def QA_fetch_get_extensionmarket_info(ip=None, port=None):
ip, port = get_extensionmarket_ip(ip, port)
apix = TdxExHq_API()
with apix.connect(ip, port):
global extension_market_info
extension_market_info = apix.to_df(apix.get_markets())
return extension_market_info
def __init__(self):
self.cf = config
self.tools = tdx_tools
self.qihuo_api = TdxExHq_API()
self.gupiao_api = TdxHq_API()
self.cflen = 0
self.table = pt.PrettyTable()
def QA_fetch_get_future_realtime(code, ip=None, port=None):
'期货实时价格'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
__data = pd.DataFrame()
code_market = extension_market_info.query('code=="{}"'.format(code))
with apix.connect(ip, port):
__data = apix.to_df(apix.get_instrument_quote(
int(code_market.market),code))
__data['datetime'] = datetime.datetime.now()
# data = __data[['datetime', 'active1', 'active2', 'last_close', 'code', 'open', 'high', 'low', 'price', 'cur_vol',
# 's_vol', 'b_vol', 'vol', 'ask1', 'ask_vol1', 'bid1', 'bid_vol1', 'ask2', 'ask_vol2',
# 'bid2', 'bid_vol2', 'ask3', 'ask_vol3', 'bid3', 'bid_vol3', 'ask4',
# 'ask_vol4', 'bid4', 'bid_vol4', 'ask5', 'ask_vol5', 'bid5', 'bid_vol5']]
return _data.set_index('code', drop=False, inplace=False)
def QA_fetch_get_future_day(code,
start_date,
end_date,
frequence='day',
ip=best_ip['future'],
port=7727):
'期货数据 日线'
apix = TdxExHq_API()
start_date = str(start_date)[0:10]
today_ = datetime.date.today()
lens = QA_util_get_trade_gap(start_date, today_)
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
with apix.connect(ip, port):
code_market = extension_market_info.query('code=="{}"'.format(code))
data = pd.concat([
apix.to_df(
apix.get_instrument_bars(_select_type(frequence),
int(code_market.market), str(code),
(int(lens / 700) - i) * 700, 700))
for i in range(int(lens / 700) + 1)
],
axis=0)
data = data.assign(date=data['datetime'].apply(lambda x: str(x[0:10]))).assign(code=str(code))\
.assign(date_stamp=data['datetime'].apply(lambda x: QA_util_date_stamp(str(x)[0:10]))).set_index('date', drop=False, inplace=False)
return data.drop(
['year', 'month', 'day', 'hour', 'minute', 'datetime'],
axis=1)[start_date:end_date].assign(
date=data['date'].apply(lambda x: str(x)[0:10]))
def QA_fetch_get_future_transaction(code, start, end, retry=2, ip=None, port=None):
'期货历史成交分笔'
ip, port = get_extensionmarket_ip(ip, port)
apix = TdxExHq_API()
global extension_market_list
extension_market_list = QA_fetch_get_extensionmarket_list(
) if extension_market_list is None else extension_market_list
real_start, real_end = QA_util_get_real_datelist(start, end)
if real_start is None:
return None
real_id_range = []
with apix.connect(ip, port):
code_market = extension_market_list.query('code=="{}"'.format(code))
data = pd.DataFrame()
for index_ in range(trade_date_sse.index(real_start), trade_date_sse.index(real_end) + 1):
try:
data_ = __QA_fetch_get_future_transaction(
code, trade_date_sse[index_], retry, int(code_market.market), apix)
if len(data_) < 1:
return None
except Exception as e:
QA_util_log_info('Wrong in Getting {} history transaction data in day {}'.format(
code, trade_date_sse[index_]))
else:
QA_util_log_info('Successfully Getting {} history transaction data in day {}'.format(
code, trade_date_sse[index_]))
data = data.append(data_)
if len(data) > 0:
return data.assign(datetime=data['datetime'].apply(lambda x: str(x)[0:19]))
else:
return None
def QA_fetch_get_future_day(code, start_date, end_date, frequence='day', ip=None, port=None):
'期货数据 日线'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
start_date = str(start_date)[0:10]
today_ = datetime.date.today()
lens = QA_util_get_trade_gap(start_date, today_)
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
with apix.connect(ip, port):
code_market = extension_market_info.query('code=="{}"'.format(code))
data = pd.concat([apix.to_df(apix.get_instrument_bars(_select_type(
frequence), int(code_market.market), str(code), (int(lens / 700) - i) * 700, 700))for i in range(int(lens / 700) + 1)], axis=0)
data = data.assign(date=data['datetime'].apply(lambda x: str(x[0:10]))).assign(code=str(code))\
.assign(date_stamp=data['datetime'].apply(lambda x: QA_util_date_stamp(str(x)[0:10]))).set_index('date', drop=False, inplace=False)
return data.drop(['year', 'month', 'day', 'hour', 'minute', 'datetime'], axis=1)[start_date:end_date].assign(date=data['date'].apply(lambda x: str(x)[0:10]))
def __init__(self, **kwargs):
try:
default = settings.get('SERVER').get('EX')[0]
self.bestip = config.get('BESTIP').get('EX', default)
except ValueError:
self.bestip = ('112.74.214.43', 7727)
self.client = TdxExHq_API(**kwargs)
def xapi_x(retry_count=3):
for _ in range(retry_count):
try:
api = TdxExHq_API(heartbeat=True)
api.connect(ct._get_xxserver(), ct.X_PORT)
except Exception as e:
print(e)
else:
return api
raise IOError(ct.NETWORK_URL_ERROR_MSG)
def __init__(self, host: Optional[str] = None):
self._env = env = Env()
env.read_env()
tdx_host = host if host else env.str('TDX_HOST')
self._api = TdxExHq_API(heartbeat=True, multithread=True)
self._ip, self._port = tdx_host.split(':')
self._server_tz = timezone('Asia/Shanghai')
self._pill = Event()
self._market_mapping = dict(
zip(["SHFE", "CZCE", "DCE", "CFFEX", "US"], [30, 28, 29, 47, 74]))
def xapi_x(retry_count=3):
for _ in range(retry_count):
try:
api = TdxExHq_API(heartbeat=True)
api.connect(ct._get_xxserver(), ct.X_PORT)
except Exception as e:
print(e)
else:
return api
raise IOError(ct.NETWORK_URL_ERROR_MSG)
def exhq():
ex_api = TdxExHq_API(auto_retry=True, raise_exception=False)
try:
is_tdx_ex_connect = ex_api.connect('106.14.95.149', 7727, time_out=30)
except Exception as e:
print('time out to connect to pytdx')
print(e)
if is_tdx_ex_connect is not False: # 失败了返回False，成功了返回地址
print('connect to pytdx extend api successful')
else:
ex_api = None
return ex_api
def connect(self, is_reconnect=False):
"""
连接API
:return:
"""
# 创建api连接对象实例
try:
if self.api is None or not self.connection_status:
self.write_log(u'开始连接通达信行情服务器')
self.api = TdxExHq_API(heartbeat=True,
auto_retry=True,
raise_exception=True)
# 选取最佳服务器
if is_reconnect or len(self.best_ip) == 0:
self.best_ip = get_cache_json(TDX_FUTURE_CONFIG)
last_datetime_str = self.best_ip.get('datetime', None)
if last_datetime_str:
try:
last_datetime = datetime.strptime(
last_datetime_str, '%Y-%m-%d %H:%M:%S')
if (datetime.now() - last_datetime
).total_seconds() > 60 * 60 * 2:
self.best_ip = {}
except Exception as ex: # noqa
self.best_ip = {}
else:
self.best_ip = {}
if len(self.best_ip) == 0:
self.best_ip = self.select_best_ip()
self.api.connect(self.best_ip['ip'], self.best_ip['port'])
# 尝试获取市场合约统计
c = self.api.get_instrument_count()
if c < 10:
err_msg = u'该服务器IP {}/{}无响应'.format(
self.best_ip['ip'], self.best_ip['port'])
self.write_error(err_msg)
else:
self.write_log(u'创建tdx连接, IP: {}/{}'.format(
self.best_ip['ip'], self.best_ip['port']))
# print(u'创建tdx连接, IP: {}/{}'.format(self.best_ip['ip'], self.best_ip['port']))
self.connection_status = True
# if not is_reconnect:
# 更新 symbol_exchange_dict , symbol_market_dict
# self.qryInstrument()
except Exception as ex:
self.write_log(u'连接服务器tdx异常:{},{}'.format(str(ex),
traceback.format_exc()))
return False
return True
def test_get_history_instrument_bars_range():
log.info("查询代码列表")
api = TdxExHq_API(auto_retry=True)
try:
with api.connect('61.152.107.141', 7727):
data = api.get_history_instrument_bars_range(
74, "BABA", 20170613, 20170620)
assert data is not None
assert type(data) is list
assert len(data) > 0
except socket.timeout as e:
pass
def QA_fetch_get_future_min(code,
start,
end,
frequence='1min',
ip=best_ip['future'],
port=7727):
'期货数据 分钟线'
apix = TdxExHq_API()
type_ = ''
start_date = str(start)[0:10]
today_ = datetime.date.today()
lens = QA_util_get_trade_gap(start_date, today_)
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
if str(frequence) in ['5', '5m', '5min', 'five']:
frequence, type_ = 0, '5min'
lens = 48 * lens
elif str(frequence) in ['1', '1m', '1min', 'one']:
frequence, type_ = 8, '1min'
lens = 240 * lens
elif str(frequence) in ['15', '15m', '15min', 'fifteen']:
frequence, type_ = 1, '15min'
lens = 16 * lens
elif str(frequence) in ['30', '30m', '30min', 'half']:
frequence, type_ = 2, '30min'
lens = 8 * lens
elif str(frequence) in ['60', '60m', '60min', '1h']:
frequence, type_ = 3, '60min'
lens = 4 * lens
if lens > 20800:
lens = 20800
with apix.connect(ip, port):
code_market = extension_market_info.query('code=="{}"'.format(code))
data = pd.concat([
apix.to_df(
apix.get_instrument_bars(frequence, int(code_market.market),
str(code),
(int(lens / 700) - i) * 700, 700))
for i in range(int(lens / 700) + 1)
],
axis=0)
data = data\
.assign(datetime=pd.to_datetime(data['datetime']), code=str(code))\
.drop(['year', 'month', 'day', 'hour', 'minute'], axis=1, inplace=False)\
.assign(date=data['datetime'].apply(lambda x: str(x)[0:10]))\
.assign(date_stamp=data['datetime'].apply(lambda x: QA_util_date_stamp(x)))\
.assign(time_stamp=data['datetime'].apply(lambda x: QA_util_time_stamp(x)))\
.assign(type=type_).set_index('datetime', drop=False, inplace=False)[start:end]
return data.assign(datetime=data['datetime'].apply(lambda x: str(x)))
def __init__(self,
market,
code,
date,
start=None,
ip='140.207.226.39',
port=7722):
self.market = market
self.code = code
self.date = date
self.start = start
self.api = TdxExHq_API()
connect = self.api.connect(ip, port)
def QA_fetch_get_future_min(code, start, end, frequence='1min', ip=None, port=None):
'期货数据 分钟线'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
type_ = ''
start_date = str(start)[0:10]
today_ = datetime.date.today()
lens = QA_util_get_trade_gap(start_date, today_)
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
if str(frequence) in ['5', '5m', '5min', 'five']:
frequence, type_ = 0, '5min'
lens = 48 * lens
elif str(frequence) in ['1', '1m', '1min', 'one']:
frequence, type_ = 8, '1min'
lens = 240 * lens
elif str(frequence) in ['15', '15m', '15min', 'fifteen']:
frequence, type_ = 1, '15min'
lens = 16 * lens
elif str(frequence) in ['30', '30m', '30min', 'half']:
frequence, type_ = 2, '30min'
lens = 8 * lens
elif str(frequence) in ['60', '60m', '60min', '1h']:
frequence, type_ = 3, '60min'
lens = 4 * lens
if lens > 20800:
lens = 20800
with apix.connect(ip, port):
code_market = extension_market_info.query('code=="{}"'.format(code))
data = pd.concat([apix.to_df(apix.get_instrument_bars(frequence, int(code_market.market), str(
code), (int(lens / 700) - i) * 700, 700)) for i in range(int(lens / 700) + 1)], axis=0)
data = data\
.assign(datetime=pd.to_datetime(data['datetime']), code=str(code))\
.drop(['year', 'month', 'day', 'hour', 'minute'], axis=1, inplace=False)\
.assign(date=data['datetime'].apply(lambda x: str(x)[0:10]))\
.assign(date_stamp=data['datetime'].apply(lambda x: QA_util_date_stamp(x)))\
.assign(time_stamp=data['datetime'].apply(lambda x: QA_util_time_stamp(x)))\
.assign(type=type_).set_index('datetime', drop=False, inplace=False)[start:end]
return data.assign(datetime=data['datetime'].apply(lambda x: str(x)))
def TdxexInit(ip='106.14.95.149', port=7727):
global tdxapiex
tdxapiex = TdxExHq_API(auto_retry=True, raise_exception=False)
try:
is_tdx_ex_connect = tdxapiex.connect(ip, port, time_out=30)
except Exception as e:
#print('time out to connect to pytdx')
print(e)
if is_tdx_ex_connect is not False: # 失败了返回False，成功了返回地址
pass
#print('connect to pytdx extend api successful')
else:
tdxapiex = None
return tdxapiex
def get_instrument_info():
api = TdxExHq_API(heartbeat=True)
host = "180.153.18.176" #通信达的api地址
port = 7721 #通信达的连接端口
#开始连接通信达服务器
api.connect(host, port)
insts = []
count = 500
curr_index = 0
while (True):
insts_tmp = api.get_instrument_info(curr_index, count)
if insts_tmp is None:
break
insts.extend(insts_tmp)
curr_index = curr_index + len(insts_tmp)
if len(insts_tmp) < count:
break
#查看通信达提供的市场列表
#print api.to_df(api.get_markets())
df_inst = api.to_df(insts)
#这里笔者选择的美国知名公司列表, 所以market = 41
df_inst[df_inst['market'] == 41]
#这里教程获取AAPL单一数据，如果需要全部数据可以使用列表循环下载整个数据
#笔者获取的是苹果公司最近300天交易日行情Day版
his_kline = api.get_instrument_bars(TDXParams.KLINE_TYPE_DAILY, 41, "AAPL",
0, 300)
datadf = api.to_df(his_kline)
#保存为csv格式,命名为APPL-demo/按照逗号分隔
datadf.to_csv(os.getcwd() + "/tdx_file/" + 'APPL-demo.csv',
index=False,
sep=',')
def QA_fetch_get_future_transaction_realtime(ip=None, port=None):
'期货历史成交分笔'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip= best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip= best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
with apix.connect(ip, port):
pass
def QA_fetch_get_future_transaction_realtime(code, ip=None, port=None):
'期货历史成交分笔'
ip, port = get_extensionmarket_ip(ip, port)
apix = TdxExHq_API()
global extension_market_list
extension_market_list = QA_fetch_get_extensionmarket_list(
) if extension_market_list is None else extension_market_list
code_market = extension_market_list.query('code=="{}"'.format(code))
with apix.connect(ip, port):
data = pd.DataFrame()
data = pd.concat([apix.to_df(apix.get_transaction_data(
int(code_market.market), code, (30 - i) * 1800)) for i in range(31)], axis=0)
return data.assign(datetime=pd.to_datetime(data['date'])).assign(date=lambda x: str(x)[0:10])\
.assign(code=str(code)).assign(order=range(len(data.index))).set_index('datetime', drop=False, inplace=False)
def connect(self):
"""
连接API
:return:
"""
# 创建api连接对象实例
try:
if self.api is None or self.connection_status == False:
self.strategy.writeCtaLog(u'开始连接通达信行情服务器')
TdxFutureData.api = TdxExHq_API(heartbeat=True, auto_retry=True, raise_exception=True)
# 选取最佳服务器
self.best_ip = self.select_best_ip()
self.api.connect(self.best_ip['ip'], self.best_ip['port'])
# 尝试获取市场合约统计
c = self.api.get_instrument_count()
if c < 10:
err_msg = u'该服务器IP {}/{}无响应'.format(self.best_ip['ip'], self.best_ip['port'])
self.strategy.writeCtaError(err_msg)
else:
self.strategy.writeCtaLog(u'创建tdx连接, IP: {}/{}'.format(self.best_ip['ip'], self.best_ip['port']))
# print(u'创建tdx连接, IP: {}/{}'.format(self.best_ip['ip'], self.best_ip['port']))
TdxFutureData.connection_status = True
# 更新 symbol_exchange_dict , symbol_market_dict
self.qryInstrument()
except Exception as ex:
self.strategy.writeCtaLog(u'连接服务器tdx异常:{},{}'.format(str(ex), traceback.format_exc()))
return
def connect(self):
if self.isstock:
self.api = TdxHq_API(heartbeat=self.heartbeat)
port = 7709
TDX_IP_SETS = self.TDX_IP_SETS_STOCK
else:
self.api = TdxExHq_API(heartbeat=self.heartbeat)
port = 7727
TDX_IP_SETS = self.TDX_IP_SETS
for ip in TDX_IP_SETS:
try:
if self.api.connect(ip, port):
return
except:
pass
def get_option_daily(code_list):
"""
从pytdx模块中获取期权价格。
:param code_list:
:return:
"""
api = TdxExHq_API()
df_list = []
with api.connect(ip=PYTDX_EXHQ_SERVER):
for code in code_list:
df = api.to_df(
api.get_instrument_bars(TDXParams.KLINE_TYPE_DAILY, 8, code, 0,
100))
df_list.append(df)
df_merge = pd.concat(df_list)
df_merge.to_csv('pytdx_price.csv', encoding=TA_CSV_CODING)
return df_merge
def get_option_price_by_tdx(code):
'''
通过通达信获取option的实时价格
上海期权的市场代码是：8
:param code:
:return:df
df columns:
['market', 'code', 'pre_close', 'open', 'high', 'low', 'price',
'kaicang', 'zongliang', 'xianliang', 'neipan', 'waipan', 'chicang',
'bid1', 'bid2', 'bid3', 'bid4', 'bid5', 'bid_vol1', 'bid_vol2',
'bid_vol3', 'bid_vol4', 'bid_vol5', 'ask1', 'ask2', 'ask3', 'ask4',
'ask5', 'ask_vol1', 'ask_vol2', 'ask_vol3', 'ask_vol4', 'ask_vol5']
'''
api_ex = TdxExHq_API()
data = pd.DataFrame()
if api_ex.connect('61.49.50.181', 7727):
data = api_ex.to_df(api_ex.get_instrument_quote(8, code))
return data
class ExQuotes(object):
"""扩展市场实时行情"""
def __init__(self, **kwargs):
self.client = TdxExHq_API(**kwargs)
self.bestip = ('202.108.253.130', 7709)
def bars(
self,
symbol='',
category='1',
market='0',
start='0',
offset='100'):
'''
获取实时日K线数据
:param symbol:
:param category:
:param market:
:param start:
:param offset:
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
data = self.client.get_security_bars(
int(category), int(market), str(symbol), int(start), int(offset))
return self.client.to_df(data)
def markets(self):
'''
获取实时市场列表
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
data = self.client.get_markets()
return self.client.to_df(data)
def instrument(self, start=0, offset=100):
'''
:param start:
:param offset:
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
data = self.client.get_instrument_info(int(start), int(offset))
return self.client.to_df(data)
def ping(ip, port=7709, type_='stock'):
api = TdxHq_API()
apix = TdxExHq_API()
__time1 = datetime.datetime.now()
try:
if type_ in ['stock']:
with api.connect(ip, port, time_out=0.7):
res = api.get_security_list(0, 1)
#print(len(res))
if res is not None:
if len(res) > 800:
print('GOOD RESPONSE {}'.format(ip))
return datetime.datetime.now() - __time1
else:
print('BAD RESPONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
else:
print('BAD RESPONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
elif type_ in ['future']:
with apix.connect(ip, port, time_out=0.7):
res = apix.get_instrument_count()
if res is not None:
if res > 20000:
print('GOOD RESPONSE {}'.format(ip))
return datetime.datetime.now() - __time1
else:
print('️Bad FUTUREIP REPSONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
else:
print('️Bad FUTUREIP REPSONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
except Exception as e:
if isinstance(e, TypeError):
print(e)
print('Tushare内置的pytdx版本和最新的pytdx 版本不同, 请重新安装pytdx以解决此问题')
print('pip uninstall pytdx')
print('pip install pytdx')
else:
print('BAD RESPONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
def QA_fetch_get_future_realtime(code, ip=None, port=None):
'期货实时价格'
ip, port = get_extensionmarket_ip(ip, port)
apix = TdxExHq_API()
global extension_market_list
extension_market_list = QA_fetch_get_extensionmarket_list(
) if extension_market_list is None else extension_market_list
__data = pd.DataFrame()
code_market = extension_market_list.query('code=="{}"'.format(code))
with apix.connect(ip, port):
__data = apix.to_df(apix.get_instrument_quote(
int(code_market.market), code))
__data['datetime'] = datetime.datetime.now()
# data = __data[['datetime', 'active1', 'active2', 'last_close', 'code', 'open', 'high', 'low', 'price', 'cur_vol',
# 's_vol', 'b_vol', 'vol', 'ask1', 'ask_vol1', 'bid1', 'bid_vol1', 'ask2', 'ask_vol2',
# 'bid2', 'bid_vol2', 'ask3', 'ask_vol3', 'bid3', 'bid_vol3', 'ask4',
# 'ask_vol4', 'bid4', 'bid_vol4', 'ask5', 'ask_vol5', 'bid5', 'bid_vol5']]
return __data.set_index('code', drop=False, inplace=False)
def get_fast_exhq_ip(self) -> (str, int):
fast_exhq_ip_dict = {}
exhq_api = TdxExHq_API()
for name, ip in self.exhq_ips_dict.items():
with exhq_api.connect(ip, self.exhq_port):
start_time = time.time()
instrument_count = exhq_api.get_instrument_count()
cost_time = time.time() - start_time
self.log.write_log(f"{name}({ip}), time: {cost_time:.3f}s, response: {instrument_count}")
fast_exhq_ip_dict[f"{ip}:{self.exhq_port}"] = cost_time
ip_str, port_str = min(fast_exhq_ip_dict, key=fast_exhq_ip_dict.get).split(":")
self.log.write_log(f"-"*50)
self.log.write_log(f"Select ({ip_str} : {port_str})")
self.log.write_log(f"-"*50)
return ip_str, int(port_str)
def QA_fetch_get_future_list(ip=best_ip['future']['ip'], port=best_ip['future']['port']):
'期货代码list'
apix = TdxExHq_API()
with apix.connect(ip, port):
market_info = apix.get_markets()
num = apix.get_instrument_count()
return pd.concat([apix.to_df(
apix.get_instrument_info((int(num / 500) - i) * 500, 500))
for i in range(int(num / 500) + 1)], axis=0).set_index('code', drop=False)
def QA_fetch_get_future_transaction(code, start, end, retry=2, ip=None, port=None):
'期货历史成交分笔'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
real_start, real_end = QA_util_get_real_datelist(start, end)
if real_start is None:
return None
real_id_range = []
with apix.connect(ip, port):
code_market = extension_market_info.query('code=="{}"'.format(code))
data = pd.DataFrame()
for index_ in range(trade_date_sse.index(real_start), trade_date_sse.index(real_end) + 1):
try:
data_ = __QA_fetch_get_future_transaction(
code, trade_date_sse[index_], retry,int(code_market.market), apix)
if len(data_) < 1:
return None
except Exception as e:
QA_util_log_info('Wrong in Getting {} history transaction data in day {}'.format(
code, trade_date_sse[index_]))
else:
QA_util_log_info('Successfully Getting {} history transaction data in day {}'.format(
code, trade_date_sse[index_]))
data = data.append(data_)
if len(data) > 0:
return data.assign(datetime=data['datetime'].apply(lambda x: str(x)[0:19]))
else:
return None
class Datacent:
def __init__(self):
self.cf = config
self.qihuo_api = TdxExHq_API()
self.cflen = 0
def qihuo_connectSer(self):
self.qihuo_api.connect('218.80.248.229', 7721)
qihuoret = self.qihuo_api.connect('218.80.248.229', 7721)
if qihuoret == False:
print("期货没有连接。。。")
return qihuoret
else:
print("已连接期货数据服务")
qihuoret = True
return qihuoret
def qihuoK(
self,
cflen,
):
data = self.qihuo_api.get_instrument_bars(
self.cf.category, int(self.cf.cfqihuo[cflen]["marketid"]),
self.cf.cfqihuo[cflen]['code'], 0,
self.cf.categorycount) #7: 扩展行情查询k线数据
df = pd.DataFrame(
data,
columns=[
'datetime',
'stockname',
'open',
'high',
'low',
'close',
'code',
],
)
df['stockname'] = self.cf.cfqihuo[cflen]["stockname"]
df['code'] = self.cf.cfqihuo[cflen]["code"]
return df
def tdx_ping_future(ip, port=7709, type_='stock'):
apix = TdxExHq_API()
__time1 = dt.datetime.now()
try:
with apix.connect(ip, port, time_out=0.7):
res = apix.get_instrument_count()
if res is not None:
if res > 40000:
return dt.datetime.now() - __time1
else:
#print('️Bad FUTUREIP REPSONSE {}'.format(ip))
return dt.timedelta(9, 9, 0)
else:
#print('️Bad FUTUREIP REPSONSE {}'.format(ip))
return dt.timedelta(9, 9, 0)
#
except Exception as e:
pass
#print('BAD RESPONSE {}'.format(ip))
return dt.timedelta(9, 9, 0)
def connect(self, is_reconnect=False):
"""
连接API
:return:
"""
# 创建api连接对象实例
try:
if self.api is None or not self.connection_status:
self.write_log(u'开始连接通达信行情服务器')
self.api = TdxExHq_API(heartbeat=True,
auto_retry=True,
raise_exception=True)
# 选取最佳服务器
if is_reconnect or len(self.best_ip) == 0:
self.best_ip = get_cache_ip()
if len(self.best_ip) == 0:
self.best_ip = self.select_best_ip()
self.api.connect(self.best_ip['ip'], self.best_ip['port'])
# 尝试获取市场合约统计
c = self.api.get_instrument_count()
if c < 10:
err_msg = u'该服务器IP {}/{}无响应'.format(
self.best_ip['ip'], self.best_ip['port'])
self.write_error(err_msg)
else:
self.write_log(u'创建tdx连接, IP: {}/{}'.format(
self.best_ip['ip'], self.best_ip['port']))
# print(u'创建tdx连接, IP: {}/{}'.format(self.best_ip['ip'], self.best_ip['port']))
self.connection_status = True
# if not is_reconnect:
# 更新 symbol_exchange_dict , symbol_market_dict
# self.qryInstrument()
except Exception as ex:
self.write_log(u'连接服务器tdx异常:{},{}'.format(str(ex),
traceback.format_exc()))
return
def __exhq_ping(self, ip, port):
api = TdxExHq_API()
with api.connect(ip, port, time_out=0.7):
assert api.get_instrument_count() > 20000
api.disconnect()
return True
return False
def ping(ip, port=7709, type_='stock'):
api = TdxHq_API()
apix = TdxExHq_API()
__time1 = datetime.datetime.now()
try:
if type_ in ['stock']:
with api.connect(ip, port, time_out=0.7):
if len(api.get_security_list(0, 1)) > 800:
return datetime.datetime.now() - __time1
else:
print('BAD RESPONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
elif type_ in ['future']:
with apix.connect(ip, port, time_out=0.7):
if apix.get_instrument_count() > 10000:
return datetime.datetime.now() - __time1
else:
print('️Bad FUTUREIP REPSONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
except:
print('BAD RESPONSE {}'.format(ip))
return datetime.timedelta(9, 9, 0)
def QA_fetch_get_future_transaction_realtime(code,ip=None, port=None):
'期货历史成交分笔'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
global extension_market_info
extension_market_info = QA_fetch_get_future_list(
) if extension_market_info is None else extension_market_info
code_market = extension_market_info.query('code=="{}"'.format(code))
with apix.connect(ip, port):
data = pd.DataFrame()
data = pd.concat([apix.to_df(apix.get_transaction_data(
int(code_market.market), code, (30 - i) * 1800)) for i in range(31)], axis=0)
return data.assign(datetime=pd.to_datetime(data['date'])).assign(date=lambda x: str(x)[0:10])\
.assign(code=str(code)).assign(order=range(len(data.index))).set_index('datetime', drop=False, inplace=False)
def QA_fetch_get_future_list(ip=None, port=None):
'期货代码list'
global best_ip
if ip is None and port is None and best_ip['future']['ip'] is None and best_ip['future']['port'] is None:
best_ip = select_best_ip()
ip = best_ip['future']['ip']
port = best_ip['future']['port']
elif ip is None and port is None and best_ip['future']['ip'] is not None and best_ip['future']['port'] is not None:
ip = best_ip['future']['ip']
port = best_ip['future']['port']
else:
pass
apix = TdxExHq_API()
with apix.connect(ip, port):
market_info = apix.get_markets()
num = apix.get_instrument_count()
return pd.concat([apix.to_df(
apix.get_instrument_info((int(num / 500) - i) * 500, 500))
for i in range(int(num / 500) + 1)], axis=0).set_index('code', drop=False)
result = []
for i in range(count):
(category, market, unused_bytes, code_raw, name_raw, desc_raw) = \
struct.unpack("<BB3s9s17s9s", body_buf[pos: pos+40])
code = code_raw.decode("gbk", 'ignore')
name = name_raw.decode("gbk", 'ignore')
desc = desc_raw.decode("gbk", 'ignore')
one = OrderedDict(
[
("category", category),
("market", market),
("code", code.rstrip("\x00")),
("name", name.rstrip("\x00")),
("desc", desc.rstrip("\x00")),
]
)
pos += 64
result.append(one)
return result
if __name__ == '__main__':
from pytdx.exhq import TdxExHq_API
api = TdxExHq_API()
api.connect('121.14.110.210', 7727)
ret = api.get_instrument_info(200, 100)
print(ret)
('bid5', b5),
('bid_vol1', bv1),
('bid_vol2', bv2),
('bid_vol3', bv3),
('bid_vol4', bv4),
('bid_vol5', bv5),
('ask1', a1),
('ask2', a2),
('ask3', a3),
('ask4', a4),
('ask5', a5),
('ask_vol1', av1),
('ask_vol2', av2),
('ask_vol3', av3),
('ask_vol4', av4),
('ask_vol5', av5),
]
)
]
if __name__ == '__main__':
from pytdx.exhq import TdxExHq_API
api = TdxExHq_API()
with api.connect('61.152.107.141', 7727):
print(api.to_df(api.get_instrument_quote(47, "IF1709")))
else: #512
direction = 0
nature_name = ''
result.append(OrderedDict([
("date", date),
("hour", hour),
("minute", minute),
("second", second),
("price", price),
("volume", volume),
("zengcang", zengcang),
("nature", nature),
("nature_mark", nature // 10000),
("nature_value", nature % 10000),
("nature_name", nature_name),
("direction", direction),
]))
return result
if __name__ == "__main__":
from pytdx.exhq import TdxExHq_API
api = TdxExHq_API()
with api.connect('121.14.110.210', 7727):
print(api.to_df(api.get_transaction_data(47, 'IFL9')))
# print(api.to_df(api.get_transaction_data(31, "00020")))
])
klines.append(kline)
return klines
#00000000 01 01 08 6A 01 01 16 00 16 00 FF 23 2F 49 46 4C ...j.... ...#/IFL
#00000010 30 00 F0 F4 94 13 07 00 01 00 00 00 00 00 F0 00 0....... ........
#00000000: 01 01 08 6A 01 01 16 00 16 00 FF 23 4A 4E 56 44 ...j.......#JNVD
#00000010: 41 00 C0 EC A3 13 07 00 01 00 00 00 00 00 C0 03 A...............
#00000000 01 01 08 6A 01 01 16 00 16 00 FF 23 2F 49 46 31 ...j.... ...#/IF1
#00000010 37 30 39 00 94 13 07 00 01 00 00 00 00 00 F0 00 709..... ........
if __name__ == '__main__':
import pprint
from pytdx.exhq import TdxExHq_API
api = TdxExHq_API()
with api.connect('61.152.107.141', 7727):
x = api.to_df(api.get_history_instrument_bars_range(74, "BABA", 20170613,20170620))
pprint.pprint(x.tail())
("low", low),
("close", close),
("position", position),
("trade", trade),
("price", price),
("year", year),
("month", month),
("day", day),
("hour", hour),
("minute", minute),
("datetime", "%d-%02d-%02d %02d:%02d" % (year, month, day, hour, minute)),
("amount", amount),
])
klines.append(kline)
return klines
if __name__ == '__main__':
from pytdx.exhq import TdxExHq_API
from pytdx.params import TDXParams
api = TdxExHq_API()
# cmd = GetInstrumentBars(api)
# cmd.setParams(4, 7, "10000843", 0, 10)
# print(cmd.send_pkg)
with api.connect('61.152.107.141', 7727):
print(api.to_df(api.get_instrument_bars(TDXParams.KLINE_TYPE_EXHQ_1MIN, 74, 'BABA')).tail())
print(api.to_df(api.get_instrument_bars(TDXParams.KLINE_TYPE_DAILY, 31, '00001')).tail())
direction = 0
nature_name = ''
result.append(OrderedDict([
("date", date),
("hour", hour),
("minute", minute),
("price", price),
("volume", volume),
("zengcang", zengcang),
("natrue_name", nature_name),
("nature_name", nature_name), #修正了nature_name的拼写错误(natrue), 为了保持兼容性，原有的natrue_name还会保留一段时间
("direction", direction),
("nature", nature),
]))
return result
if __name__ == '__main__':
from pytdx.exhq import TdxExHq_API
api = TdxExHq_API()
with api.connect('121.14.110.210', 7727):
# print(api.to_df(api.get_history_transaction_data(4, 'SR61099D', 20171025))[["date","price","volume",'zengcang','nature','t1','t2']])
print(api.to_df(api.get_history_transaction_data(47, 'IFL0', 20170811)))
#print(api.to_df(api.get_history_transaction_data(31, "01918", 20171026))[["date","price","volume",'zengcang','nature']])
#api.to_df(api.get_history_transaction_data(47, 'IFL0', 20170810)).to_excel('//Users//wy//data//iflo.xlsx')
