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[新功能] tdx 期货指数数据，每天自动增量更新至csv文件

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msincenselee 2020-01-04 12:22:22 +08:00
parent 2d8d61cc91
commit 23fb096ab7
5 changed files with 703 additions and 64 deletions
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514
vnpy/data/tdx/future_contracts.json Normal file
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@ -0,0 +1,514 @@
{
"A": {
"underlying_symbol": "A",
"mi_symbol": "a2005",
"full_symbol": "A2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"AG": {
"underlying_symbol": "AG",
"mi_symbol": "ag2007",
"full_symbol": "AG2007",
"exchange": "SHFE",
"symbol_size": "15",
"price_tick": "1"
},
"AL": {
"underlying_symbol": "AL",
"mi_symbol": "al2002",
"full_symbol": "AL2002",
"exchange": "SHFE",
"symbol_size": "5",
"price_tick": "5"
},
"AP": {
"underlying_symbol": "AP",
"mi_symbol": "AP005",
"full_symbol": "AP2005",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"AU": {
"underlying_symbol": "AU",
"mi_symbol": "au2006",
"full_symbol": "AU2006",
"exchange": "SHFE",
"symbol_size": "1000",
"price_tick": "0.05"
},
"B": {
"underlying_symbol": "B",
"mi_symbol": "b2003",
"full_symbol": "B2003",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"BB": {
"underlying_symbol": "BB",
"mi_symbol": "bb2012",
"full_symbol": "BB2012",
"exchange": "DCE",
"symbol_size": "500",
"price_tick": "0.05"
},
"BU": {
"underlying_symbol": "BU",
"mi_symbol": "bu2006",
"full_symbol": "BU2006",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "2"
},
"C": {
"underlying_symbol": "C",
"mi_symbol": "c2005",
"full_symbol": "C2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"CF": {
"underlying_symbol": "CF",
"mi_symbol": "CF005",
"full_symbol": "CF2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "5"
},
"CJ": {
"underlying_symbol": "CJ",
"mi_symbol": "CJ005",
"full_symbol": "CJ2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "5"
},
"CS": {
"underlying_symbol": "CS",
"mi_symbol": "cs2005",
"full_symbol": "CS2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"CU": {
"underlying_symbol": "CU",
"mi_symbol": "cu2003",
"full_symbol": "CU2003",
"exchange": "SHFE",
"symbol_size": "5",
"price_tick": "10"
},
"CY": {
"underlying_symbol": "CY",
"mi_symbol": "CY005",
"full_symbol": "CY2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "5"
},
"EB": {
"underlying_symbol": "EB",
"mi_symbol": "eb2005",
"full_symbol": "EB2005",
"exchange": "DCE",
"symbol_size": "5",
"price_tick": "1"
},
"EG": {
"underlying_symbol": "EG",
"mi_symbol": "eg2005",
"full_symbol": "EG2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"FB": {
"underlying_symbol": "FB",
"mi_symbol": "fb2005",
"full_symbol": "FB2005",
"exchange": "DCE",
"symbol_size": "500",
"price_tick": "0.05"
},
"FG": {
"underlying_symbol": "FG",
"mi_symbol": "FG005",
"full_symbol": "FG2005",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"FU": {
"underlying_symbol": "FU",
"mi_symbol": "fu2005",
"full_symbol": "FU2005",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "1"
},
"HC": {
"underlying_symbol": "HC",
"mi_symbol": "hc2005",
"full_symbol": "HC2005",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "1"
},
"I": {
"underlying_symbol": "I",
"mi_symbol": "i2005",
"full_symbol": "I2005",
"exchange": "DCE",
"symbol_size": "100",
"price_tick": "0.5"
},
"IC": {
"underlying_symbol": "IC",
"mi_symbol": "IC2003",
"full_symbol": "IC2003",
"exchange": "CFFEX",
"symbol_size": "200",
"price_tick": "0.2"
},
"IF": {
"underlying_symbol": "IF",
"mi_symbol": "IF2003",
"full_symbol": "IF2003",
"exchange": "CFFEX",
"symbol_size": "300",
"price_tick": "0.2"
},
"IH": {
"underlying_symbol": "IH",
"mi_symbol": "IH2003",
"full_symbol": "IH2003",
"exchange": "CFFEX",
"symbol_size": "300",
"price_tick": "0.2"
},
"J": {
"underlying_symbol": "J",
"mi_symbol": "j2005",
"full_symbol": "J2005",
"exchange": "DCE",
"symbol_size": "100",
"price_tick": "0.5"
},
"JD": {
"underlying_symbol": "JD",
"mi_symbol": "jd2005",
"full_symbol": "JD2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"JM": {
"underlying_symbol": "JM",
"mi_symbol": "jm2005",
"full_symbol": "JM2005",
"exchange": "DCE",
"symbol_size": "60",
"price_tick": "0.5"
},
"JR": {
"underlying_symbol": "JR",
"mi_symbol": "JR011",
"full_symbol": "JR2011",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"L": {
"underlying_symbol": "L",
"mi_symbol": "l2005",
"full_symbol": "L2005",
"exchange": "DCE",
"symbol_size": "5",
"price_tick": "5"
},
"LR": {
"underlying_symbol": "LR",
"mi_symbol": "LR007",
"full_symbol": "LR2007",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"M": {
"underlying_symbol": "M",
"mi_symbol": "m2005",
"full_symbol": "M2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"MA": {
"underlying_symbol": "MA",
"mi_symbol": "MA005",
"full_symbol": "MA2005",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"NI": {
"underlying_symbol": "NI",
"mi_symbol": "ni2003",
"full_symbol": "NI2003",
"exchange": "SHFE",
"symbol_size": "1",
"price_tick": "10"
},
"NR": {
"underlying_symbol": "NR",
"mi_symbol": "nr2004",
"full_symbol": "NR2004",
"exchange": "INE",
"symbol_size": "10",
"price_tick": "5"
},
"OI": {
"underlying_symbol": "OI",
"mi_symbol": "OI005",
"full_symbol": "OI2005",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"P": {
"underlying_symbol": "P",
"mi_symbol": "p2005",
"full_symbol": "P2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "2"
},
"PB": {
"underlying_symbol": "PB",
"mi_symbol": "pb2002",
"full_symbol": "PB2002",
"exchange": "SHFE",
"symbol_size": "5",
"price_tick": "5"
},
"PM": {
"underlying_symbol": "PM",
"mi_symbol": "PM011",
"full_symbol": "PM2011",
"exchange": "CZCE",
"symbol_size": "50",
"price_tick": "1"
},
"PP": {
"underlying_symbol": "PP",
"mi_symbol": "pp2005",
"full_symbol": "PP2005",
"exchange": "DCE",
"symbol_size": "5",
"price_tick": "1"
},
"RB": {
"underlying_symbol": "RB",
"mi_symbol": "rb2005",
"full_symbol": "RB2005",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "1"
},
"RI": {
"underlying_symbol": "RI",
"mi_symbol": "RI011",
"full_symbol": "RI2011",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"RM": {
"underlying_symbol": "RM",
"mi_symbol": "RM005",
"full_symbol": "RM2005",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"RR": {
"underlying_symbol": "RR",
"mi_symbol": "rr2005",
"full_symbol": "RR2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "1"
},
"RS": {
"underlying_symbol": "RS",
"mi_symbol": "RS011",
"full_symbol": "RS2011",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"RU": {
"underlying_symbol": "RU",
"mi_symbol": "ru2005",
"full_symbol": "RU2005",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "5"
},
"SA": {
"underlying_symbol": "SA",
"mi_symbol": "SA005",
"full_symbol": "SA2005",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"SC": {
"underlying_symbol": "SC",
"mi_symbol": "sc2003",
"full_symbol": "SC2003",
"exchange": "INE",
"symbol_size": "1000",
"price_tick": "0.1"
},
"SF": {
"underlying_symbol": "SF",
"mi_symbol": "SF005",
"full_symbol": "SF2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "2"
},
"SM": {
"underlying_symbol": "SM",
"mi_symbol": "SM005",
"full_symbol": "SM2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "2"
},
"SN": {
"underlying_symbol": "SN",
"mi_symbol": "sn2006",
"full_symbol": "SN2006",
"exchange": "SHFE",
"symbol_size": "1",
"price_tick": "10"
},
"SP": {
"underlying_symbol": "SP",
"mi_symbol": "sp2005",
"full_symbol": "SP2005",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "2"
},
"SR": {
"underlying_symbol": "SR",
"mi_symbol": "SR005",
"full_symbol": "SR2005",
"exchange": "CZCE",
"symbol_size": "10",
"price_tick": "1"
},
"SS": {
"underlying_symbol": "SS",
"mi_symbol": "ss2006",
"full_symbol": "SS2006",
"exchange": "SHFE",
"symbol_size": "5",
"price_tick": "5"
},
"T": {
"underlying_symbol": "T",
"mi_symbol": "T2003",
"full_symbol": "T2003",
"exchange": "CFFEX",
"symbol_size": "10000",
"price_tick": "0.005"
},
"TA": {
"underlying_symbol": "TA",
"mi_symbol": "TA005",
"full_symbol": "TA2005",
"exchange": "CZCE",
"symbol_size": "5",
"price_tick": "2"
},
"TF": {
"underlying_symbol": "TF",
"mi_symbol": "TF2003",
"full_symbol": "TF2003",
"exchange": "CFFEX",
"symbol_size": "10000",
"price_tick": "0.005"
},
"TS": {
"underlying_symbol": "TS",
"mi_symbol": "TS2003",
"full_symbol": "TS2003",
"exchange": "CFFEX",
"symbol_size": "20000",
"price_tick": "0.005"
},
"UR": {
"underlying_symbol": "UR",
"mi_symbol": "UR005",
"full_symbol": "UR2005",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"V": {
"underlying_symbol": "V",
"mi_symbol": "v2005",
"full_symbol": "V2005",
"exchange": "DCE",
"symbol_size": "5",
"price_tick": "5"
},
"WH": {
"underlying_symbol": "WH",
"mi_symbol": "WH005",
"full_symbol": "WH2005",
"exchange": "CZCE",
"symbol_size": "20",
"price_tick": "1"
},
"WR": {
"underlying_symbol": "WR",
"mi_symbol": "wr2012",
"full_symbol": "WR2012",
"exchange": "SHFE",
"symbol_size": "10",
"price_tick": "1"
},
"Y": {
"underlying_symbol": "Y",
"mi_symbol": "y2005",
"full_symbol": "Y2005",
"exchange": "DCE",
"symbol_size": "10",
"price_tick": "2"
},
"ZC": {
"underlying_symbol": "ZC",
"mi_symbol": "ZC005",
"full_symbol": "ZC2005",
"exchange": "CZCE",
"symbol_size": "100",
"price_tick": "0.2"
},
"ZN": {
"underlying_symbol": "ZN",
"mi_symbol": "zn2003",
"full_symbol": "ZN2003",
"exchange": "SHFE",
"symbol_size": "5",
"price_tick": "5"
}
}

95
vnpy/data/tdx/refill_tdx_future_bars.py Normal file
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@ -0,0 +1,95 @@
# flake8: noqa
"""
下载通达信指数合约1分钟bar => vnpy项目目录/bar_data/
"""
import os
import sys
import json
from collections import OrderedDict
import pandas as pd
vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', '..'))
if vnpy_root not in sys.path:
sys.path.append(vnpy_root)
os.environ["VNPY_TESTING"] = "1"
from vnpy.data.tdx.tdx_future_data import *
# 保存的1分钟指数 bar目录
bar_data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
# 开始日期（每年大概需要几分钟）
start_date = '20160101'
# 创建API对象
api_01 = TdxFutureData()
# 更新本地合约缓存信息
api_01.update_mi_contracts()
def bar_to_dict(bar_data: BarData):
d = OrderedDict({
'datetime': bar_data.datetime,
'symbol': bar_data.symbol,
'vt_symbol': bar_data.vt_symbol,
'exchange': bar_data.exchange.value,
'open': bar_data.open_price,
'close': bar_data.close_price,
'high': bar_data.high_price,
'low': bar_data.low_price,
'volume': bar_data.volume,
'open_interest': bar_data.open_interest,
'trading_day': bar_data.trading_day
})
return d
for underlying_symbol in api_01.future_contracts.keys():
index_symbol = underlying_symbol + '99'
print(f'开始更新:{index_symbol}')
# csv数据文件名
bar_file_path = os.path.abspath(os.path.join(bar_data_folder, f'{underlying_symbol}99_{start_date}_1m.csv'))
# 如果文件存在，
if os.path.exists(bar_file_path):
df_old = pd.read_csv(bar_file_path, index_col=0)
df_old = df_old.rename(lambda x: pd.to_datetime(x, format="%Y-%m-%d %H:%M:%S"))
# 取最后一条时间
last_dt = df_old.index[-1]
start_dt = last_dt - timedelta(days=1)
print(f'文件{bar_file_path}存在，最后时间:{start_date}')
else:
df_old = None
start_dt = datetime.strptime(start_date, '%Y%m%d')
print(f'文件{bar_file_path}不存在，开始时间:{start_date}')
result, bars = api_01.get_bars(symbol=index_symbol,
period='1min',
callback=None,
start_dt=start_dt,
return_bar=False)
# [dict] => dataframe
df_extern = pd.DataFrame(bars)
df_extern.set_index('datetime', inplace=True)
if df_old is not None:
# 扩展数据
print('扩展数据')
data_df = pd.concat([df_old, df_extern], axis=0)
else:
data_df = df_extern
# 数据按时间戳去重
print('按时间戳去重')
data_df = data_df[~data_df.index.duplicated(keep='first')]
# 排序
data_df = data_df.sort_index()
# print(data_df.head())
print(data_df.tail())
data_df.to_csv(bar_file_path, index=True)
print(f'更新{index_symbol}数据 => 文件{bar_file_path}')

2
vnpy/data/tdx/tdx_common.py
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@ -126,4 +126,4 @@ class FakeStrategy(object):
self.write_log(content, level=ERROR)
def display_bar(self, bar, bar_is_completed=True, freq=1):
print(u'{} {}'.format(bar.vtSymbol, bar.datetime))
print(u'{} {}'.format(bar.vt_symbol, bar.datetime))

137
vnpy/data/tdx/tdx_future_data.py
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@ -17,7 +17,7 @@ import traceback
from datetime import datetime, timedelta, time
from logging import ERROR
from typing import Dict
from typing import Dict, Callable
from pandas import to_datetime
from pytdx.exhq import TdxExHq_API
@ -91,7 +91,7 @@ def get_tdx_marketid(symbol):
class TdxFutureData(object):
# ----------------------------------------------------------------------
def __init__(self, strategy, best_ip={}):
def __init__(self, strategy=None, best_ip={}):
"""
构造函数
:param strategy: 上层策略，主要用与使用write_log（）
@ -195,8 +195,17 @@ class TdxFutureData(object):
save_cache_json(best_future_ip, TDX_FUTURE_CONFIG)
return best_future_ip
# ----------------------------------------------------------------------
def qryInstrument(self):
def _get_vn_exchange(self, symbol):
"""获取"""
underlying_symbol = get_underlying_symbol(symbol).upper()
info = self.future_contracts.get(underlying_symbol, None)
if info:
return Exchange(info.get('exchange'))
else:
market_id = get_tdx_marketid(symbol)
return Tdx_Vn_Exchange_Map.get(str(market_id), Exchange.INE)
def qry_instrument(self):
"""
查询/更新合约信息
:return:
@ -225,19 +234,29 @@ class TdxFutureData(object):
def get_bars(self,
symbol: str,
period: str,
callback,
callback: Callable = None,
bar_freq: int = 1,
start_dt: datetime = None):
start_dt: datetime = None,
end_dt: datetime = None,
return_bar=True):
"""
返回k线数据
symbol：合约
period: 周期: 1min,3min,5min,15min,30min,1day,3day,1hour,2hour,4hour,6hour,12hour
callback: 逐一bar去驱动回调函数, 只有 return_bar = True时才回调
bar_freq: 回调时的参数
start_dt: 取数据的开始时间
end_dt: 取数据的结束时间
return_bar: 返回 第二个数据内容，True:BarData, False:dict
"""
ret_bars = []
tdx_symbol = symbol.upper().replace('_', '')
tdx_symbol = tdx_symbol.replace('99', 'L9')
tdx_index_symbol = get_underlying_symbol(symbol) + 'L9'
underlying_symbol = get_underlying_symbol(symbol).upper()
tdx_index_symbol = underlying_symbol + 'L9'
vn_exchange = self._get_vn_exchange(underlying_symbol)
self.connect()
if self.api is None:
return False, ret_bars
@ -253,7 +272,11 @@ class TdxFutureData(object):
qry_start_date = datetime.now() - timedelta(days=10)
else:
qry_start_date = start_dt
end_date = datetime.combine(datetime.now() + timedelta(days=1), time(ALL_MARKET_END_HOUR, 0))
if end_dt is None:
self.write_log(u'没有设置结束时间，缺省为当日')
end_date = datetime.combine(datetime.now() + timedelta(days=1), time(ALL_MARKET_END_HOUR, 0))
else:
end_date = end_dt
if qry_start_date > end_date:
qry_start_date = end_date
self.write_log('{}开始下载tdx:{} {}数据, {} to {}.'
@ -290,12 +313,6 @@ class TdxFutureData(object):
data = data.assign(datetime=to_datetime(data['datetime']))
data = data.assign(ticker=symbol)
data['instrument_id'] = data['ticker']
# if future['market'] == 28 or future['market'] == 47:
# # 大写字母: 郑州商品 or 中金所期货
# data['instrument_id'] = data['ticker']
# else:
# data['instrument_id'] = data['ticker'].apply(lambda x: x.lower())
data['symbol'] = symbol
data = data.drop(
['year', 'month', 'day', 'hour', 'minute', 'price', 'amount', 'ticker'],
@ -312,11 +329,11 @@ class TdxFutureData(object):
str(datetime.now()), tdx_symbol, len(data)))
return False, ret_bars
data['total_turnover'] = data['volume']
data['total_turnover'] = data['volume'] * data['close']
data["limit_down"] = 0
data["limit_up"] = 999999
data['trading_date'] = data['datetime']
data['trading_date'] = data['trading_date'].apply(lambda x: (x.strftime('%Y-%m-%d')))
data['trading_day'] = data['datetime']
data['trading_day'] = data['trading_day'].apply(lambda x: (x.strftime('%Y-%m-%d')))
monday_ts = data['datetime'].dt.weekday == 0 # 星期一
night_ts1 = data['datetime'].dt.hour > ALL_MARKET_END_HOUR
night_ts2 = data['datetime'].dt.hour < ALL_MARKET_BEGIN_HOUR
@ -326,52 +343,54 @@ class TdxFutureData(object):
monday_ts2 = monday_ts & night_ts2 # 星期一的夜盘(00:00~04:00), 再减两天
data.loc[monday_ts2, 'datetime'] -= timedelta(days=2)
# data['datetime'] -= timedelta(minutes=1) # 直接给Strategy使用, RiceQuant格式, 不需要减1分钟
data['dt_datetime'] = data['datetime']
# data['dt_datetime'] = data['datetime']
data['date'] = data['datetime'].apply(lambda x: (x.strftime('%Y-%m-%d')))
data['time'] = data['datetime'].apply(lambda x: (x.strftime('%H:%M:%S')))
data['datetime'] = data['datetime'].apply(lambda x: float(x.strftime('%Y%m%d%H%M%S')))
data = data.set_index('dt_datetime', drop=False)
# data = data[int(last_date.strftime('%Y%m%d%H%M%S')):int(end_date.strftime('%Y%m%d%H%M%S'))]
# data = data[str(last_date):str(end_date)]
# data['datetime'] = data['datetime'].apply(lambda x: float(x.strftime('%Y%m%d%H%M%S')))
data = data.set_index('datetime', drop=False)
if return_bar:
self.write_log('dataframe => [bars]')
for index, row in data.iterrows():
add_bar = BarData(gateway_name='tdx',
symbol=symbol,
exchange=vn_exchange,
datetime=index)
try:
add_bar.date = row['date']
add_bar.time = row['time']
add_bar.trading_day = row['trading_day']
add_bar.open_price = float(row['open'])
add_bar.high_price = float(row['high'])
add_bar.low_price = float(row['low'])
add_bar.close_price = float(row['close'])
add_bar.volume = float(row['volume'])
add_bar.openInterest = float(row['open_interest'])
except Exception as ex:
self.write_error(
'error when convert bar:{},ex:{},t:{}'.format(row, str(ex), traceback.format_exc()))
# print('error when convert bar:{},ex:{},t:{}'.format(row, str(ex), traceback.format_exc()))
return False, ret_bars
for index, row in data.iterrows():
add_bar = BarData()
try:
add_bar.symbol = row['symbol']
add_bar.datetime = index
add_bar.date = row['date']
add_bar.time = row['time']
add_bar.trading_date = row['trading_date']
add_bar.open_price = float(row['open'])
add_bar.high_price = float(row['high'])
add_bar.low_price = float(row['low'])
add_bar.close_price = float(row['close'])
add_bar.volume = float(row['volume'])
add_bar.openInterest = float(row['open_interest'])
except Exception as ex:
self.write_error(
'error when convert bar:{},ex:{},t:{}'.format(row, str(ex), traceback.format_exc()))
# print('error when convert bar:{},ex:{},t:{}'.format(row, str(ex), traceback.format_exc()))
return False
if start_dt is not None and index < start_dt:
continue
ret_bars.append(add_bar)
if callback is not None:
freq = bar_freq
bar_is_completed = True
if period != '1min' and index == data['dt_datetime'][-1]:
# 最后一个bar，可能是不完整的，强制修改
# - 5min修改后freq基本正确
# - 1day在VNPY合成时不关心已经收到多少Bar, 所以影响也不大
# - 但其它分钟周期因为不好精确到每个品种, 修改后的freq可能有错
if index > current_datetime:
bar_is_completed = False
# 根据秒数算的话，要+1，例如13:31,freq=31，第31根bar
freq = NUM_MINUTE_MAPPING[period] - int((index - current_datetime).total_seconds() / 60)
callback(add_bar, bar_is_completed, freq)
if start_dt is not None and index < start_dt:
continue
ret_bars.append(add_bar)
if callback is not None:
freq = bar_freq
bar_is_completed = True
if period != '1min' and index == data['datetime'][-1]:
# 最后一个bar，可能是不完整的，强制修改
# - 5min修改后freq基本正确
# - 1day在VNPY合成时不关心已经收到多少Bar, 所以影响也不大
# - 但其它分钟周期因为不好精确到每个品种, 修改后的freq可能有错
if index > current_datetime:
bar_is_completed = False
# 根据秒数算的话，要+1，例如13:31,freq=31，第31根bar
freq = NUM_MINUTE_MAPPING[period] - int((index - current_datetime).total_seconds() / 60)
callback(add_bar, bar_is_completed, freq)
else:
self.write_log('dataframe => [ dict ]')
ret_bars = list(data.T.to_dict().values())
return True, ret_bars
except Exception as ex:
self.write_error('exception in get:{},{},{}'.format(tdx_symbol, str(ex), traceback.format_exc()))

19
vnpy/data/tdx/test_tdx_future.py
View File

@ -1,7 +1,7 @@
# flake8: noqa
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:
sys.path.append(vnpy_root)
@ -22,7 +22,7 @@ str_markets = json.dumps(markets, indent=1, ensure_ascii=False)
print(u'{}'.format(str_markets))
# 获取所有的期货合约明细
api_01.qryInstrument()
# api_01.qry_instrument()
# 获取某个合约得最新价
# price = api_01.get_price('rb2005')
@ -59,8 +59,19 @@ corr = df.corr()
print(corr)
corr_rate = round(abs(corr.iloc[0, 1]) * 100, 2)
"""
# api.get_bars(symbol, period='5min', callback=display_bar)
# api_01.get_bars('IF99', period='1day', callback=t1.display_bar)
# 获取bar，并通过回调方式，提高给策略，逐一onbar
# api_01.get_bars('IF99', period='1min', callback=t1.display_bar, bar_freq=1)
# 获取bar，只返回 list[dict]
result, bars = api_01.get_bars('IF99', period='1min', return_bar=False)
if result:
print('前十根bar')
for bar in bars[0:10]:
print(bar)
print('后十根bar')
for bar in bars[-10:]:
print(bar)
# result,datas = api_01.get_transaction_data(symbol='ni1905')
# api_02 = TdxFutureData(t2)
# api_02.get_bars('IF99', period='1min', callback=t1.display_bar)