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)
