def get_zhangtingconcept_countMap(dayCount):
nowDate = fd.getLastestOpenDate()
#（1）获取所有concept的集合(大于1)
startDate = fd.preOpenDate(nowDate, dayCount)
rows = dao.select("select concept from zhangting_concept where date>=%s group by concept", (startDate))
concepts = []
for row in rows:
concept = row['concept']
concepts.append(concept)
#（2）迭代concept，获取count，在特定的date
# date = nowDate
# while date > startDate:
# rows = dao.select("select concept, count(0) count from zhangting_concept where date=%s group by concept", (date))
# for row in rows:
# concept = row['concept']
# count = row['count']
date = startDate
ret = {}
concept_count_rel = {}
for concept in concepts:
countsArr = []
_date = date
while _date <= nowDate:
row = dao.select("select count(0) count from zhangting_concept where date=%s and concept=%s", (_date, concept))
count = str(row[0]['count'])
countsArr.append(count)
_date = fd.nextOpenDate(_date, 1)
concept_count_rel.setdefault(concept, countsArr)
ret.setdefault('concept_count_rel', concept_count_rel)
ret.setdefault('concepts', concepts)
#（3）返回图标接受的数据model
# endDate = fd.getLastestOpenDate()
# startDate = fd.preOpenDate(endDate, dayCount)
# nowDate = startDate
# ret = {}
# while nowDate <= endDate:
# try:
# arr = dao.select("select count(0) count, concept from zhangting_concept where date = %s GROUP BY concept", (nowDate))
# except Exception as e:
# return "get_zhangtingconcept_countMap mysql error"
# map = {}
# for it in arr:
# count = it['count']
# concept = it['concept']
# map.setdefault(concept, count)
# ret[nowDate] = map
# nowDate = fd.nextOpenDate(nowDate, 1)
dates = []
_date = date
while _date <= nowDate:
dates.append(_date)
_date = fd.nextOpenDate(_date, 1)
ret.setdefault('dates', dates)
return ret
def crawlSecurityData_AtRear(dayCount):
securities = fd.get_all_securities()
max_date = dao.select("select max(date) max_date from security_data",
())[0]['max_date']
endDate = fd.getLastestOpenDate()
if max_date is not None:
startDate = fd.nextOpenDate(max_date, 1)
else:
startDate = fd.preOpenDate(endDate, dayCount)
isFromHist = False
if startDate > endDate: return
for code in securities:
count = 0
df = ts.get_k_data(code, startDate, endDate)
if df.index.__len__() == 0:
isFromHist = True
df = ts.get_hist_data(code, startDate, endDate)
arr_values = []
while count < df.index.__len__():
open = str(df['open'].values[count])
close = str(df['close'].values[count])
high = str(df['high'].values[count])
low = str(df['low'].values[count])
volume = str(df['volume'].values[count])
if isFromHist is True:
date = df.index[count]
else:
date = str(df['date'].values[count])
arr_values.append((code, date, open, close, high, low, volume))
count = count + 1
print("Date: " + date + " Code: " + code)
dao.update("delete from security_data where code=%s and date=%s",
(code, date))
dao.updatemany(
"insert into security_data(code, date, open, close, high, low, volume) values(%s,%s,%s,%s,%s,%s,%s)",
arr_values)
def caculateMarketAnd2DB():
openDates = fd.getOpenDates()
openDates.reverse()
max_date = dao.select("select max(date) max_date from security_data",
())[0]['max_date']
min_date = dao.select("select min(date) min_date from security_data",
())[0]['min_date']
startDate = min_date
endDate = max_date
pdv = None
for date in openDates:
if date == '' or date > endDate or date < fd.nextOpenDate(
startDate, 10):
continue
arr = dao.select(
"select code, date, open, close, high, low, volume from "
"security_data where date=%s", (date))
ye_arr = dao.select(
"select code, date, open, close, high, low, volume from "
"security_data where date=(select max(date) from security_data where date<%s) ",
(date))
ty_arr = dao.select(
"select code, date, open, close, high, low, volume from "
"security_data where date=(select max(date) from security_data where date<%s) ",
(fd.preOpenDate(date, 1)))
pre_ty_arr = dao.select(
"select code, date, open, close, high, low, volume from "
"security_data where date=(select max(date) from security_data where date<%s) ",
(fd.preOpenDate(date, 2)))
code_item = {}
code_ye_item = {}
code_ty_item = {}
code_pre_ty_item = {}
for item in arr:
code_item[item['code']] = item
for ye_item in ye_arr:
code_ye_item[ye_item['code']] = ye_item
for ty_item in ty_arr:
code_ty_item[ty_item['code']] = ty_item
for pre_ty_item in pre_ty_arr:
code_pre_ty_item[pre_ty_item['code']] = pre_ty_item
yzzt_count = 0
yzdt_count = 0
dt = 0
zrzt = 0
zt_count = 0
zt_high_count = 0
_1bzt_count = 0
_1bzt_high_count = 0
_2bzt_count = 0
_2bzt_high_count = 0
_3bzt_count = 0
_3bzt_high_count = 0
_4bzt_count = 0
_4bzt_high_count = 0
_5bzt_count = 0
_5bzt_high_count = 0
_6bzt_count = 0
_6bzt_high_count = 0
sum_chg = 0
ye_zt_count = 0
for item in arr:
code = item['code']
# if code != '000760': continue
try:
ye_item = code_ye_item[code]
except:
_date = item['date']
ye_items = dao.select(
"select code, date, open, close, high, low, volume from security_data "
"where code=%s and date=(select max(date) from security_data where date<%s and code=%s) ",
(code, _date, code))
if ye_items is None or ye_items.__len__() == 0:
continue
else:
ye_item = ye_items[0]
try:
ty_item = code_ty_item[code]
except:
_date = ye_item['date']
ty_items = dao.select(
"select code, date, open, close, high, low, volume from security_data "
"where code=%s and date=(select max(date) from security_data where date<%s and code=%s) ",
(code, _date, code))
if ty_items is None or ty_items.__len__() == 0: continue
else: ty_item = ty_items[0]
try:
pre_ty_item = code_pre_ty_item[code]
except:
_date = ty_item['date']
pre_ty_items = dao.select(
"select code, date, open, close, high, low, volume from security_data "
"where code=%s and date=(select max(date) from security_data where date<%s and code=%s) ",
(code, _date, code))
if pre_ty_items is None or pre_ty_items.__len__() == 0:
continue
else:
pre_ty_item = pre_ty_items[0]
if (_is_yzzt(item, ye_item) == True): yzzt_count = yzzt_count + 1
if (_is_yzdt(item, ye_item) == True): yzdt_count = yzdt_count + 1
if (_is_dt(ye_item, ty_item) == True): dt = dt + 1
if (_is_zrzt(ye_item, ty_item) == True): zrzt = zrzt + 1
lb = _is_lb(code, date, item, ye_item, ty_item)
if (lb == 6): _6bzt_count = _6bzt_count + 1
elif (lb == 5): _5bzt_count = _5bzt_count + 1
elif (lb == 4): _4bzt_count = _4bzt_count + 1
elif (lb == 3): _3bzt_count = _3bzt_count + 1
elif (lb == 2): _2bzt_count = _2bzt_count + 1
elif (lb == 1): _1bzt_count = _1bzt_count + 1
if is_zt(item, ye_item) == True: zt_count = zt_count + 1
if is_high_zt(item, ye_item) == True:
zt_high_count = zt_high_count + 1
pre_lb = _is_ye_lb(code, date, ye_item, ty_item, pre_ty_item)
if pre_lb == 0 and is_high_zt(item, ye_item):
_1bzt_high_count = _1bzt_high_count + 1
if pre_lb == 1 and is_high_zt(item, ye_item) == True:
_2bzt_high_count = _2bzt_high_count + 1
if pre_lb == 2 and is_high_zt(item, ye_item) == True:
_3bzt_high_count = _3bzt_high_count + 1
if pre_lb == 3 and is_high_zt(item, ye_item) == True:
_4bzt_high_count = _4bzt_high_count + 1
if pre_lb == 4 and is_high_zt(item, ye_item) == True:
_5bzt_high_count = _5bzt_high_count + 1
if pre_lb == 5 and is_high_zt(item, ye_item) == True:
_6bzt_high_count = _6bzt_high_count + 1
if is_ye_zt(ye_item, ty_item) == True:
today_chg = get_chg(item, ye_item)
sum_chg = sum_chg + today_chg
ye_zt_count = ye_zt_count + 1
print("Code: " + code + " Date: " + date)
zt_success = None
if zt_high_count > 0: zt_success = round((zt_count / zt_high_count), 2)
_1bzt_success = -1
if _1bzt_high_count > 0:
_1bzt_success = round((_1bzt_count / _1bzt_high_count), 2)
_2bzt_success = -1
if _2bzt_high_count > 0:
_2bzt_success = round((_2bzt_count / _2bzt_high_count), 2)
_3bzt_success = -1
if _3bzt_high_count > 0:
_3bzt_success = round((_3bzt_count / _3bzt_high_count), 2)
_4bzt_success = -1
if _4bzt_high_count > 0:
_4bzt_success = round((_4bzt_count / _4bzt_high_count), 2)
_5bzt_success = -1
if _5bzt_high_count > 0:
_5bzt_success = round((_5bzt_count / _5bzt_high_count), 2)
_6bzt_success = -1
if _6bzt_high_count > 0:
_6bzt_success = round((_6bzt_count / _6bzt_high_count), 2)
today_avg_chg_when_yezt = round((sum_chg / ye_zt_count), 2)
print('Date: ' + date + ' yzzt_count: ' + str(yzzt_count) +
' yzdt_count: ' + str(yzdt_count) + ' dt: ' + str(dt) +
' zrzt:' + str(zrzt))
dao.update("delete from market_environment where date=%s", (date))
if pdv is None:
dao.update(
"insert into market_environment(date, yzzt_count, yzdt_count, dt_count, zrzt_count, "
"1bzt_count, 2bzt_count, 3bzt_count, 4bzt_count, 5bzt_count, 6bzt_count, "
"1bzt_success, 2bzt_success, 3bzt_success, 4bzt_success, 5bzt_success, 6bzt_success, "
"zt_success, today_avg_chg_when_yezt) values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)",
(date, yzzt_count, yzdt_count, dt, zrzt, _1bzt_count,
_2bzt_count, _3bzt_count, _4bzt_count, _5bzt_count,
_6bzt_count, _1bzt_success, _2bzt_success, _3bzt_success,
_4bzt_success, _5bzt_success, _6bzt_success, zt_success,
today_avg_chg_when_yezt))
else:
dao.update(
"insert into market_environment(date, yzzt_count, ye_yzzt_count, yzdt_count, ye_yzdt_count, dt_count, ye_dt_count, zrzt_count, ye_zrzt_count, "
"1bzt_count, ye_1bzt_count, 2bzt_count, ye_2bzt_count, 3bzt_count, ye_3bzt_count, 4bzt_count, ye_4bzt_count, 5bzt_count, ye_5bzt_count, 6bzt_count, ye_6bzt_count, "
"1bzt_success, ye_1bzt_success, 2bzt_success, ye_2bzt_success, 3bzt_success, ye_3bzt_success, 4bzt_success, ye_4bzt_success, 5bzt_success, ye_5bzt_success, 6bzt_success, ye_6bzt_success, "
"zt_success, ye_zt_success, today_avg_chg_when_yezt, ye_today_avg_chg_when_yezt) values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,"
"%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)",
(date, yzzt_count, pdv[1], yzdt_count, pdv[2], dt, pdv[3],
zrzt, pdv[4], _1bzt_count, pdv[5], _2bzt_count, pdv[6],
_3bzt_count, pdv[7], _4bzt_count, pdv[8], _5bzt_count, pdv[9],
_6bzt_count, pdv[10], _1bzt_success, pdv[11], _2bzt_success,
pdv[12], _3bzt_success, pdv[13], _4bzt_success, pdv[14],
_5bzt_success, pdv[15], _6bzt_success, pdv[16], zt_success,
pdv[17], today_avg_chg_when_yezt, pdv[18]))
pdv = (date, yzzt_count, yzdt_count, dt, zrzt, _1bzt_count,
_2bzt_count, _3bzt_count, _4bzt_count, _5bzt_count, _6bzt_count,
_1bzt_success, _2bzt_success, _3bzt_success, _4bzt_success,
_5bzt_success, _6bzt_success, zt_success,
today_avg_chg_when_yezt)