session():
            header = {'Connection': 'keep-alive',
                    'Expires': '-1',
                    'Upgrade-Insecure-Requests': '1',
                    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) \
                    AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36'
                    }
            
            website = requests.get(url, headers=header)
            soup = BeautifulSoup(website.text, 'lxml')
            crumb = re.findall('"CrumbStore":{"crumb":"(.+?)"}', str(soup))

            return (header, crumb[0], website.cookies)

    # 
    def convert_to_unix(self, date):
        """
        The second function just converts the provided start/stop dates into unix timestamps, because yahoo finance uses these in the request url. 

        converts date to unix timestamp
        
        parameters: date - in format (dd-mm-yyyy)
        
        returns integer unix timestamp
        """
        datum = datetime.strptime(date, '%d-%m-%Y')
        
        return int(mktime(datum.timetuple()))


    def load_csv_data(self, stock, interval='1d', day_begin='01-01-1991', day_end='02-11-2021'):
        """
        While the last function does the actual requesting of the historical stock data.
        This function returns a list of the individual daily values, containing the header (row 0) and subsequently one line per day. 
        
        queries yahoo finance api to receive historical data in csv file format
        
        parameters: 
            stock - short-handle identifier of the company
            
            interval - 1d, 1wk, 1mo - daily, weekly monthly data
            
            day_begin - starting date for the historical data (format: dd-mm-yyyy)
            
            day_end - final date of the data (format: dd-mm-yyyy)
        
        returns a list of comma seperated value lines
        """
        day_begin_unix = self.convert_to_unix(day_begin)
        day_end_unix = self.convert_to_unix(day_end)
        
        header, crumb, cookies = self._get_crumbs_and_cookies(stock)
        
        with requests.session():
            url = 'https://query1.finance.yahoo.com/v7/finance/download/' \
                '{stock}?period1={day_begin}&period2={day_end}&interval={interval}&events=history&crumb={crumb}' \
                .format(stock=stock, day_begin=day_begin_unix, day_end=day_end_unix, interval=interval, crumb=crumb)
                    
            website = requests.get(url, headers=header, cookies=cookies)
        
            return website.text.split('\n')[:-1]

    def get_csv_data(self, ticker='^DJI', interval='1d', day_begin='01-01-1991', day_end='02-11-2021'):
        return self.load_csv_data(ticker, interval='1d', day_begin='01-01-1991', day_end='02-11-2021')


def main(argv):
    getquote = MaikFetchStockData()
    print(f"length: {len(argv)}")
    if len(argv) == 1:
        stock = input("Please enter stock symbol: ")
    else:
        stock = argv[1]
    csvdata = getquote.load_csv_data(stock)
    print(csvdata)


if __name__ == '__main__':
    main(sys.argv)

sample output for python MaikFetchStockData.py ^DJI > DJI.csv

Output:
['Date,Open,High,Low,Close,Adj Close,Volume',
'1992-01-02,1357.599976,1357.619995,1330.900024,1342.099976,1342.099976,41400',
'1992-01-03,1342.300049,1354.630005,1342.300049,1350.699951,1350.699951,45900',
'1992-01-06,1350.699951,1366.219971,1349.219971,1365.500000,1365.500000,48800',
'1992-01-07,1365.500000,1383.030029,1361.550049,1383.000000,1383.000000,57000',

...

'2021-02-05,12727.879883,12833.669922,12727.879883,12788.509766,12788.509766,852300',
'2021-02-08,12793.919922,12894.870117,12782.839844,12874.919922,12874.919922,1231400',
'2021-02-09,12871.200195,12993.620117,12780.129883,12959.900391,12959.900391,830100',
'2021-02-10,12976.240234,13041.500000,12885.309570,12954.530273,12954.530273,809300']

to use in your own program,

from MaikFetchStockData import MaikFetchStockData

class myclass:
    def __init__(self):
        self.fetch_stockdata = MaikFetchStockData().get_csv_data

    def get_stuff(self, symbol):
        return self.fetch_stockdata(symbol)

if __name__ == '__main__':
    mc = myclass()
    print(mc.get_stuff('MSFT'))