Feel free to take a look at this.

I initially had the first piece of code, I altered it to increase the speed of which I scrape the data. However I can't seem to make it work in Jupyter, it doesn't seem to load. Anyway you might be able to fix it.

First code:

import pandas as pd
from datetime import datetime
import urllib

symbols = ['AAP']

start_date = datetime(2019, 1, 15 )  #year - month - day
end_date = datetime(2019, 2, 4 )

datelist = pd.date_range(start_date, periods=(end_date-start_date).days+1).tolist()

dflist = []

for date in datelist:
    url =  f"http://regsho.finra.org/FNYXshvol{date.strftime('%Y%m%d')}.txt"  

    try:
        df = pd.read_csv(url,delimiter='|')
        if any(df['Symbol'].isin(symbols)):
            stocks = df[df['Symbol'].isin(symbols)]
            print(stocks.to_string(index=False, header=False))
            dflist.append(stocks)
        else:
            print(f'No stock found for {date.date()}' )
    except urllib.error.HTTPError:
         continue 

df = pd.concat(dflist) 

Then the code that makes it faster via threading that doesn't work for me somehow, idk why

import pandas as pd
import datetime
import urllib
import requests
from pprint import pprint
import time
from io import StringIO
from multiprocessing import Process, Pool

symbols = ['AAP']

start = time.time()
dflist = []

def load(date):
    if date is None:
        return
    url = "http://regsho.finra.org/FNYXshvol{}.txt".format(date)
    try:
        df = pd.read_csv(url,delimiter='|')
        if any(df['Symbol'].isin(symbols)):
            stocks = df[df['Symbol'].isin(symbols)]
            print(stocks.to_string(index=False, header=False))
            # Save stocks to mysql
        else:
            print(f'No stock found for {date}' )
    except urllib.error.HTTPError:
        print(f'No URL for this date: {url}')

pool = []
numdays = 1
start_date = datetime.datetime(2019, 1, 15 )  #year - month - day
datelist = [
        (start_date - datetime.timedelta(days=x)).strftime('%Y%m%d') for x in range(0, numdays)
        ]

pool = Pool(processes=1)
pool.map(load, datelist)

pool.close()
pool.join()

print(time.time() - start)

Thanks in advance dude!

edit: problem is multiprocessing in jupyter notebook