def serialListenForSell():
f = open('persist.txt', 'r')
code = str(f.readline())
f.close()
if code is not None and code != 'Nothing' and code != "":
print("[" + str(du.getHMS()) + "]:已获取code:" + code)
df = gs.getDataFrame(code)
pre_b1_v = float(df['b1_v'][0])
while True:
if du.getHMS() < "09:24:20":
time.sleep(5)
continue
df = gs.getDataFrame(code)
rate = float(gs.getRate(gs.getDataFrame(code)))
if rate < 0 and du.getHMS() < "10:30:00":
time.sleep(5)
continue
if rate > 9.89:
b1_v = float(df['b1_v'][0])
if pre_b1_v - b1_v > 1280:
sellAction(code=code)
break
else:
sellAction(code=code)
break
print("[" + str(du.getHMS()) + "]:持续监听卖出->rate:" + str(rate) +
"->b1_v:" + str(pre_b1_v) + "->volumeDis:" +
str(pre_b1_v - b1_v))
pre_b1_v = float(df['b1_v'][0])
time.sleep(5)
else:
print("[" + str(du.getHMS()) + "]:没有持仓")
def prepareForAppChannelKpi():
listParams = []
channelType = 0
while (channelType < 7):
channelType = channelType + 1
temp = (channelType, 1000000, 10000 * random.randint(10, 40),
DateUtil.getNowTime(), DateUtil.getNowTime())
listParams.append(temp)
return tuple(listParams)
def prepareForAppSummaryDaily():
date_rang = DateUtil.getDateRang("2016-03-01", "2016-04-01")
now = DateUtil.getNowTime()
listParams = []
for num in date_rang:
tmp = (random.randint(2000,
10000), random.randint(2000,
10000), num, now, now)
listParams.append(tmp)
return tuple(listParams)
def startNotifyInTimeBigEmotion4Sell():
while True:
hms = du.getHMS()
if '09:25' in hms or '09:30' in hms or '09:32' in hms or '09:35' in hms or '09:40' in hms or '09:50' in hms or '10:00' in hms:
if Config.isBigEmotionGood == False:
pm.sendContent('市场环境氛围_差', '市场环境氛围_差')
else:
pm.sendContent('市场环境氛围_好', '市场环境氛围_好')
time.sleep(60)
time.sleep(1)
print("[" + du.getHMS() +
"] startNotifyInTimeBigEmotion4Sell: tik tok...")
if hms > '10:30:00':
break
def prepareForAppStatDaily():
appKeys = MySqlUtil.db_qa_sql_select("SELECT app_key FROM app", "open_api")
date_rang = DateUtil.getDateRang("2016-03-01", "2016-04-01")
listParams = []
for num in date_rang:
for key in appKeys:
tmp = (key, random.randint(500,
1000), random.randint(50000, 100000),
random.randint(8000, 15000), random.randint(60, 1800),
random.randint(3000, 6000), random.randint(60, 1800),
round(random.random(), 2), round(random.random(), 2),
round(random.random(),
2), num, DateUtil.getNowTime(), DateUtil.getNowTime())
listParams.append(tmp)
return tuple(listParams)
def sendContent(title, content):
try:
requests.get('http://95.163.200.245:11251/sendEmail/[' + du.getYMD() +
':' + conf.hostname + ']：' + title + '/' + content + '/' +
default_receivers)
except Exception as e:
print("ERROR Send Check Mail!")
def stu_selectcourse(self, studinfo, xuanke_counter=0):
studenetId = studinfo['stu']['id']
studentNo = studinfo['stu']['studentNo']
semeId = str(int(studinfo['stu']['xueqi']['id']) + 1) #本学期选下学期的课
stu_plan_name = studinfo['stu']['planObj']['name']
dateutil = DateUtil.DateUtil()
semenum = dateutil.getSCTermNo(stu_plan_name)
tobeelectlistinfo = self.get_stu_tobeelect(studinfo)
if tobeelectlistinfo and len(tobeelectlistinfo) == 2:
stu_cur_eleactive = tobeelectlistinfo[0]
tobeelectlist = tobeelectlistinfo[1]
if stu_cur_eleactive and len(
stu_cur_eleactive) > 0 and self.getifforceselectcourse(
) != True:
self.log('学生' + str(studentNo) + '已有选课记录，不再进行自动选课。', True)
else:
# 优选本学期的推荐课,判断是否为推荐选课
tobeelectlist = self.selectCourseService.get_recommend_courselist(
studentNo)
if xuanke_counter > 0:
# 在所有推荐选课列表中先选主修课再选选修课
#mainstudy_courselist=self.selectCourseService.get_recommend_courselist(studentNo,0)
#if len(mainstudy_courselist)>=xuanke_counter:
# tobeelectlist=mainstudy_courselist[0:xuanke_counter]
#else:
# selectstudy_courselist=self.selectCourseService.get_recommend_courselist(studentNo,1)
# selectstudy_coursecount=len(selectstudy_courselist)
# if selectstudy_coursecount>0:
# selectstudycount=xuanke_counter-len(mainstudy_courselist)
# if selectstudycount>selectstudy_coursecount:
# selectstudycount=selectstudy_coursecount
# mainstudy_courselist.extend(selectstudy_courselist[0:selectstudycount])
# tobeelectlist =mainstudy_courselist
tobeelectlist = tobeelectlist[0:xuanke_counter]
# 组织自动选课数据
selectcourselist = []
selectcoursetime = self.getcurrenttime()
for course in tobeelectlist:
# 优选本学期的推荐课,判断是否为推荐选课，如果是则选择
courseid = course['courseId']
coursetype = '必修'
if course['type'] == 0:
coursetype = '必修'
if course['type'] == 1:
coursetype = '选修'
selectcouse = {
"coursePlanId": course['id'],
"courseD": course['courseD'],
"studentId": studenetId,
"studentNo": studentNo,
"courseId": courseid,
"planId": course['planId'],
"semeId": semeId,
"type": coursetype,
"time": selectcoursetime
}
selectcourselist.append(selectcouse)
selectcourse_data = json.dumps(selectcourselist,
ensure_ascii=False)
self.submit_selectcourse(studinfo, selectcourse_data)
def createJpg(uid, needCreateJpg=True, jpgName="分析词云"):
# get data directory (using getcwd() is needed to support running example in generated IPython notebook)
dpath = path.dirname(__file__) if "__file__" in locals() else os.getcwd()
# Read the whole text.
txtFilePath = FileUtil.getTxtFilePath(uid)
text = open(txtFilePath, encoding="utf-8").read()
# print(text)
# 设置字体，使其支持中文显示，需要提前下载对应的字体
font = dpath + "\simfang.ttf"
# Generate a word cloud image
wordcloud = WordCloud(collocations=False,
font_path=font,
width=1400,
height=1400,
margin=2).generate(text)
if needCreateJpg:
# 把产生的词云保存进图片
if not jpgName:
jpgName = "default_" + DateUtil.nowNoSplit()
if not jpgName.endswith(".jpg"):
jpgName = jpgName + ".jpg"
print("生成图片名：" + jpgName)
file_pref = txtFilePath[0:txtFilePath.rfind((os.sep))]
wordcloud.to_file(file_pref + jpgName)
# Display the generated image:
# the matplotlib way:
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.show()
def update(end_date):
indexes = bd.getStocks(True)
for each in indexes:
stock_code = each[0]
stock_code_163 = each[3]
start_date = each[5]
if start_date is None:
start_date = du.convertStringToDate("1990-01-01", "%Y-%m-%d")
elif start_date == end_date:
continue
else:
start_date = start_date + timedelta(1)
data = bd.getStockData(stock_code_163, start_date, end_date)
last_updated_date = data[0].split(",")[0]
bd.insertBasicData(stock_code, data)
bd.insertTechData(stock_code, data)
bd.insertAnalysisData(stock_code, data)
bd.updateMasterDate("LAST_UPDATED_DATE", last_updated_date, stock_code_163)
stocks = bd.getStocks(False)
for each in stocks:
stock_code = each[0]
stock_code_163 = each[3]
stock_code_sina = each[4]
start_date = each[5]
if start_date is None:
start_date = du.convertStringToDate("1990-01-01", "%Y-%m-%d")
elif start_date == end_date:
continue
else:
start_date = start_date + timedelta(1)
data = bd.getStockData(stock_code_163, start_date, end_date)
last_updated_date = data[0].split(",")[0]
bd.insertBasicData(stock_code, data)
bd.insertTechData(stock_code, data)
bd.insertAnalysisData(stock_code, data)
bd.updateMasterDate("LAST_UPDATED_DATE", last_updated_date, stock_code_163)
rf = bd.getRecoveryFactor(stock_code_163, stock_code_sina, start_date)
bd.insertRecoveryFactor(stock_code, rf)
def process(image_file):
tags = exifread.process_file(image_file)
for tag in tags.keys():
# print "key:%s, value:%s" % (tag, tags[tag])
if tag == "Image DateTime":
diff_str, date_str = DateUtil.get_days(tags[tag])
ImageUtil.set_text(image_file, diff_str, date_str)
def smartUpdate(end_date=date.today()):
sql = "SELECT * FROM stockmaster where LAST_UPDATED_DATE < '" + du.convertDateToString(end_date, "%Y-%m-%d") + "'"
result_set = dbu.query(sql)
while len(result_set) > 0:
for each in result_set:
stock_code = each[0]
index_indicator = each[2]
stock_code_163 = each[3]
stock_code_sina = each[4]
start_date = each[5]
logger.info("UPDATING STOCK, STOCK CODE IS " + stock_code)
if start_date is None:
start_date = du.convertStringToDate("1990-01-01", "%Y-%m-%d")
elif start_date == end_date:
continue
else:
start_date = start_date + timedelta(1)
data = bd.getStockData(stock_code_163, start_date, end_date)
if len(data) > 0:
last_updated_date = data[0].split(",")[0]
bd.insertBasicData(stock_code, data)
logger.info("INSERT BASIC DATA COMPLETED")
bd.insertTechData(stock_code, data)
logger.info("INSERT TECH DATA COMPLETED")
bd.insertAnalysisData(stock_code, data)
logger.info("INSERT ANALYSIS DATA COMPLETED")
bd.updateMasterDate("LAST_UPDATED_DATE", last_updated_date, stock_code_163)
logger.info("LAST DATE UPDATED")
if str(index_indicator) == "1":
rf = bd.getRecoveryFactor(stock_code_163, stock_code_sina, start_date)
bd.insertRecoveryFactor(stock_code, rf)
logger.info("INSERT RF DATA COMPLETED")
else:
logger.error("NO DATA IS RECEIVED FROM 163")
result_set = dbu.query(sql)
if len(result_set) > 0:
logger.info("NOT ALL STOCKS ARE UPDATED, WAIT 10 MINUTES FOR NEXT UPDATE")
tm.sleep(10*60)
return "COMPLETED"
def get_month_maxdate(stockno):
try:
sql = "select max(date) maxdate from stock_month_data where code='"+stockno+"'"
conn = MySQLdb.connect(host='localhost',user='******',passwd='123456',db='stock')
cursor = conn.cursor()
n = cursor.execute(sql)
maxdate = ''
for r in cursor:
maxdate = r[0]
cursor.close()
conn.close
if maxdate=='':
stockDf =ts.get_stock_basics()
sssj = str(stockDf.ix[stockno]['timeToMarket']) #上市日期YYYYMMDD
return dateutil.convertDate(sssj)
return dateutil.get_next_day(maxdate)
except Exception,e:
print e.message
def sendCodeArr(codeArr):
content = "_".join(codeArr) + "_共" + str(codeArr.__len__()) + "个"
title = str(codeArr.__len__()) + "个"
try:
requests.get('http://95.163.200.245:11251/sendEmail/[' + du.getYMD() +
':' + conf.hostname + ']：盘前选股_' + title + '/候选：' +
content + '/' + default_receivers)
except Exception as e:
print("ERROR Send Check Mail!")
def num2date(v):
"""
Convert numerical value to python date.
:param v: Numerical value of date.
:returns: Python date
"""
t = DateUtil.fromOADate(v)
return pydate(t)
def sellIn0925():
res = requests.get("http://95.163.200.245:11252/chicang/read")
if res.text is None or res.text == "Nothing":
return
code = str(res.text)
while True:
time.sleep(5)
if du.getHMS() > Config.SellTime:
df = gs.getDataFrame(code)
if df is None:
return
name = gs.getStockName(df)
pre_close = str(round(float(df['pre_close'][0]), 2))
sp = str(round(float(pre_close) * 0.91, 2))
sellAction(code, name, sp, '100')
requests.get("http://95.163.200.245:11252/chicang/deleteall")
break
else:
print('[' + du.getHMS() + ']:sellIn0925 waitting...')
def date2num(t):
"""
Convert python date to numerical value.
:param t: Python date.
:returns: Numerical value
"""
tt = jdate(t)
v = DateUtil.toOADate(tt)
return v
def log(string):
filename = _getFilename("LOG")
try:
if Config.IS_PRINT_CONSOLE == True:
print(string)
if Config.IS_PRINT_FILE == True:
f = open('log/' + filename, 'a')
f.write('[' + du.getYMDHMS() + "]: " + string + "\n")
f.close()
except:
return
def calcTRIX(stock_code, date, period):
global ITERATOR_COUNT
TR = calcEMA(stock_code, date, period)
pday = du.convertDateToString(bd.getStockDate(stock_code, date, 1), "%Y-%m-%d")
ITERATOR_COUNT = 0
TR_pday = calcEMA(stock_code, pday, period)
print TR
print pday
print TR_pday
return (TR - TR_pday) / TR_pday * 100
def get_qfq_maxdate(stockno):
try:
sql = "select max(date) maxdate from stock_qfq_data where code='"+stockno+"'"
engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8')
#df.to_sql('inst_detail', engine, if_exists='append')
conn = MySQLdb.connect(host='localhost',user='******',passwd='123456',db='stock')
cursor = conn.cursor()
n = cursor.execute(sql)
maxdate = ''
for r in cursor:
maxdate = r[0][0:10]
cursor.close()
conn.close
if maxdate=='':
stockDf =ts.get_stock_basics()
sssj = str(stockDf.ix[stockno]['timeToMarket']) #上市日期YYYYMMDD
return dateutil.convertDate(sssj)
return dateutil.get_next_day(maxdate)
except Exception,e:
print e.message
def dates2nums(dates):
"""
Convert python dates to numerical values.
:param dates: (*list*) Python dates.
:returns: (*list*) Numerical values
"""
values = []
for t in dates:
tt = jdate(t)
values.append(DateUtil.toOADate(tt))
return values
def nums2dates(values):
"""
Convert numerical values to python dates.
:param values: Numerical values of date.
:returns: Python dates
"""
tt = []
for v in values:
t = DateUtil.fromOADate(v)
tt.append(pydate(t))
return tt
def getRecoveryFactor(stock_code_163, stock_code_sina, start_date):
url_base = 'http://vip.stock.finance.sina.com.cn/corp/go.php/vMS_FuQuanMarketHistory/stockid/'
url_stock = stock_code_sina + '.phtml?'
today = date.today()
current_year = int(today.strftime("%Y"))
current_quarter = du.getQuarter(int(today.strftime("%m")))
start_year = int(start_date.strftime("%Y"))
start_quarter = du.getQuarter(int(start_date.strftime("%m")))
recovery_factor = []
for year in range(start_year, current_year + 1):
for quarter in range(1, 5):
if (year <= start_year) and (quarter < start_quarter):
continue
if (year >= current_year) and (quarter > current_quarter):
break
url_year = 'year=' + str(year)
url_quarter = '&jidu=' + str(quarter)
url = url_base + url_stock + url_year + url_quarter
#print url
html = urllib.urlopen(url)
content = html.read()
html.close()
soup = BeautifulSoup(content, 'html.parser')
# print type(soup.find(id='FundHoldSharesTable'))
for tr in soup.find(id='FundHoldSharesTable').find_all('tr')[2:]:
row = [stock_code_163, stock_code_sina]
for td in tr.find_all('td'):
for div in td.find_all('div'):
if len(div.find_all('a')) > 0:
row.append(div.a.contents[0].strip())
else:
row.append(div.contents[0].strip())
recovery_factor.append(row)
# print recoveryFactor
return recovery_factor
def calcEMA(stock_code, date, period):
if ITERATOR_COUNT >= MAX_ITERATOR:
EXPMA = MA.calcMA(stock_code, date, period)
# print "MIN Date： " +date+ " MA:"+ str(EXPMA)
return EXPMA
else:
global ITERATOR_COUNT
ITERATOR_COUNT = ITERATOR_COUNT + 1
close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
pday = du.convertDateToString(bd.getStockDate(stock_code, date, 1), "%Y-%m-%d")
EXPMA_pday = calcEMA(stock_code, pday, period)
EXPMA = 2 * (close_today - EXPMA_pday) / (period + 1) + EXPMA_pday
# print date + ": EXPMA: "+str(EXPMA_PDAY)+" CLOSE: " + str(CLOSE_TODAY) + " EXPMA = " +str(EXPMA)
return round(EXPMA, 3)
def get_szzs_maxdate():
try:
sql = "select max(date) maxdate from stock_index_data where code='000001'"
conn = MySQLdb.connect(host='localhost',user='******',passwd='123456',db='stock')
cursor = conn.cursor()
n = cursor.execute(sql)
maxdate = ''
for r in cursor:
maxdate = r[0]
cursor.close()
conn.close
if len(maxdate)>10:
maxdate=maxdate[0:10]
return dateutil.get_next_day(maxdate)
except Exception,e:
print e.message
def sellAction(code=None, name=None, price=None, posi='100'):
if name is None:
df = gs.getDataFrame(code)
name = gs.getStockName(df)
price = str(round(float(df['b1_p'][0]), 2))
posi = '100'
if du.getHMS() < '09:25:00':
df = gs.getDataFrame(code)
pre_close = str(round(float(df['pre_close'][0]), 2))
price = round(float(pre_close) * 0.92, 2)
config_words = code + "," + name + "," + posi + "," + str(price) + ",0"
f_config = open('C:/auto/SellAction.txt', 'w')
f_config.write(config_words)
f_config.close()
pm.sendSellDoneEmail(code)
lu.log("SellAction: 已写入执行句子：" + config_words)
f = open('persist.txt', 'w')
f.write("")
f.close()
def updateWithoutRF(end_date):
stocks = bd.getStockCodes()
for each in stocks:
stock_code = each[0]
stock_code_163 = each[3]
start_date = each[5]
if start_date is None:
start_date = du.convertStringToDate("1990-01-01", "%Y-%m-%d")
elif start_date == end_date:
continue
else:
start_date = start_date + timedelta(1)
data = bd.getStockData(stock_code_163, start_date, end_date)
last_updated_date = data[0].split(",")[0]
bd.insertBasicData(stock_code, data)
bd.insertTechData(stock_code, data)
bd.insertAnalysisData(stock_code, data)
bd.updateMasterDate("LAST_UPDATED_DATE", last_updated_date, stock_code_163)
def get_stu_courseplanlist(self,
login_name,
stu_plan_name,
stu_plan_id,
retrytime=None):
dateutil = DateUtil.DateUtil()
semenum = dateutil.getSCTermNo(stu_plan_name)
request_url = 'https://jxjyxb.bucm.edu.cn/api/v1/student/courseplan/list_stu'
post_data = {
'page': 1,
'pageSize': 100,
'coursePlan.planId': stu_plan_id,
'coursePlan.semenum': semenum
}
try:
response = self.session.post(request_url,
data=post_data,
headers=self.headers)
if response.status_code == 200:
print('选课信息---' + response.text)
stu_course_json = json.loads(response.text)
stu_course_plan = stu_course_json['pager']['datas']
except:
self.log(neterror_msg, True)
set_retrytime = int(self.get_retrytime())
if retrytime is None:
retrytime = int(set_retrytime)
else:
retrytime = int(retrytime) - 1
if retrytime > 0:
self.log('重复尝试第' + str(set_retrytime - retrytime + 1) + '次',
True)
retryinterval = self.get_retryinterval()
time.sleep(retryinterval)
self.get_stu_courseplanlist(login_name, stu_plan_name,
stu_plan_id, retrytime)
return stu_course_plan
def analyzeAllStocks(date):
stock_codes = bd.getStockCodes()
for each in stock_codes:
stock_code = each[0]
analyze(stock_code, du.convertDateToString(date, "%Y-%m-%d"))
import BasicData as fd
from datetime import *
import DateUtil as du
import ROC
# Main function
if __name__ == '__main__':
'''
start_date = datetime.strptime("2016-02-01", '%Y-%m-%d')
end_date = date.today()
stocks = fd.getStocks(True)
print stocks
print "**********************************"
stocks = fd.getStocks(False)
print stocks
print "**********************************"
index = fd.getBasicData("0000001", start_date, end_date)
print index
print "**********************************"
rf = fd.getRecoveryFactor("0600079", "600079", start_date)
print rf
print "**********************************"
resultSet = ROC.getROC("000001", "2015-12-21")
print resultSet[0][0]
'''
print du.convertDateToString(fd.getStockDate("000001", "2015-12-21", 1)[0][0], "%Y-%m-%d")
def sendListenStartEmail(receivers=default_receivers):
if conf.IS_SEND_MAIL == False:
return
Async_req('http://95.163.200.245:11251/sendListenStartEmail/' +
conf.hostname + '/' + du.getYMD() + '/' + receivers).start()
def sendSellDoneEmail(code="002197", receivers=default_receivers):
if conf.IS_SEND_MAIL == False:
return
Async_req('http://95.163.200.245:11251/sendSellDoneEmail/' + code + '/' +
conf.hostname + '/' + du.getYMD() + '/' + receivers).start()
def getHisDataFrame(code, date):
preOneDay = du.getPreDayYMD(30, date)
df = ts.get_k_data(code, preOneDay, date)
return df
def startListenIsBigEmotionGood():
queryWords = "非st；昨日涨停；昨日成交量>1000万；按昨日最终涨停时间升序排序前20；"
w = execjs.eval("encodeURIComponent('" + queryWords + "')")
url = 'https://www.iwencai.com/stockpick/search?typed=1&preParams=&ts=1&f=3&qs=pc_~soniu~stock~stock~history~query&selfsectsn=&querytype=stock&searchfilter=&tid=stockpick&w=' + w
browser = None
try:
browser = webdriver.Chrome(
os.path.abspath('.') + '\driver\chromedriver.exe')
browser.get(url)
time.sleep(4)
browser.implicitly_wait(1)
try:
elem = browser.find_element_by_css_selector(
'#resultWrap #showPerpage select option[value="50"]')
if elem is not None:
elem.click()
except:
lu.log("get_html_forWencai Execption")
html = browser.execute_script(
"return document.documentElement.outerHTML")
browser.quit(
) # 关闭浏览器。当出现异常时记得在任务浏览器中关闭PhantomJS，因为会有多个PhantomJS在运行状态，影响电脑性能
soup = BeautifulSoup(html, "html.parser")
eles = soup.select(
'#resultWrap .static_con_outer .tbody_table tr td.item div.em')
index = 0
codeArr = []
while index < eles.__len__():
o_str = eles[index].text.strip()
if (o_str.isdigit()):
codeArr.append(o_str)
index = index + 1
except Exception as e:
browser.quit()
return None
while True:
if du.getHMS() < '09:25:00':
print("[" + du.getHMS() +
"] startListenIsBigEmotionGood: tik tok...")
time.sleep(3)
continue
riskCount = 0
for code in codeArr:
#记录开盘涨跌幅，只记录一次
if map_code_openrate_rel.keys().__len__(
) == 0 and du.getHMS() > "09:25:30" and du.getHMS() < "09:30:00":
df = gs.getDataFrame(code)
rate = gs.getRate(df)
map_code_openrate_rel[code] = rate
#记录竞价涨跌幅
if du.getHMS() > "09:30:00":
df = gs.getDataFrame(code)
rate = gs.getRate(df)
map_code_now_rel[code] = rate
#计算riskCount
if map_code_openrate_rel.keys().__len__(
) > 0 and map_code_now_rel.keys().__len__() > 0:
for code in map_code_now_rel.keys():
r_now = float(map_code_now_rel[code])
r_open = float(map_code_openrate_rel[code])
#现在涨跌幅<0
if r_now < 0:
riskCount = riskCount + 1
if (r_now - r_open) < 0:
riskCount = riskCount + 1
if map_code_openrate_rel.keys().__len__(
) == 0 or map_code_now_rel.keys().__len__() == 0:
Config.isBigEmotionGood = False
if riskCount > 6:
Config.isBigEmotionGood = False
else:
Config.isBigEmotionGood = True
time.sleep(30)
print("[" + du.getHMS() +
"] startListenIsBigEmotionGood: after cal tik tok...")
def dayreport_generate(importdate):
try:
starttime = time.localtime(time.time())
conn = MySQLdb.connect(host='localhost',user='******',passwd='123456',db='stock',charset="utf8")
cursor = conn.cursor()
#importdate = time.strftime('%Y-%m-%d',time.localtime(time.time()))
#importdate='2015-11-13'
sql ="select * from stock_basic where code not in(select stockno from stock_day_report where importdate like'"+importdate+"%')"
cursor.execute(sql)
for stockrow in cursor.fetchall():
stockno = stockrow[0]
#stockno='600000'
stockname=stockrow[1]
print stockno+stockname
#获得同花顺的相关数据
#在这个地方增加循环的操作
#http://stockpage.10jqka.com.cn/realHead_v2.html#hs_600061
url = "http://stockpage.10jqka.com.cn/"+stockno
request = urllib2.Request(url)
response = urllib2.urlopen(request)
content = response.read()
soup = BeautifulSoup(content,'html5lib')
csvout = csv.writer(sys.stdout)
###获得主营业务
request = urllib2.Request("http://stockpage.10jqka.com.cn/"+stockno+"/operate/")
response = urllib2.urlopen(request)
contentZyyw = response.read()
soupZyyw = BeautifulSoup(contentZyyw,"html5lib")
csvout1 = csv.writer(sys.stdout)
cplxTag = soupZyyw.find("ul",class_="main_intro_list")
if cplxTag==None:
cplx = ""
else:
cplx = cplxTag.li.p.text
print cplx
sshySql= "select * from stock_industry_classified where code=\'"+stockno+"\'"
print sshySql
cursor.execute(sshySql)
sshy = ""
for rowSshy in cursor.fetchall():
sshy = rowSshy[3].strip()
print soup.find_all("dl", class_="company_details")
for content1 in soup.find_all("dl", class_="company_details"):
print "company_details"
print content1
for details in content1.find_all("dt"):
if details.string==unicode("所属地域：","utf-8"):
ssdy= details.next_sibling.next_sibling.string.strip()
print details.string+ssdy
elif details.string==unicode("涉及概念：","utf-8"):
sjgn = details.next_sibling.next_sibling["title"]
print sjgn
elif details.string==unicode("主营业务：","utf-8"):
zyyw = details.next_sibling.next_sibling.string
print zyyw
elif details.string==unicode("上市日期：","utf-8"):
sssj = details.next_sibling.next_sibling.string
print sssj
elif details.string==unicode("每股净资产：","utf-8"):
mgjzc = details.next_sibling.next_sibling.string[:-1]
print mgjzc[:-1]
elif details.string==unicode("每股收益：","utf-8"):
mgsy = details.next_sibling.next_sibling.string[:-1]
print mgsy[:-1]
elif details.string==unicode("净利润：","utf-8"):
jlr = details.next_sibling.next_sibling.string[:-2]
print jlr[:-2]
elif details.string==unicode("净利润增长率：","utf-8"):
jlrzzl = details.next_sibling.next_sibling.string[:-1]
print jlrzzl[:-1]
elif details.string==unicode("营业收入：","utf-8"):
yysr = details.next_sibling.next_sibling.string[:-2]
print yysr[:-2]
elif details.string==unicode("每股现金流：","utf-8"):
mgxjl = details.next_sibling.next_sibling.string[:-1]
print mgxjl[:-1]
elif details.string==unicode("每股公积金：","utf-8"):
mggjj = details.next_sibling.next_sibling.string[:-1]
print mggjj[:-1]
elif details.string==unicode("每股未分配利润：","utf-8"):
mgwfplr = details.next_sibling.next_sibling.string[:-1]
print mgwfplr[:-1]
elif details.string==unicode("总股本：","utf-8"):
zgb = details.next_sibling.next_sibling.string[:-1]
print zgb[:-1]
elif details.string==unicode("流通股：","utf-8"):
ltg = details.next_sibling.next_sibling.string[:-1]
print ltg[:-1]
#从东方财富抓取数据
if stockno[0:2]=="60":
dfUrl = "http://quote.eastmoney.com/sh"+stockno+".html"
else:
dfUrl = "http://quote.eastmoney.com/sz"+stockno+".html"
request = urllib2.Request(dfUrl)
response = urllib2.urlopen(request)
dfcontent = response.read()
dfSoup = BeautifulSoup(dfcontent,"lxml")
csvout = csv.writer(sys.stdout)
hxTableTag = dfSoup.find("table",id="rtp2")
print "hxtabletag"
print hxTableTag
if hxTableTag!=None:
trContent = hxTableTag.find_all("tr")
dtsyl = trContent[0].find_all("td")[1].text[6:]
sjl = trContent[1].find_all("td")[1].text[4:]
mlv = trContent[4].find_all("td")[0].text[4:][:-1]
jlv = trContent[4].find_all("td")[1].text[4:][:-1]
roe = trContent[5].find_all("td")[0].text[4:][:-1]
fzl = trContent[5].find_all("td")[1].text[4:][:-1]
zsz = trContent[6].find_all("td")[1].text[3:][:-1]
print "zsz"+zsz
ltsz = trContent[7].find_all("td")[1].text[3:][:-1]
print "jlv" +trContent[4].find_all("td")[1].text[4:]
#获得解禁时间
jjSql = "select min(jjsj) jjsj from stock_jjsj where stockno='"+stockno+"' and jjsj>='"+importdate+"'"
cursor.execute(jjSql)
jjRow = cursor.fetchone()
print jjRow
if jjRow[0] ==None:
jjsj = ""
else:
jjsj = jjRow[0]
#获得上月收盘价
#获得本日收盘价
#获得上个月
pre_month = dateutil.get_pre_month()
print pre_month
syspjSQL ="select * from stock_day_data where date=(select max(date) from stock_day_data where code='"+stockno+"' and left(date,7)='"+pre_month+"') and code='"+stockno+"' "
brspjSQL = "select * from stock_day_data where date like'"+importdate+"%' and code='"+stockno+"'"
cursor.execute(syspjSQL)
syspjRow = cursor.fetchone()
print syspjRow
if syspjRow==None:
syspj = ""
else:
syspj = str(syspjRow[4])
if syspj is None :
syspj=""
#本日收盘价
cursor.execute(brspjSQL)
brspjRow = cursor.fetchone()
print brspjRow
if None==brspjRow:
print "brspj"
brspj = ""
else:
brspj = str(brspjRow[4])
tenHolder = getTenHolder(stockno)
if tenHolder.find("'") !=-1:
tenHolder = tenHolder.replace("'", "\\'")
gdrs = getGdbhs(stockno)
insertsql = "insert into stock_day_report (stockno,stockname,importdate,ssdy,sjgn,cplx,sshy,sssj,mgjzc,mgsy,jlr,jlrzzl,yysr,mgxjl,mggjj,mgwfplr,zgb,ltg," \
"zsz,ltsz,sjl,dtsyl," \
"mlv,jlv,roe,fzl,jjsj,syspj,brspj,tenholder,gdrs" \
") " \
"values(\'"+stockno+"\',\'"+stockname+"\',\'"+importdate+"\',\'"+ssdy+"\',\'"+sjgn+"\',\'"+cplx+"\',\'"+sshy+"\',\'"+sssj+"\',\'"+mgjzc+"\',\'"+mgsy+"\',\'"+jlr+"\',\'"+jlrzzl+"\',\'"+yysr+"\',\'"+mgxjl+"\',\'"+mggjj+"\',\'"+mgwfplr+"\',\'"+zgb+"\',\'"+ltg+"\'," \
"\'"+zsz+"\',\'"+ltsz+"\',\'"+sjl+"\',\'"+dtsyl+"\',\'"+mlv+"\',\'"+jlv+"\',\'"+roe+"\',\'"+fzl+"\',\'"+jjsj+"\',\'"+syspj+"\',\'"+brspj+"\',\'"+tenHolder+"\',\'"+gdrs+"\')"
print insertsql
cursor.execute(insertsql)
conn.commit()
cursor.close()
df = pd.read_sql("select * from stock_day_report where importdate='"+importdate+"' and brspj!=0 order by sshy,ltg,zgb",conn)
df.rename(columns={'stockno':'股票代码','stockname':'股票名称','sshy':'所属行业','sjgn':'涉及概念','brspj':'本日收盘价','syspj':'上月收盘价','ltg':'流通股','zgb':'总股本','jlr':'净利润','yysr':'营业收入','mgjzc':'每股净资产','mgsy':'每股收益','jlrzzl':'净利润增长率','mgxjl':'每股现金流','mggjj':'每股公积金','mgwfplr':'每股未分配利润','dtsyl':'动态市盈率','sjl':'市净率','ltsz':'流通市值','zsz':'总市值','jjsj':'解禁时间','mlv':'毛利率','jlv':'净利率','roe':'ROE','fzl':'负债率','importdate':'导入日期','sssj':'上市时间','cplx':'产品类型','ssdy':'所属地域','lrzy':'利润总额','tenholder':'十大持股人','gdrs':'股东人数'}, inplace=True)
print df
#首先执行相关数据导入操作
df.to_csv('d:/'+importdate+'.csv',encoding='gbk', index=False)
if mailutil.send_mail("每日股票报告", importdate +"report", r"d:/"+importdate+".csv"):
print "1111"
else:
print "2222！"
except Exception,e:
print e.message
print e
def listenZhangting(self, codeArr):
isEnd = False
line = ''
forbidden_line = ''
forbidden_control_msg = {}
forbidden_control_msg['count'] = 0
forbidden_control_msg['limit'] = 3
loopCount = 0
rate_underZero_codes = []
while True:
if du.getHMS() > '11:30:00' and du.getHMS() < '12:59:30':
time.sleep(10)
print('sleeping...')
obj = Action.getForbiddenCodeString(forbidden_line,
forbidden_control_msg)
forbidden_control_msg = obj['msg']
forbidden_line = obj['line']
# if self.threadLocal.buyCount == Config.positions.__len__():
# isEnd = True
# lu.log("----------------->仓位数组已使用完")
if codeArr.__len__() == 0:
isEnd = True
lu.log("----------------->无监听标的")
if self.isTime2Exit():
isEnd = True
lu.log("----------------->不在设置的交易时间内")
time.sleep(3)
if isEnd is True:
break
begintime = clock()
i = 0
if loopCount == 0 or loopCount % Config.LOOPCOUNT_2_REFRESH_NONEEDTOCHECKISZHANGTING == 0:
print('重新分配监听优化数组，放弃监听')
rate_underZero_codes = []
while i < codeArr.__len__():
code = codeArr[i]
if code in line or code in forbidden_line:
i = i + 1
continue
i = i + 1
# 涨跌幅过滤
if code in rate_underZero_codes:
continue
dataFrame = self.ds.getDataFrame(code)
if dataFrame is None:
continue
if loopCount == 0 or loopCount % Config.LOOPCOUNT_2_REFRESH_NONEEDTOCHECKISZHANGTING == 0:
rate = self.ds.getRate(dataFrame)
if rate < Config.RATE_2_Listen:
print('统计入涨跌幅优化数组，放弃监听->' + code + ":" + str(rate))
rate_underZero_codes.append(code)
else:
print('进入监听名单->' + code + ":" + str(rate))
# 涨跌幅过滤
if code in rate_underZero_codes:
continue
if self.ds.isZhangting(dataFrame) is False:
continue
#Test
# if loopCount >= 0:
# continue
name = self.ds.getStockName(dataFrame)
zhangtingprice = self.ds.getZhangtingPrice(dataFrame)
if self.isShouldBuy():
#posi = Config.positions[self.threadLocal.buyCount]
posi = '100'
if posi != '0':
Action.buyAction(code, name, zhangtingprice, posi)
self.threadLocal.buyCount = self.threadLocal.buyCount + 1
isEnd = True
break
else:
lu.log(
'------------------------------------->posi == "0" 放弃买入'
)
else:
lu.log('------------------------------------->未达到条件放弃买入')
line = line + code + '~'
break
print('$$$$$$$$$$$$zhangtingcodes: ' + line +
' - zhangtingcount: ' + str(line.count('~')))
print(
'$$$$$$$$$$$$spend------------------------------------------------>'
+ str(clock() - begintime))
time.sleep(1)
loopCount = loopCount + 1
print(
'$$$$$$$$$$$$loopC------------------------------------------------>'
+ str(loopCount) + "->" +
str(Config.LOOPCOUNT_2_REFRESH_NONEEDTOCHECKISZHANGTING))
def risk(code, startYMD=du.getPreDayYMD(1)):
days_ForCaculating = 20
today = startYMD
preOneDay = du.getPreDayYMD(days_ForCaculating + 10, startYMD)
df = ts.get_k_data(code, preOneDay, today)
pre_close = 0
riskcount = 0
yesterdayIsZhangting = False
count = 0
little_shangying_count = 0
isHasPlus4PercentDay = False
pre_o_rate = 0
pre_h_rate = 0
pre_c_rate = 0
for x in range(len(df.index)):
if x == 0:
pre_close = df['close'].iloc[x]
continue
# code = df['code'].iloc[x]
# date = df['date'].iloc[x]
# low = df['low'].iloc[x]
# volume = df['volume'].iloc[x]
open = df['open'].iloc[x]
close = df['close'].iloc[x]
high = df['high'].iloc[x]
# 当日最高阶幅度
h_rate = round(float((high - pre_close) / pre_close) * 100, 2)
# 当日收盘幅度
c_rate = round(float((close - pre_close) / pre_close) * 100, 2)
# 当日开盘幅度
o_rate = round(float((open - pre_close) / pre_close) * 100, 2)
# 保证取到14天的数据
if count + days_ForCaculating < len(df.index):
pre_close = df['close'].iloc[x]
count = count + 1
yesterdayIsZhangting = False
if high == close and h_rate > 9.5 and o_rate > 3:
yesterdayIsZhangting = True
continue
#! 板后统计开盘溢价
if yesterdayIsZhangting == True:
if o_rate > 0:
#第一等级风险：虽然高开，但是一路低走，人气涣散
if o_rate > 0 and (o_rate - c_rate) > 6:
riskcount = riskcount + (c_rate - o_rate) * 1000
elif riskcount < 0:
riskcount = riskcount + o_rate * 1000
else:
riskcount = riskcount + o_rate * 3
#print("板后统计开盘溢价: " + date)
else:
riskcount = riskcount + o_rate
#print("板后亏钱开盘: " + str(o_rate*1000))
yesterdayIsZhangting = False
#!第二等级风险：烂板天
if h_rate > 9.5 and h_rate != c_rate and h_rate - c_rate > 5:
#print("烂板: " + date)
riskcount = riskcount + (c_rate - h_rate) * 1000
#a = 1
else:
# ! 高开统计（非烂板基础上）
if c_rate > 2 and o_rate > 1 and h_rate < 8:
riskcount = riskcount + o_rate
#print("高开高走统计: " + date)
# !第三等级风险：长上影+长阴实体
if h_rate - o_rate > 4 and o_rate - c_rate > 4:
riskcount = riskcount + (c_rate - h_rate) * 1000
if h_rate - o_rate > 2:
if little_shangying_count > 0.618 * days_ForCaculating:
riskcount = riskcount - 1
little_shangying_count = little_shangying_count + 1
# 统计这么多天来，是否存在实体涨幅大于4
if c_rate > 4 and c_rate - o_rate > 2:
isHasPlus4PercentDay = True
if h_rate > 9.5 and (h_rate - c_rate) < 1:
yesterdayIsZhangting = True
pre_close = df['close'].iloc[x]
pre_o_rate = o_rate
pre_h_rate = h_rate
pre_c_rate = c_rate
count = count + 1
if riskcount < 1 and riskcount > -1:
riskcount = 0
if isHasPlus4PercentDay == False:
riskcount = riskcount - 10
return riskcount
bd.updateMasterDate("LAST_UPDATED_DATE", last_updated_date, stock_code_163)
logger.info("LAST DATE UPDATED")
if str(index_indicator) == "1":
rf = bd.getRecoveryFactor(stock_code_163, stock_code_sina, start_date)
bd.insertRecoveryFactor(stock_code, rf)
logger.info("INSERT RF DATA COMPLETED")
else:
logger.error("NO DATA IS RECEIVED FROM 163")
result_set = dbu.query(sql)
if len(result_set) > 0:
logger.info("NOT ALL STOCKS ARE UPDATED, WAIT 10 MINUTES FOR NEXT UPDATE")
tm.sleep(10*60)
return "COMPLETED"
if __name__ == '__main__':
end_date = date.today()
if bd.isHoliday(du.convertDateToString(end_date, "%Y-%m-%d")) == "W":
logger.info("TODAY IS WORKING DAY, CONTINUE")
if smartUpdate(end_date) == "COMPLETED":
bd.callTechUpdateProc()
logger.info("CALL PROC TO UPDATE TECH DATA")
tm.sleep(60*5)
sa.analyzeAllStocks(end_date)
logger.info("ANALYSIS COMPLETE")
else:
logger.info("PROGRAM EXITS BECAUSE OF HOLIDAY")
# -*- coding: utf-8 -*-
import traceback
# import hashlib
from DateUtil import *
from DbUtil import *
VIP_USE_TIMES = (5, 80, 600, 1300, 0)
# 月会员3次
# 季度10次
# 半年会员21次
# 年会员43次
# 永久会员
db = DbUtil()
date_util = DateUtil()
def is_use_forever(vip_type):
if vip_type == VipType.forever:
return True
else:
return False
# def get_use_times(vip_type):
# if vip_type in VipType:
# return VIP_USE_TIMES[vip_type.value]
# else:
# return 0
def getZhangTingCodeArr(date):
preDate = du.getPreDayYMD(1, date)
qw = '非st；'+preDate+'日涨跌幅；'+date+'日最大涨幅>9.89；'+preDate+'日涨跌幅<9'
return getCodeArr(qw)