def GQ_fetch_stock_realtime_adv(
code=None,
num=1,
collections=client.get_collection('realtime_{}'.format(date.today())),
verbose=True,
suffix=False,
):
'''
返回当日的上下五档, code可以是股票可以是list, num是每个股票获取的数量
:param code:
:param num:
:param collections: realtime_XXXX-XX-XX 每天实时时间
:param suffix: 股票代码是否带沪深交易所后缀
:return: DataFrame
'''
if code is not None:
# code 必须转换成list 去查询数据库，因为五档数据用一个collection保存了股票，指数及基金，所以强制必须使用标准化代码
if isinstance(code, str):
code = [normalize_code(code)]
elif isinstance(code, list):
code = [normalize_code(symbol) for symbol in code]
pass
else:
print(
"QA Error GQ_fetch_stock_realtime_adv parameter code is not List type or String type"
)
#print(verbose, code)
items_from_collections = [
item for item in collections.find({'code': {
'$in': code
}},
limit=num * len(code),
sort=[('datetime',
pymongo.DESCENDING)])
]
if (items_from_collections is None) or \
(len(items_from_collections) == 0):
if verbose:
print(
"QA Error GQ_fetch_stock_realtime_adv find parameter code={} num={} collection={} return NOne"
.format(code, num, collections))
return
data = pd.DataFrame(items_from_collections)
if (suffix == False):
# 返回代码数据中是否包含交易所代码
data['code'] = data.apply(lambda x: x.at['code'][:6], axis=1)
data_set_index = data.set_index(['datetime', 'code'],
drop=False).drop(['_id'], axis=1)
return data_set_index
else:
print("QA Error GQ_fetch_stock_realtime_adv parameter code is None")
def formater_l1_tick(code: str, l1_tick: dict) -> dict:
"""
处理分发 Tick 数据，新浪和tdx l1 tick差异字段格式化处理
"""
if ((len(code) == 6) and code.startswith('00')):
l1_tick['code'] = normalize_code(code, l1_tick['now'])
else:
l1_tick['code'] = normalize_code(code)
l1_tick['servertime'] = l1_tick['time']
l1_tick['datetime'] = '{} {}'.format(l1_tick['date'], l1_tick['time'])
l1_tick['price'] = l1_tick['now']
l1_tick['vol'] = l1_tick['volume']
del l1_tick['date']
del l1_tick['time']
del l1_tick['now']
del l1_tick['name']
del l1_tick['volume']
#print(l1_tick)
return l1_tick