def main():
act = input(
"1.执行今日操作\n2.进行数据模拟\n 3.拉取全部基金列表\n4.拉取指定基金数据\n5.进行当前数据排名\n6.修复拉取忽略列表\n"
)
if act == "1":
for code in code_list:
market = simulation_market()
market.code = code
market.handel_today()
elif act == "2":
market = simulation_market()
code = input("fund code = ")
start_day = input("start date = ")
end_day = input("end date = ")
start_money = int(input("start money = "))
market.auto_running(code, start_day, end_day, start_money)
elif act == "3":
fund_data_manager.get_ins().check_out_all_fund_code()
elif act == "4":
fund_data_manager.get_ins().check_out_fund_base_data()
elif act == "5":
fund_filter.rank_fund_base_data()
elif act == "6":
db = db_loader.get_ins().load_db("fund_base_data")
code_list_cur = db.get_all_keys()
ignore_db = db_loader.get_ins().load_db("ignore_base_data_pull_list")
ignore_db.set_info("ignore_list", code_list_cur)
db_loader.get_ins().close()
def rank_fund_base_data():
db = db_loader.get_ins().load_db("fund_base_data")
fund_list_db = db_loader.get_ins().load_db("fund_list")
key_list = db.get_all_keys()
filter_list = []
filter_type = ["股票型", "指数型"]
for key in key_list:
if not fund_list_db.get_info(key)[3] in filter_type:
continue
dic = db.get_info(key)
filter1 = False or "sharpe_rate" in dic
filter2 = False or "standard_dev" in dic
filter3 = False or "rank4" in dic
filter4 = False or "same_rank" in dic
filter5 = False or "stage_rate" in dic
filter6 = False or "same_avg" in dic
filter7 = False or "hs_300" in dic
if filter1 and filter2 and filter3 and filter4 and filter5 and filter6 and filter7:
filter_list.append(key)
score_list = []
for code in filter_list:
item = filter_code(code)
score_list.append(item)
sort_list = []
for item in score_list:
is_insert = True
for index in range(0, len(sort_list)):
if sort_list[index][1] < item[1]:
is_insert = False
sort_list.insert(index, item)
break
if is_insert:
sort_list.append(item)
f = open('fund_rank.csv', "w", encoding='utf-8-sig', newline='')
csv_writer = csv.writer(f)
csv_writer.writerow(
["代码", "基金名", "四分位", "夏普率", "标准差", "同类排名", "阶段涨幅", "总分"])
fund_db = db_loader.get_ins().load_db("fund_list")
for item in sort_list:
code = item[0]
name = fund_db.get_info(code)[2]
score_list = item[2]
all_score = item[1]
rank4 = score_list[0]
sharpe = score_list[1]
standard = score_list[2]
same = score_list[3]
stage = score_list[4]
csv_writer.writerow(
[code, name, rank4, sharpe, standard, same, stage, all_score])
f.close()
def handel_today(self):
if self.code == None:
self.code = input("input code = ")
else:
print("====================> handel ", self.code)
is_exist = fund_data_manager.get_ins().check_fund_data_exist(self.code)
if not is_exist:
print("缺少基础数据库，需要先checkout当前基金数据")
fund_data_puller.main()
tactics = None
if fund_data_manager.get_ins().check_fund_data_exist("running_data_" +
self.code):
print("加载交易进程")
tactics = every_day_tactics(0, "", self.code)
tactics.load_today()
else:
print("不存在该进程")
if input("初始化交易进程？(Y/N) ") == "y":
start_date = input("start date (year-mon-day) ")
if start_date == "":
today_struct = time.localtime()
start_date = "{0}-{1}-{2}".format(
str(today_struct[0]).zfill(2),
str(today_struct[1]).zfill(2),
str(today_struct[2]).zfill(2))
start_money = input("start money ")
tactics = every_day_tactics(int(start_money), start_date,
self.code)
db_loader.get_ins().load_db("running_data_" + self.code)
else:
return
self.tactics.append(tactics)
if fund_data_manager.get_ins().check_today_need_pull(self.code):
tactics.update_db_data()
today_struct = time.localtime()
today = "{0}-{1}-{2}".format(
str(today_struct[0]).zfill(2),
str(today_struct[1]).zfill(2),
str(today_struct[2]).zfill(2))
print("今日交易日期", today, "操作代码", self.code)
is_go = True
self.today = today
tactics.on_end_today(self.today)
self.simulation()
tactics.save_today()
if input("显示折线图？(Y/N) ") == "y":
ret = self.filter_tactic_record()
self.draw_plt(ret)
def check_today_need_pull(self,code):
pull_record_db = db_loader.get_ins().load_db("pull_record")
date = pull_record_db.get_info(code)
if date == None :
return True
else:
today_struct = time.localtime()
today_date = "{0}-{1}-{2}".format(str(today_struct[0]).zfill(2),str(today_struct[1]).zfill(2),str(today_struct[2]).zfill(2))
today_stamp = time.mktime(time.strptime(today_date,'%Y-%m-%d'))
last_stamp = time.mktime(time.strptime(date,'%Y-%m-%d'))
return today_stamp > last_stamp
def get_day_data(self,code,day): db = db_loader.get_ins().load_db(code) data = db.get_info(day) if not data: db.set_info(day,"sub") return "sub" else: if data != "sub": data[1] = float(data[1]) data[2] = float(data[2]) return data
def main():
act = str(input(" update or check out ? (1/2) "))
code = str(input("input code = "))
if act == "2":
if db_loader.get_ins().check_db_exist(code):
go = input("this code data is exist ! go on ? y/n ")
if go == "y":
update(code)
return
elif go == "n":
print("cancel CHECK OUT")
return
else:
check_out(code)
return
elif act == "1":
if db_loader.get_ins().check_db_exist(code):
update(code)
return
else:
check_out(code)
return
def save_today(self):
db = db_loader.get_ins().get_db("running_data_" + self.code)
db.set_info("start_money", self.start_money)
db.set_info("trading_list", self.trading_list)
db.set_info("cur_money", self.cur_money)
db.set_info("hold_stock", self.hold_stock)
db.set_info("last_money", self.last_money)
db.set_info("start_day", self.start_day)
db.set_info("today", self.today)
db.set_info("record_list", self.record_list)
db.set_info("today_trading_money", self.today_trading_money)
db.set_info("today_sell_vol", self.today_sell_vol)
db.set_info("temp_data", self.temp_data)
db.set_info("buy_list", self.buy_list)
db.set_info("risk_per", self.risk_per)
db.set_info("price_list", self.price_list)
db.set_info("sell_per", self.sell_per)
db.set_info("wave", self.wave)
db.set_info("wave_dir", self.wave_dir)
db.set_info("last_dir", self.last_dir)
db.set_info("limit_price", self.limit_price)
db.flush()
def filter_code(code):
print(code)
db = db_loader.get_ins().load_db("fund_base_data")
dic = db.get_info(code)
rank4 = filter_rank4(dic["rank4"])
sharpe = filter_sharpe_rate(dic["sharpe_rate"])
standard = filter_standard_dev(dic["standard_dev"])
same = filter_rank(dic["same_rank"])
ret = filter_stage_rate(dic["stage_rate"], dic["same_avg"], dic["hs_300"])
stage = ret[0]
samve_avg = ret[1]
hs = ret[2]
nrank4 = np.array(rank4)
nsharpe = np.array(sharpe)
nstandard = np.array(standard)
nsame = np.array(same)
nstage = np.array(stage)
nsame_avg = np.array(samve_avg)
nhs = np.array(hs)
nstage = nstage - nsame_avg + (nstage - nhs)
score = 0
data = {
"rank4": nrank4,
"sharpe": nsharpe,
"standard": nstandard,
"same": nsame,
"stage": nstage,
}
score_list = []
for key in data:
arg1 = data[key]
arg2 = cost_list[key]
cur_score = np.multiply(arg1, arg2).sum() * fix_list[key]
score += cur_score
score_list.append(round(cur_score, 3))
return (code, score, score_list)
def load_today(self):
db = db_loader.get_ins().get_db("running_data_" + self.code)
self.start_money = db.get_info("start_money")
self.last_money = db.get_info("last_money")
self.cur_money = db.get_info("cur_money")
self.trading_list = db.get_info("trading_list")
self.hold_stock = db.get_info("hold_stock")
self.start_day = db.get_info("start_day")
self.today = db.get_info("today")
self.record_list = db.get_info("record_list")
self.today_trading_money = db.get_info("today_trading_money")
self.today_sell_vol = db.get_info("today_sell_vol")
self.temp_data = db.get_info("temp_data")
self.buy_list = db.get_info("buy_list")
self.risk_per = db.get_info("risk_per")
self.price_list = db.get_info("price_list")
self.sell_per = db.get_info("sell_per")
date = self.find_next_trad_day(self.start_day)
self.start_price = fund_data_manager.get_ins().get_day_data(
self.code, date)
self.wave = db.get_info("wave") or []
self.wave_dir = db.get_info("wave_dir") or 0
self.last_dir = db.get_info("last_dir") or 0
self.limit_price = db.get_info("limit_price") or 0
def check_out_fund_base_data(self):
db = db_loader.get_ins().load_db("fund_list")
code_list = db.get_all_keys()
spider.catch_fund_base_data(code_list)
def check_out_all_fund_code(self):
data_list = spider.catch_all_fund_list()
db = db_loader.get_ins().load_db("fund_list")
for item in data_list:
db.set_info(item[0],item)
def save_check_out_date(self,code,date):
pull_record_db = db_loader.get_ins().load_db("pull_record")
pull_record_db.set_info(code,date)
def check_fund_data_exist(self,code): return db_loader.get_ins().check_db_exist(code)
def set_history_data(self,code,server_data): db = db_loader.get_ins().load_db(code) for item in server_data: key = item[0] db.set_info(key,item) db.flush()
def test():
db = db_loader.get_ins().load_db("fund_list")
info = db.get_info("004698")
print(info)
def catch_fund_base_data(code_list):
db = db_loader.get_ins().load_db("fund_base_data")
ignore_db = db_loader.get_ins().load_db("ignore_base_data_pull_list")
ignore_list = ignore_db.get_info("ignore_list") or []
base_url = 'http://fund.eastmoney.com/{0}.html?spm=001.1.swh'
sharpe_url = 'http://fundf10.eastmoney.com/tsdata_{0}.html'
driver = webdriver.PhantomJS(
executable_path=
r"C:\\Users\\myppc\\Desktop\\hzy\\phantomjs-2.1.1-windows\\bin\\phantomjs.exe"
)
for code in code_list:
if code in ignore_list:
continue
info = {}
try:
url = base_url.format(code)
driver.get(url)
body_element = driver.find_element_by_xpath(
"//div[@id='body']").find_element_by_xpath(
"//div[@class='quotationItem_left quotationItem_left02']")
gain_element = body_element.find_element_by_xpath(
"//div[@id='IncreaseAmount']").find_element_by_xpath(
"//li[@id='increaseAmount_stage']")
gain_text = gain_element.text
gain_text_list = re.split(
"阶段涨幅\n|同类平均\n|沪深300\n|跟踪标的\n|同类排名\n|四分位排名\n", gain_text)[1:]
if "跟踪标的\n" in gain_text:
del gain_text_list[3]
name_list = [
"stage_rate", "same_avg", "hs_300", "same_rank", "rank4"
]
index = 0
for item in gain_text_list:
name = name_list[index]
info[name] = item.split("\n")
index += 1
db.set_info(code, info)
print("succ stage1 ", code)
except BaseException:
print("check out error 1 ", code)
db.flush()
time.sleep(round(random.uniform(0.5, 2.5), 2))
try:
url = sharpe_url.format(code)
driver.get(url)
sharpe_element = driver.find_element_by_xpath(
"//div[@class='boxitem w790']").find_element_by_xpath(
"//table[@class='fxtb']")
sharpe_text = sharpe_element.text
sharpe_text_list = re.split("\n标准差 |\n夏普比率 |\n信息比率",
sharpe_text)[1:]
if "\n信息比率" in sharpe_text:
del sharpe_text_list[2]
name_list = ["standard_dev", "sharpe_rate"]
index = 0
for item in sharpe_text_list:
name = name_list[index]
info[name] = item.split(" ")
index += 1
db.set_info(code, info)
print("succ stage2 ", code)
except BaseException:
print("check out error 2 ", code)
db.flush()
ignore_list.append(code)
ignore_db.set_info("ignore_list", ignore_list)
time.sleep(round(random.uniform(0.5, 2.5), 2))
db.flush()
ignore_db.flush()