@author: 躺着也挣钱
QQ群 ： 422922984
"""
import pandas as pd
from fcoin3 import Fcoin
from datetime import datetime
#if python3 use
#from fcoin import Fcoin
fcoin = Fcoin()
fcoin.auth('key ', 'secret')
#取K线数据
ft_usdt = fcoin.get_candle('M3', 'ftusdt') #M3 = 分钟线， 取150条数据
# 取得当前账户信息
print(fcoin.get_balance())
#
print(fcoin.get_symbols())
print(fcoin.get_currencies())
#
#print(fcoin.buy('fteth', 0.0001, 10))
#
class App():
def __init__(self):
self.fcoin = Fcoin()
self.fcoin.auth(config.api_key, config.api_secret)
self.log = Log("")
self.symbol = 'ftusdt'
self.order_id = None
self.dic_balance = defaultdict(lambda: None)
self.now_price = 0.0
self.type = 0
self.fee = 0.0
self.count_flag = 0
self.fall_rise = 0
self.buy_price = 0.0
# 正在卖出
self.in_sell = False
# 卖出价格
self.sell_price = 0.0
# 价格队列
self.price_queue = []
# 验证是否卖出价格
self.check_sell_price = 0.0
# 总共的增量
self.total_increment = 0.0
# 服务器时间
self.diff_server_time = None
stategy_quick.set_app(self)
candle_data.set_app(self)
def digits(self, num, digit):
site = pow(10, digit)
tmp = num * site
tmp = math.floor(tmp) / site
return tmp
def get_ticker(self):
if self.sell_price is None:
self.get_market_ticker()
return self.now_price
def get_must_sell_ticker(self):
if self.sell_price is None:
self.get_market_ticker()
return self.buy_price
def get_must_buy_ticker(self):
if self.sell_price is None:
self.get_market_ticker()
return self.sell_price
def get_market_ticker(self):
ticker = self.fcoin.get_market_ticker(self.symbol)['data']['ticker']
self.now_price = ticker[0]
self.buy_price = ticker[2]
self.sell_price = ticker[4]
# 获取当前用户持币信息
def get_blance(self):
if self.dic_blance is None:
self.syn_blance()
return self.dic_blance
# 同步持币信息
def syn_blance(self):
dic_blance = defaultdict(lambda: None)
data = self.fcoin.get_balance()
if data:
for item in data['data']:
dic_blance[item['currency']] = balance(
float(item['available']), float(item['frozen']),
float(item['balance']))
self.dic_blance = dic_blance
return dic_blance
def save_csv(self, array):
with open("data/trade.csv", "a+", newline='') as w:
writer = csv.writer(w)
writer.writerow(array)
def reset_save_attrubute(self):
self.now_price = 0.0
self.type = 0
self.fee = 0.0
self.order_id = None
# 获取当前服务器时间
def get_server_time(self):
if self.diff_server_time is None:
self.synchronize_time()
return datetime.datetime.fromtimestamp(
int((int(datetime.datetime.now().timestamp() * 1000) +
self.diff_server_time) / 1000))
# 同步时间
def synchronize_time(self):
# self.server_time = datetime.datetime.fromtimestamp(int(self.fcoin.get_server_time() / 1000))
self.diff_server_time = int(self.fcoin.get_server_time()) - int(
datetime.datetime.now().timestamp() * 1000)
# print(self.diff_server_time)
def dateDiffInSeconds(self, date1, date2):
timedelta = date2 - date1
return timedelta.days * 24 * 3600 + timedelta.seconds
def do_hour(self):
self.dic_balance = self.get_blance()
ft = self.dic_balance["ft"]
usdt = self.dic_balance["usdt"]
print('ft:%s usdt:%s' % (ft.available, usdt.available))
if usdt.available > 50:
# 买入ft
price = self.digits(self.get_must_buy_ticker(), 6)
amount = self.digits(usdt.available / price * 0.98, 2)
if amount >= 5:
self.log.info('buy price--[%s] amout--[%s]' % (price, amount))
data = self.fcoin.buy(self.symbol, price, amount, 'limit')
if data:
self.order_id = data['data']
self.log.info('buy order success price--[%s] amout--[%s]' %
(price, amount))
server_time = self.get_server_time()
start_time = server_time.replace(minute=58,
second=50,
microsecond=0)
sleep_seconds = self.dateDiffInSeconds(
server_time, start_time)
if sleep_seconds > 1:
time.sleep(sleep_seconds)
self.dic_balance = self.get_blance()
ft = self.dic_balance["ft"]
usdt = self.dic_balance["usdt"]
new_price = price
while new_price <= price:
new_price = self.digits(self.get_must_sell_ticker(), 6)
time.sleep(5)
if new_price > price:
self.log.info('sell price--[%s] amout--[%s]' %
(price, amount))
data = self.fcoin.sell(self.symbol, new_price, amount,
'limit')
self.log.info(
'sell order success price--[%s] amout--[%s]' %
(new_price, amount))
else:
self.sell_ft()
# 查找到合理的卖点
def get_sell_point(self):
pass
def get_sell_count(self):
return config.sell_count
# 卖出ft
def sell_ft(self):
# 卖出ft
# 1）未持续上涨，直接卖出
# 2）持续上涨，查找高点
if self.get_server_time().minute < 5 and not self.in_sell:
self.in_sell = True
# 1、查看时间区间是在预期范围 01
if self.get_ticker() > self.check_sell_price:
# 2、查找合理点位卖出，
data = self.fcoin.sell(self.symbol, self.get_sell_point(),
self.get_sell_count(), 'limit')
# 让订单卖出
while (True):
# 获取订单状态
is_done = True
#
if is_done:
self.sell_done = True
break
else:
# 超过时间判断
# 超过时间重新下单
pass
self.in_sell = False
def get_buy_point(self):
pass
def get_sell_count(self):
pass
# 买入ft,直到买入成功为止
def buy_ft(self):
# 根据时间获取买入策略
# 已经超过
# 如果已经超过买入点，默认检测5分钟不够买，下降趋势情况下，超过根据涨跌获取买入点
pass
def get_price_queue(self):
data = run.fcoin.get_candle("M1", run.symbol)
self.price_queue = []
for item in data['data']:
self.price_queue.append(item['close'])
trades_1 = '#'
trades_2 = '#'
trades_3 = '#'
trades_5 = '#'
trades_10 = '#'
trades_20 = '#'
trades_30 = '#'
trades_60 = '#'
# 1分钟
new_price = self.price_queue[0]
old_price = self.price_queue[1]
trades_1 = self.digits((new_price - old_price) / old_price * 100, 6)
# 2分钟
new_price = self.price_queue[0]
old_price = self.price_queue[2]
trades_2 = self.digits((new_price - old_price) / old_price * 100, 6)
# 3分钟
new_price = self.price_queue[0]
old_price = self.price_queue[3]
trades_3 = self.digits((new_price - old_price) / old_price * 100, 6)
# 5分钟
new_price = self.price_queue[0]
old_price = self.price_queue[5]
trades_5 = self.digits((new_price - old_price) / old_price * 100, 6)
# 10分钟
new_price = self.price_queue[0]
old_price = self.price_queue[10]
trades_10 = self.digits((new_price - old_price) / old_price * 100, 6)
# 20分钟
new_price = self.price_queue[0]
old_price = self.price_queue[20]
trades_20 = self.digits((new_price - old_price) / old_price * 100, 6)
# 30分钟
new_price = self.price_queue[0]
old_price = self.price_queue[30]
trades_30 = self.digits((new_price - old_price) / old_price * 100, 6)
# 60分钟
new_price = self.price_queue[0]
old_price = self.price_queue[60]
trades_60 = self.digits((new_price - old_price) / old_price * 100, 6)
print(
'数据行情(百分比) 1m--[%s] 2m--[%s] 3m--[%s] 5m--[%s] 10m--[%s] 20m--[%s] 30m--[%s] 60m--[%s]'
% (str(trades_1), str(trades_2), str(trades_3), str(trades_5),
str(trades_10), str(trades_20), str(trades_30), str(trades_60)))
def average(self, array):
total = 0.0
n = len(array)
for num in array:
total += num
return 1.0 * total / n
# 增长量计算
def increment(self):
data = self.fcoin.get_candle("H1", run.symbol)
for item in data['data']:
timeArray = time.localtime(item['id'])
otherStyleTime = time.strftime("%Y-%m-%d %H:%M:%S", timeArray)
# print("%s ----- %s" % (otherStyleTime, item))
total_increment = 0
for index in range(self.get_server_time().hour):
new_price = data['data'][index + 1]['close']
# print(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(data['data'][index+ 1]['id'])))
old_price = data['data'][index + 1 + 24]['close']
total_increment += (new_price - old_price) / old_price
self.total_increment = total_increment
print(total_increment)
pre_date_data = []
max_data = []
min_data = []
cur_hour = self.get_server_time().hour
for index in range(24 + cur_hour):
cur_data = data['data'][index]
pre_date_data.append(cur_data['close'])
pre_date_data.append(cur_data['high'])
pre_date_data.append(cur_data['low'])
max_data.append(cur_data['high'])
min_data.append(cur_data['low'])
# print(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(data['data'][index + cur_hour]['id'])))
# 变化系数计算
cur_change_data = []
pre_change_data = []
for index in range(12):
cur_data = data['data'][index]
pre_data = data['data'][index + 24]
cur_change_data.append(cur_data['close'])
pre_change_data.append(pre_data['close'])
change_price = np.average(np.array(cur_change_data)) / np.average(
np.array(pre_change_data))
print(change_price)
np_data = np.array(pre_date_data)
np_data_max = np.array(max_data)
np_data_min = np.array(min_data)
np_data_max.sort()
max_avg_price = np.average(np_data_max[len(np_data_max) - 3:])
np_data_min.sort()
min_avg_price = np.average(np_data_min[0:3])
# 极差
# print(ptp(data))
# print(var(data))
# print(std(data))
# print(mean(data) / std(data))
# print(data.min())
# print(median(data))
# print(mean(data))
# print(data)
median_data = np.average(np_data)
print(np_data)
print(median_data)
print(max_avg_price)
print(min_avg_price)
self.check_min_sell_price = (
median_data - (median_data - min_avg_price) * 0.3) * change_price
self.check_could_sell_price = (
median_data + (max_avg_price - median_data) * 0.7) * change_price
self.check_max_buy_price = (
median_data + (max_avg_price - median_data) * 0.3) * change_price
self.check_could_buy_price = (
median_data - (median_data - min_avg_price) * 0.7) * change_price
print(self.check_min_sell_price)
print(self.check_could_sell_price)
print(self.check_max_buy_price)
print(self.check_could_buy_price)
# 获取区间
def get_interval(self):
print(candle_data.get_candle_M1())
# 计算区间
def calculation_interval(self):
candle_M1 = candle_data.get_candle_M1()
candle_M1_data = candle_M1['data']
for index in range(60):
candle_M1_data[60 - 1 - index]
# 改为定时任务
def loop(self):
stategy_quick.schedule()
candle_data.schedule()
# 开启卖出线程
# schedule.every(2).seconds.do(self.get_interval)
schedule.every(1).seconds.do(self.get_market_ticker)
# schedule.every(10).seconds.do(self.sell_ft)
# schedule.every(30).seconds.do(self.get_price_queue)
# schedule.every(10).seconds.do(self.print_price_queue)
while True:
schedule.run_pending()
time.sleep(1)