def QA_fetch_stock_min_adv(
code,
start, end=None,
frequence='1min',
if_drop_index=True,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.stock_min):
'''
'获取股票分钟线'
:param code: 字符串str eg 600085
:param start: 字符串str 开始日期 eg 2011-01-01
:param end: 字符串str 结束日期 eg 2011-05-01
:param frequence: 字符串str 分钟线的类型 支持 1min 1m 5min 5m 15min 15m 30min 30m 60min 60m 类型
:param if_drop_index: Ture False ， dataframe drop index or not
:param collections: mongodb 数据库
:return: QA_DataStruct_Stock_min 类型
'''
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15min', '15m']:
frequence = '15min'
elif frequence in ['30min', '30m']:
frequence = '30min'
elif frequence in ['60min', '60m']:
frequence = '60min'
else:
print("QA Error QA_fetch_stock_min_adv parameter frequence=%s is none of 1min 1m 5min 5m 15min 15m 30min 30m 60min 60m" % frequence)
return None
# __data = [] 未使用
end = start if end is None else end
if len(start) == 10:
start = '{} 09:30:00'.format(start)
if len(end) == 10:
end = '{} 15:00:00'.format(end)
if start == end:
# 🛠 todo 如果相等，根据 frequence 获取开始时间的 时间段 QA_fetch_stock_min， 不支持start end是相等的
print("QA Error QA_fetch_stock_min_adv parameter code=%s , start=%s, end=%s is equal, should have time span! " % (
code, start, end))
return None
# 🛠 todo 报告错误 如果开始时间 在 结束时间之后
res = QA_fetch_stock_min(
code, start, end, format='pd', frequence=frequence)
if res is None:
print("QA Error QA_fetch_stock_min_adv parameter code=%s , start=%s, end=%s frequence=%s call QA_fetch_stock_min return None" % (
code, start, end, frequence))
return None
else:
res_set_index = res.set_index(['datetime', 'code'], drop=if_drop_index)
# if res_set_index is None:
# print("QA Error QA_fetch_stock_min_adv set index 'datetime, code' return None")
# return None
return QA_DataStruct_Stock_min(res_set_index)
def QA_fetch_stock_min_adv(
code,
start, end=None,
frequence='1min',
if_drop_index=True,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.stock_min):
'''
'获取股票分钟线'
:param code: 字符串str eg 600085
:param start: 字符串str 开始日期 eg 2011-01-01
:param end: 字符串str 结束日期 eg 2011-05-01
:param frequence: 字符串str 分钟线的类型 支持 1min 1m 5min 5m 15min 15m 30min 30m 60min 60m 类型
:param if_drop_index: Ture False ， dataframe drop index or not
:param collections: mongodb 数据库
:return: QA_DataStruct_Stock_min 类型
'''
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15min', '15m']:
frequence = '15min'
elif frequence in ['30min', '30m']:
frequence = '30min'
elif frequence in ['60min', '60m']:
frequence = '60min'
else:
print("QA Error QA_fetch_stock_min_adv parameter frequence=%s is none of 1min 1m 5min 5m 15min 15m 30min 30m 60min 60m" % frequence)
return None
# __data = [] 未使用
end = start if end is None else end
if len(start) == 10:
start = '{} 09:30:00'.format(start)
if len(end) == 10:
end = '{} 15:00:00'.format(end)
if start == end:
# 🛠 todo 如果相等，根据 frequence 获取开始时间的 时间段 QA_fetch_stock_min， 不支持start end是相等的
print("QA Error QA_fetch_stock_min_adv parameter code=%s , start=%s, end=%s is equal, should have time span! " % (
code, start, end))
return None
# 🛠 todo 报告错误 如果开始时间 在 结束时间之后
res = QA_fetch_stock_min(
code, start, end, format='pd', frequence=frequence)
if res is None:
print("QA Error QA_fetch_stock_min_adv parameter code=%s , start=%s, end=%s frequence=%s call QA_fetch_stock_min return None" % (
code, start, end, frequence))
return None
else:
res_set_index = res.set_index(['datetime', 'code'], drop=if_drop_index)
# if res_set_index is None:
# print("QA Error QA_fetch_stock_min_adv set index 'datetime, code' return None")
# return None
return QA_DataStruct_Stock_min(res_set_index)
def QA_fetch_stock_min_adv(code,
start,
end=None,
frequence='1min',
if_drop_index=False,
collections=DATABASE.stock_min):
'获取股票分钟线'
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15min', '15m']:
frequence = '15min'
elif frequence in ['30min', '30m']:
frequence = '30min'
elif frequence in ['60min', '60m']:
frequence = '60min'
__data = []
end = start if end is None else end
if len(start) == 10:
start = '{} 09:30:00'.format(start)
if len(end) == 10:
end = '{} 15:00:00'.format(end)
return QA_DataStruct_Stock_min(
QA_fetch_stock_min(code, start, end, format='pd',
frequence=frequence).set_index(['datetime', 'code'],
drop=if_drop_index))
def get(self):
"""
采用了get_arguents来获取参数
默认参数: code-->000001 start-->2017-01-01 09:00:00 end-->now
"""
code = self.get_argument('code', default='000001')
start = self.get_argument('start', default='2017-01-01 09:00:00')
end = self.get_argument('end', default=str(datetime.datetime.now()))
frequence = self.get_argument('frequence', default='1min')
if_fq = self.get_argument('if_fq', default=False)
if if_fq:
data = QA_util_to_json_from_pandas(
QA_fetch_stock_min_adv(code, start, end,
frequence).to_qfq().data)
self.write({'result': data})
else:
data = QA_util_to_json_from_pandas(
QA_fetch_stock_min(code,
start,
end,
format='pd',
frequence=frequence))
self.write({'result': data})
self.write({'result': data})
def __get_stock_min_data(self, __bid):
__data = QA_util_to_json_from_pandas(QA_fetch_stock_min(str(
__bid.code)[0:6], str(__bid.datetime)[0:19], str(__bid.datetime)[0:10], 'pd'))
if len(__data) == 0:
pass
else:
__data = __data[0]
return __data
def test_getMin_diffQA(self):
code = '000001'
days = 20 * 1.2
start = str(datetime.datetime.now() - datetime.timedelta(days))
end = str(datetime.datetime.now() - datetime.timedelta(0))
df = qm.get(code, start, end, frequence='1min')
df2 = QA_fetch_stock_min(code, start, end=end, format='pd', frequence='1min')
# todo df的长度比df2长。未找出原因
data1, data2 = df, df2
self.assertTrue(len(data1) == len(data2), "和QA返回的分钟线数据长度不一致:{}:{}".format(len(data1), len(data2)))
if len(data1) > len(data2):
print("array1f的长度比array2长")
data1 = data1[-len(data2):]
elif len(data1) < len(data2):
print("array2的长度比array1长")
data2 = data2[-len(data1):]
obo = self.differOneByOne(data1, data2)
self.assertTrue(data1.equals(data2),
"和QA返回的分钟线数据不一致:{}".format(obo))
def test_get_min_diffQA(self):
code = '000001'
days = 10 * 1.2
start = datetime.datetime.now() - datetime.timedelta(days)
end = datetime.datetime.now() - datetime.timedelta(0)
array1 = qm.get(code, start, end, frequence='1min')
array2 = QA_fetch_stock_min(code, start, end, frequence='1min')
# todo df的长度比df2长。未找出原因
if len(array1) > len(array2):
print("array1f的长度比array2长")
array1 = array1[-len(array2):]
elif len(array1) < len(array2):
print("array2的长度比array1长")
array2 = array2[-len(array1):]
self.assertTrue(
len(array1) == len(array2),
"和QA返回的分钟线数据长度不一致:{}:{}".format(len(array1), len(array2)))
# todo 连续获取分钟数据时，不定时返回结果不想等。报错
self.assertTrue(
np.array_equal(array1, array2), "和QA返回的分钟线数据不一致:{}".format(
np.setdiff1d(array1, array2, assume_unique=True)))
def __get_data(__bid):
__data = QA_util_to_json_from_pandas(
QA_fetch_stock_min(
str(__bid['code'])[0:6], __bid['time'], __bid['time'], 'pd'))
# 我们只需要找到这个时间点下一条数据就行
return __data