def hull_moving_average(close, n):
try:
df = pd.DataFrame()
df['hull_mavg'] = hma(close, n)
return df
except Exception as e:
raise (e)
def getData(self):
#get url to data from kraken api
pair = self.pair
interval = str(self.interval)
base = 'https://api.kraken.com'
endpoint = '/0/public/OHLC'
params = '?pair=' + pair + '&interval=' + interval
url = base + endpoint + params
#download the data
json_string = requests.get(url)
dictionary = json.loads(json_string.text)
dict_len = len(dictionary['result'][pair])
self.dflength = dict_len
#creat pandas df
col_names = ['time', 'open', 'high', 'low', 'close', 'volume', 'sma20', 'sma40', 'rsi', 'obv','hma20']
df = pd.DataFrame(columns = col_names)
#creat df cause the import stuff would work
for x in range(dict_len):
temp = dictionary['result'][pair][x]
df = df.append({col_names[0]: temp[0], col_names[1]: temp[1], col_names[2]: temp[2], col_names[3]: temp[3], col_names[4]: temp[4], col_names[5]: temp[5]}, ignore_index=True)
#turn df into floats
for col in col_names:
df[col] = df[col].astype(float)
#add techinical indicatiors to the df
df['time'] = [datetime.fromtimestamp(x) for x in df['time']]
df['sma20'] = sma(df['close'].tolist(), 20)
df['sma40'] = sma(df['close'].tolist(), 50)
df['hma20'] = hma(df['close'].tolist(), 200)
df['rsi'] = rsi(df['close'].tolist(), 10)
df['obv'] = obv(df['close'].tolist(), df['volume'].tolist())
return df
def hull_moving_average(dataframe, period, field='close') -> ndarray:
from pyti.hull_moving_average import hull_moving_average as hma
return hma(dataframe[field], period)
def hull_moving_average(data, period):
return hma(data, period)
