def QA_fetch_stock_min_adv(code,
start,
end,
type_='1min',
if_drop_index=False,
collections=QA_Setting.client.quantaxis.stock_min):
'获取股票分钟线'
if type_ in ['1min', '1m']:
type_ = '1min'
elif type_ in ['5min', '5m']:
type_ = '5min'
elif type_ in ['15min', '15m']:
type_ = '15min'
elif type_ in ['30min', '30m']:
type_ = '30min'
elif type_ in ['60min', '60m']:
type_ = '60min'
__data = []
if isinstance(code, str):
for item in collections.find({
'code': str(code),
"time_stamp": {
"$gte": QA_util_time_stamp(start),
"$lte": QA_util_time_stamp(end)
},
'type': type_
}):
__data.append([
str(item['code']),
float(item['open']),
float(item['high']),
float(item['low']),
float(item['close']),
float(item['vol']), item['datetime'], item['time_stamp'],
item['date']
])
__data = DataFrame(__data,
columns=[
'code', 'open', 'high', 'low', 'close',
'volume', 'datetime', 'time_stamp', 'date'
])
__data['datetime'] = pd.to_datetime(__data['datetime'])
return QA_DataStruct_Stock_min(
__data.query('volume>1').set_index(['datetime', 'code'],
drop=if_drop_index))
elif isinstance(code, list):
'新增codelist的代码'
return QA_DataStruct_Stock_min(
pd.concat([
QA_fetch_stock_min_adv(code_, start, end, type_,
if_drop_index).data for code_ in code
]).set_index(['datetime', 'code'], drop=if_drop_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 to_qfq(self, res):
u = res.data.reset_index()
u = u.assign(date=u.datetime.apply(lambda x: x.date()))
u = u.set_index(['date', 'code'], drop=False)
codelist = u.index.levels[1].unique().tolist()
start = u.index.levels[0][0]
end = u.index.levels[0][-1]
adjx = self.get_stock_adj(codelist, start, end)
if adjx is None:
data = u.set_index(['datetime', 'code'])
else:
adjx = adjx.reset_index()
adjx = adjx.assign(code=adjx.order_book_id).set_index(
['date', 'code']).adj
data = u.join(adjx).set_index(['datetime', 'code']).fillna(1)
for col in ['open', 'high', 'low', 'close']:
data[col] = data[col] * data['adj']
try:
data['high_limit'] = data['high_limit'] * data['adj']
data['low_limit'] = data['high_limit'] * data['adj']
except:
pass
return QA_DataStruct_Stock_min(data.sort_index(), if_fq='qfq')
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)
if isinstance(code, str):
for item in collections.find({
'code': str(code), "time_stamp": {
"$gte": QA_util_time_stamp(start),
"$lte": QA_util_time_stamp(end)
}, 'type': frequence
}):
__data.append([str(item['code']), float(item['open']), float(item['high']), float(
item['low']), float(item['close']), float(item['vol']), item['datetime'], item['time_stamp'], item['date']])
__data = DataFrame(__data, columns=[
'code', 'open', 'high', 'low', 'close', 'volume', 'datetime', 'time_stamp', 'date'])
__data['datetime'] = pd.to_datetime(__data['datetime'])
return QA_DataStruct_Stock_min(__data.query('volume>1').set_index(['datetime', 'code'], drop=if_drop_index))
elif isinstance(code, list):
'新增codelist的代码'
return QA_DataStruct_Stock_min(pd.concat([QA_fetch_stock_min_adv(code_, start, end, frequence, if_drop_index).data for code_ in code]).set_index(['datetime', 'code'], drop=if_drop_index).sort_index())
def QA_fetch_stocklist_min_adv(code,
start,
end=None,
frequence='1min',
if_drop_index=False,
collections=DATABASE.stock_min):
return QA_DataStruct_Stock_min(
pd.concat(QA_fetch_stocklist_min(
code, [start, end], frequence)).query('volume>1').set_index(
['datetime', 'code'], drop=if_drop_index).sort_index())
def QA_fetch_stocklist_min_adv(
code,
start,
end,
type_='1min',
if_drop_index=False,
collections=QA_Setting.client.quantaxis.stock_min):
return QA_DataStruct_Stock_min(
pd.concat(QA_fetch_stocklist_min(code, [start, end],
type_)).query('volume>1').set_index(
['datetime', 'code'],
drop=if_drop_index))
def test_data_struct_min_stock(self):
code = '000001'
days = 10 * 1.2
start = datetime.datetime.now() - datetime.timedelta(days)
end = datetime.datetime.now() - datetime.timedelta(0)
df = qm.get(code, start, end, frequence='1min')
if df is not None and len(df.index.names) == 1:
df = df.set_index(['date', 'code'], drop=True)
ds = qd(frequence=8).dataStruct(df)
ds2 = QA_DataStruct_Stock_min(df)
self.assertIsInstance(ds, QA_DataStruct_Stock_min)
self.assertIsInstance(ds2, QA_DataStruct_Stock_min)
def get_stock_min(self, codelist, start, end):
codelist = promise_list(codelist)
if 'XS' not in codelist[0]:
codelist = pd.Series(codelist).apply(lambda x: x + '.XSHE' if x[
0] != '6' else x + '.XSHG').tolist()
columns_raw = [
'datetime', 'order_book_id', 'open', 'high', 'low', 'close',
'volume', 'total_turnover'
]
res = self.client.query_dataframe(
"SELECT * FROM quantaxis.stock_cn_1min WHERE ((`datetime` >= '{}')) \
AND (`datetime` <= '{}') AND (`order_book_id` IN ({}))"
.format(start, end, "'{}'".format(
"','".join(codelist)))).loc[:, columns_raw].drop_duplicates(
['datetime', 'order_book_id'])
return QA_DataStruct_Stock_min(
res.assign(
datetime=pd.to_datetime(res.datetime),
code=res.order_book_id,
amount=res.total_turnover,
type='1min',
).set_index(['datetime', 'code']).sort_index())
