[update] gateway & data

examples/stock/demo_01.py

@@ -0,0 +1,76 @@
+# flake8: noqa
+
+# 示例代码
+# 从本地股票数据加载，前复权，显示主图指标、副图指标、缠论
+
+import os
+import sys
+import json
+
+vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+if vnpy_root not in sys.path:
+    print(f'sys.path append({vnpy_root})')
+    sys.path.append(vnpy_root)
+
+os.environ["VNPY_TESTING"] = "1"
+
+from vnpy.data.tdx.tdx_common import FakeStrategy
+from vnpy.data.tdx.tdx_stock_data import *
+from vnpy.component.cta_line_bar import CtaMinuteBar
+from vnpy.trader.ui.kline.ui_snapshot import UiSnapshot
+from vnpy.trader.ui import create_qapp
+from vnpy.data.common import get_stock_bars
+
+if __name__ == "__main__":
+
+    # 创建一个假的策略
+    t1 = FakeStrategy()
+
+    # 股票代码.交易所
+    vt_symbol = '000001.SZSE'
+    # 数据周期
+    bar_freq = '15m'
+    # 一根bar代表的分钟数
+    bar_interval = int(bar_freq.replace('m', ''))
+
+    # 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
+    print('加载数据')
+    bars, msg = get_stock_bars(vt_symbol=vt_symbol, freq=bar_freq)
+
+    # 创建一个15分钟bar的 kline对象
+    setting = {}
+    setting['name'] = f'{vt_symbol}_{bar_freq}'
+    setting['bar_interval'] = bar_interval
+    setting['para_ma1_len'] = 55  # 双均线
+    setting['para_ma2_len'] = 89
+    setting['para_macd_fast_len'] = 12  # 激活macd
+    setting['para_macd_slow_len'] = 26
+    setting['para_macd_signal_len'] = 9
+    setting['para_active_chanlun'] = True  # 激活缠论
+    setting['price_tick'] = 1
+    setting['is_stock'] = True
+    setting['underly_symbol'] = vt_symbol.split('.')[0]
+    kline = CtaMinuteBar(strategy=t1, cb_on_bar=None, setting=setting)
+
+    # 推送bar到kline中
+    for bar in bars:
+        kline.add_bar(bar, bar_is_completed=True, bar_freq=bar_interval)
+
+    # 获取kline的切片数据
+    data = kline.get_data()
+    snapshot = {
+        'strategy': "demo",
+        'datetime': datetime.now(),
+        "kline_names": [kline.name],
+        "klines": {kline.name: data}}
+
+    # 创建一个GUI界面应用app
+    qApp = create_qapp()
+
+    # 创建切片回放工具窗口
+    ui = UiSnapshot()
+    # 显示切片内容
+    ui.show(snapshot_file="",
+            d=snapshot)
+
+    sys.exit(qApp.exec_())

prod/jobs/refill_tdx_stock_bars.py

@@ -147,18 +147,15 @@ def refill(symbol_info):
     #     thread_tasks.append(task)
 
 
-def resample(symbol, exchange, x_mins=[5, 15, 30]):
+def resample(vt_symbol, x_mins=[5, 15, 30]):
     """
     更新多周期文件
-    :param symbol:
-    :param exchange:
+    :param vt_symbol: 代码.交易所
     :param x_mins:
     :return:
     """
     d1 = datetime.now()
-    out_files, err_msg = resample_bars_file(vnpy_root=vnpy_root,
-                                            symbol=symbol,
-                                            exchange=exchange,
+    out_files, err_msg = resample_bars_file(vt_symbol=vt_symbol,
                                             x_mins=x_mins)
     d2 = datetime.now()
     microseconds = round((d2 - d1).microseconds / 100, 0)

vnpy/amqp/consumer.py

@@ -5,7 +5,7 @@ import pika
 import random
 import traceback
 from vnpy.amqp.base import base_broker
-
+from vnpy.component.base import MyEncoder
 
 #   模式1：接收者
 class receiver(base_broker):
@@ -307,7 +307,7 @@ class rpc_server(base_broker):
     def reply(self, chan, reply_data, reply_to, reply_id, delivery_tag):
         """返回调用结果"""
         # data => string
-        reply_msg = json.dumps(reply_data)
+        reply_msg = json.dumps(reply_data,cls=MyEncoder)
         # 发送返回消息
         chan.basic_publish(exchange=self.exchange,
                            routing_key=reply_to,

vnpy/api/easytrader/remoteclient.py

@@ -114,7 +114,7 @@ class RemoteClient:
 # 整个接口对外保持和原来的一致
 # 通过对原requests接口的“鸭子类型替换”来实现透明化
 
-def use(broker, host, port=1430, use_zmq=True, **kwargs):
+def use(broker, host, port=1430, use_zmq=False, **kwargs):
     if use_zmq:
         return ZMQRemoteClient(broker, host, port)
     else:

vnpy/api/rest/rest_client.py

@@ -140,6 +140,7 @@ class RestClient(object):
         self.logger: Optional[logging.Logger] = None
 
         self.proxies = None
+        self.cookies = {}
 
         self.thread_executor = ThreadPoolExecutor(max_workers=os.cpu_count() * 20)
 
@@ -436,8 +437,13 @@ class RestClient(object):
                         if status_code == 204:
                             json_body = None
                         else:
+                            try:
                                 json_body = response.json()
+                            except Exception as ex:
+                                json_body = response.content.decode('utf-8')
                         self._process_json_body(json_body, request)
+                        if response.cookies.get_dict():
+                            self.cookies.update(response.cookies)
                     else:
                         if request.on_failed:
                             request.status = RequestStatus.failed
@@ -462,7 +468,7 @@ class RestClient(object):
             else:
                 self.on_error(t, v, tb, request)
 
-    def _process_json_body(self, json_body: Optional[dict], request: "Request"):
+    def _process_json_body(self, json_body: Union[dict,str], request: "Request"):
         status_code = request.response.status_code
         if self.is_request_success(json_body, request):
             request.status = RequestStatus.success

vnpy/app/account_recorder/engine.py

@@ -243,7 +243,7 @@ class AccountRecorder(BaseEngine):
                         end_day = dt_now.strftime('%Y%m%d')
                         gw = self.main_engine.get_gateway(gw_name)
                         if gw is None:
-                            continue
+                            self.write_log(f'Account_recorder找不到{gw_name}')
                         if hasattr(gw, 'qryHistory'):
                             self.write_log(u'向{}请求{}数据，{}~{}'.format(gw_name, data_type, begin_day, end_day))
                             gw.qryHistory(data_type, begin_day, end_day)

vnpy/app/cta_crypto/template.py

@@ -20,7 +20,7 @@ from .base import StopOrder
 from vnpy.component.cta_grid_trade import CtaGrid, CtaGridTrade
 from vnpy.component.cta_position import CtaPosition
 from vnpy.component.cta_policy import CtaPolicy
-
+from vnpy.component.base import MyEncoder
 
 class CtaTemplate(ABC):
     """CTA策略模板"""
@@ -1368,7 +1368,7 @@ class CtaFutureTemplate(CtaTemplate):
             if policy:
                 op = getattr(policy, 'to_json', None)
                 if callable(op):
-                    self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
+                    self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
 
     def save_dist(self, dist_data):
         """
@@ -2152,7 +2152,7 @@ class CtaSpotTemplate(CtaTemplate):
             if policy:
                 op = getattr(policy, 'to_json', None)
                 if callable(op):
-                    self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
+                    self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
 
     def save_dist(self, dist_data):
         """

vnpy/app/cta_stock/template.py

@@ -20,6 +20,7 @@ from .base import StopOrder,EngineType
 from vnpy.component.cta_grid_trade import CtaGrid, CtaGridTrade
 from vnpy.component.cta_position import CtaPosition
 from vnpy.component.cta_policy import CtaPolicy
+from vnpy.component.base import MyEncoder
 
 class CtaTemplate(ABC):
     """CTA股票策略模板"""
@@ -602,7 +603,7 @@ class CtaStockTemplate(CtaTemplate):
         """初始化Policy"""
         self.write_log(u'init_policy(),初始化执行逻辑')
         self.policy.load()
-        self.write_log('{}'.format(json.dumps(self.policy.to_json(),indent=2, ensure_ascii=False)))
+        self.write_log('{}'.format(json.dumps(self.policy.to_json(),indent=2, ensure_ascii=False,cls=MyEncoder)))
 
     def init_position(self):
         """
@@ -1075,9 +1076,12 @@ class CtaStockTemplate(CtaTemplate):
                 continue
 
             # 实盘运行时，要加入市场买卖量的判断
+            limit_down = None
             if not force and not self.backtesting:
                 symbol_tick = self.cta_engine.get_tick(vt_symbol)
                 if symbol_tick:
+                    if symbol_tick.limit_down > 0:
+                        limit_down = symbol_tick.limit_down
                     symbol_volume_tick = self.cta_engine.get_volume_tick(vt_symbol)
                     # 根据市场计算，前5档买单数量
                     if all([symbol_tick.ask_volume_1, symbol_tick.ask_volume_2, symbol_tick.ask_volume_3,
@@ -1095,7 +1099,11 @@ class CtaStockTemplate(CtaTemplate):
                                 self.write_log(u'修正批次卖出{}数量:{}=>{}'.format(vt_symbol, org_sell_volume, sell_volume))
 
             # 获取当前价格
+            if limit_down is None or cur_price > limit_down:
                 sell_price = cur_price - self.cta_engine.get_price_tick(vt_symbol)
+            else:
+                sell_price = cur_price
+
             # 发出委托卖出
             vt_orderids = self.sell(
                 vt_symbol=vt_symbol,
@@ -1134,7 +1142,7 @@ class CtaStockTemplate(CtaTemplate):
         dist_record = dict()
         dist_record['volume'] = grid.volume
         dist_record['price'] = self.cta_engine.get_price(grid.vt_symbol)
-        dist_record['operation'] = 'execute finished'
+        dist_record['operation'] = 'sell finished'
         dist_record['signal'] = grid.type
         self.save_dist(dist_record)
 
@@ -1322,6 +1330,11 @@ class CtaStockTemplate(CtaTemplate):
             elif order_status == Status.CANCELLED:
                 self.write_log(u'委托单{}已成功撤单，删除{}'.format(vt_orderid, order_info))
                 canceled_ids.append(vt_orderid)
+            elif order_status == Status.CANCELLING:
+
+                if over_seconds > self.cancel_seconds * 3:
+                    self.write_log(u'委托单{}正在撤单，超时{},删除{}'.format(vt_orderid,over_seconds, order_info))
+                    canceled_ids.append(vt_orderid)
 
         # 删除撤单的订单
         for vt_orderid in canceled_ids:
@@ -1381,7 +1394,7 @@ class CtaStockTemplate(CtaTemplate):
             policy = getattr(self, 'policy')
             op = getattr(policy, 'to_json', None)
             if callable(op):
-                self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False)))
+                self.write_log(u'当前Policy:{}'.format(json.dumps(policy.to_json(), indent=2, ensure_ascii=False,cls=MyEncoder)))
 
     def save_dist(self, dist_data):
         """

vnpy/app/cta_strategy_pro/engine.py

@@ -76,7 +76,7 @@ from .base import (
     STOPORDER_PREFIX,
 )
 from .template import CtaTemplate
-from vnpy.component.base import MARKET_DAY_ONLY
+from vnpy.component.base import MARKET_DAY_ONLY, MyEncoder
 from vnpy.component.cta_position import CtaPosition
 
 STOP_STATUS_MAP = {

vnpy/component/cta_line_bar.py

@@ -165,6 +165,7 @@ class CtaLineBar(object):
         self.price_tick = 1  # 商品的最小价格单位
         self.round_n = 4  # round() 小数点的截断数量
         self.is_7x24 = False  # 是否7x24小时运行（ 一般为数字货币）
+        self.is_stock = False # 是否为股票
 
         # 当前的Tick的信息
         self.cur_tick = None  # 当前 onTick()函数接收的 最新的tick
@@ -230,6 +231,8 @@ class CtaLineBar(object):
         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
         if setting:
             self.set_params(setting)
+            if self.is_stock:
+                self.is_7x24 = True
 
             # 修正self.minute_interval
             if self.interval == Interval.SECOND:
@@ -283,6 +286,7 @@ class CtaLineBar(object):
         self.param_list.append('interval')  # bar的类型
         self.param_list.append('mode')  # tick/bar模式
         self.param_list.append('is_7x24')  # 是否为7X24小时运行的bar（一般为数字货币)
+        self.param_list.append('is_stock')  # 是否为7X24小时运行的bar（一般为数字货币)
         self.param_list.append('price_tick')  # 最小跳动，用于处理指数等不一致的价格
         self.param_list.append('underly_symbol')  # 短合约，
 

vnpy/data/common.py

@@ -1,20 +1,196 @@
 import os
 import pandas as pd
+import numpy as np
+from typing import Union, List
+from datetime import datetime
+
+# 所有股票的复权因子
+STOCK_ADJUST_FACTORS = {}
+
+def get_bardata_folder(data_folder: str) -> str:
+    """
+    如果data_folder为空白，就返回bar_data的目录
+    :param data_folder:
+    :return:
+    """
+    if len(data_folder) == 0 or not os.path.exists(data_folder):
+        vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+        data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
+    return data_folder
+
+def get_stock_bars(vt_symbol:str,
+                 freq: str = "1d",
+                 start_date: str = "",
+                 fq_type:str ="qfq") -> (List, str):
+    """
+    获取本地文件的股票bar数据
+    :param vt_symbol:
+    :param freq:
+    :param start_date: 20180101 或者 2018-01-01
+    :param fq_type: qfq:前复权；hfq:后复权; 空白:不复权
+    :return:
+    """
+    # 获取未复权的bar dataframe数据
+    df, err_msg = get_stock_raw_data(vt_symbol=vt_symbol, freq=freq, start_date=start_date)
+    bars = []
+    if len(err_msg) > 0 or df is None:
+        return bars, err_msg
+
+    if fq_type != "":
+        from vnpy.data.stock.adjust_factor import get_all_adjust_factor
+        STOCK_ADJUST_FACTORS = get_all_adjust_factor()
+        adj_list = STOCK_ADJUST_FACTORS.get(vt_symbol, [])
+
+        if len(adj_list) > 0:
+
+            for row in adj_list:
+                row.update({'dividOperateDate': row.get('dividOperateDate')[:10] + ' 09:30:00'})
+            # list -> dataframe, 转换复权日期格式
+            adj_data = pd.DataFrame(adj_list)
+            adj_data["dividOperateDate"] = pd.to_datetime(adj_data["dividOperateDate"], format="%Y-%m-%d %H:%M:%S")
+            adj_data = adj_data.set_index("dividOperateDate")
+            # 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
+            df = stock_to_adj(df, adj_data, adj_type='fore' if fq_type == 'qfw' else 'back')
+
+        from vnpy.trader.object import BarData
+        from vnpy.trader.constant import Exchange
+        symbol, exchange = vt_symbol.split('.')
+
+        for dt, bar_data in df.iterrows():
+            bar_datetime = dt  # - timedelta(seconds=bar_interval_seconds)
+
+            bar = BarData(
+                gateway_name='backtesting',
+                symbol=symbol,
+                exchange=Exchange(exchange),
+                datetime=bar_datetime
+            )
+            if 'open' in bar_data:
+                bar.open_price = float(bar_data['open'])
+                bar.close_price = float(bar_data['close'])
+                bar.high_price = float(bar_data['high'])
+                bar.low_price = float(bar_data['low'])
+            else:
+                bar.open_price = float(bar_data['open_price'])
+                bar.close_price = float(bar_data['close_price'])
+                bar.high_price = float(bar_data['high_price'])
+                bar.low_price = float(bar_data['low_price'])
+
+            bar.volume = int(bar_data['volume']) if not np.isnan(bar_data['volume']) else 0
+            bar.date = dt.strftime('%Y-%m-%d')
+            bar.time = dt.strftime('%H:%M:%S')
+            str_td = str(bar_data.get('trading_day', ''))
+            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', 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,
                                                 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:
@@ -75,4 +257,4 @@ def resample_bars_file(vnpy_root, symbol, exchange, x_mins=[], include_day=False
             print(f'生成[日线] => {target_file}')
             out_files.append(target_file)
 
-    return out_files,err_msg
+    return out_files, err_msg

vnpy/data/stock/adjust_factor.py

@@ -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)

vnpy/data/tdx/tdx_common.py

@@ -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:

vnpy/data/tdx/tdx_stock_data.py

@@ -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,

vnpy/data/tdx/test_tdx_stock.py

@@ -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)

vnpy/gateway/ths/ths_gateway.py

@@ -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
             )

vnpy/trader/gateway.py

@@ -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)