def get_div_yield(symbol):
stock = YahooFinancials(symbol)
if stock.get_dividend_yield() != None:
y = stock.get_dividend_yield()
elif stock.get_summary_data()[symbol] != None:
y = stock.get_summary_data()[symbol]['yield']
else:
y = 0
if y == None:
return 0
else:
return y
def summary_data(ticker):
# summary_data_list = []
# for ticker in tickers:
yahoo_financials = YahooFinancials(ticker)
ass = yahoo_financials.get_summary_data(reformat=True)
summary_data = pd.DataFrame.from_dict(ass).T
# summary_data_list.append(summary_data)
return summary_data
def getMarketCap(self, ticker):
# retrieve stock market cap
# ----Input-----
# ticker: ticker name for the stock
# ----output----
# stock market cap
dataSource = YahooFinancials(ticker)
return dataSource.get_summary_data()[ticker]['marketCap']
def fundamentals(tickers, begin="2020-05-26", end="2020-06-26",):
format_header = '{:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>10} {:>10}'
format_numbers = '{:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>6} {:>10.2e} {:>10.2E}'
print(format_header.format('ticker', 'P/E', 'EARNSH', 'BK/PR', 'DY', 'DR', 'VAR', 'PEG', 'PS', 'PCI', 'VOLPR', 'CM',))
for ticker in tickers:
yf = YF(ticker)
try:
pe = get_number_for_None(get_number_for_None(yf.get_pe_ratio()))
prices = yf.get_historical_price_data(begin, end, "daily")[ticker]['prices']
stat_pr = calc_statistics(prices)
var_pr = get_number_for_None(100 * stat_pr[1] / stat_pr[0])
volume = get_number_for_None(stat_pr[4])
es = get_number_for_None(yf.get_earnings_per_share())
sh = get_number_for_None(yf.get_num_shares_outstanding(price_type='current'))
''' "pegRatio" "priceToBook" "heldPercentInstitutions" '''
statistics = yf.get_key_statistics_data()[ticker]
summary = yf.get_summary_data()[ticker]
peg = get_number_for_None(statistics["pegRatio"])
PCI = get_number_for_None(statistics["heldPercentInstitutions"])
bv = yf.get_key_statistics_data()[ticker]['bookValue']
pr = yf.get_current_price()
if pr is not None and bv is not None:
pr_bv = get_number_for_None(pr/bv)
else:
pr_bv = '-99.99'
f_s = yf.get_financial_stmts('annual', 'income')['incomeStatementHistory'][ticker][0]
f_s_key = list(f_s.keys())[0]
totalRevenue = f_s[f_s_key]['totalRevenue']
outstanding = statistics["sharesOutstanding"]
rev_per_share = totalRevenue / outstanding
if pr is not None and es is not None:
p_s = get_number_for_None(rev_per_share/float(es))
else:
p_s = '99'
dy = get_number_for_None(yf.get_dividend_yield())
dr = get_number_for_None(yf.get_dividend_rate())
volume10days = summary['averageVolume10days']
marketCap = summary['marketCap']
# float(volume)*pr
# float(sh)*pr)
print(format_numbers.format(ticker, pe, es, pr_bv, dy, dr, var_pr, peg, p_s, PCI, volume10days, marketCap))
except Exception as e:
print(ticker, e)
def _DownloadTotalAssetsFromYahooFinance(self, symbols: List[Text]) -> List[Optional[Text]]:
csv_data = []
assets = YahooFinancials(symbols)
summaries = assets.get_summary_data()
for symbol in symbols:
today = datetime.datetime.now().strftime("%Y-%m-%d")
if symbol in summaries and 'totalAssets' in summaries[symbol] and summaries[symbol]['totalAssets'] is not None:
lines = ['Date,Amount'] # Header
total_assets = summaries[symbol]['totalAssets']
csv_data.append(f'Date,TotalAssets\n{today},{total_assets}\n')
else:
csv_data.append(None)
return csv_data
def defaultapi(ticker):
tick = YF(ticker)
print(tick.get_summary_data())
print(mark)
print(tick.get_stock_quote_type_data())
print(mark)
print(tick.get_stock_price_data())
print(mark)
print(tick.get_current_price())
print(mark)
print(tick.get_dividend_rate())
try:
r = tick._cache.keys()
except AttributeError:
pass
else:
print(mark)
print(r)
summary_ticker['diff10Av'] = 100 * diff10Av > limit
def set_ticker(summary_ticker, ticker):
summary_ticker['ticker'] = ticker
if __name__ == '__main__':
str_out = ' '
for key in keys:
str_out += ' ' + keys_head[key]
print(str_out)
for ticker in tickers:
try:
yf = YahooFinancials(ticker)
summary = yf.get_summary_data()
info_dict[ticker] = summary[ticker]
# fiftyTwoWeekHigh
calc_pc_fifty(summary[ticker], 'fiftyTwoWeekHigh')
volume_diff(summary[ticker])
str_out = ticker
for key in keys:
try:
resp = summary[ticker][key]
if resp == True or resp == False:
str_out += ' ' + "{}".format(resp)
else:
str_out += ' ' + "{0:.1f}".format(resp)
except Exception as e:
str_out += ' ' + "{:12.12}".format(resp)
tickerDataFrame = pd.read_csv(csvPath)
tickerSeries = tickerDataFrame['ticker'][0:nStocks]
#get the list of tickers from the column named ticker
#create ASX stocks by appending .AX to the stock name
if asxStocks:
for i in range(len(tickerSeries)):
tickerSeries[i] = tickerSeries[i] + '.AX'
print('Loaded in tickers series -->\n ', tickerSeries)
return tickerSeries
if __name__ == '__main__':
#load ticker series
#here we use the ASX 200 largest companies by market capitalisation
tickerSeries = tickers_from_csv(CSV_PATH, nStocks=5)
#create the YahooFinancials connection object
stocks = YahooFinancials(tickerSeries)
#Pull the data and time it
startTime = time.time()
data = stocks.get_summary_data()
timeTaken = time.time() - startTime
print('Download took {t} seconds'.format(t=timeTaken))
stockDataFrame = pd.DataFrame(data)
stockDataFrame.to_csv(OUTPUT_PATH)