def prep(tickers):
reader = STOCK_TIMESERIES.init()
values = map(lambda ticker: reader.extract_from_yahoo(ticker), tickers)
values = map(lambda data: pd.DataFrame(data)['Adj Close'], values)
values = list(values)
ret = dict(zip(tickers, values))
ret = pd.DataFrame(ret, columns=tickers)
return ret
def save(cls, local_dir, ticker, dud):
filename = '{}/{}.pkl'.format(local_dir, ticker)
if cls.reader is None:
cls.reader = STOCK_TIMESERIES.init()
prices = cls.reader.extract_from_yahoo(ticker)
if prices is None:
dud.append(ticker)
return dud
STOCK_TIMESERIES.save(filename, ticker, prices)
return dud
def _init(cls) :
if not (cls._data_list is None) :
return cls._data_list
target = 'test_finance_end'
end = globals().get(target,None)
reader = STOCK_TIMESERIES.init(end=end)
target = 'test_finance_stock_list'
stock_list = globals().get(target,[])
cls._data_list = map(lambda stock : reader.extract_from_yahoo(stock), stock_list)
cls._data_list = list(cls._data_list)
return cls._data_list
def _prices(cls, wait_on_failure, local_dir, ticker, dud):
if dud is None:
dud = []
filename = '{}/{}.pkl'.format(local_dir, ticker)
reader = STOCK_TIMESERIES.init()
prices = reader.extract_from_yahoo(ticker)
if prices is None:
dud.append(ticker)
time.sleep(wait_on_failure)
return dud
STOCK_TIMESERIES.save(filename, ticker, prices)
del prices
return dud
def main(local, *stock_list):
logging.info(stock_list)
reader = STOCK_TIMESERIES.init()
for stock in stock_list:
filename = '{}/historical_prices/{}.pkl'.format(local, stock)
ret = reader.extract_from_yahoo(stock)
logging.debug(ret.tail(5))
STOCK_TIMESERIES.save(filename, stock, ret)
if len(stock_list) > 0: return
nasdaq = NASDAQ.init()
for stock in nasdaq():
filename = '{}/historical_prices/{}.pkl'.format(local, stock)
ret = reader.extract_from_yahoo(stock)
STOCK_TIMESERIES.save(filename, stock, ret)
def instance(cls) :
if not (cls._singleton is None) :
return cls._singleton
target = 'env'
env = globals().get(target,None)
target = 'data_store_stock'
stock = globals().get(target,'')
if not isinstance(stock,str) :
stock = str(stock)
target = 'data_store_fund'
fund = globals().get(target,'')
if not isinstance(fund,str) :
fund = str(fund)
reader = STOCK_TIMESERIES.init()
env.mkdir(stock)
env.mkdir(fund)
cls._singleton = cls(env,stock,fund,reader)
return cls._singleton
def instance(cls, **kwargs) :
if not (cls._singleton is None) :
return cls._singleton
target = 'env'
_env = globals().get(target,None)
target = "data_store"
data_store = globals().get(target,[])
target = "output_file"
output_file = globals().get(target,[])
target = 'config_file'
config_file = globals().get(target,[])
if not isinstance(config_file,list) :
config_file = list(config_file)
if len(_env.argv) > 1 :
config_file = [_env.argv[1]]
if len(_env.argv) > 2 :
output_file = [_env.argv[2]]
reader = STOCK_TIMESERIES.init()
env.mkdir(data_store)
cls._singleton = cls(_env,data_store,config_file,output_file,reader)
return cls._singleton
log_msg = '%(module)s.%(funcName)s(%(lineno)s) %(levelname)s - %(message)s'
logging.basicConfig(stream=sys.stdout, format=log_msg, level=logging.DEBUG)
def prep(*ini_list) :
ini_list = filter(lambda x : "benchmark" in x , ini_list)
print (ini_list)
for path, section, key, stock_list in INI.loadList(*ini_list) :
if section == 'Index' : pass
else : continue
yield key, stock_list
file_list = env.list_filenames('local/historical_prices/*pkl')
ini_list = env.list_filenames('local/*.ini')
reader = STOCK_TIMESERIES.init()
for name, stock_list in prep(*ini_list) :
for stock in stock_list :
print ((stock,name))
data = reader.extract_from_yahoo(stock)
if data is None : continue
ret = data[['Adj Close']]
print (ret.head(2))
print (ret.tail(2))
print (ret.mean())
print (ret.std())
print (ret.mean()[0])
print (ret.std()[0])
print (HELPER.find(ret,period=FINANCE.YEAR,span=0))
print (HELPER.find(ret,period=FINANCE.YEAR))
print ((stock,name))
def read(cls, ticker):
if cls.reader is None:
cls.reader = STOCK_TIMESERIES.init()
return cls.reader.extract_from_yahoo(ticker)