def analysis_stock(stock_code, stock_name, trade_data, boll_result):
base = BaseStock("base")
datas = base.get_stock_data(stock_code, stock_name,
timeUtil.day_after_day(trade_data, -30),
trade_data)
if datas is not None and len(datas) > 1:
if datas[0].get_trade_date() != trade_data:
return None
# 比较时间交易记录
trade_time_data = datas[0]
# 比较时间，前一天交易记录
trade_time_pre = datas[1]
if boll_result is None:
ball = Boll()
boll_result = ball.get_boll(stock_code, stock_name)
if boll_result[trade_data] is None:
return None
# 判断是否上穿Boll线中轨
if trade_time_data.get_close() >= boll_result[trade_time_data.get_trade_date()]["avg_line"] and trade_time_pre.get_close() <= \
boll_result[trade_time_pre.get_trade_date()]["avg_line"]:
# 获取在Boll线中轨下的天数
continue_down_count = 0
for tt in range(1, len(datas)):
if datas[tt].get_close() <= boll_result[
datas[tt].get_trade_date()]["avg_line"]:
continue_down_count += 1
trade_time_data.set_down_line_day_count(continue_down_count)
return trade_time_data
else:
return None
def get_boll(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(
stock_code, stock_name, timeUtil.day_after_day(date, day_len),
date)
if stock_dates is not None and len(stock_dates) > 1:
boll_result = {}
stock_dates.reverse()
# N天之内所有的开盘总和
day_count_sum = 0
for index in range(len(stock_dates)):
self.trade_date.append(stock_dates[index].get_trade_date())
day_count_sum += stock_dates[index].get_close()
if index < self.analysis_day:
boll_result[stock_dates[index].get_trade_date()] = {
"up_track": 0,
"avg_line": 0,
"down_track": 0,
}
else:
day_count_sum = day_count_sum - stock_dates[
index - self.analysis_day].get_close()
middle_value = day_count_sum / self.analysis_day
md = 0.0
for i in range(index - self.analysis_day + 1, index + 1):
md = md + math.pow(
middle_value - stock_dates[i].get_close(), 2)
md = md / self.analysis_day
md = math.sqrt(md)
boll_result[stock_dates[index].get_trade_date()] = {
"up_track": middle_value + 2 * md,
"avg_line": middle_value,
"down_track": middle_value - 2 * md,
}
return boll_result
else:
return None
def get_pre_stock_data(self, stock_code, trade_date, pre_count):
if pre_count is None or pre_count > 0:
return None
stock_datas = self.get_stock_data(
stock_code, "", timeUtil.day_after_day(trade_date, -30),
trade_date)
key_index = -1 * pre_count
if stock_datas is not None and len(stock_datas) > key_index:
return stock_datas[key_index]
return None
# def get_stock_realtime(self, stock_code):
# resultList = self.pro.ts.get_realtime_quotes('000581').values.tolist()
# # ts_code trade_date open high low close pre_close change pct_chg vol amount
# if resultList is not None and len(resultList) > 0:
# for one in resultList:
# print(one)
# 1 000004.SZ,20190722,20.36,20.36,19.60,19.60,20.35,-0.75,-3.69,4882.00,9651.82
# 2 000004.SZ,20190719,20.25,20.82,20.15,20.35,20.23,0.12,0.59,2515.00,5152.03
# 3 000004.SZ,20190718,20.24,20.30,19.67,20.23,20.35,-0.12,-0.59,2410.39,4855.03
if __name__ == '__main__':
base = BaseStock("base")
datas = base.get_stock_data('601318.SH', '国农科技', '20190302',
timeUtil.day_after(0))
# # printUtil.p_list(datas)
print(datas[0].get_trade_date())
##TEST
#
# print(base.query_stock_data('000004.SZ', '国农科技', timeUtil.day_after(-1), timeUtil.day_after(-1))[0])
# stock = base.get_all_stock()
#
# count = 1
# for one in stock:
# base.get_one_stock_daily(one, stock[one])
# count = count + 1
# if count > 20:
def get_macd(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(
stock_code, stock_name, timeUtil.day_after_day(date, day_len),
date)
if stock_dates is not None and len(stock_dates) > 1:
stock_dates.reverse()
macd_result = {}
# 计算EMA
EMA1 = []
EMA2 = []
for index in range(len(stock_dates)):
self.trade_date.append(stock_dates[index].get_trade_date())
if index == 0:
# 初始化短时EMA和长时EMA
EMA1.append(stock_dates[index].get_close())
EMA2.append(stock_dates[index].get_close())
else:
EMA1.append(
2 / (self.short + 1) *
(stock_dates[index].get_close() - EMA1[index - 1]) +
EMA1[index - 1])
EMA2.append(
2 / (self.long + 1) *
(stock_dates[index].get_close() - EMA2[index - 1]) +
EMA2[index - 1])
self._ema_short = EMA1
self._ema_lang = EMA2
self._diff = []
for index in range(len(EMA1)):
self._diff.append(EMA1[index] - EMA2[index])
for index in range(len(EMA1)):
if index == 0:
self._eda.append(self._diff[index])
else:
self._eda.append(
2 / (self.dif + 1) *
(self._diff[index] - self._eda[index - 1]) +
self._eda[index - 1])
# macd
self._delta = []
for index in range(len(self._diff)):
self._delta.append((self._diff[index] - self._eda[index]) * 2)
for ii in range(0, len(self.trade_date)):
macd_result[self.trade_date[ii]] = {
"diff": self._diff[ii],
"eda": self._eda[ii],
"macd": self._delta[ii]
}
return macd_result
else:
print("No Data Find! %s[%s] on %s " %
(stock_code, stock_name, date))
return None
# macd = Macd()
# result = macd.get_macd('000004.SZ', '国农科技')
# print(result)
and pre_stock_data.get_close() > pre_trade_data_avg["5"]:
return current_stock_data
return None
if __name__ == '__main__':
base = BaseStock("base")
stock = base.get_all_stock()
avg = Avg()
ball = Boll()
print("Save data in:" + constant.date_file_path)
for i in range(5):
analysis_date = "20190821"
trade_data = timeUtil.day_after_day(analysis_date, -1 * i)
print("Start---" + trade_data)
result_file_path = constant.date_file_path + "Line5Up10_" + trade_data + ".txt"
# result_file_path = constant.date_file_path + "Line5Up10.txt"
pt.p_file_no_format_add(result_file_path, [
"code,date,O,H,L,C,P,Diff,R,count,sum,avg5,avg10,avg20,up_track,avg_line,down_track"
.replace(",", " ")
])
for one in stock:
shoot_stock = analysis_stock(one, stock[one], trade_data)
if shoot_stock is not None:
print(" %s(%s):%s" %
(stock[one], one, shoot_stock.get_trade_date()))
after_n_day_trade = base.get_stock_data(
shoot_stock.get_ts_code(), stock[one],
def mork_bollBackDownLine(self, stock_code, stock_name, statistics_data):
base = BaseStock("base")
avg = Avg()
avg_result = avg.get_avg(stock_code, stock_name)
ball_class = Boll()
boll_result = ball_class.get_boll(stock_code, stock_name)
for i in range(0, 150):
catch_stock = boll.analysis_stock(
stock_code, stock_name,
timeUtil.day_after_day(timeUtil.today(), i * -1), boll_result)
if catch_stock is not None:
after_datas = base.get_stock_data(
stock_code, stock_name,
timeUtil.day_after_day(catch_stock.get_trade_date(), 1),
timeUtil.day_after_day(catch_stock.get_trade_date(), 20))
after_datas.reverse()
if len(after_datas) >= 1:
catch_down_line_day = catch_stock.get_down_line_day_count()
if catch_down_line_day >= self._minDownDay and catch_down_line_day <= self._maxDownDay:
print(stock_name + ":" + str(catch_stock))
print("%s 突破日股价 %.2f Boll下轨天数 %d" %
(stock_code, catch_stock.get_close(),
catch_down_line_day))
test_trade = {
"stockCode": stock_code,
"startBuy": 0,
"startBuyDate": "",
"endBuy": 0,
"endBuyDate": "",
# 止损率
"lostBuffRate": self._lostBuffRate,
# 止盈利率
"winBuffRate": self._winBuffRate,
"earn": 0,
"earnRate": 0,
"holdDay": 0,
"forceSell": False,
"forceSellType": ""
}
print("Line5[%.3f] - close[%.3f]" %
(avg_result[catch_stock.get_trade_date()]["5"],
catch_stock.get_close()))
self.cal_print_avg_line(catch_stock, avg_result,
after_datas, 0, test_trade)
for cal_day in range(2, self._calDay + 1):
if len(after_datas) >= cal_day:
self.cal_print_avg_line(
catch_stock, avg_result, after_datas,
cal_day - 1, test_trade)
if test_trade["startBuy"] > 0:
print(
"stockCode %s startBuy %.2f startBuyDate %s endBuy %.2f endBuyDate %s earn %.2f earnRate %.2f holdDay %d forceSell %s forceSellType %s"
%
(test_trade["stockCode"],
test_trade["startBuy"],
test_trade["startBuyDate"],
test_trade["endBuy"],
test_trade["endBuyDate"], test_trade["earn"],
test_trade["earnRate"], test_trade["holdDay"],
test_trade["forceSell"],
test_trade["forceSellType"]))
if test_trade["forceSellType"] == "down5Line":
statistics_data[
"down5LineTime"] = statistics_data[
"down5LineTime"] + 1
statistics_data[
"down5LineMoney"] = statistics_data[
"down5LineMoney"] + test_trade[
"earnRate"]
elif test_trade["forceSellType"] == "winBuffRate":
statistics_data[
"winTime"] = statistics_data["winTime"] + 1
statistics_data["winMoney"] = statistics_data[
"winMoney"] + test_trade["earnRate"]
elif test_trade["forceSellType"] == "lostBuffRate":
statistics_data["lostTime"] = statistics_data[
"lostTime"] + 1
statistics_data["lostMoney"] = statistics_data[
"lostMoney"] + test_trade["earnRate"]
else:
statistics_data["otherTime"] = statistics_data[
"otherTime"] + 1
statistics_data[
"otherMoney"] = statistics_data[
"otherMoney"] + test_trade["earnRate"]
print(
"code %s winTime %d winMoney %.3f down5LineTime %d down5LineMoney %.3f lostTime %d lostMoney %.3f otherTime %d otherMoney %.3f"
% (stock_code, statistics_data["winTime"],
statistics_data["winMoney"],
statistics_data["down5LineTime"],
statistics_data["down5LineMoney"],
statistics_data["lostTime"],
statistics_data["lostMoney"],
statistics_data["otherTime"],
statistics_data["otherMoney"]))
return statistics_data
from Analysis import Analysis
from indexData.MofComData import MofComData
from indexData.PigPrice365Day import PigData
from tools.PrintUtil import *
from indexData.BaseData import BaseData
import tools.TimeUtil as tu
import IndexConstants
bd = BaseData('sample')
mofComData = MofComData('MofComData')
analysis = Analysis()
next_month = tu.qi_huo_next_month()
pre_year_date = tu.pre_year_date()
today_date = tu.today()
cycle_index = [1, 2, 5, 10, 30, 100, 200]
# 猪肉
pigDate = PigData("猪肉")
p_file(IndexConstants.date_file_path + 'qihuo' + today_date + '.txt',
analysis.change_rate_day(pigDate.get_data(), cycle_index), pigDate.name)
# 鸡蛋
p_file(
IndexConstants.date_file_path + 'qihuo' + today_date + '.txt',
analysis.change_rate_day(
bd.get_qihuo_simaple('JD' + next_month + '.DCE', pre_year_date,
today_date, '鸡蛋'), cycle_index),
'鸡蛋' + tu.qi_huo_next_month())
# 铁矿石
def get_avg(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(stock_code, stock_name, timeUtil.day_after_day(date, day_len), date)
if stock_dates is not None and len(stock_dates) > 1:
avg_result= {}
stock_dates.reverse()
day3_line = []
day4_line = []
day5_line = []
day6_line = []
day7_line = []
day8_line = []
day9_line = []
day10_line = []
day15_line = []
day20_line = []
day30_line = []
day60_line = []
day120_line = []
trade_date = []
day3 = 0
day4 = 0
day5 = 0
day6 = 0
day7 = 0
day8 = 0
day9 = 0
day10 = 0
day15 = 0
day20 = 0
day30 = 0
day60 = 0
day120 = 0
for index in range(len(stock_dates)):
trade_date.append(stock_dates[index].get_trade_date())
# Day 3
day3 += stock_dates[index].get_close()
if index < 3:
day3_line.append(day3 / (index + 1))
else:
day3 -= stock_dates[index - 3].get_close()
day3_line.append(day3 / 3)
# Day 4
day4 += stock_dates[index].get_close()
if index < 4:
day4_line.append(day4 / (index + 1))
else:
day4 -= stock_dates[index - 4].get_close()
day4_line.append(day4 / 4)
# Day 5
day5 += stock_dates[index].get_close()
if index < 5:
day5_line.append(day5 / (index + 1))
else:
day5 -= stock_dates[index - 5].get_close()
day5_line.append(day5 / 5)
# Day 6
day6 += stock_dates[index].get_close()
if index < 6:
day6_line.append(day6 / (index + 1))
else:
day6 -= stock_dates[index - 6].get_close()
day6_line.append(day6 / 6)
# Day 7
day7 += stock_dates[index].get_close()
if index < 7:
day7_line.append(day7 / (index + 1))
else:
day7 -= stock_dates[index - 7].get_close()
day7_line.append(day7 / 7)
# Day 8
day8 += stock_dates[index].get_close()
if index < 8:
day8_line.append(day8 / (index + 1))
else:
day8 -= stock_dates[index - 8].get_close()
day8_line.append(day8 / 8)
# Day 9
day9 += stock_dates[index].get_close()
if index < 9:
day9_line.append(day9 / (index + 1))
else:
day9 -= stock_dates[index - 9].get_close()
day9_line.append(day9 / 9)
# Day 10
day10 += stock_dates[index].get_close()
if index < 10:
day10_line.append(day10 / (index + 1))
else:
day10 -= stock_dates[index - 10].get_close()
day10_line.append(day10 / 10)
# Day 15
day15 += stock_dates[index].get_close()
if index < 15:
day15_line.append(day15 / (index + 1))
else:
day15 -= stock_dates[index - 15].get_close()
day15_line.append(day15 / 15)
# Day 20
day20 += stock_dates[index].get_close()
if index < 20:
day20_line.append(day20 / (index + 1))
else:
day20 -= stock_dates[index - 20].get_close()
day20_line.append(day20 / 20)
# Day 30
day30 += stock_dates[index].get_close()
if index < 30:
day30_line.append(day30 / (index + 1))
else:
day30 -= stock_dates[index - 30].get_close()
day30_line.append(day30 / 30)
# Day 60
day60 += stock_dates[index].get_close()
if index < 60:
day60_line.append(day60 / (index + 1))
else:
day60 -= stock_dates[index - 60].get_close()
day60_line.append(day60 / 60)
# Day 120
day120 += stock_dates[index].get_close()
if index < 120:
day120_line.append(day120 / (index + 1))
else:
day120 -= stock_dates[index - 120].get_close()
day120_line.append(day120 / 120)
# END LOOP-------------------------------
for ii in range(0,len(trade_date)):
avg_result[trade_date[ii]] = {
"3": day3_line[ii],
"4": day4_line[ii],
"5": day5_line[ii],
"6": day6_line[ii],
"7": day7_line[ii],
"8": day8_line[ii],
"9": day9_line[ii],
"10": day10_line[ii],
"15": day15_line[ii],
"20": day20_line[ii],
"30": day30_line[ii],
"60": day60_line[ii],
"120": day120_line[ii]
}
return avg_result
else:
return None
def get_data(self):
res_data = self.get_ts_qihuo("I" + tu.qi_huo_next_month() + '.DCE',
tu.pre_year_date(), tu.today())
# res_data = self.get_ts_qihuo("I1906" + '.DCE', tu.pre_year_date(), tu.today())
self.return_data = {"name": "铁矿石", "week": 7, "data": res_data}
return self.return_data
count = 1
index = 1
for one in stock:
count = count + 1
if count < 3509:
continue
else:
index = index + 1
index = index + 1
print(str(count) + "--" + one)
stock_datas = base.query_stock_data(one, stock[one], timeUtil.day_after(-20000), timeUtil.today())
if stock_datas is not None:
stock_file_path = constant.stock_file_path + one + '.txt'
p_file_list_with_no_format(stock_file_path, stock_datas)
# stock_datas_hfq = base.query_stock_data_hfq(one, stock[one], timeUtil.day_after(-20000), timeUtil.today())
# if stock_datas_hfq is not None:
# stock_file_path = constant.stock_file_path_hfq + one + '.txt'
# p_file_list_with_no_format(stock_file_path, stock_datas_hfq)
if index > 190:
print("wait 1 minute for tushare rule.....")
time.sleep(60)
index = 0