def QA_fetch_stock_block_adv(code=None, blockname=None, collections=DATABASE.stock_block):
'''
返回板块 ❌
:param code:
:param blockname:
:param collections: 默认数据库 stock_block
:return: QA_DataStruct_Stock_block
'''
if code is not None and blockname is None:
# 返回这个股票代码所属的板块
data = pd.DataFrame([item for item in collections.find(
{'code': {'$in': code}})])
data = data.drop(['_id'], axis=1)
return QA_DataStruct_Stock_block(data.set_index(['blockname', 'code'], drop=True).drop_duplicates())
elif blockname is not None and code is None:
#
# 🛠 todo fnished 返回 这个板块所有的股票
# 返回该板块所属的股票
# print("QA Error blockname is Not none code none, return all code from its block name have not implemented yet !")
items_from_collections = [item for item in collections.find(
{'blockname': re.compile(blockname)})]
data = pd.DataFrame(items_from_collections).drop(['_id'], axis=1)
data_set_index = data.set_index(['blockname', 'code'], drop=True)
return QA_DataStruct_Stock_block(data_set_index)
else:
# 🛠 todo 返回 判断 这个股票是否和属于该板块
data = pd.DataFrame(
[item for item in collections.find()]).drop(['_id'], axis=1)
data_set_index = data.set_index(['blockname', 'code'], drop=True)
return QA_DataStruct_Stock_block(data_set_index)
def QA_fetch_stock_block_adv(code=None,
blockname=None,
collections=DATABASE.stock_block):
'''
返回板块
:param code:
:param blockname:
:param collections: 默认数据库 stock_block
:return:
'''
if code is not None and blockname is None:
# 根据代码 和 板块名称 查找
data = pd.DataFrame(
[item for item in collections.find({'code': code})]).drop(['_id'],
axis=1)
return QA_DataStruct_Stock_block(
data.set_index('code', drop=False).drop_duplicates())
elif blockname is not None and code is None:
# 板块名称 查找
data = pd.DataFrame([
item
for item in collections.find({'blockname': re.compile(blockname)})
]).drop(['_id'], axis=1)
else:
# ？？
data = pd.DataFrame([item
for item in collections.find()]).drop(['_id'],
axis=1)
return QA_DataStruct_Stock_block(
data.set_index('code', drop=False).drop_duplicates())
def QA_fetch_stock_block_adv(code=None,
blockname=None,
collections=DATABASE.stock_block):
"""返回板块
Keyword Arguments:
code {[type]} -- [description] (default: {None})
blockname {[type]} -- [descrioption] (default : {None})
collections {[type]} -- [description] (default: {DATABASE})
Returns:
[type] -- [description]
"""
if code is not None and blockname is None:
data = pd.DataFrame(
[item for item in collections.find({'code': code})]).drop(['_id'],
axis=1)
return QA_DataStruct_Stock_block(
data.set_index('code', drop=False).drop_duplicates())
elif blockname is not None and code is None:
data = pd.DataFrame([
item
for item in collections.find({'blockname': re.compile(blockname)})
]).drop(['_id'], axis=1)
else:
data = pd.DataFrame([item
for item in collections.find()]).drop(['_id'],
axis=1)
return QA_DataStruct_Stock_block(
data.set_index('code', drop=False).drop_duplicates())
def QA_fetch_stock_block_adv(code=None, collections=QA_Setting.client.quantaxis.stock_block):
if code is not None:
data = pd.DataFrame([item for item in collections.find(
{'code': code})]).drop(['_id'], axis=1)
return QA_DataStruct_Stock_block(data.set_index('code', drop=False).drop_duplicates())
else:
data = pd.DataFrame([item for item in collections.find()]).drop(['_id'], axis=1)
return QA_DataStruct_Stock_block(data.set_index('code', drop=False).drop_duplicates())
def QA_fetch_stock_block_adv(code=None,
blockname=None,
collections=DATABASE.stock_block):
'''
返回板块 ❌
:param code:
:param blockname: 为list时模糊查询多版块交集
:param collections: 默认数据库 stock_block
:return: QA_DataStruct_Stock_block
'''
if isinstance(blockname, (list, )) and len(blockname) > 0:
reg_join = "|".join(blockname)
df = DataFrame([i for i in collections.aggregate([ \
{"$match": {"blockname": {"$regex": reg_join}}}, \
{"$group": {"_id": "$code", "count": {"$sum": 1}, "blockname": {"$push": "$blockname"}}}, \
{"$match": {"count": {"$gte": len(blockname)}}}, \
{"$project": {"code": "$_id", "blockname": 1, "_id": 0, }}, \
])])
df.blockname = df.blockname.apply(lambda x: ",".join(x))
return QA_DataStruct_Stock_block(
df.set_index(["blockname", "code"], drop=False))
elif code is not None and blockname is None:
# 返回这个股票代码所属的板块
data = pd.DataFrame(
[item for item in collections.find({'code': {
'$in': code
}})])
data = data.drop(['_id'], axis=1)
return QA_DataStruct_Stock_block(
data.set_index(['blockname', 'code'], drop=True).drop_duplicates())
elif blockname is not None and code is None:
#
# 🛠 todo fnished 返回 这个板块所有的股票
# 返回该板块所属的股票
# print("QA Error blockname is Not none code none, return all code from its block name have not implemented yet !")
items_from_collections = [
item
for item in collections.find({'blockname': re.compile(blockname)})
]
data = pd.DataFrame(items_from_collections).drop(['_id'], axis=1)
data_set_index = data.set_index(['blockname', 'code'], drop=True)
return QA_DataStruct_Stock_block(data_set_index)
else:
# 🛠 todo 返回 判断 这个股票是否和属于该板块
data = pd.DataFrame([item
for item in collections.find()]).drop(['_id'],
axis=1)
data_set_index = data.set_index(['blockname', 'code'], drop=True)
return QA_DataStruct_Stock_block(data_set_index)