How to Extract Yahoo Finance Data with Stock Prices, Price Change, Bids, and more?

Steps of Extracting Yahoo Finance

  • Make an URL of search result pages from Yahoo Finance.
  • Download HTML of search result pages with Python requests.
  • Scrolling the page with LXML-LXML as well as help you navigate an HTML tree structure through Xpaths. We have well-defined the Xpaths for details needed for a code.
  • Save downloaded data into the JSON file.

The Script We Have Used

from lxml import html
import requests
import json
import argparse
from collections import OrderedDict
def get_headers():
return {"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9",
"accept-encoding": "gzip, deflate, br",
"accept-language": "en-GB,en;q=0.9,en-US;q=0.8,ml;q=0.7",
"cache-control": "max-age=0",
"dnt": "1",
"sec-fetch-dest": "document",
"sec-fetch-mode": "navigate",
"sec-fetch-site": "none",
"sec-fetch-user": "?1",
"upgrade-insecure-requests": "1",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.122 Safari/537.36"}
def parse(ticker):
url = "" % (ticker, ticker)
response = requests.get(
url, verify=False, headers=get_headers(), timeout=30)
print("Parsing %s" % (url))
parser = html.fromstring(response.text)
summary_table = parser.xpath(
summary_data = OrderedDict()
other_details_json_link = "{0}?formatted=true&lang=en-US®ion=US&modules=summaryProfile%2CfinancialData%2CrecommendationTrend%2CupgradeDowngradeHistory%2Cearnings%2CdefaultKeyStatistics%2CcalendarEvents&".format(
summary_json_response = requests.get(other_details_json_link)
json_loaded_summary = json.loads(summary_json_response.text)
summary = json_loaded_summary["quoteSummary"]["result"][0]
y_Target_Est = summary["financialData"]["targetMeanPrice"]['raw']
earnings_list = summary["calendarEvents"]['earnings']
eps = summary["defaultKeyStatistics"]["trailingEps"]['raw']
datelist = []
for i in earnings_list['earningsDate']:
earnings_date = ' to '.join(datelist)
for table_data in summary_table:
raw_table_key = table_data.xpath(
raw_table_value = table_data.xpath(
table_key = ''.join(raw_table_key).strip()
table_value = ''.join(raw_table_value).strip()
summary_data.update({table_key: table_value})
summary_data.update({'1y Target Est': y_Target_Est, 'EPS (TTM)': eps,
'Earnings Date': earnings_date, 'ticker': ticker,
'url': url})
return summary_data
except ValueError:
print("Failed to parse json response")
return {"error": "Failed to parse json response"}
return {"error": "Unhandled Error"}
if __name__ == "__main__":
argparser = argparse.ArgumentParser()
argparser.add_argument('ticker', help='')
args = argparser.parse_args()
ticker = args.ticker
print("Fetching data for %s" % (ticker))
scraped_data = parse(ticker)
print("Writing data to output file")
with open('%s-summary.json' % (ticker), 'w') as fp:
json.dump(scraped_data, fp, indent=4)

How the Scraper Has Got Executed?

python3 -h
usage: [-h] ticker
positional arguments: ticker optional arguments: -h, --help show this help message and exit
python3 AAPL
"Previous Close": "293.16",
"Open": "295.06",
"Bid": "298.51 x 800",
"Ask": "298.88 x 900",
"Day's Range": "294.48 - 301.00",
"52 Week Range": "170.27 - 327.85",
"Volume": "36,263,602",
"Avg. Volume": "50,925,925",
"Market Cap": "1.29T",
"Beta (5Y Monthly)": "1.17",
"PE Ratio (TTM)": "23.38",
"EPS (TTM)": 12.728,
"Earnings Date": "2020-07-28 to 2020-08-03",
"Forward Dividend & Yield": "3.28 (1.13%)",
"Ex-Dividend Date": "May 08, 2020",
"1y Target Est": 308.91,
"ticker": "AAPL",
"url": ""

Why Do You Need to Scrape Yahoo Finance News?



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