def fetch_cnstock_hist_to_mongo():
'''get qoute data '''
#set log
LOGGER_NAME = "TONGLIAN_DATA"
mylog = logger.getLogger(LOGGER_NAME)
#get the stock list
today = datetime.strftime(datetime.today(),"%Y%m%d")
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find({"exchangeCD":{"$in":["XSHE","XSHG"]},"listStatusCD":"L"})
for row in cursor:
ticker = str(row['ticker'])
mylog.info("update history data of %s"%(ticker))
exchangeCD = str(row['exchangeCD'])
listDate = str(row['listDate']).replace("-", "").replace("NaN", "")
if exchangeCD == 'XSHG' and not ticker.startswith("6"):
continue
#get hist data
cursor2 = db.cn_stock_hist.find({"ticker":ticker})
if cursor2.count() > 0:
continue
mylog.info("insert data of %s"%(ticker))
st = ts.Market()
df = st.MktEqud(ticker=ticker,beginDate=listDate, endDate=today, field="")
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
db.cn_stock_hist.insert(json.loads(df.to_json(orient='records')))
time.sleep(1)
def run():
ts.set_token(ct.DATA_YES_TOKEN)
st = ts.Market()
today = datetime.strftime(datetime.today(),"%Y%m%d")
stock_list = st.MktEqud(tradeDate="20160513",field="ticker,PE,secShortName")
if not isinstance(stock_list,pd.DataFrame) or stock_list.empty:
return
stock_list['ticker'] = stock_list['ticker'].map(lambda x: str(x).zfill(6))
result = []
mongo = Mongo()
db = mongo.getDB()
for i in stock_list.index:
code = stock_list.loc[i,'ticker']
pe = stock_list.loc[i,'PE']
name = stock_list.loc[i,'secShortName']
if np.isnan(pe):
continue
cursor = db.year_min_value.find({"ticker":code})
if cursor.count() <= 0:
continue
pe_list = []
for row in cursor:
pe_list.append(row['pe'])
min_pe = min(pe_list)
rate = (pe - min_pe)/min_pe
result.append({"code":code,"name":name,"pe":pe,"min_pe":min_pe,"rate":rate})
df = pd.DataFrame(result)
if db.lowest_pe_stock.find().count() > 0:
db.lowest_pe_stock.remove()
db.lowest_pe_stock.insert(json.loads(df.to_json(orient='records')))
def check_stock(code):
mongo = Mongo()
db = mongo.getDB()
cursor = db.mainreports.find({"code":code})
report_list = dict()
for row in cursor:
report_list[str(row['date'])] = row
if len(report_list) == 0:
return False,None,None
key_list = list(report_list.keys())
key_list.sort()
key_list.reverse()
last_two_quarter = key_list[0:2]
last_date = str(key_list[0])
year = int(last_date[0:4])
last_three_year = [str(year-1)+"-12-31",str(year-2)+"-12-31",str(year-3)+"-12-31"]
last_three_year2 = [v for v in last_three_year if v in key_list]
"连续三年业绩增长都小于30%，最近3个季度业绩增长大于30%"
year_grow = []
for key in last_three_year2:
if report_list[key]['profits_yoy']:
year_grow.append(report_list[key]['profits_yoy'])
quarter_grow = []
for key in last_two_quarter:
if report_list[key]['profits_yoy']:
quarter_grow.append(report_list[key]['profits_yoy'])
if (sum(year_grow)/3)!=0 and (max(quarter_grow) - sum(year_grow)/3)/abs((sum(year_grow)/3)) > 1:
return True,quarter_grow,year_grow
return False,quarter_grow,year_grow
def check_stock(code,forcast_rate):
query_text = '业绩预增,预告业绩变动幅度排序'
mongo = Mongo()
db = mongo.getDB()
cursor = db.mainreports.find({"code":code})
report_list = dict()
for row in cursor:
report_list[str(row['date'])] = row
if len(report_list) == 0:
return False,None
key_list = report_list.keys()
key_list.sort()
key_list.reverse()
last_four_quarter = key_list[0:4]
"连续三年业绩增长都小于30%，最近3个季度业绩增长大于30%"
quarter_profit_grow = []
for key in last_four_quarter:
if report_list[key]['profits_yoy']:
quarter_profit_grow.append(report_list[key]['profits_yoy'])
if (sum(quarter_profit_grow)/4)!=0 and (forcast_rate - sum(quarter_profit_grow)/4)/abs((sum(quarter_profit_grow)/4)) > 1:
return True,quarter_profit_grow
return False,quarter_profit_grow
def fetch_stock_list_to_mongo():
eq = ts.Equity()
df = eq.Equ(equTypeCD='A', listStatusCD='L', field='')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find()
if cursor.count() == 0:
db.stock_list.insert(json.loads(df.to_json(orient='records')))
def batchUpdateMainReport(stockCodeList):
LOGGER_NAME = "UPDATE_DATA"
mylog = logger.getLogger(LOGGER_NAME)
mongodb = Mongo()
for code in stockCodeList:
time.sleep(1)
mylog.info("update mainreport data of %s" % (code))
mongodb.updateMainReport(code)
def batchUpdateMainReport(stockCodeList):
LOGGER_NAME = "UPDATE_DATA"
mylog = logger.getLogger(LOGGER_NAME)
mongodb = Mongo()
for code in stockCodeList:
time.sleep(1)
mylog.info("update mainreport data of %s"%(code))
mongodb.updateMainReport(code)
def fetch_stock_list_to_mongo():
eq = ts.Equity()
df = eq.Equ(equTypeCD='A', listStatusCD='L', field='')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find()
if cursor.count() == 0:
db.stock_list.insert(json.loads(df.to_json(orient='records')))
def query_store(query,store):
res = query_iwencai(query)
if res is None or not res.has_key("result"):
pass
ticker_list = []
for item in res["result"]:
ticker_list.append(dict(ticker=item[0][0:6]))
mongo = Mongo()
db = mongo.getDB()
db[store].remove()
db[store].insert(ticker_list)
def query_store(query, store):
res = query_iwencai(query)
if res is None or not res.has_key("result"):
pass
ticker_list = []
for item in res["result"]:
ticker_list.append(dict(ticker=item[0][0:6]))
mongo = Mongo()
db = mongo.getDB()
db[store].remove()
db[store].insert(ticker_list)
def run():
'''get qoute data '''
#set log
LOGGER_NAME = "HISTORY_DATA"
mylog = logger.getLogger(LOGGER_NAME)
#get the stock list
today = datetime.strftime(datetime.today(),"%Y%m%d")
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find({"listStatusCD":"L"})
for row in cursor:
ticker = str(row['ticker'])
mylog.info("update history data of %s"%(ticker))
exchangeCD = str(row['exchangeCD'])
listDate = str(row['listDate']).replace("-", "").replace("NaN", "")
if exchangeCD == 'XSHG' and not ticker.startswith("6"):
continue
#get hist data
cursor2 = db.cn_stock_hist.find({"ticker":ticker}).sort("tradeDate",pymongo.DESCENDING).limit(1)
st = ts.Market()
if cursor2.count() > 0:
start_date = str(cursor2[0]['tradeDate']).replace("-", "")
df = st.MktEqud(ticker=ticker,beginDate=start_date, endDate=today, field="")
if df is not None and not df.empty:
if df['accumAdjFactor'][0] == 1:
mylog.info("update new data of %s from %s"%(ticker,start_date))
df = df[1:]
else:
mylog.info("factor change remove data of %s"%(ticker))
db.cn_stock_hist.remove({"ticker":ticker})
df = st.MktEqud(ticker=ticker,beginDate=listDate, endDate=today, field="")
else:
mylog.info("fisrt insert data of %s"%(ticker))
df = st.MktEqud(ticker=ticker,beginDate=listDate, endDate=today, field="")
if df is not None and not df.empty:
mylog.info("processing insert of %s"%(ticker))
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
db.cn_stock_hist.insert(json.loads(df.to_json(orient='records')))
time.sleep(1)
def fetch_cnstock_hist_to_mongo():
'''get qoute data '''
#set log
LOGGER_NAME = "TONGLIAN_DATA"
mylog = logger.getLogger(LOGGER_NAME)
#get the stock list
today = datetime.strftime(datetime.today(), "%Y%m%d")
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find({
"exchangeCD": {
"$in": ["XSHE", "XSHG"]
},
"listStatusCD": "L"
})
for row in cursor:
ticker = str(row['ticker'])
mylog.info("update history data of %s" % (ticker))
exchangeCD = str(row['exchangeCD'])
listDate = str(row['listDate']).replace("-", "").replace("NaN", "")
if exchangeCD == 'XSHG' and not ticker.startswith("6"):
continue
#get hist data
cursor2 = db.cn_stock_hist.find({"ticker": ticker})
if cursor2.count() > 0:
continue
mylog.info("insert data of %s" % (ticker))
st = ts.Market()
df = st.MktEqud(ticker=ticker,
beginDate=listDate,
endDate=today,
field="")
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
db.cn_stock_hist.insert(json.loads(df.to_json(orient='records')))
time.sleep(1)
# -*- coding:utf-8 -*-
from quantdata.db.mongo import Mongo
from datetime import datetime
from quantdata import logger
import pandas as pd
import json
mongo = Mongo()
db = mongo.getDB()
#set log
LOGGER_NAME = "get the PB"
mylog = logger.getLogger(LOGGER_NAME)
#get the stocklist
stock_list = db.stock_list.find()
for row in stock_list:
ticker = str(row['ticker'])
mylog.info("processing %s" % (ticker))
stock_hist_list = db.cn_stock_hist.find({"ticker": ticker})
hist_list = []
for stock_row in stock_hist_list:
tradDate = datetime.strptime(stock_row['tradeDate'], "%Y-%m-%d")
if stock_row['PE'] <= 0 or stock_row['PB'] <= 0:
continue
hist_list.append({
'ticker': ticker,
'date': stock_row['tradeDate'],
'pb': stock_row['PB'],
'pe': stock_row['PE'],
'gr_year': tradDate.year,
if report_list[key]['profits_yoy']:
year_grow.append(report_list[key]['profits_yoy'])
quarter_grow = []
for key in last_two_quarter:
if report_list[key]['profits_yoy']:
quarter_grow.append(report_list[key]['profits_yoy'])
if (sum(year_grow)/3)!=0 and (max(quarter_grow) - sum(year_grow)/3)/abs((sum(year_grow)/3)) > 1:
return True,quarter_grow,year_grow
return False,quarter_grow,year_grow
if __name__ == "__main__":
stokList = quotes.get_stock_hq_list()
data_list = []
for i in stokList.index:
try:
flag, quarter_grow,year_grow = check_stock(stokList.loc[i,"code"])
if flag:
data = {"code":stokList.loc[i,"code"],"quarter_grow1":quarter_grow[0],"quarter_grow2":quarter_grow[1],\
"year_grow1":year_grow[0],"year_grow2":year_grow[1],"year_grow3":year_grow[2],"mktcap":stokList.loc[i,"mktcap"],\
"name":stokList.loc[i,"name"]}
data_list.append(data)
except:
continue
mongo = Mongo()
db = mongo.getDB()
db["guaidian_list"].remove()
db["guaidian_list"].insert(data_list)