def sync_dol_bar(pair, db_name, record_name, threhold, interval='1m'):
#get time of last row from db
# 'features.sqlite',"x_features"
pre_sql = psql.Preprocess_sql(db_name, record_name)
time = str(pre_sql.get_last_n(1).date_time[0])
# get klines from last time to current time
klines = get_data.get_klines_df(time, symbol=pair, interval=interval)
if get_data.is_limit(klines, threhold):
#convert klines to dol_bar
dol_bar = get_data.form_dol_bar(klines, threhold)
# get last 25 rows
# combine them to nwe dol bar
#calculate features
#get only df2
#store to db
last_twenty = pre_sql.get_last_n(25)
p = proprecess.Proprecessing()
p.combine_df(last_twenty, dol_bar)
p.add_features()
new_bars = p.get_df2()
pre_sql.store_df(new_bars)
print("finished")
else:
print("up to date")
def live_trading(self):
time = str(self.pre_sql.get_last_n(1).date_time[0])
# get klines from last time to current time
klines = get_data.get_klines_df(time,
symbol=self.pair,
interval=self.interval)
if get_data.is_limit(klines, self.threshold):
#convert klines to dol_bar
dol_bar = get_data.form_dol_bar(klines, self.threshold)
# get last 25 rows
# combine them to nwe dol bar
#calculate features
#get only df2
#store to db
last_twenty = self.pre_sql.get_last_n(25)
p = proprecess.Proprecessing()
p.combine_df(last_twenty, dol_bar)
p.add_features()
new_bars = p.get_df2()
self.pre_sql.store_df(new_bars)
df = new_bars.iloc[-1]
if new_bars['side']:
features = df[self.columns].tolist()
pred = int(self.predict.predict([features])[0])
num_allowed = self.configs.get_trading_num()
if num_allowed['long'] > 0 and pred == self.long_strategy[
"pred"] and side == self.long_strategy["side"]:
print("trade long")
self.configs.update_trading_num("long", -1)
elif num_allowed['short'] > 0 and pred == self.short_strategy[
"pred"] and side == self.short_strategy["side"]:
print("trade short")
self.configs.update_trading_num("short", -1)
def live_trading(self):
print("start live trading")
time = str(self.pre_sql.get_last_n(1).date_time[0])
# get klines from last time to current time
klines = get_data.get_klines_df(time,
symbol=self.pair,
interval=self.interval)
print("get klines")
if get_data.is_limit(klines, self.threshold):
log = {}
log["is_limit()"] = "klines dollar value > threshold"
print("klines dollar value > threshold")
#convert klines to dol_bar
dol_bar = get_data.form_dol_bar(klines, self.threshold)
# get last 25 rows
# combine them to nwe dol bar
#calculate features
#get only df2
#store to db
last_twenty = self.pre_sql.get_last_n(50)
p = proprecess.Proprecessing()
p.combine_df(last_twenty, dol_bar)
p.add_features()
new_bars = p.get_df2()
self.pre_sql.store_df(new_bars)
df = new_bars.iloc[-1]
print("last one")
print(df)
df = df.where(pd.notnull(df), None)
log['side'] = df['side']
if df['side']:
features = df[self.columns].tolist()
pred = int(self.predict.predict([features])[0])
num_allowed = self.configs.get_trading_num()
long_allowed = self.configs.query_config(self.pair, "long")
short_allowed = self.configs.query_config(self.pair, "short")
"""
long number available for the pair
short number available for the pair
"""
long_num = self.configs.get_trade_avl(self.pair, "long")
short_num = self.configs.get_trade_avl(self.pair, "short")
log['pred'] = pred
log['num_allowed'] = num_allowed
if long_allowed and num_allowed[
'long'] > 0 and long_num > 0 and pred == self.long_strategy[
"pred"] and df['side'] == self.long_strategy[
"side"]:
log['trade_long'] = "execuated"
self.log_func.insert_log(log)
return "long"
elif short_allowed and num_allowed[
'short'] > 0 and short_num > 0 and pred == self.short_strategy[
"pred"] and df['side'] == self.short_strategy[
"side"]:
log['trade_short'] = "execuated"
self.log_func.insert_log(log)
return "short"
else:
return "N"
self.log_func.insert_log(log)
else:
self.log_func.insert_log(log)
return "N"
import get_data as gd
import pandas as pd
import time
start_time = time.time()
df = pd.read_csv('x_features.csv',index_col=0)
df.index = pd.to_datetime(df.index)
d = str(df.iloc[-1:].index[0])
df = gd.get_klines_df(d,interval="12h")
# df = gd.convert_raw_data(d,interval="12h")
dol = gd.form_dol_bar(df,1851265300)
print(dol)
# print(gd.is_limit(k,3099318401.0))
print("--- %s seconds ---" % (time.time() - start_time))