from trading_trend a, stock_info s \
where a.date between '" + prevday + "' and '" + currday + "' and s.code = a.code and s.market = 'KOSDAQ' \
and s.code in (select code from daily_info where date = '" + yesterday + "' and marcap between 1000000 and 10000000) \
group by a.code) A \
order by pension_fund desc, foreigner desc \
limit 5)"
cur.execute(query)
df = pd.read_sql(query, conn)
print(df)
if conn:
conn.close()
ret = "no|market|code|name|wics|personal|foreigner|pension_fund\n"
idx = 1
for d in df.iterrows():
ret = ret + str(idx) + "|" + str(d[1]['market']) + "|" + str(
d[1]['code']) + "|" + str(d[1]['name']) + "|" + str(
d[1]['wics']) + "|" + str(d[1]['personal']) + "|" + str(
d[1]['foreigner']) + "|" + str(d[1]['pension_fund']) + "\n"
if idx % 5 == 0:
ret = ret + "\n"
idx = idx + 1
# print("%2d|%s|%s|%s|%f|%f" % (d[1]['s_order'], str(d[1]['code']), str(d[1]['name']), str(d[1]['sector']), d[1]['per'], d[1]['roa']))
print(ret)
bot = favisbot()
bot.whisper('plain',
"day_top5_bysellbuy(%s-%s) \n %s" % (prevday, currday, ret))
#!/usr/bin/python
import requests
import time
import bs4 # beautifulsoup
# user define package import
import sys
sys.path.append("/app/favis")
from msgbot.favisbot import favisbot
bot = favisbot()
'''@param gmtstr'''
def gmtstr_to_kststr(gmtstr, gmtstr_format, kststr_format):
# convert kst (gmt + 9 hour)
dt = time.mktime(time.strptime(gmtstr, gmtstr_format)) + (60 * 60 * 9)
return time.strftime(kststr_format,time.localtime(dt))
# DART realtime official notice rss feed url
url = 'http://dart.fss.or.kr/api/todayRSS.xml'
data = requests.get(url)
data = bs4.BeautifulSoup(data.text, 'lxml')
# extract item list
notices = data.findAll("item")
for notice in notices:
title = notice.find('title').string
link = notice.find('guid').string
regdate = gmtstr_to_kststr(notice.find('dc:date').string, '%Y-%m-%dT%H:%M:%SZ', '%Y-%m-%d %H:%M:%S')