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bfx.py
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bfx.py
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#!/usr/bin/env python3.6
# Logging module
import coloredlogs, logging
logger = logging.getLogger(__name__)
coloredlogs.install(level='DEBUG', logger=logger)
# Datetime
from datetime import datetime, timedelta as datetime_timedelta
import time
from dateutil.relativedelta import relativedelta
# For api requests
from requests import get as requests_get
# # Loading/unloading json (for api requests)
from json import dumps as json_dumps, loads as json_loads
class Timeperiods:
timeframes_list = ['1T','5T','15T','30T','1H','2H','3H','4H','6H','8H','12H','1D','W-MON','MS']
timeframes = {
'1T' : {
'seconds': 60,
},
'5T' : {
'upcycle': '1T',
'seconds':5*60,
'group_intervals': [0,5,10,15,20,25,30,35,40,45,50,55]
},
'15T' : {
'upcycle': '5T',
'seconds':15*60,
'group_intervals': [0,15,30,45]
},
'30T' : {
'upcycle': '15T',
'seconds':30*60,
'group_intervals': [0,30]
},
'1H' : {
'upcycle': '30T',
'seconds':60*60,
'group_intervals': [0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]
},
'2H' : {
'upcycle': '1H',
'seconds':2*(60*60),
'group_intervals': [0,2,4,6,8,10,12,14,16,18,20,22]
},
'3H' : {
'upcycle': '1H',
'seconds':3*(60*60),
'group_intervals': [0,3,6,9,12,18,21]
},
'4H' : {
'upcycle': '2H',
'seconds':4*(60*60),
'group_intervals': [0,4,8,12,16,20]
},
'6H' : {
'upcycle': '3H',
'seconds':6*(60*60),
'group_intervals': [0,6,12,18]
},
'8H' : {
'upcycle': '4H',
'seconds':8*(60*60),
'group_intervals': [0,8,16]
},
'12H' : {
'upcycle': '6H',
'seconds':12*(60*60),
'group_intervals': [0,12]
},
'1D' : {
'upcycle': '12H',
'seconds':24*(60*60)
},
'W-MON': {
'upcycle': '1D',
'seconds':7*(24*(60*60))
},
'MS' : {
'upcycle': '1D',
}
}
def __init__(self):
pass
def increment_timeperiods(self, orig_timestamp, num=1, resolution=None):
if resolution == None:
resolution = '1T'
if resolution == 'MS':
output = orig_timestamp + relativedelta(months=num)
return output
else:
output = orig_timestamp + relativedelta(seconds=(self.timeframes[resolution]['seconds']*num))
return output
def now(self):
return DateUtils.now_utc().replace(second=0, microsecond=0)
def get_timeperiods(self, now=None, resolution=None):
periods = {}
if now == None:
now = self.now()
year = now.year
month = now.month
day = now.day
hour = now.hour
minute = now.minute
periods['1T'] = now
# 5T, 15T, 30T
bins = ['5T','15T','30T']
for timeperiod in bins:
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)+" "+str(hour).zfill(2)+":00"
for i in Timeperiods.timeframes[ timeperiod ]['group_intervals']:
if i <= minute:
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)+" "+str(hour).zfill(2)+":"+str(i).zfill(2)
periods[timeperiod] = datetime.strptime(p, '%Y-%m-%d %H:%M')
# 1H
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)+" "+str(hour).zfill(2)+":00"
p = datetime.strptime(p, '%Y-%m-%d %H:%M')
periods['1H'] = p
# 2H, 3H, 4H, 6H, 8H, 12H
bins = ['2H','3H','4H','6H','8H','12H']
for timeperiod in bins:
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)+" 00:00"
for i in Timeperiods.timeframes[ timeperiod ]['group_intervals']:
if i <= hour:
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)+" "+str(i).zfill(2)+":00"
periods[timeperiod] = datetime.strptime(p, '%Y-%m-%d %H:%M')
# 1D
p = str(year)+"-"+str(month).zfill(2)+"-"+str(day).zfill(2)
p = datetime.strptime(p, '%Y-%m-%d').replace(hour=0, minute=0)
periods['1D'] = p
# W-MON
to_beggining_of_week = datetime_timedelta(days=now.weekday())
p = (now - to_beggining_of_week).replace(hour=0, minute=0)
periods['W-MON'] = p
# M
p = datetime.strptime(str(year)+"-"+str(month).zfill(2)+"-01", '%Y-%m-%d')
#next_month = p.replace(day=28) + datetime_timedelta(days=4)
#p = next_month - datetime_timedelta(days=next_month.day)
periods['MS'] = p
if resolution != None:
return periods[resolution]
else:
return periods
############################################################
class BFX( Timeperiods ):
api_limit_seconds = 5
resolution_to_api = {
'1T': '1m',
'5T': '5m',
'15T': '15m',
'30T': '30m',
'1H': '1h',
'2H': '1h',
'3H': '3h',
'4H': '1h',
'6H': '6h',
'12H': '12h',
'1D': '1D',
'2D': '1D',
'W-MON': '1D'
}
api_timeframe_resample_mapping = {
'2H' : '1H',
'4H' : '1H',
'2D' : '1D',
'W-MON': '1D'
}
def datetime_to_miliseconds(self, inputdate=None):
if inputdate == None:
inputdate = datetime.utcnow()
return (inputdate - datetime.utcfromtimestamp(0)).total_seconds() * 1000
def api_request_candles(self, resolution, ticker, start_date=None, end_date=None, limit=200):
resolution_api = resolution
resolution_increment = resolution
if resolution in self.api_timeframe_resample_mapping:
resolution_increment = self.api_timeframe_resample_mapping[ resolution ]
logger.info('Getting optimal subperiod, '+str(resolution_increment)+' end date.')
next_timeperiod = self.increment_timeperiods( end_date, 1 )
optimal_subperiod = self.increment_timeperiods( end_date, 1, resolution_increment )
while optimal_subperiod < next_timeperiod:
if optimal_subperiod < self.now():
end_date = optimal_subperiod
optimal_subperiod = self.increment_timeperiods( optimal_subperiod, 1, resolution_increment )
if start_date == None:
start_date = self.get_timeperiods(resolution=resolution)
start_date = self.increment_timeperiods( start_date, -limit )
limit = 200
if end_date == None:
end_date = self.get_timeperiods(resolution=resolution)
start_date_ms = self.datetime_to_miliseconds(start_date)
end_date_ms = self.datetime_to_miliseconds(end_date)
logger.info( 'Api request candles from '+str(start_date)+' to '+str(end_date) )
# Base URL to be getting the candlestick data from
base_url = 'https://api.bitfinex.com/v2/candles/trade:'+resolution_api+':t'+ticker+'/hist?limit='+str(limit)
if start_date != None:
api_query_url = base_url+'&start='+str(start_date_ms)+'&sort=1'
candles = self.api_request( api_query_url, skip_slow=True )
cut_off = len(candles)
for i,c in enumerate(candles):
if c[0] > end_date_ms:
cut_off = i
break
candles = candles[0:cut_off]
logger.info( 'First candle returned: '+str( datetime.utcfromtimestamp(candles[0][0]/1000.0) )+', '+str(candles[0]) )
logger.info( 'Last candle returned: '+str( datetime.utcfromtimestamp(candles[len(candles)-1][0]/1000.0) )+', '+str(candles[len(candles)-1]) )
last_date_ms = candles[len(candles)-1][0]
while last_date_ms < end_date_ms:
api_query_url = base_url+'&start='+str(last_date_ms)+'&sort=1'
api_candles = self.api_request( api_query_url )
cut_off = len(api_candles)-1
for i, c in enumerate(api_candles):
if c[0] > end_date_ms:
cut_off = i
break
candles = candles[0:len(candles)-1] + api_candles[0:cut_off+1]
logger.info('First candle returned: '+str( datetime.utcfromtimestamp(api_candles[0][0]/1000.0) )+', '+str(api_candles[0]) )
logger.info( 'Last candle used: '+str( datetime.utcfromtimestamp(api_candles[cut_off][0]/1000.0) )+', '+str(api_candles[cut_off]) )
last_date_ms = candles[len(candles)-1][0]
output = []
candle_len = len(candles)
for i,candle in enumerate(candles):
c = self.candles_map_api_to_list( candle )
output.append(c)
expected_nxt_ms = int( self.datetime_to_miliseconds( self.increment_timeperiods( c['timestamp'], 1, resolution_increment ) ) )
if i < candle_len-1:
if candles[i+1][0] != expected_nxt_ms:
logger.warning('Api returned missing candles, at '+str(candle[0])+', expected '+str(expected_nxt_ms)+', got '+str(candles[i+1][0]) )
logger.warning('at: '+str( datetime.utcfromtimestamp(candle[0]/1000.0) ))
logger.warning('expected_nxt_ms: '+str( datetime.utcfromtimestamp(expected_nxt_ms/1000.0) ))
logger.warning('got: '+str( datetime.utcfromtimestamp(candles[i+1][0]/1000.0) ))
done = False
while done == False:
fake_candle = [ expected_nxt_ms, candle[2], candle[2], candle[2], candle[2], 0 ]
logger.warning('Caution: Adding fake candle '+str( datetime.utcfromtimestamp(expected_nxt_ms/1000.0) )+' '+str(fake_candle))
c = self.candles_map_api_to_list( fake_candle )
output.append(c)
expected_nxt_ms = expected_nxt_ms + (self.timeframes[resolution_increment]['seconds']*1000)
if expected_nxt_ms == candles[i+1][0]:
done = True
elif expected_nxt_ms < candles[i+1][0]:
continue
elif expected_nxt_ms > candles[i+1][0]:
error('The expected next timestamp: '+str(expected_nxt_ms)+' is greater than the next timestamp: '+str(candles[i+1][0]))
exit()
if resolution in self.api_timeframe_resample_mapping:
df = self.list_to_df(output).resample(resolution, closed='left', label='left').agg(self.resample_aggregation)
output = []
for index, row in df.iterrows():
output.append({
'timestamp': index.to_pydatetime(),
'open': row['open'],
'high': row['high'],
'low': row['low'],
'close': row['close'],
'volume': row['volume']
})
return output
def api_request(self, url, skip_slow=False):
if (self.api_limit_seconds > 0) and (skip_slow == False):
logger.info('Slow api mode, sleeping for '+str(self.api_limit_seconds)+' seconds')
time.sleep(self.api_limit_seconds)
logger.info( 'Requesting: '+url )
response = requests_get(url).text
data = json_loads(response)
# Check we actually got the data back
# Not just an api error
completed = 0
while completed == 0:
if isinstance(data, list):
if str(data[0]) == 'error':
# Log the error
lmsg = 'BFX API Error: '+str(data)
error(lmsg)
# give it a bit of time
time.sleep(15)
# Re-request the data
response = requests_get(url).text
# Load the response
data = json_loads(response)
## Re-run
else:
# The response json does not contain error
# Therefore we have the response we wanted
# So api request actuall completed successfully
completed = 1
elif isinstance(data, dict):
if 'error' in data:
# Log the error
lmsg = 'BFX API Error: '+str(data)
error(lmsg)
# give it a bit of time
error('Sleeping for '+str(config.bfx_api_rate_limit_delay)+' seconds')
time.sleep(config.bfx_api_rate_limit_delay)
# Re-request the data
response = requests_get(url).text
# Load the response
data = json_loads(response)
else:
# WTF has the api returned then ?
lmsg = 'API error'
error(data)
error(lmsg)
exit()
return data
def candles_map_api_to_list(self, row, offset=True):
ts = row[0]
return {
'timestamp': datetime.utcfromtimestamp(ts/1000.0),
'open': row[1],
'high': row[3],
'low': row[4],
'close': row[2],
'volume': row[5]
}