def result(): return parse_ticker_dataframe(RESULT_BITTREX['result'], arrow.get('2017-08-30T10:00:00'))
def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]: """Creates a dataframe and populates indicators for given ticker data""" return { pair: populate_indicators(parse_ticker_dataframe(pair_data)) for pair, pair_data in tickerdata.items() }
def result(): with open('freqtrade/tests/testdata/BTC_ETH-1.json') as data_file: return parse_ticker_dataframe(json.load(data_file))
def result(): with open('freqtrade/tests/testdata/btc-eth.json') as data_file: data = json.load(data_file) return parse_ticker_dataframe(data['result'])
def preprocess(backdata) -> Dict[str, DataFrame]: processed = {} for pair, pair_data in backdata.items(): processed[pair] = populate_indicators( parse_ticker_dataframe(pair_data)) return processed
def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]: """Creates a dataframe and populates indicators for given ticker data""" return {pair: populate_indicators(parse_ticker_dataframe(pair_data)) for pair, pair_data in tickerdata.items()}
def result(): with open('freqtrade/tests/testdata/BTC_ETH-1.json') as data_file: return parse_ticker_dataframe(json.load(data_file))
# gather data while True: # check time t = datetime.utcnow() s = t.second m = t.minute if s == 0 and m % trade_interval == 0: # get OHLC candles period = 'M' + str(trade_interval) resp = hitbtc.get_candles(market, limit=1000, period=period) # parse response into data frame and add technical indicators df = parse_ticker_dataframe(resp, exchange_name='HitBTC') df = populate_indicators(df) # add ask, bid, and last ticker = hitbtc.get_tickers(market) df['ask'] = ticker['ask'] df['bid'] = ticker['bid'] df['last'] = ticker['last'] # save the last row of data frame file_name = list(str(df['date'][len(df) - 1])) file_name = "".join(file_name).replace(' ', '_').replace(':', '-') + '.csv' save_path = os.path.join(market_path, file_name) df.tail(1).to_csv(save_path, index=False)