def default(self, obj):
# print("obj.__class__", obj.__class__, "isinstance(obj.__class__, DeclarativeMeta)", isinstance(obj.__class__, DeclarativeMeta))
if isinstance(obj.__class__, DeclarativeMeta):
# an SQLAlchemy class
fields = {}
for field in [
x for x in dir(obj)
if not x.startswith('_') and x != 'metadata'
]:
data = obj.__getattribute__(field)
try:
json.dumps(
data
) # this will fail on non-encodable values, like other classes
fields[field] = data
except TypeError: # 添加了对datetime的处理
print(data)
if isinstance(data, datetime):
fields[field] = data.isoformat()
elif isinstance(data, date):
fields[field] = data.isoformat()
elif isinstance(data, timedelta):
fields[field] = (datetime.min +
data).time().isoformat()
else:
fields[field] = None
# a json-encodable dict
return fields
elif isinstance(obj, date):
return json.dumps(date_2_str(obj))
return json.JSONEncoder.default(self, obj)
def get(self, status):
"""
获取投资组合列表数据
"""
args = paginate_parser.parse_args()
page_no = args['page_no']
count = args['count']
user_id = session.get('user_id')
# 获取各个组合 最新交易日
date_latest_query = db.session.query(
PortfolioValueDaily.pl_id,
func.max(PortfolioValueDaily.trade_date).label(
'trade_date_max')).group_by(
PortfolioValueDaily.pl_id).subquery('date_latest')
# 获取各个投资组合 最新净值
nav_latest_query = db.session.query(
PortfolioValueDaily.pl_id, PortfolioValueDaily.trade_date,
PortfolioValueDaily.rr, PortfolioValueDaily.nav).filter(
PortfolioValueDaily.pl_id == date_latest_query.c.pl_id,
PortfolioValueDaily.trade_date ==
date_latest_query.c.trade_date_max).subquery('nav_latest')
# 分页查询投资组合信息及最新净值
if status == 'my':
filter_c = PortfolioInfo.create_user_id == user_id
elif status == 'all':
filter_c = or_(PortfolioInfo.access_type == 'public',
PortfolioInfo.create_user_id == user_id)
elif status == 'star':
# TODO: 星标投资组合
filter_c = not_(func.isnull(FavoriteCompare.update_time))
else:
filter_c = None
if filter_c is None:
raise KeyError('status 参数错误 status = %s' % status)
else:
pagination = PortfolioInfo.query.outerjoin(
nav_latest_query,
PortfolioInfo.pl_id == nav_latest_query.c.pl_id).add_columns(
nav_latest_query.c.trade_date,
nav_latest_query.c.rr,
nav_latest_query.c.nav,
).outerjoin(User).add_columns(User.username).outerjoin(
FavoritePortfolio,
and_(PortfolioInfo.pl_id == FavoritePortfolio.pl_id,
FavoritePortfolio.user_id == user_id)).add_columns(
func.if_(
func.isnull(FavoritePortfolio.update_time), 0,
1).label('favorite')).filter(
filter_c).paginate(page_no, count)
logger.debug('%d / %d 页 %d / %d 条数据',
pagination.page, pagination.pages,
len(pagination.items), pagination.total)
ret_dic_list = [{
'pl_id':
data.PortfolioInfo.pl_id,
'name':
data.PortfolioInfo.name,
'date_from':
date_2_str(data.PortfolioInfo.date_from),
'date_to':
date_2_str(data.PortfolioInfo.date_to),
'status':
data.PortfolioInfo.status,
'desc':
data.PortfolioInfo.desc,
'create_user_id':
data.PortfolioInfo.create_user_id,
'username':
data.username,
'favorite':
data.favorite,
'trade_date':
date_2_str(data.trade_date),
'rr':
try_2_float(data.rr),
'nav':
try_2_float(data.nav),
'access_type':
data.PortfolioInfo.access_type,
} for data in pagination.items]
ret_dic = {
'page': pagination.page,
'pages': pagination.pages,
'count': len(pagination.items),
'total': pagination.total,
'has_prev': pagination.has_prev,
'has_next': pagination.has_next,
'data': ret_dic_list,
}
return ret_dic
def update_pl_compare_result(cmp_id, date_from, date_to, **kwargs):
"""
对给定 cmp_id 更新指定日期段内的比较结果
PortfolioCompareInfo 中 params 格式
compare_method：'>', '<', 'between'
compare_method 为 between时，asset1 与两个参考数据进行比较，否则与1个参考数据进行比较
compare_type：'rel.rr', 'abs.rr', 'abs.fix_point'
compare_type 为 rel 与 资产或资产组合进行比较，abs 与数值进行比较；
rr 代表与收益率进行比较，fix_point 代表与实际价格进行比较
:param cmp_id:
:param date_from:
:param date_to:
:param kwargs: 便于被调用时接受其他冗余参数使用，暂时无用
:return:
"""
result_df = None
pl_comp_info = PortfolioCompareInfo.query.get(cmp_id)
if pl_comp_info.params is None or pl_comp_info.params == "":
raise ValueError('cmp_id: %s 无效' % cmp_id)
# 获取参数，计算日期范围交集
date_from = max([pl_comp_info.date_from, str_2_date(date_from)])
date_to = min([pl_comp_info.date_to, str_2_date(date_to)])
param_dic = json.loads(pl_comp_info.params)
if 'date_start' in param_dic and len(param_dic['date_start']) >= 6:
date_start = max([str_2_date(param_dic['date_start']), date_from])
else:
date_start = max([pl_comp_info.date_from, date_from])
compare_method = param_dic['compare_method']
if compare_method not in ('>', '<', 'between'):
raise ValueError("cmp_id: %s param_dic['compare_method']: %s 无效" %
(cmp_id, param_dic['compare_method']))
compare_type = param_dic['compare_type']
if compare_type not in ('rel.rr', 'abs.rr', 'abs.fix_point'):
raise ValueError("cmp_id: %s param_dic['compare_type']: %s 无效" %
(cmp_id, param_dic['compare_type']))
has_value_asset = False # 判断是否存在 value 类型的资产
max_len_asset_n = None
val_s_dic = {}
need_repead_dic = {}
# 获取相关数据，每条数据为一组 Series, 合并组成 df
for asset_num in range(
1, 4 if compare_method == 'between' else 3): # 以后可能出现不止2个数值进行运算
asset_type_n_key = 'asset_type_' + str(asset_num)
asset_type = param_dic[asset_type_n_key]
# 用来从 param_dic 中取出相应的参数
asset_or_value_n_key = 'value_' + str(
asset_num) if asset_type == 'value' else 'asset_' + str(asset_num)
# 用来保持到计算结果 Series 中并对列进行命名，后续的比较计算均依赖于此名称
asset_n_key = 'asset_' + str(asset_num)
bind_db, table_name = ASSET_TYPE_TABLE_NAME_DIC[asset_type]
if table_name is None:
has_value_asset = True
val_s = pd.Series(name=asset_n_key,
data=param_dic[asset_or_value_n_key])
need_repeat = True
elif table_name == 'pl_value_daily':
engine = db.get_engine(
bind=bind_db) if bind_db is not None else db.engine
sql_str = """SELECT trade_date, rr FROM pl_value_daily
WHERE pl_id = %s AND trade_date BETWEEN %s AND %s
ORDER BY trade_date"""
val_s = pd.read_sql(
sql_str,
engine,
params=[param_dic[asset_or_value_n_key], date_start, date_to],
index_col='trade_date')['rr'].rename(asset_n_key)
val_s = (val_s + 1).cumprod()
need_repeat = False
else:
engine = db.get_engine(
bind=bind_db) if bind_db is not None else db.engine
sql_str = """select trade_date, close from {0}
where wind_code = %s and trade_date between %s and %s
ORDER BY trade_date""".format(table_name)
val_s = pd.read_sql(
sql_str,
engine,
params=[param_dic[asset_or_value_n_key], date_start, date_to],
index_col='trade_date')['close'].rename(asset_n_key)
need_repeat = False
# 加入字典
val_s_dic[asset_n_key] = val_s
need_repead_dic[asset_n_key] = need_repeat
# 选择最长的一组数据进行记录，用于最后将 value型数据扩展长度
if not need_repeat:
if max_len_asset_n is None:
max_len_asset_n = asset_n_key
elif len(val_s_dic[max_len_asset_n]) < len(val_s):
max_len_asset_n = asset_n_key
# 如果存在 value 型数据则扩展期长度与最长的一组数据一致
if has_value_asset:
for asset_n_key, need_repeat in need_repead_dic.items():
if need_repeat:
max_len_asset_val_s = val_s_dic[max_len_asset_n]
asset_val = val_s_dic[asset_n_key].repeat(
len(max_len_asset_val_s))
asset_val.index = max_len_asset_val_s.index
val_s_dic[asset_n_key] = asset_val
# 合并数据
data_df = pd.DataFrame(val_s_dic)
# 只比较 pl_comp_info.date_from pl_comp_info.date_to 之间的数据
is_fit = (data_df.index >= pl_comp_info.date_from) & (data_df.index <=
pl_comp_info.date_to)
data_sub_df = data_df[is_fit]
if data_sub_df.shape[0] == 0:
return result_df
if compare_method == '>':
func = compare_func_larger
elif compare_method == '<':
func = compare_func_larger
elif compare_method == 'between':
func = compare_func_between
else:
raise ValueError("cmp_id: %s param_dic['compare_method']: %s 暂不支持" %
(cmp_id, param_dic['compare_method']))
calc_result_df = pd.DataFrame([
pd.Series(
func(y), name=x, index=['result', 'shift_value', 'shift_rate'])
for x, y in data_sub_df.T.items()
],
index=data_sub_df.index)
result_df = data_sub_df.merge(calc_result_df,
left_index=True,
right_index=True)
if result_df.shape[0] == 0:
return None
# data_sub_df['result'] = data_sub_df.apply(func, axis=1)
result_df['cmp_id'] = cmp_id
result_df.index.rename('trade_date', inplace=True)
# 删除重复数据
result_date_min = result_df.index.min()
result_date_max = result_df.index.max()
db.session.query(PortfolioCompareResult).filter(
PortfolioCompareResult.cmp_id == cmp_id,
PortfolioCompareResult.trade_date >= result_date_min,
PortfolioCompareResult.trade_date <= result_date_max).delete()
db.session.commit()
# 插入数据
result_df.to_sql('pl_compare_result', db.engine, if_exists='append')
logger.debug('更新 cmp_id:%d %s - %s %d 条记录', cmp_id,
date_2_str(result_date_min), date_2_str(result_date_max),
result_df.shape[0])
return result_date_max
def get(self, _id, status):
"""
投资组合资产分布比例
"""
logger.info('pl_id=%s, status=%s', _id, status)
if status == 'latest':
result_list = db.session.query(
PortfolioData.trade_date, PortfolioData.asset_type,
func.sum(PortfolioData.weight).label('weight')).group_by(
PortfolioData.trade_date, PortfolioData.asset_type).filter(
and_(
PortfolioData.trade_date == (db.session.query(
func.max(PortfolioData.trade_date)).filter(
PortfolioData.pl_id == _id)),
PortfolioData.pl_id == _id)).all()
elif status == 'recent':
# count = request.args.get('count', 5, type=int)
args = paginate_parser.parse_args()
count = args['count']
data_list = [
date_2_str(d[0])
for d in db.session.query(PortfolioData.trade_date).filter(
PortfolioData.pl_id == _id).group_by(
PortfolioData.trade_date).limit(count).all()
]
result_list = db.session.query(
PortfolioData.trade_date, PortfolioData.asset_type,
func.sum(PortfolioData.weight).label('weight')).group_by(
PortfolioData.trade_date, PortfolioData.asset_type).filter(
and_(PortfolioData.trade_date.in_(data_list),
PortfolioData.pl_id == _id)).all()
elif status == 'all':
result_list = db.session.query(
PortfolioData.trade_date, PortfolioData.asset_type,
func.sum(PortfolioData.weight).label('weight')).group_by(
PortfolioData.trade_date, PortfolioData.asset_type).all()
else:
raise KeyError('status 参数错误 status = %s' % status)
# 合并数据结果
ret_dic_list = []
ret_dic_dic = {}
for data in result_list:
trade_date = data.trade_date
if trade_date in ret_dic_dic:
pl_list, asset_name_list = ret_dic_dic[trade_date]
else:
pl_list = []
asset_name_list = []
ret_dic_dic[trade_date] = (pl_list, asset_name_list)
ret_dic_list.append({
'trade_date': date_2_str(trade_date),
'data': pl_list,
'name_list': asset_name_list
})
# 扩展
pl_list.append({
'name': data.asset_type,
'value': try_2_float(data.weight),
})
asset_name_list.append(data.asset_type)
ret_dic = {
'count': len(ret_dic_list),
'data': ret_dic_list,
}
# logger.debug("ret_dic:%s", ret_dic)
return ret_dic
def get_pl_data_list_by_date(_id, status, page_no, count):
"""
获取制定投资组合的成分及权重数据（分页）
status
:param _id:
:param status: latest 最近一次调仓数据, recent 最近几日调仓数据，日期逆序排列
:return:
"""
# logger.info('pl_id=%s, status=%s', _id, status)
# PortfolioData.query.filter(PortfolioData.id == pl_id, PortfolioData.trade_date == 1)
if status == 'latest':
date_cur = db.session.query(func.max(
PortfolioData.trade_date)).filter(
PortfolioData.pl_id == _id).scalar()
# 最新调仓日期
pagination = PortfolioData.query.filter(
PortfolioData.pl_id == _id,
PortfolioData.trade_date == date_cur).paginate(page_no, count)
elif status == 'recent':
pagination = PortfolioData.query.group_by(
PortfolioData.trade_date).filter(
PortfolioData.pl_id == _id).order_by(
PortfolioData.trade_date.desc()).paginate(
page_no, count)
else:
raise KeyError('status = %s 不支持' % status)
logger.debug('%d / %d 页 %d / %d 条数据', pagination.page,
pagination.pages, len(pagination.items), pagination.total)
date_list = [data.trade_date for data in pagination.items]
date_grouped_dic = {}
ret_dic_list = []
if len(date_list) > 0:
# date_grouped_dic 中的 value 为 data_list 实际与 ret_dic_list 中对应日期的 data_list 为同一对象
# 因此可以直接修改
items = db.session.query(PortfolioData).filter(
PortfolioData.pl_id == _id,
PortfolioData.trade_date.in_(date_list)).all()
for data in items:
date_cur = date_2_str(data.trade_date)
if date_cur in date_grouped_dic:
data_list = date_grouped_dic[date_cur]
else:
data_list = []
date_grouped_dic[date_cur] = data_list
ret_dic_list.append({
'trade_date': date_cur,
'data': data_list
})
# 获取资产及资产类别中文名称
asset_name = get_asset_name(data.asset_type, data.asset_code)
# 因为list是引用性数据，直接放入 ret_dic_list
# 对 data_list 的修改直接反应到 ret_dic_list 中去
data_list.append({
'id':
data.id,
'asset_code':
data.asset_code,
'asset_name':
asset_name,
'asset_type':
data.asset_type,
'trade_date':
date_cur,
'weight':
try_2_float(data.weight),
'weight_before':
try_2_float(data.weight_before),
'price_type':
data.price_type,
'direction':
data.direction,
})
ret_dic = {
'page': pagination.page,
'pages': pagination.pages,
'count': len(pagination.items),
'total': pagination.total,
'has_prev': pagination.has_prev,
'has_next': pagination.has_next,
'data': ret_dic_list,
}
# logger.debug(ret_dic)
return ret_dic
def get_pl_data_list(_id, status, page_no, count):
"""
获取制定投资组合的成分及权重数据（分页）
:param _id:
:param status:
:param page_no:
:param count:
:return:
"""
if status == 'latest':
pagination = PortfolioData.query.filter(
PortfolioData.pl_id == _id,
PortfolioData.trade_date == (db.session.query(
func.max(PortfolioData.trade_date)).filter(
PortfolioData.pl_id == _id))).paginate(page_no, count)
elif status == 'recent':
pagination = PortfolioData.query.filter(
PortfolioData.pl_id == _id).order_by(
PortfolioData.trade_date.desc()).paginate(page_no, count)
else:
raise KeyError('status = %s 不支持' % status)
logger.debug('%d / %d 页 %d / %d 条数据', pagination.page,
pagination.pages, len(pagination.items), pagination.total)
date_grouped_dic = {}
ret_dic_list = []
for data in pagination.items:
date_cur = date_2_str(data.trade_date)
if date_cur in date_grouped_dic:
data_list = date_grouped_dic[date_cur]
else:
data_list = []
date_grouped_dic[date_cur] = data_list
ret_dic_list.append({
'trade_date': date_cur,
'data': data_list
})
# 获取资产及资产类别中文名称
asset_name = get_asset_name(data.asset_type, data.asset_code)
# 因为list是引用性数据，直接放入 ret_dic_list
# 对 data_list 的修改直接反应到 ret_dic_list 中去
data_list.append({
'id': data.id,
'asset_code': data.asset_code,
'asset_name': asset_name,
'asset_type': data.asset_type,
'trade_date': date_cur,
'weight': try_2_float(data.weight),
'weight_before': try_2_float(data.weight_before),
'price_type': data.price_type,
'direction': data.direction,
})
ret_dic = {
'page': pagination.page,
'pages': pagination.pages,
'count': len(pagination.items),
'total': pagination.total,
'has_prev': pagination.has_prev,
'has_next': pagination.has_next,
'data': ret_dic_list,
}
# logger.debug(ret_dic)
return ret_dic
def get(self, status):
"""
获取比较列表数据（分页）
"""
args = paginate_parser.parse_args()
page_no = args['page_no']
count = args['count']
user_id = session.get('user_id')
logger.debug('get_cmp_list user_id:%s', user_id)
if status == 'my':
filter_c = PortfolioCompareInfo.create_user_id == user_id
having_c = None
elif status == 'all':
filter_c = or_(PortfolioCompareInfo.create_user_id == user_id,
PortfolioCompareInfo.access_type == 'public')
having_c = None
elif status == 'star':
filter_c = and_(
or_(PortfolioCompareInfo.create_user_id == user_id,
PortfolioCompareInfo.access_type == 'public'),
not_(func.isnull(FavoriteCompare.update_time)))
having_c = None
elif status == 'verified':
filter_c = or_(PortfolioCompareInfo.create_user_id == user_id,
PortfolioCompareInfo.access_type == 'public')
having_c = column('complete_rate') >= 1
elif status == 'unverified':
filter_c = or_(PortfolioCompareInfo.create_user_id == user_id,
PortfolioCompareInfo.access_type == 'public')
having_c = or_(
column('complete_rate').is_(None),
column('complete_rate') < 1)
else:
raise KeyError('status 参数错误 status = %s' % status)
# 整理数据
# logger.debug("data_list_df len:%d", data_list_df.shape[0])
# data_list_df = data_list_df.where(data_list_df.notna(), None)
# data_list = data_list_df.to_dict('record')
# data_table_dic = {'data': data_list}
# logger.debug(data_table_dic)
query = PortfolioCompareInfo.query.outerjoin(
PortfolioCompareResult
).group_by(PortfolioCompareResult.cmp_id).add_columns(
func.count().label('tot_count'),
func.min(
PortfolioCompareResult.trade_date).label('trade_date_min'),
func.max(
PortfolioCompareResult.trade_date).label('trade_date_max'),
func.sum(PortfolioCompareResult.result).label('fit_count'),
(func.sum(PortfolioCompareResult.result) /
func.count()).label('fit_rate'),
((func.max(PortfolioCompareResult.trade_date) -
PortfolioCompareInfo.date_from) /
(PortfolioCompareInfo.date_to - PortfolioCompareInfo.date_from)
).label('complete_rate')).outerjoin(User).add_columns(
User.username).outerjoin(
FavoriteCompare,
and_(
PortfolioCompareInfo.cmp_id == FavoriteCompare.cmp_id,
FavoriteCompare.user_id == user_id)).add_columns(
func.if_(
func.isnull(FavoriteCompare.update_time), 0,
1).label('favorite')).filter(
and_(filter_c,
PortfolioCompareInfo.is_del == 0))
if having_c is None:
pagination = query.paginate(page_no, count)
else:
pagination = query.having(having_c).paginate(page_no, count)
logger.debug('%d / %d 页 %d / %d 条数据', pagination.page,
pagination.pages, len(pagination.items), pagination.total)
ret_dic_list = [{
'cmp_id':
data.PortfolioCompareInfo.cmp_id,
'name':
data.PortfolioCompareInfo.name,
'status':
data.PortfolioCompareInfo.status,
'params':
data.PortfolioCompareInfo.params,
'desc':
data.PortfolioCompareInfo.desc,
'date_from':
date_2_str(data.PortfolioCompareInfo.date_from),
'date_to':
date_2_str(data.PortfolioCompareInfo.date_to),
'trade_date_min':
date_2_str(data.trade_date_min),
'trade_date_max':
date_2_str(data.trade_date_max),
'create_user_id':
data.PortfolioCompareInfo.create_user_id,
'username':
data.username,
'favorite':
data.favorite,
'complete_rate':
try_2_float(data.complete_rate),
} for data in pagination.items]
ret_dic = {
'page': pagination.page,
'pages': pagination.pages,
'count': len(pagination.items),
'total': pagination.total,
'has_prev': pagination.has_prev,
'has_next': pagination.has_next,
'data': ret_dic_list,
}
return ret_dic
def get(self, _id):
"""
获取投资组合的绩效及统计信息
"""
ret_data = {"general": {}, "performance": {}, "others": {}}
pl_obj = db.session.query(PortfolioInfo, User.username).filter(
PortfolioInfo.pl_id == _id,
User.id == PortfolioInfo.create_user_id).first()
ret_data['general']['pl_id'] = pl_obj.PortfolioInfo.pl_id
ret_data['general']['name'] = pl_obj.PortfolioInfo.name
ret_data['general']['date_from'] = date_2_str(
pl_obj.PortfolioInfo.date_from)
ret_data['general']['date_to'] = date_2_str(
pl_obj.PortfolioInfo.date_to)
ret_data['general'][
'create_user_id'] = pl_obj.PortfolioInfo.create_user_id
ret_data['general']['create_user_name'] = pl_obj.username
ret_data['general']['created_at'] = datetime_2_str(
pl_obj.PortfolioInfo.create_dt)
ret_data['general']['access_type'] = pl_obj.PortfolioInfo.access_type
ret_data['general']['status'] = pl_obj.PortfolioInfo.status
ret_data['general']['is_del'] = pl_obj.PortfolioInfo.is_del
ret_data['general']['desc'] = pl_obj.PortfolioInfo.desc
# date_latest = db.session.query(func.max(PortfolioValueDaily.trade_date)).filter(
# PortfolioValueDaily.pl_id == _id).scalar()
pl_df = pd.read_sql("select trade_date, nav from " +
PortfolioValueDaily.__tablename__ +
" where pl_id = %s order by trade_date",
db.engine,
params=[_id],
index_col='trade_date')
if pl_df.shape[0] > 0:
stat_dic_dic = calc_performance(pl_df, freq=None)
if 'nav' in stat_dic_dic:
performance_dic = stat_dic_dic['nav']
for key in list(performance_dic.keys()):
value = performance_dic[key]
if value is None:
performance_dic[key] = '-'
elif type(value) is date:
performance_dic[key] = date_2_str(value)
elif type(value) is not str and not np.isfinite(value):
performance_dic[key] = '-'
ret_data['performance'] = stat_dic_dic['nav']
else:
logger.warning('stat_dic_dic:\n%s', stat_dic_dic)
# 星标数量
star_count = db.session.query(
func.count()).filter(FavoritePortfolio.pl_id == _id).scalar()
ret_data['others']['star_count'] = int(star_count)
# 最新净值
latest_nav_sub_query = db.session.query(
PortfolioValueDaily.nav).filter(
PortfolioValueDaily.pl_id == _id,
PortfolioValueDaily.trade_date == (db.session.query(
func.max(PortfolioValueDaily.trade_date)).filter(
PortfolioValueDaily.pl_id == _id))).subquery()
# 收益率排名
max_trade_date_sub_query = db.session.query(
PortfolioValueDaily.pl_id,
func.max(PortfolioValueDaily.trade_date).label(
'trade_date_max')).group_by(
PortfolioValueDaily.pl_id).subquery()
latest_nav_list_sub_query = db.session.query(
PortfolioValueDaily.pl_id, PortfolioValueDaily.nav).join(
max_trade_date_sub_query,
and_(
PortfolioValueDaily.pl_id ==
max_trade_date_sub_query.c.pl_id,
PortfolioValueDaily.trade_date ==
max_trade_date_sub_query.c.trade_date_max)).order_by(
PortfolioValueDaily.nav.asc()).subquery()
# 净值排名
nav_rank_count = db.session.query(func.count()).filter(
latest_nav_list_sub_query.c.nav >= latest_nav_sub_query.c.nav
).scalar()
# 总产品数量
pl_count_has_nav = db.session.query(
func.count(
db.session.query(PortfolioValueDaily.pl_id).group_by(
PortfolioValueDaily.pl_id).subquery().c.pl_id)).scalar()
ret_data['others']['rank'] = 0 if pl_count_has_nav == 0 else float(
nav_rank_count / pl_count_has_nav)
return ret_data