[update] gateway & data
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msincenselee
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examples/stock/demo_01.py
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76
examples/stock/demo_01.py
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@ -0,0 +1,76 @@
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# flake8: noqa
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# 示例代码
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# 从本地股票数据加载，前复权，显示主图指标、副图指标、缠论
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import os
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import sys
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import json
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vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
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if vnpy_root not in sys.path:
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print(f'sys.path append({vnpy_root})')
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sys.path.append(vnpy_root)
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os.environ["VNPY_TESTING"] = "1"
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from vnpy.data.tdx.tdx_common import FakeStrategy
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from vnpy.data.tdx.tdx_stock_data import *
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from vnpy.component.cta_line_bar import CtaMinuteBar
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from vnpy.trader.ui.kline.ui_snapshot import UiSnapshot
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from vnpy.trader.ui import create_qapp
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from vnpy.data.common import get_stock_bars
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if __name__ == "__main__":
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# 创建一个假的策略
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t1 = FakeStrategy()
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# 股票代码.交易所
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vt_symbol = '000001.SZSE'
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# 数据周期
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bar_freq = '15m'
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# 一根bar代表的分钟数
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bar_interval = int(bar_freq.replace('m', ''))
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# 获取某个合约得的分时数据,周期是15分钟，返回数据类型是barData
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print('加载数据')
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bars, msg = get_stock_bars(vt_symbol=vt_symbol, freq=bar_freq)
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# 创建一个15分钟bar的 kline对象
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setting = {}
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setting['name'] = f'{vt_symbol}_{bar_freq}'
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setting['bar_interval'] = bar_interval
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setting['para_ma1_len'] = 55 # 双均线
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setting['para_ma2_len'] = 89
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setting['para_macd_fast_len'] = 12 # 激活macd
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setting['para_macd_slow_len'] = 26
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setting['para_macd_signal_len'] = 9
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setting['para_active_chanlun'] = True # 激活缠论
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setting['price_tick'] = 1
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setting['is_stock'] = True
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setting['underly_symbol'] = vt_symbol.split('.')[0]
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kline = CtaMinuteBar(strategy=t1, cb_on_bar=None, setting=setting)
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# 推送bar到kline中
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for bar in bars:
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kline.add_bar(bar, bar_is_completed=True, bar_freq=bar_interval)
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# 获取kline的切片数据
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data = kline.get_data()
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snapshot = {
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'strategy': "demo",
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'datetime': datetime.now(),
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"kline_names": [kline.name],
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"klines": {kline.name: data}}
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# 创建一个GUI界面应用app
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qApp = create_qapp()
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# 创建切片回放工具窗口
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ui = UiSnapshot()
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# 显示切片内容
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ui.show(snapshot_file="",
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d=snapshot)
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sys.exit(qApp.exec_())
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@ -147,18 +147,15 @@ def refill(symbol_info):
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# thread_tasks.append(task)
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def resample(symbol, exchange, x_mins=[5, 15, 30]):
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def resample(vt_symbol, x_mins=[5, 15, 30]):
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"""
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更新多周期文件
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:param symbol:
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:param exchange:
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:param vt_symbol: 代码.交易所
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:param x_mins:
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:return:
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"""
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d1 = datetime.now()
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out_files, err_msg = resample_bars_file(vnpy_root=vnpy_root,
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symbol=symbol,
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exchange=exchange,
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out_files, err_msg = resample_bars_file(vt_symbol=vt_symbol,
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x_mins=x_mins)
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d2 = datetime.now()
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microseconds = round((d2 - d1).microseconds / 100, 0)
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@ -5,7 +5,7 @@ import pika
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import random
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import traceback
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from vnpy.amqp.base import base_broker
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from vnpy.component.base import MyEncoder
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# 模式1：接收者
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class receiver(base_broker):
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@ -307,7 +307,7 @@ class rpc_server(base_broker):
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def reply(self, chan, reply_data, reply_to, reply_id, delivery_tag):
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"""返回调用结果"""
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# data => string
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reply_msg = json.dumps(reply_data)
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reply_msg = json.dumps(reply_data,cls=MyEncoder)
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# 发送返回消息
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chan.basic_publish(exchange=self.exchange,
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routing_key=reply_to,
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@ -114,7 +114,7 @@ class RemoteClient:
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# 整个接口对外保持和原来的一致
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# 通过对原requests接口的“鸭子类型替换”来实现透明化
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def use(broker, host, port=1430, use_zmq=True, **kwargs):
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def use(broker, host, port=1430, use_zmq=False, **kwargs):
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if use_zmq:
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return ZMQRemoteClient(broker, host, port)
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else:
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@ -140,6 +140,7 @@ class RestClient(object):
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self.logger: Optional[logging.Logger] = None
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self.proxies = None
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self.cookies = {}
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self.thread_executor = ThreadPoolExecutor(max_workers=os.cpu_count() * 20)
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@ -436,8 +437,13 @@ class RestClient(object):
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if status_code == 204:
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json_body = None
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else:
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try:
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json_body = response.json()
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except Exception as ex:
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json_body = response.content.decode('utf-8')
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self._process_json_body(json_body, request)
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if response.cookies.get_dict():
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self.cookies.update(response.cookies)
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else:
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if request.on_failed:
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request.status = RequestStatus.failed
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@ -462,7 +468,7 @@ class RestClient(object):
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else:
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self.on_error(t, v, tb, request)
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def _process_json_body(self, json_body: Optional[dict], request: "Request"):
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def _process_json_body(self, json_body: Union[dict,str], request: "Request"):
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status_code = request.response.status_code
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if self.is_request_success(json_body, request):
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request.status = RequestStatus.success
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@ -243,7 +243,7 @@ class AccountRecorder(BaseEngine):
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end_day = dt_now.strftime('%Y%m%d')
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gw = self.main_engine.get_gateway(gw_name)
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if gw is None:
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continue
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self.write_log(f'Account_recorder找不到{gw_name}')
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if hasattr(gw, 'qryHistory'):
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self.write_log(u'向{}请求{}数据，{}~{}'.format(gw_name, data_type, begin_day, end_day))
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gw.qryHistory(data_type, begin_day, end_day)
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@ -20,7 +20,7 @@ from .base import StopOrder
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from vnpy.component.cta_grid_trade import CtaGrid, CtaGridTrade
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from vnpy.component.cta_position import CtaPosition
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from vnpy.component.cta_policy import CtaPolicy
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from vnpy.component.base import MyEncoder
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class CtaTemplate(ABC):
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"""CTA策略模板"""
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@ -1368,7 +1368,7 @@ class CtaFutureTemplate(CtaTemplate):
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if policy:
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op = getattr(policy, 'to_json', None)
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if callable(op):
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
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def save_dist(self, dist_data):
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"""
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@ -2152,7 +2152,7 @@ class CtaSpotTemplate(CtaTemplate):
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if policy:
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op = getattr(policy, 'to_json', None)
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if callable(op):
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
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def save_dist(self, dist_data):
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"""
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@ -20,6 +20,7 @@ from .base import StopOrder,EngineType
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from vnpy.component.cta_grid_trade import CtaGrid, CtaGridTrade
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from vnpy.component.cta_position import CtaPosition
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from vnpy.component.cta_policy import CtaPolicy
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from vnpy.component.base import MyEncoder
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class CtaTemplate(ABC):
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"""CTA股票策略模板"""
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@ -602,7 +603,7 @@ class CtaStockTemplate(CtaTemplate):
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"""初始化Policy"""
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self.write_log(u'init_policy(),初始化执行逻辑')
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self.policy.load()
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self.write_log('{}'.format(json.dumps(self.policy.to_json(),indent=2, ensure_ascii=False)))
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self.write_log('{}'.format(json.dumps(self.policy.to_json(),indent=2, ensure_ascii=False,cls=MyEncoder)))
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def init_position(self):
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"""
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@ -1075,9 +1076,12 @@ class CtaStockTemplate(CtaTemplate):
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continue
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# 实盘运行时，要加入市场买卖量的判断
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limit_down = None
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if not force and not self.backtesting:
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symbol_tick = self.cta_engine.get_tick(vt_symbol)
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if symbol_tick:
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if symbol_tick.limit_down > 0:
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limit_down = symbol_tick.limit_down
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symbol_volume_tick = self.cta_engine.get_volume_tick(vt_symbol)
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# 根据市场计算，前5档买单数量
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if all([symbol_tick.ask_volume_1, symbol_tick.ask_volume_2, symbol_tick.ask_volume_3,
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@ -1095,7 +1099,11 @@ class CtaStockTemplate(CtaTemplate):
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self.write_log(u'修正批次卖出{}数量:{}=>{}'.format(vt_symbol, org_sell_volume, sell_volume))
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# 获取当前价格
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if limit_down is None or cur_price > limit_down:
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sell_price = cur_price - self.cta_engine.get_price_tick(vt_symbol)
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else:
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sell_price = cur_price
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# 发出委托卖出
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vt_orderids = self.sell(
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vt_symbol=vt_symbol,
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@ -1134,7 +1142,7 @@ class CtaStockTemplate(CtaTemplate):
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dist_record = dict()
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dist_record['volume'] = grid.volume
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dist_record['price'] = self.cta_engine.get_price(grid.vt_symbol)
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dist_record['operation'] = 'execute finished'
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dist_record['operation'] = 'sell finished'
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dist_record['signal'] = grid.type
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self.save_dist(dist_record)
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@ -1322,6 +1330,11 @@ class CtaStockTemplate(CtaTemplate):
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elif order_status == Status.CANCELLED:
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self.write_log(u'委托单{}已成功撤单，删除{}'.format(vt_orderid, order_info))
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canceled_ids.append(vt_orderid)
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elif order_status == Status.CANCELLING:
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if over_seconds > self.cancel_seconds * 3:
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self.write_log(u'委托单{}正在撤单，超时{},删除{}'.format(vt_orderid,over_seconds, order_info))
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canceled_ids.append(vt_orderid)
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# 删除撤单的订单
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for vt_orderid in canceled_ids:
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@ -1381,7 +1394,7 @@ class CtaStockTemplate(CtaTemplate):
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policy = getattr(self, 'policy')
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op = getattr(policy, 'to_json', None)
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if callable(op):
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
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self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
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def save_dist(self, dist_data):
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"""
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@ -76,7 +76,7 @@ from .base import (
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STOPORDER_PREFIX,
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)
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from .template import CtaTemplate
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from vnpy.component.base import MARKET_DAY_ONLY
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from vnpy.component.base import MARKET_DAY_ONLY, MyEncoder
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from vnpy.component.cta_position import CtaPosition
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STOP_STATUS_MAP = {
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@ -165,6 +165,7 @@ class CtaLineBar(object):
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self.price_tick = 1 # 商品的最小价格单位
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self.round_n = 4 # round() 小数点的截断数量
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self.is_7x24 = False # 是否7x24小时运行（ 一般为数字货币）
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self.is_stock = False # 是否为股票
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# 当前的Tick的信息
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self.cur_tick = None # 当前 onTick()函数接收的 最新的tick
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@ -230,6 +231,8 @@ class CtaLineBar(object):
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self.minute_interval = None # 把各个周期的bar转换为分钟，在first_tick中，用来修正bar为整点分钟周期
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if setting:
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self.set_params(setting)
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if self.is_stock:
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self.is_7x24 = True
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# 修正self.minute_interval
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if self.interval == Interval.SECOND:
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@ -283,6 +286,7 @@ class CtaLineBar(object):
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self.param_list.append('interval') # bar的类型
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self.param_list.append('mode') # tick/bar模式
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self.param_list.append('is_7x24') # 是否为7X24小时运行的bar（一般为数字货币)
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self.param_list.append('is_stock') # 是否为7X24小时运行的bar（一般为数字货币)
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self.param_list.append('price_tick') # 最小跳动，用于处理指数等不一致的价格
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self.param_list.append('underly_symbol') # 短合约，
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@ -1,20 +1,196 @@
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import os
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import pandas as pd
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import numpy as np
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from typing import Union, List
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from datetime import datetime
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# 所有股票的复权因子
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STOCK_ADJUST_FACTORS = {}
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def get_bardata_folder(data_folder: str) -> str:
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"""
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如果data_folder为空白，就返回bar_data的目录
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:param data_folder:
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:return:
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"""
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if len(data_folder) == 0 or not os.path.exists(data_folder):
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vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
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data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
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return data_folder
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def get_stock_bars(vt_symbol:str,
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freq: str = "1d",
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start_date: str = "",
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fq_type:str ="qfq") -> (List, str):
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"""
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获取本地文件的股票bar数据
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:param vt_symbol:
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:param freq:
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:param start_date: 20180101 或者 2018-01-01
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:param fq_type: qfq:前复权；hfq:后复权; 空白:不复权
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:return:
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"""
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# 获取未复权的bar dataframe数据
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df, err_msg = get_stock_raw_data(vt_symbol=vt_symbol, freq=freq, start_date=start_date)
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bars = []
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if len(err_msg) > 0 or df is None:
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return bars, err_msg
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if fq_type != "":
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from vnpy.data.stock.adjust_factor import get_all_adjust_factor
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STOCK_ADJUST_FACTORS = get_all_adjust_factor()
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adj_list = STOCK_ADJUST_FACTORS.get(vt_symbol, [])
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if len(adj_list) > 0:
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for row in adj_list:
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row.update({'dividOperateDate': row.get('dividOperateDate')[:10] + ' 09:30:00'})
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# list -> dataframe, 转换复权日期格式
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adj_data = pd.DataFrame(adj_list)
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adj_data["dividOperateDate"] = pd.to_datetime(adj_data["dividOperateDate"], format="%Y-%m-%d %H:%M:%S")
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adj_data = adj_data.set_index("dividOperateDate")
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# 调用转换方法，对open,high,low,close, volume进行复权, fore, 前复权， 其他，后复权
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df = stock_to_adj(df, adj_data, adj_type='fore' if fq_type == 'qfw' else 'back')
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from vnpy.trader.object import BarData
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from vnpy.trader.constant import Exchange
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symbol, exchange = vt_symbol.split('.')
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for dt, bar_data in df.iterrows():
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bar_datetime = dt # - timedelta(seconds=bar_interval_seconds)
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bar = BarData(
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gateway_name='backtesting',
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symbol=symbol,
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exchange=Exchange(exchange),
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datetime=bar_datetime
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)
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if 'open' in bar_data:
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bar.open_price = float(bar_data['open'])
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bar.close_price = float(bar_data['close'])
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bar.high_price = float(bar_data['high'])
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bar.low_price = float(bar_data['low'])
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else:
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bar.open_price = float(bar_data['open_price'])
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bar.close_price = float(bar_data['close_price'])
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bar.high_price = float(bar_data['high_price'])
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bar.low_price = float(bar_data['low_price'])
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bar.volume = int(bar_data['volume']) if not np.isnan(bar_data['volume']) else 0
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bar.date = dt.strftime('%Y-%m-%d')
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bar.time = dt.strftime('%H:%M:%S')
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str_td = str(bar_data.get('trading_day', ''))
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if len(str_td) == 8:
|
||||
bar.trading_day = str_td[0:4] + '-' + str_td[4:6] + '-' + str_td[6:8]
|
||||
else:
|
||||
bar.trading_day = bar.date
|
||||
|
||||
bars.append(bar)
|
||||
|
||||
return bars, ""
|
||||
|
||||
def get_stock_raw_data(vt_symbol: str,
|
||||
freq: str = "1d",
|
||||
start_date: str = "",
|
||||
bar_data_folder: str = "") -> (Union[pd.DataFrame, None], str):
|
||||
"""
|
||||
获取本地bar_data下的 交易所/股票代码_时间周期.csv原始bar数据（未复权）
|
||||
:param vt_symbol: 600001.SSE 或 600001
|
||||
:param freq: 1m,5m, 15m, 30m, 1h, 1d
|
||||
:param start_date: 开始日期
|
||||
:param bar_data_folder: 强制指定bar_data所在目录
|
||||
:return: DataFrame, err_msg
|
||||
"""
|
||||
symbol, exchange = vt_symbol.split('.')
|
||||
# 1分钟 csv文件路径
|
||||
csv_file = os.path.abspath(os.path.join(
|
||||
get_bardata_folder(bar_data_folder),
|
||||
exchange,
|
||||
f'{symbol}_{freq}.csv'))
|
||||
|
||||
if not os.path.exists(csv_file):
|
||||
err_msg = f'{csv_file} 文件不存在，不能读取'
|
||||
return None, err_msg
|
||||
try:
|
||||
# 载入原始csv => dataframe
|
||||
df = pd.read_csv(csv_file)
|
||||
|
||||
datetime_format = "%Y-%m-%d %H:%M:%S"
|
||||
# 转换时间，str =》 datetime
|
||||
df["datetime"] = pd.to_datetime(df["datetime"], format=datetime_format)
|
||||
# 使用'datetime'字段作为索引
|
||||
df.set_index("datetime", inplace=True)
|
||||
if len(start_date) > 0:
|
||||
if len(start_date) == 8:
|
||||
_format = '%Y%m%d'
|
||||
else:
|
||||
_format = '%Y-%m-%d'
|
||||
start_date = datetime.strptime(start_date, _format)
|
||||
df = df.loc[start_date:]
|
||||
|
||||
return df, ""
|
||||
|
||||
except Exception as ex:
|
||||
err_msg = f'读取异常:{str(ex)}'
|
||||
return None, err_msg
|
||||
|
||||
|
||||
def resample_bars_file(vnpy_root, symbol, exchange, x_mins=[], include_day=False):
|
||||
def stock_to_adj(raw_data: pd.DataFrame,
|
||||
adj_data: pd.DataFrame,
|
||||
adj_type: str) -> pd.DataFrame:
|
||||
"""
|
||||
股票数据复权转换
|
||||
:param raw_data: 不复权数据
|
||||
:param adj_data: 复权记录 ( 从barstock下载的复权记录列表=》df）
|
||||
:param adj_type: 复权类型, fore, 前复权； back,后复权
|
||||
:return:
|
||||
"""
|
||||
|
||||
if adj_type == 'fore':
|
||||
adj_factor = adj_data["foreAdjustFactor"]
|
||||
adj_factor = adj_factor / adj_factor.iloc[-1] # 保证最后一个复权因子是1
|
||||
else:
|
||||
adj_factor = adj_data["backAdjustFactor"]
|
||||
adj_factor = adj_factor / adj_factor.iloc[0] # 保证第一个复权因子是1
|
||||
|
||||
# 把raw_data的第一个日期，插入复权因子df，使用后填充
|
||||
if adj_factor.index[0] != raw_data.index[0]:
|
||||
adj_factor.loc[raw_data.index[0]] = np.nan
|
||||
adj_factor.sort_index(inplace=True)
|
||||
adj_factor = adj_factor.ffill()
|
||||
|
||||
adj_factor = adj_factor.reindex(index=raw_data.index) # 按价格dataframe的日期索引来扩展索引
|
||||
adj_factor = adj_factor.ffill() # 向前（向未来）填充扩展后的空单元格
|
||||
|
||||
# 把复权因子，作为adj字段，补充到raw_data中
|
||||
raw_data['adj'] = adj_factor
|
||||
|
||||
# 逐一复权高低开平和成交量
|
||||
for col in ['open', 'high', 'low', 'close']:
|
||||
raw_data[col] = raw_data[col] * raw_data['adj'] # 价格乘上复权系数
|
||||
raw_data['volume'] = raw_data['volume'] / raw_data['adj'] # 成交量除以复权系数
|
||||
|
||||
return raw_data
|
||||
|
||||
|
||||
def resample_bars_file(vt_symbol: str,
|
||||
x_mins: List[str] = [],
|
||||
include_day: bool = False,
|
||||
bar_data_folder: str = "") -> (list, str):
|
||||
"""
|
||||
重建x分钟K线（和日线）csv文件
|
||||
:param symbol:
|
||||
:param vt_symbol: 代码.交易所
|
||||
:param x_mins: [5, 15, 30, 60]
|
||||
:param include_day: 是否也重建日线
|
||||
:param vnpy_root: 项目所在根目录
|
||||
:return: out_files,err_msg
|
||||
"""
|
||||
err_msg = ""
|
||||
out_files = []
|
||||
symbol, exchange = vt_symbol.split('.')
|
||||
|
||||
# 1分钟 csv文件路径
|
||||
csv_file = os.path.abspath(os.path.join(vnpy_root, 'bar_data', exchange.value, f'{symbol}_1m.csv'))
|
||||
csv_file = os.path.abspath(os.path.join(get_bardata_folder(bar_data_folder), exchange, f'{symbol}_1m.csv'))
|
||||
|
||||
if not os.path.exists(csv_file):
|
||||
err_msg = f'{csv_file} 文件不存在，不能转换'
|
||||
@ -49,10 +225,13 @@ def resample_bars_file(vnpy_root, symbol, exchange, x_mins=[], include_day=False
|
||||
for x_min in x_mins:
|
||||
# 目标文件
|
||||
target_file = os.path.abspath(
|
||||
os.path.join(vnpy_root, 'bar_data', exchange.value, f'{symbol}_{x_min}m.csv'))
|
||||
os.path.join(get_bardata_folder(bar_data_folder), exchange, f'{symbol}_{x_min}m.csv'))
|
||||
# 合成x分钟K线并删除为空的行 参数 closed：left类似向上取值既 09：30的k线数据是包含09：30-09：35之间的数据
|
||||
# df_target = df_1m.resample(f'{x_min}min', how=ohlc_rule, closed='left', label='left').dropna(axis=0, how='any')
|
||||
df_target = df_1m.resample(f'{x_min}min', closed='left', label='left').agg(ohlc_rule).dropna(axis=0,
|
||||
df_target = df_1m.resample(
|
||||
f'{x_min}min',
|
||||
closed='left',
|
||||
label='left').agg(ohlc_rule).dropna(axis=0,
|
||||
how='any')
|
||||
# dropna(axis=0, how='any') axis参数0：针对行进行操作 1：针对列进行操作 how参数any：只要包含就删除 all：全是为NaN才删除
|
||||
|
||||
@ -64,10 +243,13 @@ def resample_bars_file(vnpy_root, symbol, exchange, x_mins=[], include_day=False
|
||||
if include_day:
|
||||
# 目标文件
|
||||
target_file = os.path.abspath(
|
||||
os.path.join(vnpy_root, 'bar_data', exchange.value, f'{symbol}_1d.csv'))
|
||||
os.path.join(get_bardata_folder(bar_data_folder), exchange, f'{symbol}_1d.csv'))
|
||||
# 合成x分钟K线并删除为空的行 参数 closed：left类似向上取值既 09：30的k线数据是包含09：30-09：35之间的数据
|
||||
# df_target = df_1m.resample(f'D', how=ohlc_rule, closed='left', label='left').dropna(axis=0, how='any')
|
||||
df_target = df_1m.resample(f'D', closed='left', label='left').agg(ohlc_rule).dropna(axis=0, how='any')
|
||||
df_target = df_1m.resample(
|
||||
f'D',
|
||||
closed='left',
|
||||
label='left').agg(ohlc_rule).dropna(axis=0, how='any')
|
||||
# dropna(axis=0, how='any') axis参数0：针对行进行操作 1：针对列进行操作 how参数any：只要包含就删除 all：全是为NaN才删除
|
||||
|
||||
if len(df_target) > 0:
|
||||
|
||||
@ -130,4 +130,21 @@ def download_adjust_factor():
|
||||
return factor_dict
|
||||
|
||||
if __name__ == '__main__':
|
||||
download_adjust_factor()
|
||||
|
||||
# 下载所有复权数据
|
||||
# download_adjust_factor()
|
||||
|
||||
# 下载某个股票的复权数据
|
||||
# f = get_adjust_factor(vt_symbol='000651.SZSE',stock_name='格力电器',need_login=True)
|
||||
#
|
||||
# for d in f:
|
||||
# print(d)
|
||||
|
||||
# 读取缓存文件中某只股票的复权数据
|
||||
factors = get_all_adjust_factor()
|
||||
f = factors.get('000651.SZSE',None)
|
||||
if f is None:
|
||||
print('获取不到数据')
|
||||
else:
|
||||
for d in f:
|
||||
print(d)
|
||||
|
||||
@ -34,7 +34,7 @@ TDX_PROXY_CONFIG = 'tdx_proxy_config.json'
|
||||
def get_tdx_market_code(code):
|
||||
# 获取通达信股票的market code
|
||||
code = str(code)
|
||||
if code[0] in ['5', '6', '9'] or code[:3] in ["009", "126", "110", "201", "202", "203", "204"]:
|
||||
if code[0] in ['5', '6', '9'] or code[:3] in ["880","009", "126", "110", "201", "202", "203", "204"]:
|
||||
# 上海证券交易所
|
||||
return 1
|
||||
# 深圳证券交易所
|
||||
@ -101,10 +101,13 @@ def get_cache_config(config_file_name):
|
||||
config = {}
|
||||
if not os.path.exists(config_file_name):
|
||||
return config
|
||||
try:
|
||||
with bz2.BZ2File(config_file_name, 'rb') as f:
|
||||
config = pickle.load(f)
|
||||
return config
|
||||
|
||||
except Exception as ex:
|
||||
print(f'读取缓存本地文件:{config_file_name}异常{str(ex)}')
|
||||
return config
|
||||
|
||||
def save_cache_config(data: dict, config_file_name):
|
||||
"""保存本地缓存的配置地址信息"""
|
||||
@ -126,8 +129,9 @@ def save_cache_json(data_dict: dict, json_file_name: str):
|
||||
save_json(filename=config_file_name, data=data_dict)
|
||||
|
||||
|
||||
def get_stock_type(code):
|
||||
def get_stock_type(code,market_id = None ):
|
||||
"""获取股票得分类"""
|
||||
if market_id is None:
|
||||
market_id = get_tdx_market_code(code)
|
||||
|
||||
if market_id == 0:
|
||||
|
||||
@ -314,13 +314,18 @@ class TdxStockData(object):
|
||||
|
||||
self.write_log('{}开始下载tdx股票: {},代码:{} {}数据, {} to {}.'
|
||||
.format(datetime.now(), name, tdx_code, tdx_period, qry_start_date, qry_end_date))
|
||||
stock_type = get_stock_type(tdx_code,market_id)
|
||||
if stock_type == 'index_cn':
|
||||
get_bar_func = self.api.get_index_bars
|
||||
else:
|
||||
get_bar_func = self.api.get_security_bars
|
||||
|
||||
try:
|
||||
_start_date = qry_end_date
|
||||
_bars = []
|
||||
_pos = 0
|
||||
while _start_date > qry_start_date:
|
||||
_res = self.api.get_security_bars(
|
||||
_res = get_bar_func(
|
||||
category=PERIOD_MAPPING[period],
|
||||
market=market_id,
|
||||
code=tdx_code,
|
||||
@ -452,8 +457,13 @@ class TdxStockData(object):
|
||||
.format(datetime.now(), period, list(PERIOD_MAPPING.keys())))
|
||||
return False, ret_bars
|
||||
tdx_period = PERIOD_MAPPING.get(period)
|
||||
stock_type = get_stock_type(tdx_code)
|
||||
if stock_type == 'index_cn':
|
||||
get_bar_func = self.api.get_index_bars
|
||||
else:
|
||||
get_bar_func = self.api.get_security_bars
|
||||
try:
|
||||
datas = self.api.get_security_bars(
|
||||
datas = get_bar_func(
|
||||
category=PERIOD_MAPPING[period],
|
||||
market=market_id,
|
||||
code=tdx_code,
|
||||
@ -490,6 +500,8 @@ class TdxStockData(object):
|
||||
self.write_error(f'获取{symbol}数据失败:{str(ex)}')
|
||||
return False, ret_bars
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
def save_cache(self,
|
||||
cache_folder: str,
|
||||
cache_symbol: str,
|
||||
|
||||
@ -19,26 +19,36 @@ t1 = FakeStrategy()
|
||||
t2 = FakeStrategy()
|
||||
|
||||
# 创建API对象(使用本地socket5代理）
|
||||
api_01 = TdxStockData(strategy=t1, proxy_ip='localhost', proxy_port=1080)
|
||||
#api_01 = TdxStockData(strategy=t1, proxy_ip='localhost', proxy_port=1080)
|
||||
# 不使用代理
|
||||
#api_01 = TdxStockData(strategy=t1)
|
||||
|
||||
# 获取市场下股票
|
||||
for market_id in range(2):
|
||||
print('get market_id:{}'.format(market_id))
|
||||
security_list = api_01.get_security_list(market_id)
|
||||
if len(security_list) == 0:
|
||||
continue
|
||||
for security in security_list:
|
||||
if security.get('code', '').startswith('12') or u'转债' in security.get('name', ''):
|
||||
str_security = json.dumps(security, indent=1, ensure_ascii=False)
|
||||
print('market_id:{},{}'.format(market_id, str_security))
|
||||
api_01 = TdxStockData(strategy=t1)
|
||||
#
|
||||
# # 获取市场下股票
|
||||
# for market_id in range(2):
|
||||
# print('get market_id:{}'.format(market_id))
|
||||
# security_list = api_01.get_security_list(market_id)
|
||||
# if len(security_list) == 0:
|
||||
# continue
|
||||
# for security in security_list:
|
||||
# if security['code'].startswith('88'):
|
||||
# str_security = json.dumps(security, indent=1, ensure_ascii=False)
|
||||
# print(str_security)
|
||||
# if security.get('code', '').startswith('12') or u'转债' in security.get('name', ''):
|
||||
# str_security = json.dumps(security, indent=1, ensure_ascii=False)
|
||||
# # print('market_id:{},{}'.format(market_id, str_security))
|
||||
|
||||
# str_markets = json.dumps(security_list, indent=1, ensure_ascii=False)
|
||||
# print(u'{}'.format(str_markets))
|
||||
|
||||
# 获取历史分钟线
|
||||
# api_01.get_bars('002024', period='1hour', callback=t1.display_bar)
|
||||
ret,result = api_01.get_bars('880351.SSE', period='1hour', callback=t1.display_bar)
|
||||
if ret:
|
||||
for bar in result:
|
||||
print(bar)
|
||||
# ret,result = api_01.get_last_bars(symbol='002024',return_bar=True)
|
||||
# if ret:
|
||||
# print(result)
|
||||
|
||||
|
||||
# api.get_bars(symbol, period='5min', callback=display_bar)
|
||||
# api.get_bars(symbol, period='1day', callback=display_bar)
|
||||
@ -50,7 +60,7 @@ for market_id in range(2):
|
||||
# for r in result[0:10] + result[-10:]:
|
||||
# print(r)
|
||||
|
||||
# 获取历史分时数据
|
||||
ret, result = api_01.get_history_transaction_data('110031', '20200504')
|
||||
for r in result[0:10] + result[-10:]:
|
||||
print(r)
|
||||
# # 获取历史分时数据
|
||||
# ret, result = api_01.get_history_transaction_data('110031', '20200504')
|
||||
# for r in result[0:10] + result[-10:]:
|
||||
# print(r)
|
||||
|
||||
@ -940,11 +940,21 @@ class ThsTdApi(object):
|
||||
return
|
||||
if '总资产' not in data:
|
||||
return
|
||||
|
||||
## 为了兼容东财的webapi，这里frozen做个特殊处理
|
||||
# if "冻结金额" in data:
|
||||
# # 同花顺直接给了冻结金额
|
||||
# frozen = float(data["冻结金额"])
|
||||
# else:
|
||||
# # 东财没有冻结金额这个项目，要计算
|
||||
# frozen = float(data["总资产"]) - float(data["资金余额"])
|
||||
frozen = 0
|
||||
|
||||
account = AccountData(
|
||||
gateway_name=self.gateway_name,
|
||||
accountid=self.userid,
|
||||
balance=float(data["总资产"]),
|
||||
frozen=float(data["总资产"]) - float(data["资金余额"]),
|
||||
frozen=frozen,
|
||||
currency="人民币",
|
||||
trading_day=self.trading_day
|
||||
)
|
||||
|
||||
@ -578,16 +578,20 @@ class IndexGenerator:
|
||||
self.exchange = setting.get('exchange', None)
|
||||
self.price_tick = setting.get('price_tick')
|
||||
self.symbols = setting.get('symbols', {})
|
||||
self.pre_oi_total = 1
|
||||
|
||||
# 订阅行情
|
||||
self.subscribe()
|
||||
|
||||
self.n = len(self.symbols)
|
||||
|
||||
|
||||
def subscribe(self):
|
||||
"""订阅行情"""
|
||||
dt_now = datetime.now()
|
||||
for symbol in list(self.symbols.keys()):
|
||||
pre_open_interest = self.symbols.get(symbol,0)
|
||||
self.pre_oi_total += pre_open_interest
|
||||
# 全路径合约 => 标准合约 ,如 ZC2109 => ZC109, RB2110 => rb2110
|
||||
vn_symbol = get_real_symbol_by_exchange(symbol, Exchange(self.exchange))
|
||||
# 先移除
|
||||
@ -596,6 +600,9 @@ class IndexGenerator:
|
||||
self.gateway.write_log(f'移除早于当月的合约{symbol}')
|
||||
continue
|
||||
|
||||
if pre_open_interest < 100:
|
||||
self.gateway.write_log(f'移除持仓量:{pre_open_interest}低于100的合约{symbol}')
|
||||
continue
|
||||
# 重新登记合约
|
||||
self.symbols[vn_symbol] = pre_open_interest
|
||||
|
||||
@ -625,12 +632,6 @@ class IndexGenerator:
|
||||
bid_price_1 = 0
|
||||
mi_tick = None
|
||||
|
||||
# 已经积累的行情tick数量，不足总数减1，不处理
|
||||
|
||||
if len(self.ticks) < min(self.n * 0.8, 3):
|
||||
self.gateway.write_log(f'{self.underlying_symbol}合约数据{len(self.ticks)}不足{self.n} 0.8,暂不合成指数')
|
||||
return
|
||||
|
||||
# 计算所有合约的累加持仓量、资金、成交量、找出最大持仓量的主力合约
|
||||
for t in self.ticks.values():
|
||||
all_interest += t.open_interest
|
||||
@ -641,6 +642,10 @@ class IndexGenerator:
|
||||
if mi_tick is None or mi_tick.open_interest < t.open_interest:
|
||||
mi_tick = t
|
||||
|
||||
if not (len(self.ticks) > min(self.n * 0.7, 3) or all_interest > self.pre_oi_total * 0.5):
|
||||
self.gateway.write_log(f'{self.underlying_symbol}合约数据{len(self.ticks)}不足{self.n} 0.7，或者累计持仓数不够昨持仓0.5,暂不合成指数')
|
||||
return
|
||||
|
||||
# 总量 > 0
|
||||
if all_interest > 0 and all_amount > 0:
|
||||
last_price = round(float(all_amount / all_interest), 4)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user