def QA_fetch_stock_transaction_adv(code,
start,
end=None,
if_drop_index=True,
collections=DATABASE.stock_transaction):
'''
:param code:
:param start:
:param end:
:param if_drop_index:
:param collections:
:return:
'''
end = start if end is None else end
data = DataFrame([
item for item in collections.find({
'code': str(code),
"date": {
"$gte": start,
"$lte": end
}
})
])
data['datetime'] = pd.to_datetime(data['datetime'])
return QA_DataStruct_Stock_transaction(
data.set_index('datetime', drop=if_drop_index))
def QA_fetch_stock_transaction_adv(
code,
start,
end=None,
frequence='tick',
if_drop_index=True,
collections=DATABASE.stock_transaction
):
'''
:param code:
:param start:
:param end:
:param if_drop_index:
:param collections:
:return:
'''
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_transaction_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_transaction(
code,
start,
end,
format='pd',
frequence=frequence,
collections= collections
)
if res is None:
print(
"QA Error QA_fetch_stock_transaction_adv parameter code=%s , start=%s, end=%s frequence=%s call QA_fetch_stock_transaction 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_transaction(res_set_index)
def QA_fetch_stock_transaction_adv(
code,
start, end,
if_drop_index=False,
collections=QA_Setting.client.quantaxis.stock_transaction):
data = DataFrame([item for item in collections.find({
'code': str(code), "date": {
"$gte": start,
"$lte": end
}})]).drop('_id', axis=1, inplace=False)
data['datetime'] = pd.to_datetime(data['date'] + ' ' + data['time'])
return QA_DataStruct_Stock_transaction(data.set_index('datetime', drop=if_drop_index))