def corr_update(corr, codes):
ra_index = base_ra_index.find(corr['ra_index_id'])
if ra_index is None:
click.echo(click.style(
"unknown index [%s]for calc corr!" % (corr['ra_index_id']), fg="yellow"))
return False
yesterday = (datetime.now() - timedelta(days=1));
enddate = yesterday.strftime("%Y-%m-%d")
#
# 加载指数数据
#
index_code = ra_index['ra_code']
if corr['ra_date_type'] == 1:
df_nav_index = DBData.db_index_value_daily('2015-10-08', enddate, codes=[index_code])
else:
df_nav_index = DBData.db_index_value('2015-10-08', enddate, codes=[index_code])
df_inc_index = df_nav_index.pct_change().fillna(0.0)
#
# 加载基金列表
#
df_fund = base_ra_fund.load(codes=codes)
data = []
with click.progressbar(length=len(df_fund.index), label=('update corr for corr %d' % (corr['globalid'])).ljust(30)) as bar:
for _,fund in df_fund.iterrows():
bar.update(1)
tmp = corr_update_fund(corr, fund, df_inc_index)
if tmp is not None:
data.append([
corr['globalid'],
fund['globalid'],
fund['ra_code'],
"%.4f" % (tmp),
])
df_new = pd.DataFrame(data, columns=['ra_corr_id', 'ra_fund_id', 'ra_fund_code', 'ra_corr'])
df_new = df_new.set_index(['ra_corr_id', 'ra_fund_id'])
db = database.connection('base')
# 加载旧数据
t2 = Table('ra_corr_fund', MetaData(bind=db), autoload=True)
columns2 = [
t2.c.ra_corr_id,
t2.c.ra_fund_id,
t2.c.ra_fund_code,
t2.c.ra_corr,
]
stmt_select = select(columns2, (t2.c.ra_corr_id == corr['globalid']))
if codes is not None:
stmt_select = stmt_select.where(t2.c.ra_fund_code.in_(codes))
df_old = pd.read_sql(stmt_select, db, index_col=['ra_corr_id', 'ra_fund_id'])
if not df_old.empty:
df_old['ra_corr'] = df_old['ra_corr'].map("{:.4f}".format)
# 更新数据库
database.batch(db, t2, df_new, df_old, timestamp=True)
def find_asset_name(asset_id):
if asset_id.strip().isdigit():
#print int(asset_id)
asset_id = int(asset_id)
xtype = asset_id / 10000000
if 12 == xtype:
record = base_ra_index.find(asset_id)
return record[2].strip()
else:
return None
elif asset_id.strip().startswith('ERI'):
record = base_exchange_rate_index.find(asset_id)
return record[2].strip()
else:
return None
def match_asset_pool(gid):
if gid.isdigit():
xtype = int(gid) / 10000000
else:
xtype = re.sub(r'([\d]+)', '', gid).strip()
result = 0
if xtype == 1:
result = gid
elif xtype == 5:
xtab = {
'4111010': 11110100, #大盘资产修型
'41110101': 11110100, #大盘资产修型(实验)
'41110102': 11110100, #巨潮大盘指数修型
'41110105': 11110217, #价值资产修型
'41110200': 11110200, #小盘资产修型
'41110201': 11110200, #小盘资产修型(实验)
'41110202': 11110200, #巨潮小盘指数修型
'41110205': 11110213, #上涨资产修型
'41110206': 11110214, #震荡资产修型
'41110207': 11110215, #下跌资产修型
'41110208': 11110216, #成长资产修型
'41120200': 11120200, #标普资产修型
'41120500': 11120500, #恒生资产修型
'41120501': 11120500, #恒生资产修型(实验)
'41120502': 11120500, #恒生指数修型
'41400100': 11400100, #黄金资产修型
'41400101': 11400100, #黄金资产修型(实验)
'41400102': 11400100, #黄金指数修型
}
if gid in xtab:
result = xtab[gid]
elif xtype == 12:
#
# 指数资产
#
xtab = {
'120000001': 11110100, # 沪深300, 大盘池
'120000002': 11110200, # 中证500, 小盘池
'120000003': 11110100, # 巨潮大盘, 大盘池
'120000004': 11110200, # 巨潮小盘, 小盘池
'120000010': 11210100, # 国债指数，利率债池
'120000011': 11210200, # 中证信用债指数，信用债池
'120000014': 11400100, # 沪金指数, 黄金池
'120000028': 11400300, # 原油指数, 原油池
'120000029': 11400400, # 商品指数, 商品池
'120000031': 11400500, # 房地产指数, 房地产池
}
if gid in xtab:
result = xtab[gid]
else:
asset = base_ra_index.find(gid)
name = asset['ra_name']
if '标普' in name:
result = 11120200
elif '黄金' in name:
result = 11400100
elif '恒生' in name:
result = 11120500
elif xtype == 'ERI':
xtab = {
'ERI000001': 11120200, # 标普500人民币计价指数, 标普基金池
'ERI000002': 11120500, # 恒生指数人民币计价指数, 恒生基金池
}
if gid in xtab:
result = xtab[gid]
else:
pass
return result