def get_and_save_quotes_data(etfname, date):
etfname = etfname
date = date
etfData = LoadHoldingsdata().LoadHoldingsAndClean(etfname=etfname,
fundholdingsdate=date)
ob = TradesQuotesProcesses(symbols=etfData.getSymbols(), date=date)
ob.fetch_and_store_runner(collection_name=quotesCollection)
quotesDataDf = ob.get_data(collection_name=quotesCollection,
pipeline=quotespipeline)
print(quotesDataDf)
print("SAVED Quotes for {} {}".format(etfname, date))
def all_process_runner_trades(self, symbols=None, date_for=None):
if not symbols:
etf_data = LoadHoldingsdata().LoadHoldingsAndClean(
etfname=self.etf_name, fundholdingsdate=self.date)
symbols = etf_data.getSymbols()
# symbols_to_download = [symbol for symbol in symbols if
# not self.symbol_check_trades(symbol=symbol, collection=self.per_sec_live_trades)]
trades_quotes_proc_obj = TradesQuotesProcesses(symbols=symbols,
date=date_for)
print("Processing historic trade data")
trades_quotes_proc_obj.trades_fetch_and_store_runner_live(
collection_name=self.connection.ETF_db.PerSecLiveTrades,
per_sec_create_url_func=self.create_urls_for_trades)
def getAndSaveTradesData(etfname, date):
etfname = etfname
date = date
etfData = LoadHoldingsdata().LoadHoldingsAndClean(etfname=etfname,
fundholdingsdate=date)
ob = TradesQuotesProcesses(symbols=etfData.getSymbols(), date=date)
ob.fetch_and_store_runner(collection_name=tradeCollection,
trade_data_flag=True)
tradesDataDf = ob.get_data(collection_name=tradeCollection,
pipeline=tradespipeline)
tradesDataDf['Trade Price'] = (tradesDataDf['High Price'] +
tradesDataDf['Low Price']) / 2
print(tradesDataDf)
print("SAVED {} {}".format(etfname, date))