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yahoo-finance-scraper.py
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yahoo-finance-scraper.py
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from lxml import html
import requests
from time import sleep
from collections import OrderedDict
import csv
import argparse
import os
import logging
import urllib3
urllib3.disable_warnings()
import pandas as pd
import sys
# File where the tickers downloaded from Wikipedia are stored
TICKERS = 'tickers.csv'
logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s', level=logging.INFO)
def __init_dict(ticker):
'''
Cretes a dict object.
'''
summary_data = OrderedDict()
summary_data['ticker'] = ticker
summary_data['current_price'] = 'NA'
summary_data['PEG_5y'] = 'NA'
summary_data['trailing_pe'] = 'NA'
summary_data['forward_pe'] = 'NA'
summary_data['beta'] = 'NA'
summary_data['enterprise_to_ebitda'] = 'NA'
summary_data['52_week_change_pct'] = 'NA'
summary_data['SPY_52_week_change_pct'] = 'NA'
summary_data['short_pct_of_float'] = 'NA'
summary_data['profit_margins_pct'] = 'NA'
summary_data['earnings_growth_pct'] = 'NA'
summary_data['revenue_growth_pct'] = 'NA'
summary_data['ROA_pct'] = 'NA'
summary_data['ROE_pct'] = 'NA'
summary_data['total_cash_bn'] = 'NA'
summary_data['total_debt_bn'] = 'NA'
summary_data['total_revenue_bn'] = 'NA'
summary_data['target_low_price'] = 'NA'
summary_data['target_mean_price'] = 'NA'
summary_data['target_median_price'] = 'NA'
summary_data['target_high_price'] = 'NA'
return summary_data
def _parse_data(ticker, json_string):
'''
Parse the data from JSON.
'''
summary_data = __init_dict(ticker)
try:
summary_data['current_price'] = float(json_string["quoteSummary"]["result"][0]["financialData"]['currentPrice']['fmt'])
except:
pass
try:
summary_data['PEG_5y'] = float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['pegRatio']['fmt'])
except:
pass
try:
summary_data['trailing_pe'] = round(summary_data['current_price'] / float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['trailingEps']['fmt']), 2)
except:
pass
try:
summary_data['forward_pe'] = float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['forwardPE']['fmt'])
except:
pass
try:
summary_data['beta'] = float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['beta']['fmt'])
except:
pass
try:
summary_data['enterprise_to_ebitda'] = float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['enterpriseToEbitda']['fmt'])
except:
pass
try:
summary_data['52_week_change_pct'] = round(float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['52WeekChange']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['SPY_52_week_change_pct'] = round(float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['SandP52WeekChange']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['short_pct_of_float'] = round(float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['shortPercentOfFloat']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['profit_margins_pct'] = round(float(json_string["quoteSummary"]["result"][0]["defaultKeyStatistics"]['profitMargins']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['earnings_growth_pct'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['earningsGrowth']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['revenue_growth_pct'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['revenueGrowth']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['ROA_pct'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['returnOnAssets']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['ROE_pct'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['returnOnEquity']['raw']) * 100.0, 2)
except:
pass
try:
summary_data['total_cash_bn'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['totalCash']['raw']) / 10**9, 2)
except:
pass
try:
summary_data['total_debt_bn'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['totalDebt']['raw']) / 10**9, 2)
except:
pass
try:
summary_data['total_revenue_bn'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['totalRevenue']['raw']) / 10**9, 2)
except:
pass
try:
summary_data['target_low_price'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['targetLowPrice']['raw']), 2)
except:
pass
try:
summary_data['target_mean_price'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['targetMeanPrice']['raw']), 2)
except:
pass
try:
summary_data['target_median_price'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['targetMedianPrice']['raw']), 2)
except:
pass
try:
summary_data['target_high_price'] = round(float(json_string["quoteSummary"]["result"][0]["financialData"]['targetHighPrice']['raw']), 2)
except:
pass
return summary_data
class YahooFinanceScraper():
'''
Download data from Yahoo Finance
'''
def __init__(self, input, output, pause, timeout):
'''
type input: str (path of tickers file)
type output: str (path of file where results are stored)
type pause: int (interval between two consecutive requests to yahoo finance, in seconds)
type timeout: int (timeout for HTTP requets, in seconds)
'''
self.input = input
self.output = output
self.pause = pause
self.timeout = timeout
if not os.access(self.input, os.R_OK):
logging.warning('Unable to read {0}. Donwloading list of tickers from Wikipedia...'.format(self.input))
get_tickers_from_wikipedia(self.input)
def __count_rows(self):
'''
Count the number of rows.
'''
with open(self.input, 'r') as f:
# the 1st line is a comment
return sum(1 for line in f) - 1
def download_all(self):
'''
Download data for all tickers.
'''
row_count = self.__count_rows() # count number of rows
logging.info("Total {0} rows".format(row_count))
with open(self.input, 'r') as tickers:
csv_reader = csv.reader(tickers, delimiter=',')
next(csv_reader, None) # skip the headers
counter = 0 # count number of processed tickers
write_header = True # write header the 1st time only
for row in csv_reader:
ticker = row[0]
if '.' in ticker: # e.g., Berkshire
logging.debug('Ticker {0}, replacing . with -'.format(ticker))
ticker = ticker.replace('.', '-')
counter = counter + 1
logging.info('{0}/{1}: downloading {2}...'.format(counter, row_count, ticker))
try:
summary_data = self.download(ticker)
self.write_data_about_ticker(summary_data, write_header)
write_header = False
except Exception, e:
logging.error("Error while downloading data for {0}: {1}".format(ticker, e))
sleep(self.pause)
def download(self, ticker):
'''
Download data about the specified ticker.
type ticker: str
'''
url = "https://finance.yahoo.com/quote/{0}".format(ticker)
response = requests.get(url, verify=False)
parser = html.fromstring(response.text)
summary_table = parser.xpath('//div[contains(@data-test,"summary-table")]//tr')
summary_data = OrderedDict()
other_details_json_link = "https://query2.finance.yahoo.com/v10/finance/quoteSummary/{0}?formatted=true&modules=financialData%2CdefaultKeyStatistics".format(ticker)
json_response = requests.get(other_details_json_link, timeout = self.timeout)
json_string = json_response.json()
#parsed_json = json.dumps(json_string, sort_keys=True, indent=4) # print nicely
return _parse_data(ticker, json_string)
def write_data_about_ticker(self, summary_data, write_header):
'''
Write data to CSV.
type summary data: dict
type write_header: bool
'''
flag = 'w' if write_header else 'a' # open in write or append mode
with open(self.output, flag) as f:
w = csv.DictWriter(f, fieldnames = summary_data.keys())
if write_header:
w.writeheader()
else:
pass
w.writerow(summary_data)
def get_tickers_from_wikipedia(save_to):
'''
Get list of S&P 500 components from Wikipedia
'''
url = 'https://en.wikipedia.org/wiki/List_of_S%26P_500_companies#S&P_500_Component_Stocks'
l = pd.read_html (url)
# store the result in a dataframe - you only need the first element, the table
output = pd.DataFrame(l[0])
# keep only columns: Security Symbol and GICS Sector
output = output.drop(columns=[2, 4, 5, 6, 7, 8], axis=1)
output = output[[1, 0, 3]] # swap order of ticker and company name
output.to_csv(save_to, sep=',', encoding='utf-8',index=False, header=None)
# Main
if __name__=="__main__":
parser = argparse.ArgumentParser(description='Get data about the S&P 500 companies.', usage='%(prog)s [options]')
parser.add_argument('--all_tickers', action='store_true', required = False, help = 'Download data for all companies [default: true].')
parser.add_argument('--ticker', type = str, required = False, help = 'Download data for "ticker" only.')
parser.add_argument('-d', '--download_index', action='store_true', required = False, help = 'Download list of all S&P 500 compononents [default: false].')
parser.add_argument('-i', '--input', type = str, required = False, default=TICKERS, help = 'File containing the tickers, in CSV format. Tickers are in the 1st column [default: ./tickers.csv].')
parser.add_argument('-o', '--output', type = str, required = False, default='result.csv', help = 'File where results are stored, in CSV format [default: ./result.csv].')
parser.add_argument('-a', '--append', action='store_true', required = False, help = 'Do no create header [Default: false].')
parser.add_argument('-p', '--pause', type = int, required = False, default = 4, help = 'Interval between requests to Yahoo Finance [default: 4 seconds].')
parser.add_argument('-t', '--request_timeout', type = int, required = False, default = 1, help = 'Timeout for Yahoo Finance requests.')
args = parser.parse_args()
if args.all_tickers and args.ticker is not None:
raise argparse.ArgymentTypeError('Invalid option: all-tickers and ticker cannot be used together.')
dir_path = os.path.dirname(os.path.realpath(args.output))
if not os.access(dir_path, os.W_OK):
raise argparse.ArgumentTypeError('Unable to write to {0}'.format(dir_path))
if args.download_index:
logging.info("Downloading tickers from Wikipedia...")
get_tickers_from_wikipedia(args.input)
if args.all_tickers:
logging.info("Downloading all data. It will take approximately 40 minutes...")
scraper = YahooFinanceScraper(args.input, args.output, args.pause, args.request_timeout)
scraper.download_all()
elif args.ticker:
logging.info("Downloading data for {0}".format(args.ticker))
scraper = YahooFinanceScraper(args.input, args.output, args.pause, args.request_timeout)
summary_data = scraper.download(args.ticker)
scraper.write_data_about_ticker(summary_data, args.append)
sys.exit(0)