def __init__(self, user_settings):
self.user_settings = user_settings
self.historicalMarketDataService = HistoricalMarketDataService(
self.user_settings)
self.ratioDataService = RatioDataService(self.user_settings)
self.temp_dir = getTempPath(userSettings=user_settings)
self.cacher = joblib.Memory(self.temp_dir)
self.temp_dir_data_downloaded = getTempPath(
self.user_settings
) + os.sep + 'ratio_list_from_input_vectorized.pkl'
if os.path.isfile(self.temp_dir_data_downloaded):
self.ratio_list_from_input_vectorized = joblib.load(
self.temp_dir_data_downloaded)
# self.lock = Lock()
pass
def __init__(self, user_settings):
self.tokenKey = user_settings.quandl_token
self.user_settings = user_settings
quandl.ApiConfig.api_key = self.tokenKey
self.temp_dir = getTempPath(userSettings=user_settings)
self.cacher = joblib.Memory(self.temp_dir, compress=9, verbose=0)
pass
def __init__(self, user_settings):
self.user_settings = user_settings
self.financial_downloader = gm.FinancialsDownloader()
# self.key_ratios_downloader = gm.KeyRatiosDownloader()
self.temp_dir = getTempPath(userSettings=user_settings)
self.cacher = joblib.Memory(self.temp_dir)
# kr = gm.KeyRatiosDownloader()
pass
def __init__(self, user_settings):
import os
self.tokenKey = user_settings.quandl_token
self.user_settings = user_settings
self.url = self.urlPrefixDownload % self.tokenKey
self.quandl_fundamental_data = QuandlFundamentalData(self.user_settings)
weekString = datetime.datetime.today().strftime("%W_%Y")
pathFile = getTempPath(self.user_settings) + os.sep + 'SF0_%s.csv' % weekString
isDownloaded = self.downloadUnzip(pathFile)
if not isDownloaded:
# logger.debug('Getting manually default file')
pathFile = getDatabasePath(self.user_settings) + os.sep + 'SF0.csv'
self.ratio_dict = self.quandl_fundamental_data.ratio_dict
self.temp_dir = getTempPath(self.user_settings)
self.cacher = joblib.Memory(self.temp_dir)
self.pandasData = self.getCSVData(pathFile)
pass
def __init__(self, user_settings):
self.user_settings = user_settings
self.vectorDao = VectorDao(self.user_settings)
self.vectorizedDataService = VectorOnlineService(self.user_settings)
self.vectorizedDataService.parallelDownloadInstruments = False
if self.threads > 1:
self.vectorizedDataService.parallelDownloadRatios = False
else:
self.vectorizedDataService.parallelDownloadRatios = False
self.temp_dir = getTempPath(userSettings=user_settings)
self.cacher = joblib.Memory(self.temp_dir, compress=9, verbose=0)
def getDataDictOfMatrix(self,
instrumentList,
ratioList,
fromDate,
toDate=None,
persistTempFile=None):
start = time.time()
fromDate = pd.datetime(day=fromDate.day,
month=fromDate.month,
year=fromDate.year)
if toDate is None:
toDate = pd.datetime.today()
toDate = pd.datetime(day=toDate.day,
month=toDate.month,
year=toDate.year)
fromDate = convert_date(fromDate)
toDate = convert_date(toDate)
logger.debug('getDataDictOfMatrix downloading/loading...')
logger.debug('instrumentList: %s' % instrumentList)
logger.debug('ratioList: %s' % ratioList)
logger.debug('fromDate: %s' % fromDate)
logger.debug('toDate: %s' % toDate)
logger.debug('persistTempFile: %s' % persistTempFile)
outputDict = self.__getAllInstrumentData__(instrumentList, ratioList,
fromDate, toDate)
assetType = instrumentList[0].asset_type
outputDictFinal = self.__cleanData__(outputDict,
assetType=assetType,
persistTempFile=persistTempFile)
end = time.time()
logger.info('******')
minutesTime = (end - start) / 60
logger.info('Took %f minutes to finish __getDataDictOfMatrix__' %
(minutesTime))
logger.info('******')
import os
outputDictFinal = self.__allignSymbolsDictMatrix__(outputDictFinal)
outputDictFinal = self.__cleanSymbolsDictMatrix__(outputDictFinal)
logger.info('Finished => saving dictOfMatrix_last.pickle')
save_to_file(
outputDictFinal,
getTempPath(self.user_settings) + os.sep +
'dictOfMatrix_last.pickle')
return outputDictFinal