def __init__(self, start_dt, end_dt):
"""
创建天勤回测类
Args:
start_dt (date/datetime): 回测起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
end_dt (date/datetime): 回测结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
"""
if isinstance(start_dt, datetime):
self.current_dt = int(start_dt.timestamp() * 1e9)
elif isinstance(start_dt, date):
self.current_dt = TqApi._get_trading_day_start_time(
int(
datetime(start_dt.year, start_dt.month,
start_dt.day).timestamp()) * 1000000000)
else:
raise Exception(
"回测起始时间(start_dt)类型 %s 错误, 请检查 start_dt 数据类型是否填写正确" %
(type(start_dt)))
if isinstance(end_dt, datetime):
self.end_dt = int(end_dt.timestamp() * 1e9)
elif isinstance(end_dt, date):
self.end_dt = TqApi._get_trading_day_end_time(
int(
datetime(end_dt.year, end_dt.month,
end_dt.day).timestamp()) * 1000000000)
else:
raise Exception("回测结束时间(end_dt)类型 %s 错误, 请检查 end_dt 数据类型是否填写正确" %
(type(end_dt)))
def __init__(self, start_dt, end_dt):
"""
创建天勤回测类
Args:
start_dt (date/datetime): 回测起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
end_dt (date/datetime): 回测结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
"""
if isinstance(start_dt, datetime):
self.current_dt = int(start_dt.timestamp()*1e9)
else:
self.current_dt = TqApi._get_trading_day_start_time(int(datetime(start_dt.year, start_dt.month, start_dt.day).timestamp())*1000000000)
if isinstance(end_dt, datetime):
self.end_dt = int(end_dt.timestamp()*1e9)
else:
self.end_dt = TqApi._get_trading_day_end_time(int(datetime(end_dt.year, end_dt.month, end_dt.day).timestamp())*1000000000)
async def _gen_serial(self, ins, dur):
"""k线/tick 序列的 async generator, yield 出来的行情数据带有时间戳, 因此 _send_diff 可以据此归并"""
# 先定位左端点, focus_datetime 是 lower_bound ,这里需要的是 upper_bound
# 因此将 view_width 和 focus_position 设置成一样，这样 focus_datetime 所对应的 k线刚好位于屏幕外
chart_info = {
"aid":
"set_chart",
"chart_id":
TqApi._generate_chart_id("backtest", ins, dur // 1000000000),
"ins_list":
ins,
"duration":
dur,
"view_width":
8964,
"focus_datetime":
int(self.current_dt),
"focus_position":
8964,
}
chart = TqApi._get_obj(self.data, ["charts", chart_info["chart_id"]])
current_id = None # 当前数据指针
serial = TqApi._get_obj(
self.data,
["klines", ins, str(dur)] if dur != 0 else ["ticks", ins])
async with TqChan(self.api, last_only=True) as update_chan:
serial["_listener"].add(update_chan)
chart["_listener"].add(update_chan)
await self.md_send_chan.send(chart_info.copy())
try:
async for _ in update_chan:
if not (chart_info.items() <= TqApi._get_obj(
chart, ["state"]).items()):
# 当前请求还没收齐回应, 不应继续处理
continue
left_id = chart.get("left_id", -1)
right_id = chart.get("right_id", -1)
last_id = serial.get("last_id", -1)
if (left_id == -1 and right_id == -1) or last_id == -1:
# 定位信息还没收到, 或数据序列还没收到
continue
if self.data.get("mdhis_more_data", True):
self.data["_listener"].add(update_chan)
continue
else:
self.data["_listener"].discard(update_chan)
if current_id is None:
current_id = max(left_id, 0)
while True:
if current_id > last_id:
# 当前 id 已超过 last_id
return
if current_id - chart_info.get("left_kline_id",
left_id) > 5000:
# 当前 id 已超出订阅范围, 需重新订阅后续数据
chart_info["left_kline_id"] = current_id
chart_info.pop("focus_datetime", None)
chart_info.pop("focus_position", None)
await self.md_send_chan.send(chart_info.copy())
if current_id > right_id:
break
item = serial["data"].get(str(current_id), {}).copy()
del item["_path"]
del item["_listener"]
if dur == 0:
diff = {
"ticks": {
ins: {
"last_id": current_id,
"data": {
str(current_id): item,
str(current_id - 8964): None,
}
}
}
}
if item["datetime"] > self.end_dt: # 超过结束时间
return
yield item[
"datetime"], diff, self._get_quotes_from_tick(
item)
else:
diff = {
"klines": {
ins: {
str(dur): {
"last_id": current_id,
"data": {
str(current_id): {
"datetime":
item["datetime"],
"open": item["open"],
"high": item["open"],
"low": item["open"],
"close": item["open"],
"volume": 0,
"open_oi": item["open_oi"],
"close_oi":
item["open_oi"],
},
str(current_id - 8964): None,
}
}
}
}
}
timestamp = item[
"datetime"] if dur < 86400000000000 else TqApi._get_trading_day_start_time(
item["datetime"])
if timestamp > self.end_dt: # 超过结束时间
return
yield timestamp, diff, None
diff = {
"klines": {
ins: {
str(dur): {
"data": {
str(current_id): item,
}
}
}
}
}
timestamp = item[
"datetime"] + dur - 1000 if dur < 86400000000000 else TqApi._get_trading_day_end_time(
item["datetime"])
if timestamp > self.end_dt: # 超过结束时间
return
yield timestamp, diff, self._get_quotes_from_kline(
self.data["quotes"][ins], timestamp, item)
current_id += 1
finally:
# 释放chart资源
chart_info["ins_list"] = ""
await self.md_send_chan.send(chart_info.copy())
def __init__(self, api, symbol_list, dur_sec, start_dt, end_dt,
csv_file_name):
"""
创建历史数据下载器实例
Args:
api (TqApi): TqApi实例，该下载器将使用指定的api下载数据
symbol_list (str/list of str): 需要下载数据的合约代码，当指定多个合约代码时将其他合约按第一个合约的交易时间对齐
dur_sec (int): 数据周期，以秒为单位。例如: 1分钟线为60,1小时线为3600,日线为86400,Tick数据为0
start_dt (date/datetime): 起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
end_dt (date/datetime): 结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点
csv_file_name (str): 输出csv的文件名
Example::
from datetime import datetime, date
from contextlib import closing
from tqsdk import TqApi, TqSim
from tqsdk.tools import DataDownloader
api = TqApi(TqSim())
download_tasks = {}
# 下载从 2018-01-01 到 2018-09-01 的 SR901 日线数据
download_tasks["SR_daily"] = DataDownloader(api, symbol_list="CZCE.SR901", dur_sec=24*60*60,
start_dt=date(2018, 1, 1), end_dt=date(2018, 9, 1), csv_file_name="SR901_daily.csv")
# 下载从 2017-01-01 到 2018-09-01 的 rb主连 5分钟线数据
download_tasks["rb_5min"] = DataDownloader(api, symbol_list="*****@*****.**", dur_sec=5*60,
start_dt=date(2017, 1, 1), end_dt=date(2018, 9, 1), csv_file_name="rb_5min.csv")
# 下载从 2018-01-01凌晨6点 到 2018-06-01下午4点 的 cu1805,cu1807,IC1803 分钟线数据，所有数据按 cu1805 的时间对齐
# 例如 cu1805 夜盘交易时段, IC1803 的各项数据为 N/A
# 例如 cu1805 13:00-13:30 不交易, 因此 IC1803 在 13:00-13:30 之间的K线数据会被跳过
download_tasks["cu_min"] = DataDownloader(api, symbol_list=["SHFE.cu1805", "SHFE.cu1807", "CFFEX.IC1803"], dur_sec=60,
start_dt=datetime(2018, 1, 1, 6, 0 ,0), end_dt=datetime(2018, 6, 1, 16, 0, 0), csv_file_name="cu_min.csv")
# 下载从 2018-05-01凌晨0点 到 2018-06-01凌晨0点 的 T1809 盘口Tick数据
download_tasks["T_tick"] = DataDownloader(api, symbol_list=["CFFEX.T1809"], dur_sec=0,
start_dt=datetime(2018, 5, 1), end_dt=datetime(2018, 6, 1), csv_file_name="T1809_tick.csv")
# 使用with closing机制确保下载完成后释放对应的资源
with closing(api):
while not all([v.is_finished() for v in download_tasks.values()]):
api.wait_update()
print("progress: ", { k:("%.2f%%" % v.get_progress()) for k,v in download_tasks.items() })
"""
self.api = api
if isinstance(start_dt, datetime):
self.start_dt_nano = int(start_dt.timestamp() * 1e9)
else:
self.start_dt_nano = TqApi._get_trading_day_start_time(
int(
datetime(start_dt.year, start_dt.month,
start_dt.day).timestamp()) * 1000000000)
if isinstance(end_dt, datetime):
self.end_dt_nano = int(end_dt.timestamp() * 1e9)
else:
self.end_dt_nano = TqApi._get_trading_day_end_time(
int(
datetime(end_dt.year, end_dt.month,
end_dt.day).timestamp()) * 1000000000)
self.current_dt_nano = self.start_dt_nano
self.symbol_list = symbol_list if isinstance(symbol_list,
list) else [symbol_list]
self.dur_nano = dur_sec * 1000000000
if self.dur_nano == 0 and len(self.symbol_list) != 1:
raise Exception("Tick序列不支持多合约")
self.csv_file_name = csv_file_name
self.task = self.api.create_task(self._download_data())
