def watch_history(dateEq='19890928', dateStart='19890928', dateEnd='19890928'):
global mongodb
dataFrame = pd.DataFrame()
dateArr = []
pre_ztm = []
pre_ztpos = []
ztnumArr = []
dtnumArr = []
maxconZt = []
maxconDt = []
querys = common.get_mongoDicts(dateEq=dateEq,
dateStart=dateStart,
dateEnd=dateEnd)
for query in querys:
dateArr.append(query['date'])
# print query['date']
pre_ztm.append(query['pre_ztm'])
if query['pre_ztpos'] > 1:
query['pre_ztpos'] = None
pre_ztpos.append(query['pre_ztpos'])
ztnumArr.append(query['ZT_num'])
dtnumArr.append(query['DT_num'])
maxu = max_value(query['num_ucont'])
maxd = max_value(query['num_dcont'])
if maxu == '+6':
maxu = 7
else:
maxu = int(maxu)
if maxd == '+6':
maxd = 7
else:
maxd = int(maxd)
maxconZt.append(maxu)
maxconDt.append(maxd)
dataFrame = pd.concat([
Series(dateArr),
Series(pre_ztm),
Series(pre_ztpos),
Series(ztnumArr),
Series(dtnumArr),
Series(maxconZt),
Series(maxconDt)
],
axis=1)
dataFrame = dataFrame.dropna()
dataFrame.columns = [
'date', 'pre_ztm', 'pre_ztpos', 'ZT_num', 'DT_num', 'maxZT', 'maxDT'
]
print dataFrame
common.plotFrame(dataFrame,
x='date',
y=[['pre_ztm', 'pre_ztpos'], ['ZT_num', 'DT_num'],
['maxZT', 'maxDT']],
titles=['zt_yes', 'ZDT_num', 'maxCon'],
point=10)
def update_ZDT_stocksNum_ALL(self, dateEq='19890928',dateStart = '19890928', dateEnd = '19890928'):
dateDicts = common.get_mongoDicts(dateEq=dateEq,dateStart=dateStart,dateEnd=dateEnd)
if dateDicts == 1:
print "Error, can't find the date"
return 1
else:
for dateDict in dateDicts:
cdate=[dateDict['date']]
self.update_ZDT_stocksNum([],cdate)
def update_ZDT_yesterday(self,dateEq='19890928',dateStart = '19890928', dateEnd = '19890928'):
# step 2
## 从指定日期开始，计算meat,hole, 以及pre的情况
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
dateDicts = common.get_mongoDicts(dateEq=dateEq,dateStart=dateStart,dateEnd=dateEnd)
for dateDict in dateDicts:
cdate=dateDict['date']
cdate=datetime.datetime.strptime(cdate,"%Y%m%d").strftime("%Y-%m-%d")
predate=common.get_last_date(cdate)
self.get_meat(cdate,predate,mongodb)
def update_ZDT_stocksNum_ALL(self,
dateEq='19890928',
dateStart='19890928',
dateEnd='19890928'):
dateDicts = common.get_mongoDicts(dateEq=dateEq,
dateStart=dateStart,
dateEnd=dateEnd)
if dateDicts == 1:
print "Error, can't find the date"
return 1
else:
for dateDict in dateDicts:
cdate = [dateDict['date']]
self.update_ZDT_stocksNum([], cdate)
def update_ZDT_contsNum(self, dateEq='19890928',dateStart = '19890928', dateEnd = '19890928'):
# step 2
# 给定日期区间内，计算连续涨跌停个数，并去重zt_stocks, dt_stocks, 重新计算个数
# 需要依赖数据库中已经有的涨跌停股票代码以及连续涨跌停数（如果没有连续值，则从0开始）
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
dateDicts = common.get_mongoDicts(dateEq=dateEq,dateStart=dateStart,dateEnd=dateEnd)
for dateDict in dateDicts:
cdate=dateDict['date']
print "handle continus ZDT number for %s"%cdate
cdate=datetime.datetime.strptime(cdate,"%Y%m%d").strftime("%Y-%m-%d")
predate=common.get_last_date(cdate)
common.update_numZD(cdate,predate,mongodb)
def update_freshStocks(self,dateEq='19890928',dateStart = '19890928', dateEnd = '19890928'):
# step 2
# 给定日期区间内，计算连续涨跌停个数，并去重zt_stocks, dt_stocks, 重新计算个数
# 需要依赖数据库中已经有的涨跌停股票代码以及连续涨跌停数（如果没有连续值，则从0开始）
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
try:
dateDicts = common.get_mongoDicts(dateEq=dateEq,dateStart=dateStart,dateEnd=dateEnd)
for dateDict in dateDicts:
cdate=dateDict['date']
predate=common.get_last_date(cdate)
self.oneDate_freshStocks(cdate,predate,mongodb)
except Exception,e:
print "Exception error: %s"%e
def update_ZDT_yesterday(self,
dateEq='19890928',
dateStart='19890928',
dateEnd='19890928'):
# step 2
## 从指定日期开始，计算meat,hole, 以及pre的情况
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
dateDicts = common.get_mongoDicts(dateEq=dateEq,
dateStart=dateStart,
dateEnd=dateEnd)
for dateDict in dateDicts:
cdate = dateDict['date']
cdate = datetime.datetime.strptime(cdate,
"%Y%m%d").strftime("%Y-%m-%d")
predate = common.get_last_date(cdate)
self.get_meat(cdate, predate, mongodb)
def update_ZDT_contsNum(self,
dateEq='19890928',
dateStart='19890928',
dateEnd='19890928'):
# step 2
# 给定日期区间内，计算连续涨跌停个数，并去重zt_stocks, dt_stocks, 重新计算个数
# 需要依赖数据库中已经有的涨跌停股票代码以及连续涨跌停数（如果没有连续值，则从0开始）
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
dateDicts = common.get_mongoDicts(dateEq=dateEq,
dateStart=dateStart,
dateEnd=dateEnd)
for dateDict in dateDicts:
cdate = dateDict['date']
print "handle continus ZDT number for %s" % cdate
cdate = datetime.datetime.strptime(cdate,
"%Y%m%d").strftime("%Y-%m-%d")
predate = common.get_last_date(cdate)
common.update_numZD(cdate, predate, mongodb)
def update_freshStocks(self,
dateEq='19890928',
dateStart='19890928',
dateEnd='19890928'):
# step 2
# 给定日期区间内，计算连续涨跌停个数，并去重zt_stocks, dt_stocks, 重新计算个数
# 需要依赖数据库中已经有的涨跌停股票代码以及连续涨跌停数（如果没有连续值，则从0开始）
mongoUrl = "localhost"
mongodb = pymongo.MongoClient(mongoUrl)
try:
dateDicts = common.get_mongoDicts(dateEq=dateEq,
dateStart=dateStart,
dateEnd=dateEnd)
for dateDict in dateDicts:
cdate = dateDict['date']
predate = common.get_last_date(cdate)
self.oneDate_freshStocks(cdate, predate, mongodb)
except Exception, e:
print "Exception error: %s" % e
def watch_history(dateEq='19890928',dateStart = '19890928', dateEnd = '19890928'):
global mongodb
dataFrame = pd.DataFrame()
dateArr = []
pre_ztm = []
pre_ztpos = []
ztnumArr = []
dtnumArr = []
maxconZt = []
maxconDt = []
querys = common.get_mongoDicts(dateEq=dateEq,dateStart=dateStart,dateEnd=dateEnd)
for query in querys:
dateArr.append(query['date'])
# print query['date']
pre_ztm.append(query['pre_ztm'])
if query['pre_ztpos'] > 1:
query['pre_ztpos'] = None
pre_ztpos.append(query['pre_ztpos'])
ztnumArr.append(query['ZT_num'])
dtnumArr.append(query['DT_num'])
maxu = max_value(query['num_ucont'])
maxd = max_value(query['num_dcont'])
if maxu== '+6':
maxu = 7
else:
maxu = int(maxu)
if maxd == '+6':
maxd = 7
else:
maxd = int(maxd)
maxconZt.append(maxu)
maxconDt.append(maxd)
dataFrame=pd.concat([Series(dateArr),Series(pre_ztm),Series(pre_ztpos),Series(ztnumArr),Series(dtnumArr),Series(maxconZt),Series(maxconDt)],axis=1)
dataFrame=dataFrame.dropna()
dataFrame.columns=['date','pre_ztm','pre_ztpos','ZT_num','DT_num','maxZT','maxDT']
print dataFrame
common.plotFrame(dataFrame,x='date',y=[['pre_ztm','pre_ztpos'],['ZT_num','DT_num'],['maxZT','maxDT']],titles=['zt_yes','ZDT_num','maxCon'],point=10)
def parse_content(self, content):
content = content.replace(u'var kcSTlIop=', u'').replace(u'pages', u'"pages"').replace(u'data', u'"data"')
con_dict = eval(content)
# 当前时间点
ttime = time.localtime()
thour = ttime.tm_hour
tmin = ttime.tm_min
day_list = []
if thour >= 18: # 晚上6点以后，可以得到当天收盘价了，关注复牌时间点为[明天，今天，昨天]
for n in range(2-self.dayRange, 2):
day_list.append(common.get_lastN_date(self.date, n))
else: # 否则，关注时间点为[今天，昨天，前天]
for n in range(1-self.dayRange, 1):
day_list.append(common.get_lastN_date(self.date, n))
for infos in con_dict['data']:
elements = infos.split(",")
if len(elements) < 2:
continue
secid = elements[0]
secname = elements[1]
tp_time = elements[-2]
fp_time = elements[-1]
reason = elements[5]
db_num = self.mongodb.stock.FP.find({"stcid":"%s" % secid, "tp_time":"%s" % tp_time, "fp_time":"%s" % fp_time, "target_ratio":{"$exists":True}}).count()
if db_num > 0:
continue
else:
self.mongodb.stock.FP.update({"stcid":"%s" % secid, "tp_time":"%s" % tp_time},
{"$set":{"stcid":"%s" % secid, "tp_time":"%s" % tp_time, "fp_time":"%s" % fp_time, "reason":"%s" %reason}},
True, True)
# 仅仅记录目标日期在关注日期内的信息
if fp_time in day_list:
# 期间大盘涨幅
if secid[:2] == '60':
dp_stockid = 'ZS000001'
else:
dp_stockid = 'ZS399006'
dp_frame = common.get_mysqlData([dp_stockid], [tp_time, common.get_last_date(fp_time)])
if len(dp_frame) < 2:
continue
dp_ratio = (dp_frame.loc[1, 'CLOSE_PRICE'] - dp_frame.loc[0, 'CLOSE_PRICE']) / dp_frame.loc[0, 'CLOSE_PRICE']
dp_ratio = round(dp_ratio, 2)
# 停牌时价格
stock_price = common.get_mysqlData([secid], [tp_time]).loc[0, 'CLOSE_PRICE']
if dp_ratio > 0:
diff = 0.05
else:
diff = -0.05
# 目标涨幅
target_ratio = dp_ratio + diff
# 目标价格
target_price = round(stock_price*(1+target_ratio), 2)
# 停牌时间
delta_days = common.get_mongoDicts(dateStart=tp_time,dateEnd=fp_time).count()
self.mongodb.stock.FP.update({"stcid":"%s" % secid, "tp_time":"%s" % tp_time},
{"$set":{"dp_ratio":dp_ratio, "target_ratio":target_ratio, "target_price": target_price, 'delta_days':delta_days}},
True, True)
def parse_content(self, content):
content = content.replace(u'var kcSTlIop=', u'').replace(
u'pages', u'"pages"').replace(u'data', u'"data"')
con_dict = eval(content)
# 当前时间点
ttime = time.localtime()
thour = ttime.tm_hour
tmin = ttime.tm_min
day_list = []
if thour >= 18: # 晚上6点以后，可以得到当天收盘价了，关注复牌时间点为[明天，今天，昨天]
for n in range(2 - self.dayRange, 2):
day_list.append(common.get_lastN_date(self.date, n))
else: # 否则，关注时间点为[今天，昨天，前天]
for n in range(1 - self.dayRange, 1):
day_list.append(common.get_lastN_date(self.date, n))
for infos in con_dict['data']:
elements = infos.split(",")
if len(elements) < 2:
continue
secid = elements[0]
secname = elements[1]
tp_time = elements[-2]
fp_time = elements[-1]
reason = elements[5]
db_num = self.mongodb.stock.FP.find({
"stcid": "%s" % secid,
"tp_time": "%s" % tp_time,
"fp_time": "%s" % fp_time,
"target_ratio": {
"$exists": True
}
}).count()
if db_num > 0:
continue
else:
self.mongodb.stock.FP.update(
{
"stcid": "%s" % secid,
"tp_time": "%s" % tp_time
}, {
"$set": {
"stcid": "%s" % secid,
"tp_time": "%s" % tp_time,
"fp_time": "%s" % fp_time,
"reason": "%s" % reason
}
}, True, True)
# 仅仅记录目标日期在关注日期内的信息
if fp_time in day_list:
# 期间大盘涨幅
if secid[:2] == '60':
dp_stockid = 'ZS000001'
else:
dp_stockid = 'ZS399006'
dp_frame = common.get_mysqlData(
[dp_stockid],
[tp_time, common.get_last_date(fp_time)])
if len(dp_frame) < 2:
continue
dp_ratio = (dp_frame.loc[1, 'CLOSE_PRICE'] -
dp_frame.loc[0, 'CLOSE_PRICE']
) / dp_frame.loc[0, 'CLOSE_PRICE']
dp_ratio = round(dp_ratio, 2)
# 停牌时价格
stock_price = common.get_mysqlData(
[secid], [tp_time]).loc[0, 'CLOSE_PRICE']
if dp_ratio > 0:
diff = 0.05
else:
diff = -0.05
# 目标涨幅
target_ratio = dp_ratio + diff
# 目标价格
target_price = round(stock_price * (1 + target_ratio), 2)
# 停牌时间
delta_days = common.get_mongoDicts(dateStart=tp_time,
dateEnd=fp_time).count()
self.mongodb.stock.FP.update(
{
"stcid": "%s" % secid,
"tp_time": "%s" % tp_time
}, {
"$set": {
"dp_ratio": dp_ratio,
"target_ratio": target_ratio,
"target_price": target_price,
'delta_days': delta_days
}
}, True, True)