Since I needed a multi-purpose historical quote downloader, I had written up a
python script that downloads them and write out in to various formats.
Attached is the source code which required yahoo_fin and lxml python modules to
work correctly. It can be provided with two options in fixed order, the first
is the file name to read the tickers symbols from and second is number of days
of historical quotes to download.
From: Fred Tydeman <tydeman.f...@gmail.com>
Sent: Tuesday, January 10, 2023 10:54 AM
To: Kalpesh Patel <kalpesh.pa...@usa.net>
Cc: Geoff <cleanoutmys...@gmail.com>; gnucash-user@gnucash.org
Subject: Re: [GNC] "Get Quotes" from the price database feedback
Have you considered using a Google spreadsheet along with:
GOOGLEFINANCE("NASDAQ:GOOG", "price", DATE(2014,1,1), DATE(2014,12,31), "DAILY")
GOOGLEFINANCE("NASDAQ:GOOG","price",TODAY()-30,TODAY())
It lets you get the prices on a range of dates.
#-########################################################################################################################
#-##
#-## Script to download historical quotes from Yahoo Finance
#-##
#-## Required modules:
#-## yahoo_fin
#-## lxml
#-##
#-## Author: Kalpesh Patel (kalpesh <dot> patel <at> usa <dot> net)
#-##
#-########################################################################################################################
from lxml import html
import datetime
import requests
import sys
# import stock_info module from yahoo_fin
from yahoo_fin import stock_info as si
path_to_file = '.\\'
days_of_quotes = 30
tickers = [
"ABNIX",
"IDCC",
"BK",
"INDEX:XAX",
]
if len(sys.argv) > 2 :
updated_days_of_quotes = int(sys.argv[2])
if updated_days_of_quotes > 0 :
days_of_quotes = updated_days_of_quotes
if len(sys.argv) > 1 :
with open (sys.argv[1]) as file :
read_tickers = file.readlines()
if len(read_tickers) > 0 :
tickers = [ticker.strip() for ticker in read_tickers]
qif_file = open(path_to_file + 'quotes.qif', 'w')
quicken_csv_file = open(path_to_file + 'quicken_quotes.csv', 'w')
gnucash_csv_file = open(path_to_file + 'gnucash_quotes.csv', 'w')
err_file = open(path_to_file + 'quotes_error.csv', 'w')
userAgent = {'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.114 Safari/537.36 Edg/91.0.864.59'}
userAgent = {'user-agent' : 'Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0'}
for ticker in tickers :
today = datetime.date.today()
window_end = today + datetime.timedelta(days = 1)
window_start = window_end - datetime.timedelta(days = days_of_quotes)
actual_ticker = ticker.replace ("INDEX:", '^')
try:
# print(si.get_quote_table(ticker.replace ("INDEX:", '^'), dict_result = True))
records = si.get_data(actual_ticker, start_date = window_start, end_date = window_end, index_as_date = False, interval = "1d")
except:
err_file.write(ticker + "\n")
else:
if records.size > 0 :
try:
url = "http://d.yimg.com/autoc.finance.yahoo.com/autoc?query={}®ion=1&lang=en".format(actual_ticker)
result = requests.get(url).json()
except:
pass
else:
qif_file.write('!Type:Security\n')
for x in result['ResultSet']['Result'] :
if x['symbol'] == (actual_ticker) :
qif_file.write('N' + x['name'] + '\n')
qif_file.write('S' + ticker + '\n')
security_type = 'Stock'
for x in result['ResultSet']['Result'] :
if x['type'] == 'M' :
security_type = 'Mutual Fund'
if x['type'] == 'I' :
security_type = 'Market Index'
qif_file.write('T' + security_type + '\n')
qif_file.write('^' + '\n')
try:
info_url = "https://finance.yahoo.com/quote/{}/".format(actual_ticker)
except:
pass
else:
info_result = requests.get(info_url, headers=userAgent) #.json()
tree = html.fromstring(info_result.content)
namespace = tree.xpath('//*[@id="quote-header-info"]/div[2]/div[1]/div[2]/span/text()')
exchange = str(namespace)[2:-2].split("-",1)[0].replace(" ","").upper()
for index, row in records.iterrows() :
# security = row['ticker']
security = ticker
closing_price = str(row['adjclose']).replace(",", "")
high = str(row['high'])
low = str(row['low'])
vol = str(row['volume']/100)
price_date = row['date']
date = price_date.strftime("%m/%d/%Y")
csv_quote_line = security + ", " + closing_price + ", ---, " + date + ", ---, " + high + ", " + low + ", " + vol + ', *'
gnc_quote_line = "\"" + exchange +"\",\"" + actual_ticker + "\",\"" + date + "\"," + closing_price + ",\"USD\""
qif_quote_line = '!Type:Prices' + "\n" + '"' + security + '",' + closing_price + ',"' + date + '"' + "\n" + '^'
print(gnc_quote_line)
if closing_price != "nan":
quicken_csv_file.write(csv_quote_line + "\n")
gnucash_csv_file.write(gnc_quote_line + "\n")
qif_file.write(qif_quote_line + "\n")
# print(records)
# print(records[["ticker","close","date"]])
gnucash_csv_file.close()
quicken_csv_file.close()
err_file.close()
qif_file.close()
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