def pull_data_and_count_kpi(start_date=None,
start_code=None,
retry=False,
retryDict=None):
shp = SharePuller()
df = shp.query_from_mysql()
now = datetime.datetime.now()
end = now.strftime('%Y-%m-%d')
dict = {}
# 拉取数据&保存到DB
kp = Kpuller()
# 获取基本数据，按列表计算
for index, row in df.iterrows():
code = row['code']
start = str(row['timeToMarket'])
if (start_code and code < start_code):
continue
if (retry and code not in retryDict['pd']):
continue
if (start_date != None and start < start_date):
start = start_date
dict[code] = kp.pull(code, start, end)
time.sleep(1.5)
KManager.to_csv(dict, 'pd')
def count_kpi():
shp = SharePuller();
df = shp.query_from_mysql();
for index, row in df.iterrows():
code = row['code'];
nma=NetProfitMA();
nma.run(code,to_mysql=True,type=1);
nms = NetProfitSort();
nms8= NetProfitSort8();
for dt in['2017-09-30','2017-12-31','2018-03-31','2018-06-30','2018-09-30']:
nms.run(dt,to_mysql=True,type=1)
nms8.run(dt,to_mysql=True,type=1)
def pull_data_hk(start_date=None,
start_code=None,
retry=False,
retryDict=None):
shp = SharePuller()
df = shp.query_from_mysql()
dict = {}
hkp = HkHoldPuller()
for dt in DateUtil.getDateSeq(start_date):
if (retry and dt not in retryDict['ph']):
continue
dict[dt] = hkp.pull(dt)
time.sleep(3)
KManager.to_csv(dict, 'ph')
def count_kpi(start_date,
s=True,
m=True,
start_code=None,
retry=False,
retryDict=None):
shp = SharePuller()
df = shp.query_from_mysql()
end = datetime.datetime.now().strftime('%Y-%m-%d')
# ================================
## 单指标计算
# ================================
if (s):
dict = {}
for index, row in df.iterrows():
code = row['code']
start = str(row['timeToMarket'])
if (start_code and code < start_code):
continue
if (retry and code not in retryDict['ks']):
continue
if (start_date != None and start < start_date):
start = start_date
KManager.kpi_s(code, start_date, pm, dict)
KManager.to_csv(dict, 'ks')
# ================================
## 多指标计算
# ================================
if (m):
dict = {}
if (start_date == None):
start_date = end
dict[start_date] = KManager.kpi_m(start_date, pm)
elif (start_date <= end):
for dt in DateUtil.getDateSeq(start_date):
if (retry and code not in retryDict['km']):
continue
dict[dt] = KManager.kpi_m(dt, pm)
#更新数据
pm.execute(
"update share_data_day set valid=1 where trade_date='%s'"
% (dt))
KManager.to_csv(dict, 'km')
def pull_data():
shp = SharePuller();
df = shp.query_from_mysql();
now = datetime.datetime.now()
end = now.strftime('%Y-%m-%d');
for index, row in df.iterrows():
code = row['code'];
start = str(row['timeToMarket']);
#目前start和and 还未生效
fy = FinYearPuller();
fy.pull(code, start, end);
fs = FinSeasonPuller();
fs.pull(code, start, end);
fdp = FundsPuller();
fdp.pull(code, start, end)
def count_kpi():
shp = SharePuller();
df = shp.query_from_mysql();
for index, row in df.iterrows():
code = row['code'];
nma=NetProfitMA();
nma.run(code,to_mysql=True,type=1);
nms = NetProfitSort();
nms8= NetProfitSort8();
for dt in['2017-09-30','2017-12-31','2018-03-31','2018-06-30','2018-09-30']:
nms.run(dt,to_mysql=True,type=1)
nms8.run(dt,to_mysql=True,type=1)
if(__name__=='__main__'):
shp = SharePuller();
df = shp.query_from_mysql();
for index, row in df.iterrows():
code = row['code'];
nms = NetProfitSort();
nms8 = NetProfitSort8();
for dt in [ '2018-09-30']:
nms.run(dt, to_mysql=True, type=1)
nms8.run(dt, to_mysql=True, type=1)