def __init__(self, instrument_id, time_frame, fast_length, slow_length, long_stop, short_stop, start_asset):
try:
print("{} {} 双均线多空策略已启动！".format(get_localtime(), instrument_id)) # 程序启动时打印提示信息
config.loads('config.json') # 载入配置文件
self.instrument_id = instrument_id # 合约ID
self.time_frame = time_frame # k线周期
self.exchange = OKEXFUTURES(config.access_key, config.secret_key, config.passphrase, self.instrument_id) # 初始化交易所
self.position = POSITION(self.exchange, self.instrument_id, self.time_frame) # 初始化potion
self.market = MARKET(self.exchange, self.instrument_id, self.time_frame) # 初始化market
self.indicators = INDICATORS(self.exchange, self.instrument_id, self.time_frame) # 初始化indicators
# 在第一次运行程序时，将初始资金数据保存至数据库中
self.database = "回测" # 回测时必须为"回测"
self.datasheet = self.instrument_id.split("-")[0].lower() + "_" + time_frame
if config.first_run == "true":
storage.mysql_save_strategy_run_info(self.database, self.datasheet, get_localtime(),
"none", 0, 0, 0, 0, "none", 0, 0, 0, start_asset)
# 读取数据库中保存的总资金数据
self.total_asset = storage.read_mysql_datas(0, self.database, self.datasheet, "总资金", ">")[-1][-1]
self.total_profit = storage.read_mysql_datas(0, self.database, self.datasheet, "总资金", ">")[-1][-2] # 策略总盈亏
self.counter = 0 # 计数器
self.fast_length = fast_length # 短周期均线长度
self.slow_length = slow_length # 长周期均线长度
self.long_stop = long_stop # 多单止损幅度
self.short_stop = short_stop # 空单止损幅度
self.contract_value = self.market.contract_value() # 合约面值，每次获取需发起网络请求，故于此处声明变量，优化性能
except:
logger.warning()
def __init__(self, instrument_id, time_frame, start_asset): # 策略初始化时需传入合约id、k线周期、初始资金参数
print("{} {} 海龟交易策略已启动！".format(get_localtime(), instrument_id)) # 程序启动时打印提示信息
config.loads("config.json") # 载入配置文件
self.instrument_id = instrument_id # 合约id
self.time_frame = time_frame # k线周期
self.exchange = OKEXFUTURES(config.access_key, config.secret_key, config.passphrase, self.instrument_id, leverage=20) # 初始化交易所
self.market = MARKET(self.exchange, self.instrument_id, self.time_frame) # 初始化market
self.position = POSITION(self.exchange, self.instrument_id, self.time_frame) # 初始化position
self.indicators = INDICATORS(self.exchange, self.instrument_id, self.time_frame) # 初始化indicators
self.database = "回测" # 如从purequant服务器的数据库上获取历史k线数据进行回测，必须为"回测"
self.datasheet = self.instrument_id.split("-")[0].lower() + "_" + time_frame # 数据表
if config.first_run == "true": # 程序第一次启动时保存数据，实盘时如策略中止再重启时，可以将配置文件中的first_run改成"false"，程序再次启动会直接读取数据库中保存的数据
storage.mysql_save_strategy_run_info(self.database, self.datasheet, get_localtime(),
"none", 0, 0, 0, 0, "none", 0, 0, 0, start_asset)
# 读取数据库中保存的总资金、总盈亏数据
self.total_asset = storage.read_mysql_datas(0, self.database, self.datasheet, "总资金", ">")[-1][-1]
self.total_profit = storage.read_mysql_datas(0, self.database, self.datasheet, "总资金", ">")[-1][-2] # 策略总盈亏
# 一些策略参数
self.contract_value = self.market.contract_value() # 合约面值
self.ATRLength = 20 # 平均波动周期
self.boLength = 20 # 短周期 BreakOut Length
self.fsLength = 55 # 长周期 FailSafe Length
self.teLength = 10 # 离市周期 Trailing Exit Length
self.LastProfitableTradeFilter = 1 # 使用入市过滤条件
self.PreBreakoutFailure = False # 前一次是否突破失败
self.CurrentEntries = 0 # 当前持仓的开仓次数
self.counter = 0 # 计数器，用以控制单根bar最大交易次数
def __init__(self, instrument_id, time_frame, fast_length, slow_length, long_stop, short_stop, start_asset):
config.loads('config.json') # 载入配置文件
self.instrument_id = instrument_id # 合约ID
self.time_frame = time_frame # k线周期
self.exchange = OKEXFUTURES(config.access_key, config.secret_key, config.passphrase, self.instrument_id) # 初始化交易所
self.position = POSITION(self.exchange, self.instrument_id, self.time_frame) # 初始化potion
self.market = MARKET(self.exchange, self.instrument_id, self.time_frame) # 初始化market
self.indicators = INDICATORS(self.exchange, self.instrument_id, self.time_frame) # 初始化indicators
# 在第一次运行程序时，将初始资金数据保存至数据库中
self.database = "回测" # 无论实盘或回测，此处database名称可以任意命名
self.datasheet = self.instrument_id.split("-")[0].lower() + "_" + time_frame
if config.first_run:
storage.mysql_save_strategy_run_info(self.database, self.datasheet, "策略参数为" + str(fast_length) + "&" + str(slow_length),
"none", 0, 0, 0, 0, "none", 0, 0, 0, start_asset)
# 读取数据库中保存的总资金数据
self.total_asset = storage.read_mysql_datas(0, self.database, self.datasheet, "总资金", ">")[-1][-1]
self.counter = 0 # 计数器
self.fast_length = fast_length # 短周期均线长度
self.slow_length = slow_length # 长周期均线长度
self.long_stop = long_stop # 多单止损幅度
self.short_stop = short_stop # 空单止损幅度
self.total_profit = 0
self.contract_value = self.market.contract_value() # 合约面值，每次获取需发起网络请求，故于此处声明变量，优化性能
# 声明持仓方向、数量与价格变量，每次开平仓后手动重新赋值
self.hold_direction = "none"
self.hold_amount = 0
self.hold_price = 0
print("{} {} 双均线多空策略已启动！".format(get_localtime(), instrument_id)) # 程序启动时打印提示信息
def __init__(self, platform, symbol, time_frame):
self.__platform = platform
self.__symbol = symbol
self.__time_frame = time_frame
self.__market = MARKET(self.__platform, self.__symbol,
self.__time_frame)
# pull some data
self.__indicators = INDICATORS(self.__platform, self.__symbol,
self.__time_frame)
self.__kline = platform.get_kline(self.__time_frame)
self.__kline.reverse()
# format it in pandas
try: # dataframe有7列的情况
self.__df = pd.DataFrame(self.__kline,
columns=[
'time', 'open', 'high', 'low',
'close', 'volume', 'currency_volume'
])
self.__df = self.__df.astype({
'time': 'datetime64[ns]',
'open': 'float64',
'close': 'float64',
'high': 'float64',
'low': 'float64',
'volume': 'float64',
'currency_volume': 'float64'
})
except: # dataframe只有6列的情况，如okex的现货k线数据
self.__df = pd.DataFrame(
self.__kline,
columns=['time', 'open', 'high', 'low', 'close', 'volume'])
self.__df = self.__df.astype({
'time': 'datetime64[ns]',
'open': 'float64',
'close': 'float64',
'high': 'float64',
'low': 'float64',
'volume': 'float64'
})
# create three plot 创建三层图纸，第一层画k线，第二层画成交量，第三层画一些适宜于副图显示的指标
fplt.foreground = '#FFFFFF' # 前景色
fplt.background = '#333333' # 背景色
fplt.odd_plot_background = '#333333' # 第二层图纸的背景色
fplt.cross_hair_color = "#FFFFFF" # 准星的颜色
self.__ax, self.__ax2, self.__ax3 = fplt.create_plot(symbol, rows=3)
# plot candle sticks
candles = self.__df[['time', 'open', 'close', 'high', 'low']]
fplt.candlestick_ochl(candles, ax=self.__ax)
# overlay volume on the plot
volumes = self.__df[['time', 'open', 'close', 'volume']]
fplt.volume_ocv(volumes, ax=self.__ax2)
fplt.add_legend("VOLUME", self.__ax2) # 增加"VOLUME"图例
def __init__(self, databank, database, data_sheet, exchange, instrument_id, time_frame):
print("{} {} 持仓同步功能已启动！".format(get_localtime(), instrument_id))
self.__databank = databank
self.__database = database
self.__datasheet = data_sheet
self.__exchange = exchange
self.__instrument_id = instrument_id
self.__time_frame = time_frame
self.__position = POSITION(self.__exchange, self.__instrument_id, self.__time_frame)
self.__market = MARKET(self.__exchange, self.__instrument_id, self.__time_frame)
self.__overprice_range = config.overprice_range
def __init__(self, instrument_id, time_frame, bollinger_lengths,
filter_length, start_asset):
try:
# 策略启动时控制台输出提示信息
print("{} {} 布林强盗突破策略已启动！".format(get_localtime(),
instrument_id)) # 程序启动时打印提示信息
config.loads("config.json") # 载入配置文件
# 初始化
self.instrument_id = instrument_id # 合约ID
self.time_frame = time_frame # k线周期
self.exchange = OKEXFUTURES(config.access_key, config.secret_key,
config.passphrase,
self.instrument_id) # 交易所
self.market = MARKET(self.exchange, self.instrument_id,
self.time_frame) # 行情
self.position = POSITION(self.exchange, self.instrument_id,
self.time_frame) # 持仓
self.indicators = INDICATORS(self.exchange, self.instrument_id,
self.time_frame) # 指标
# 在第一次运行程序时，将初始资金、总盈亏等数据保存至数据库中
self.database = "回测" # 数据库，回测时必须为"回测"
self.datasheet = self.instrument_id.split(
"-")[0].lower() + "_" + time_frame # 数据表
if config.first_run == "true":
storage.mysql_save_strategy_run_info(self.database,
self.datasheet,
get_localtime(), "none",
0, 0, 0, 0, "none", 0, 0,
0, start_asset)
# 读取数据库中保存的总资金数据
self.total_asset = storage.read_mysql_datas(
0, self.database, self.datasheet, "总资金", ">")[-1][-1]
self.total_profit = storage.read_mysql_datas(
0, self.database, self.datasheet, "总资金", ">")[-1][-2] # 策略总盈亏
# 策略参数
self.contract_value = self.market.contract_value() # 合约面值
self.counter = 0 # 计数器
self.bollinger_lengths = bollinger_lengths # 布林通道参数
self.filter_length = filter_length # 过滤器参数
self.out_day = 50 # 自适应出场ma的初始值为50,开仓后赋值为布林通道参数的值
except:
logger.warning()
def __init__(self, instrument_id, time_frame, fast_length, slow_length,
long_stop, short_stop, start_asset, precision):
try:
print("{} {} 双均线多空策略已启动！".format(get_localtime(),
instrument_id)) # 程序启动时打印提示信息
config.loads('config.json') # 载入配置文件
self.instrument_id = instrument_id # 合约ID
self.time_frame = time_frame # k线周期
self.precision = precision # 精度，即币对的最小交易数量
self.exchange = OKEXSPOT(config.access_key, config.secret_key,
config.passphrase,
self.instrument_id) # 初始化交易所
self.position = POSITION(self.exchange, self.instrument_id,
self.time_frame) # 初始化potion
self.market = MARKET(self.exchange, self.instrument_id,
self.time_frame) # 初始化market
self.indicators = INDICATORS(self.exchange, self.instrument_id,
self.time_frame) # 初始化indicators
# 在第一次运行程序时，将初始资金数据保存至数据库中
self.database = "回测" # 回测时必须为"回测"
self.datasheet = self.instrument_id.split(
"-")[0].lower() + "_" + time_frame
if config.first_run == "true":
storage.mysql_save_strategy_run_info(self.database,
self.datasheet,
get_localtime(), "none",
0, 0, 0, 0, "none", 0, 0,
0, start_asset)
# 读取数据库中保存的总资金数据
self.total_asset = storage.read_mysql_datas(
0, self.database, self.datasheet, "总资金", ">")[-1][-1]
self.total_profit = storage.read_mysql_datas(
0, self.database, self.datasheet, "总资金", ">")[-1][-2] # 策略总盈亏
self.counter = 0 # 计数器
self.fast_length = fast_length # 短周期均线长度
self.slow_length = slow_length # 长周期均线长度
self.long_stop = long_stop # 多单止损幅度
self.short_stop = short_stop # 空单止损幅度
self.hold_price = 0 # 注意：okex的现货没有获取持仓均价的接口，故需实盘时需要手动记录入场价格。此种写法对于不同的交易所是通用的。
# 此种写法，若策略重启，持仓价格会回归0
except:
logger.warning()
from purequant.trade import HUOBISPOT from purequant.market import MARKET from purequant.indicators import INDICATORS from purequant.position import POSITION # 账户和策略参数等信息 accessy_key = 'your access_key' secret_key = 'your secret_key' instrument_id = 'ETC-USDT' time_frame = '1d' # 初始化交易所、行情模块与指标等模块 exchange = HUOBISPOT(accessy_key, secret_key, instrument_id) market = MARKET(exchange, instrument_id, time_frame) indicators = INDICATORS(exchange, instrument_id, time_frame) position = POSITION(exchange, instrument_id, time_frame) # 下单交易，买入和卖出 # info = exchange.buy(7.35, 0.02) # 以7.35的价格买入0.02个ETC # info = exchange.sell(7.35, 0.01) # 卖出0.02个ETC # 获取行情信息 # info = exchange.get_kline(time_frame) # 获取k线数据 # info = market.last() # 获取ETC-USDT的最新成交价 # info = market.open(-1) # 获取ETC-USDT的当日开盘价 # info = market.high(-1) # 获取ETC-USDT的当日最高价 # info = market.low(-1) # 获取ETC-USDT的当日最低价 # info = market.close(-1) # 获取ETC-USDT的当日收盘价 # 持仓信息 # info = position.amount() # 获取ETC-USDT交易对的ETC可用余额
def __init__(self, platform, instrument_id, time_frame):
self.__platform = platform
self.__instrument_id = instrument_id
self.__time_frame = time_frame
self.__market = MARKET(self.__platform, self.__instrument_id, self.__time_frame)