def QA_backtest_get_block(self, block_list):
block_ = QA_fetch_stock_block_adv()
_data = []
try:
for item in block_list:
_data.extend(block_.get_block(item).code)
return np.unique(_data).tolist()
except Exception as e:
raise e
def get_day_once():
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
x = QA_Tdx_Executor()
return x.get_security_bar_concurrent(code, 'day', 1)
def get_bar(timeout=1, sleep=1):
sleep = int(sleep)
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
print(len(code))
x = QA_Tdx_Executor(timeout=float(timeout))
print(x._queue.qsize())
print(x.get_available())
while True:
_time = datetime.datetime.now()
if QA_util_if_tradetime(_time): # 如果在交易时间
data = x.get_security_bar_concurrent(code, 'day', 1)
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(sleep)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
print('Program Last Time {}'.format(
(datetime.datetime.now() - _time1).total_seconds()))
return data
else:
print('Not Trading time {}'.format(_time))
time.sleep(sleep)
def run(self):
sleep = int(self.sleep_time)
_time1 = datetime.datetime.now()
database = DATABASE.get_collection('realtime_{}'.format(
datetime.date.today()))
database.create_index([('code', QA_util_sql_mongo_sort_ASCENDING)])
database.create_index([('datetime', QA_util_sql_mongo_sort_ASCENDING)])
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
while True:
_time = datetime.datetime.now()
if QA_util_if_tradetime(_time): # 如果在交易时间
data = x.get_realtime_concurrent(code)
data[0]['datetime'] = data[1]
x.save_mongo(data[0])
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(sleep)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
print('Program Last Time {}'.format(
(datetime.datetime.now() - _time1).total_seconds()))
else:
print('Not Trading time {}'.format(_time))
time.sleep(sleep)
def QA_etl_stock_block(ui_log= None):
QA_util_log_info(
'##JOB Now ETL STOCK Block ==== {}'.format(str(datetime.date.today())), ui_log)
data = QA_fetch_stock_block_adv().data.reset_index()
QA_util_sql_store_mysql(data, "stock_block",if_exists='replace')
QA_util_log_info(
'##JOB ETL STOCK Block HAS BEEN SAVED ==== {}'.format(str(datetime.date.today())), ui_log)
def bat(timeout):
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
print(len(code))
x = QA_Tdx_Executor(timeout=timeout)
print(x._queue.qsize())
print(x.get_available())
database = DATABASE.get_collection('realtime_{}'.format(
datetime.date.today()))
print(database)
database.create_index([('code', QA_util_sql_mongo_sort_ASCENDING),
('datetime', QA_util_sql_mongo_sort_ASCENDING)])
for i in range(100000):
_time = datetime.datetime.now()
if QA_util_if_tradetime(_time): # 如果在交易时间
data = x.get_realtime_concurrent(code)
data[0]['datetime'] = data[1]
x.save_mongo(data[0])
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(1)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
print('Program Last Time {}'.format(
(datetime.datetime.now() - _time1).total_seconds()))
else:
print('Not Trading time {}'.format(_time))
time.sleep(1)
def __init__(self, block=None, block_name=None, lens=90, *args, **kwargs):
try:
self.block_code = block.code
except:
self.block_code = block
if block_name is not None:
self.block_code = QA_fetch_stock_block_adv().get_block(block_name).code
self.lens = lens
def bat(timeout=0.2, sleep=1, thread=2, size=80):
sleep = int(sleep)
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
print(len(code))
x = QA_Tdx_Executor(timeout=float(timeout),
thread_num=int(thread),
max_size=int(size))
print(x._queue.qsize())
print(x.get_available())
database = DATABASE.get_collection('realtime_{}'.format(
datetime.date.today()))
print(database)
# mongodb在排序时，复合索引并不能像关系型数据库一样提升效率，反而会降低排序性能
# 在测试的过程，发现datetime倒序索引在倒序查询时性能更高，但写入性能较低
# 此表属于写多读少，所以索引继续采用正序
database.create_index([('code', QA_util_sql_mongo_sort_ASCENDING)])
database.create_index([('datetime', QA_util_sql_mongo_sort_ASCENDING)])
while True:
_time = datetime.datetime.now()
if QA_util_if_tradetime(_time): # 如果在交易时间
data = x.get_realtime_concurrent(code)
data[0]['datetime'] = data[1]
x.save_mongo(data[0])
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(sleep)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
print('Program Last Time {}'.format(
(datetime.datetime.now() - _time1).total_seconds()))
else:
print('Not Trading time {}'.format(_time))
time.sleep(sleep)
def bat():
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
print(len(code))
x = QA_Tdx_Executor()
print(x._queue.qsize())
print(x.get_available())
#data = x.get_security_bars(code[0], '15min', 20)
# print(data)
# for i in range(5):
# print(x.get_realtime_concurrent(code))
for i in range(100000):
_time = datetime.datetime.now()
if QA_util_if_tradetime(_time): # 如果在交易时间
#data = x.get_realtime(code)
data = x.get_realtime_concurrent(code)
data[0]['datetime'] = data[1]
x.save_mongo(data[0])
# print(code[0])
#data = x.get_security_bars(code, '15min', 20)
# if data is not None:
print(len(data[0]))
# print(data)
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(1)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
print('Program Last Time {}'.format(
(datetime.datetime.now() - _time1).total_seconds()))
else:
print('Not Trading time {}'.format(_time))
time.sleep(1)
code = str(code)
if code[0] in ['5', '6', '9'] or code[:3] in [
"009", "126", "110", "201", "202", "203", "204"
]:
return 1
return 0
def save_mongo(self):
pass
if __name__ == '__main__':
import time
_time1 = datetime.datetime.now()
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_block_adv
code = QA_fetch_stock_block_adv().code
x = QA_Tdx_Executor()
print(x._queue.qsize())
print(x.get_available())
for i in range(100000):
_time = datetime.datetime.now()
#data = x.get_realtime(code)
data = x.get_realtime_concurrent(code)
# if data is not None:
# print(len(data))
# print(data[0])
print('Time {}'.format(
(datetime.datetime.now() - _time).total_seconds()))
time.sleep(1)
print('Connection Pool NOW LEFT {} Available IP'.format(
x._queue.qsize()))
def QA_etl_stock_block():
data = QA_fetch_stock_block_adv(list(QA_fetch_stock_list_adv()['code'])).data.reset_index()
QA_util_sql_store_mysql(data, "stock_block",if_exists='replace')
def block(self):
return QA_fetch_stock_block_adv(code=self.code_list)
def get_block_code(code, type='zjhhy') -> (str):
"""按照证监会行业分类，获取指定股票的同分类所有股票代码"""
df = QA_fetch_stock_block_adv()
k = df.get_code(code).data
name = k[k['type'] == type].reset_index()['blockname'].values[0]
return [c for c in df.get_block(name).code if c != code]
# coding:utf-8
# 输入一个stock_list/stock_block
# 生成相关因子
from QUANTAXIS.QAFetch.QAQuery_Advance import QA_fetch_stock_day_adv, QA_fetch_stock_min_adv, QA_fetch_stock_block_adv
from QUANTAXIS.QAAnalysis.QAAnalysis_dataframe import QA_Analysis_stock
class QA_Analysis_block():
def __init__(self, block, *args, **kwargs):
self.block_code = block
def market_data(self, start, end, _type='day'):
return QA_fetch_stock_day_adv(self.block_code, start, end)
def calc_pcg(self, market_data):
pass
ana = QA_Analysis_block(
QA_fetch_stock_block_adv().get_block('昨日涨停').code.tolist())
print(ana.market_data('2017-10-01', '2017-10-30'))