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 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 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)
class ExtQuotes(object):
"""扩展市场实时行情"""
def __init__(self, **kwargs):
self.client = TdxExHq_API(**kwargs)
# self.bestip = os.environ.setdefault("MOOTDX_SERVER", '61.152.107.141:7727')
# self.bestip = kwargs.get("bestip", '202.108.253.131:7709')
# self.bestip = self.bestip.split(':')
self.bestip = ('202.108.253.131', 7709)
# self.bestip[1] = int(self.bestip[1])
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)
return None
def quote5(self, market=47, symbol="IF1709"):
'''
查询五档行情
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
data = self.client.get_instrument_quote(market, symbol)
return self.client.to_df(data)
def minute(self, market=47, symbol="IF1709"):
'''
查询五档行情
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
data = self.client.get_minute_time_data(market, symbol)
return self.client.to_df(data)
def instrument(self, start=0, offset=100):
'''
查询代码列表
:param start:
:param offset:
:return: pd.dataFrame or None
'''
with self.client.connect(*self.bestip):
# nums = self.client.get_instrument_count()
data = self.client.get_instrument_info(int(start), int(offset))
return self.client.to_df(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 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 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 __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 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=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 QA_fetch_get_future_list(ip=best_ip['future'], port=7727):
'期货代码list'
apix = TdxExHq_API()
with apix.connect(ip, port):
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_extensionmarket_list(ip=None, port=None):
'期货代码list'
ip, port = get_extensionmarket_ip(ip, port)
apix = TdxExHq_API()
with apix.connect(ip, port):
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)
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
class ExEngine:
def __init__(self, *args, **kwargs):
self.api = TdxExHq_API(args, kwargs)
def connect(self):
self.api.connect('61.152.107.141', 7727)
return self
def __enter__(self):
return self
def exit(self):
self.api.disconnect()
def __exit__(self, exc_type, exc_val, exc_tb):
self.api.disconnect()
@lazyval
def markets(self):
return self.api.to_df(self.api.get_markets())
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 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 __exhq_list(self):
self.__paralle_exhq_ping()
api = TdxExHq_API()
ip, port = self.__ex.get()
with api.connect(ip, port):
df = list()
nums = api.get_instrument_count()
for i in range((nums // 500 + (1 if nums % 500 > 0 else 0)) + 1):
df.append(api.to_df(api.get_instrument_info(i * 500, 500)))
self.__ex.put((ip, port))
df = pandas.concat(df, sort=False).set_index('code')
return df
return None
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 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 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_hk_quote_by_tdx(code_list):
"""
获取香港主板市场行情数据
需要使用拓展行情接口
通达信接口的港股行情数据比较简陋，只有当前价格，缺乏bid，ask以及对应的量能
:param code_list:
:return:
"""
api_ex = TdxExHq_API()
result = []
if api_ex.connect('140.143.179.226', 7727):
for code in code_list:
data = api_ex.get_instrument_quote(31, code)
result.append(
[data[0]["code"], data[0]["price"], data[0]["xianliang"]])
api_ex.disconnect()
df = pd.DataFrame(data=result, columns=["code", "price", "xianliang"])
return df
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
def __exhq_bars(self, code, offset, frequency=9):
assert self.__ex.qsize() > 0
api = TdxExHq_API()
ip, port = self.__ex.get()
with api.connect(ip, port):
df = list()
for _code in code:
for _start, _count in offset:
df.append(
api.to_df(
api.get_instrument_bars(
frequency,
self.__exhq_list().xs(_code).market, _code,
_start, _count)).assign(code=_code))
api.disconnect()
self.__ex.put((ip, port))
if len(df) < 1:
return None
return pandas.concat(df, sort=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 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 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)
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
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 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 ping(self, ip, port=7709):
"""
ping行情服务器
:param ip:
:param port:
:param type_:
:return:
"""
apix = TdxExHq_API()
__time1 = datetime.now()
try:
with apix.connect(ip, port):
if apix.get_instrument_count() > 10000:
_timestamp = datetime.now() - __time1
self.write_log("服务器{ip}:{port},耗时:{_timestamp}")
return _timestamp
else:
self.write_log("该服务器IP {ip}无响应")
return timedelta(9, 9, 0)
except Exception:
self.write_error("tdx ping服务器，异常的响应{ip}")
return 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)
])
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())
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)
