#!/usr/bin/python2.7
import sys
print 'python', sys.version
import utility_3 as ut
from binance.client import Client
import time
# INDICATOR BOT #
ut.pickle_write(
'/home/ec2-user/environment/botfarming/Development/variables/indicator_trades_12h',
[])
indicator_bot = 1
file_number = 0
total_files = 1
length = '12h'
ut.pickle_write(
'/home/ec2-user/environment/botfarming/Development/variables/stop_trading_until_'
+ length,
int(time.time()) + 12 * 60 * 2 * 60)
api_key = '41EwcPBxLxrwAw4a4W2cMRpXiQwaJ9Vibxt31pOWmWq8Hm3ZX2CBnJ80sIRJtbsI'
api_secret = 'pnHoASmoe36q54DZOKsUujQqo4n5Ju25t5G0kBaioZZgGDOQPEHqgDDPA6s5dUiB'
client = Client(api_key, api_secret)
ut.run_bot_parallel(file_number, length, total_files, client, indicator_bot)
def run_optimizer_multi(lengths):
while True:
for length in lengths:
symbols = ut.pickle_read('/home/ec2-user/environment/botfarming/Development/3_binance_btc_symbols.pklz')
symbols_trimmed = {}
total_btc_coins = 0
for s in symbols:
symbol = symbols[s]
if float(symbol['24hourVolume']) > 300:
total_btc_coins += 1
symbols_trimmed[s] = symbol
print('total symbols', total_btc_coins)
if length == '1m':
data_length_multiplier = 360 # 6 hours # 3x as long, but 12 sections
minutes = 1
minutes_until_sale = 12
if length == '5m':
data_length_multiplier = 60*24*2/5 # 2 days
minutes = 5
minutes_until_sale = 12
if length == '15m':
data_length_multiplier = 60*24*7/15 # 1 wk
minutes = 15
minutes_until_sale = 12
if length == '30m':
data_length_multiplier = 60*24*14/30 # 2 wks
minutes = 30
minutes_until_sale = 12
if length == '1h':
data_length_multiplier = 60*24*14/60 # 2 wks
minutes = 60
minutes_until_sale = 12
if length == '2h':
data_length_multiplier = 60*24*30/120 # 1 month
minutes = 60 * 2
minutes_until_sale = 8
if length == '6h':
data_length_multiplier = 60*24*45/360 # 1.5 months
minutes = 60 * 6
minutes_until_sale = 4
if length == '12h':
data_length_multiplier = 60*24*90/720 # 3 months
minutes = 60 * 12
minutes_until_sale = 3
if length == '1d':
data_length_multiplier = 60*24*120/1440 # 4 months
minutes = 60 * 24
minutes_until_sale = 2
hours_per_period = round(float(data_length_multiplier*minutes/60.0), 3)
symbols_started = 0
for s in symbols_trimmed:
symbols_started += 1
print('########## symbols_started', symbols_started, 'for', length, ut.get_time())
#get data in right format for save function (could fix this)
symbol = symbols_trimmed[s]
symbols_trimmed_one = {}
for s_one in symbols:
symbol_one = symbols[s_one]
if symbol_one['symbol'] == symbol['symbol']:
symbols_trimmed_one[s] = symbol_one
# 777
optimizing_array = [1,3,5,7,9,11,13,15]
results_by_look_back = {}
for lb in optimizing_array:
results_by_look_back[str(lb)] = []
step_back_periods = 12
for step_back in range(0, step_back_periods):
end_time = int(time.time()) - data_length_multiplier * step_back * minutes * 60
results = get_optimization_factors(optimizing_array, data_length_multiplier, end_time, symbol, symbols_trimmed_one, length, minutes, minutes_until_sale)
for r in results:
results_by_look_back[str(r['look_back'])].append(r)
# results = [r, r, r...]
# r['lowest_buy_factor'] = lowest_buy_factor
# r['highest_sale_factor'] = highest_sale_factor
# r['look_back'] = optimizing
# r['optimal_buy_factor'] = lowest_buy_factor
# r['optimal_sell_factor'] = highest_sale_factor
for lb in results_by_look_back:
lowest_buy_factors = []
highest_sale_factors = []
results = results_by_look_back[lb]
for r in results:
lowest_buy_factors.append(r['optimal_buy_factor'])
highest_sale_factors.append(r['optimal_sell_factor'])
lowest_buy_factor_stats = fn.std_dev(lowest_buy_factors)
highest_sale_factor_stats = fn.std_dev(highest_sale_factors)
# print('#####################################################')
# print('LOWEST BUY FACTORS ######## LOOK_BACK', lb, s, step_back_periods, '*', hours_per_period, 'hrs')
# pprint(lowest_buy_factor_stats)
# print(lowest_buy_factors)
# print('HIGHEST SALE FACTORS ######## LOOK_BACK', lb, s, step_back_periods, '*', hours_per_period, 'hrs')
# pprint(highest_sale_factor_stats)
# print(highest_sale_factors)
# print('#####################################################')
result = {}
result['lowest_buy_factor_std_dev'] = lowest_buy_factor_stats['std_dev']
result['lowest_buy_factor_min'] = lowest_buy_factor_stats['min']
result['highest_sale_factor_std_dev'] = highest_sale_factor_stats['std_dev']
result['highest_sale_factor_min'] = highest_sale_factor_stats['min']
result['look_back'] = int(lb)
result['optimal_buy_factor'] = lowest_buy_factor_stats['mean']
result['optimal_sell_factor'] = highest_sale_factor_stats['mean']
optimization_factors_path = '/home/ec2-user/environment/botfarming/Development/optimization_factors/2_' + length + '_optimal_for_' + symbol['symbol'] + '_' + str(result['look_back']) + '.pklz'
ut.pickle_write(optimization_factors_path, result)
optimal_buy_factor, optimal_sell_factor, optimal_band_factor,
optimal_increase_factor)
optimization_factors = {}
optimization_factors['look_back'] = optimizing
optimization_factors['optimal_buy_factor'] = optimal_buy_factor
optimization_factors['optimal_sell_factor'] = optimal_sell_factor
optimization_factors[
'optimal_increase_factor'] = optimal_increase_factor
optimization_factors['optimal_band_factor'] = optimal_band_factor
optimization_factors[
'optimal_minutes_until_sale'] = optimal_minutes_until_sale
optimization_factors['gain'] = best_gain
optimization_factors['wins'] = best_wins
optimization_factors['losses'] = best_losses
ut.pickle_write(
'/home/ec2-user/environment/botfarming/Development/optimization_factors/'
+ length + '_optimal_for_' + symbol['symbol'] + '_' +
str(optimizing) + '.pklz', optimization_factors)
print(
'###################################################################'
)
print(
'###################################################################'
)
print(
'###################################################################'
)
print(
'###################################################################'
)
print(
'###################################################################'
def run_optimizer(length, minutes, minutes_until_sale):
if length == '1m':
data_length_multiplier = 360 # 6 hours # 3x as long, but 12 sections
if length == '5m':
data_length_multiplier = 60*24*2/5 # 2 days
if length == '15m':
data_length_multiplier = 60*24*7/15 # 1 wk
if length == '30m':
data_length_multiplier = 60*24*14/30 # 2 wks
if length == '1h':
data_length_multiplier = 60*24*14/60 # 2 wks
if length == '2h':
data_length_multiplier = 60*24*30/120 # 1 month
if length == '6h':
data_length_multiplier = 60*24*45/360 # 1.5 months
if length == '12h':
data_length_multiplier = 60*24*90/720 # 3 months
if length == '1d':
data_length_multiplier = 60*24*120/1440 # 4 months
while True:
print('starting..')
################################################################################ RUN OPTIMIZER
symbols = ut.pickle_read('/home/ec2-user/environment/botfarming/Development/3_binance_btc_symbols.pklz')
symbols_trimmed = {}
total_btc_coins = 0
for s in symbols:
symbol = symbols[s]
if float(symbol['24hourVolume']) > 300:
total_btc_coins += 1
symbols_trimmed[s] = symbol
print('total symbols', total_btc_coins)
symbols_started = 0
for s in symbols_trimmed:
symbols_started += 1
print('symbols_started', symbols_started)
#get data in right format for save function (could fix this)
symbol = symbols_trimmed[s]
symbols_trimmed_one = {}
for s_one in symbols:
symbol_one = symbols[s_one]
if symbol_one['symbol'] == symbol['symbol']:
symbols_trimmed_one[s] = symbol_one
# 777
optimizing_array= [1,3,5,7,9,11,13,15]
end_time = int(time.time())
results = get_optimization_factors(optimizing_array, data_length_multiplier, end_time, symbol, symbols_trimmed_one, length, minutes, minutes_until_sale)
for i, result in enumerate(results):
optimization_factors_path = '/home/ec2-user/environment/botfarming/Development/optimization_factors/1_' + length + '_optimal_for_' + symbol['symbol'] + '_' + str(result['look_back']) + '.pklz'
if result['lowest_buy_factor'] != 1:
ut.pickle_write(optimization_factors_path, result)
print('###################################################################')
print('###################################################################')
print('######### LOOK_BACK', result['look_back'], '###########', symbol['symbol'])
print('lowest_buy_factor', result['lowest_buy_factor'])
print('highest_sale_factor', result['highest_sale_factor'])
else:
ut.pickle_write(optimization_factors_path, False)
# end optimization cycle, sleep
if length == '1d':
time.sleep(4*60*60)
if length == '12h':
time.sleep(3*60*60)
if length == '6h':
time.sleep(2*60*60)
if length == '2h':
time.sleep(1*60*60)
if length == '1h':
time.sleep(30*60)
if length == '30m':
time.sleep(20*60)
max_trades_allowed = 5
max_std_increase = 1
elif length == '6h':
max_trades_allowed = 1
max_std_increase = 1
elif length == '12h':
max_trades_allowed = 1
max_std_increase = 1
elif length == '1d':
max_trades_allowed = 1
max_std_increase = 1
indicator_trades = ut.pickle_read(
'/home/ec2-user/environment/botfarming/Development/variables/indicator_trades_'
+ length)
std_dev_increase_factor = max(
0,
round((float(max_trades_allowed) - float(len(indicator_trades))) *
max_std_increase / float(max_trades_allowed), 1))
#std_dev_increase_factor = 0
ut.pickle_write(
'/home/ec2-user/environment/botfarming/Development/variables/std_dev_increase_factor_'
+ length, std_dev_increase_factor)
print('std_dev_increase_factor_' + length, std_dev_increase_factor,
ut.get_time())
time.sleep(30)
