Cache prices from yahoo and accounting metrics from SEC filings. See the blog @ http://andrewonfinance.blogspot.com/.
import pytz
import datetime
import financial_fundamentals as ff
from financial_fundamentals.accounting_metrics import QuarterlyEPS
from financial_fundamentals.indicies import S_P_500_TICKERS
start = datetime.datetime(2013, 1, 1, tzinfo=pytz.UTC)
end = datetime.datetime(2013, 8, 1, tzinfo=pytz.UTC)
eps_cache = ff.sqlite_fundamentals_cache(metric=QuarterlyEPS)
price_cache = ff.sqlite_price_cache()
# The first load_from_cache calls will take a long time as data is downloaded from
# yahoo and edgar.sec.gov, thereafter data will be loaded from cache.
eps_df = eps_cache.load_from_cache(stocks=S_P_500_TICKERS, start=start, end=end)
price_df = price_cache.load_from_cache(stocks=S_P_500_TICKERS, start=start, end=end)
price_to_earnings_df = price_df / eps_df * 4