def start_tk_crawl():
global dm
dm = DBManager("history_k_data")
# 初始化baostock
bs.login()
# 获取股票代码列表
code_list = dm.get_code_list()
for item in code_list:
max_try = 8 # 失败重连次数
ticker = item["ticker"]
print("开始加载股票数据：" + str(ticker))
for tries in range(max_try):
rs = bs.query_history_k_data_plus(
ticker,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
start_date='2008-01-01',
end_date='2019-05-31',
frequency="d",
adjustflag="3")
if rs.error_code == '0':
parse_pager(rs, ticker) # 解析数据
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
print("加载股票数据失败：" + str(ticker))
print("加载股票数据完成")
bs.logout()
def start_tk_crawl():
global dm, log
log = Logger()
dm = DBManager("em_tk_database")
log.logger.info("开始更新股票数据")
bs.login()
code_list = dm.get_code_list()
for item in code_list:
ticker = item["ticker"]
max_try = 8
for tries in range(max_try):
rs = bs.query_history_k_data(
ticker,
"date,code,open,high,low,close,volume,amount,adjustflag,turn,"
"pctChg",
frequency="w",
adjustflag="3")
if rs.error_code == '0':
parse_pager(rs, ticker)
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
log.logger.error("更新股票数据失败：" + str(ticker))
log.logger.info("结束更新股票数据")
bs.logout()
def start_pe_crawl():
global dm, log
log = Logger()
dm = DBManager("em_pe_database")
log.logger.info("开始更新指数数据")
bs.login()
code_list = dm.get_code_list()
for item in code_list:
ticker = item["ticker"]
max_try = 8
for tries in range(max_try):
rs = bs.query_history_k_data(
ticker,
"date,code,close,peTTM,pbMRQ,psTTM,pcfNcfTTM",
frequency="d",
adjustflag="2")
if rs.error_code == "0":
parse_pager(rs, ticker)
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
log.logger.error("更新股票指数数据：" + str(ticker))
log.logger.info("结束更新指数数据")
bs.logout()
def fun_analysis(cur_time=datetime.datetime.now()):
log = Logger()
log.logger.info("开始分析数据")
# 数据获取
dm_tk = DBManager("em_tk_database")
dm_pe = DBManager("em_pe_database")
code_list = [x for x in dm_tk.get_code_list()]
result_list = list()
# 数据遍历
for item in code_list:
tk_item = dm_tk.find_one_by_key({"ticker": item["ticker"]})
pe_item = dm_pe.find_one_by_key({"ticker": item["ticker"]})
tk_data_list = tk_item["data_list"]
pe_data_list = pe_item["data_list"]
# 数据计算
close_list = [
float(x["close"]) for x in tk_data_list if x["close"] != ""
]
volume_list = [
float(x["volume"]) for x in tk_data_list if x["close"] != ""
]
wmacd_list, diff_list, dea_list = get_w_macd(close_list)
# 处理核心逻辑
if wmacd_list[-1] > 0 >= wmacd_list[-2]:
if np.mean(volume_list[-5:-1]
) < volume_list[-1] and diff_list[-1] >= 0:
result_list.append({
"ticker": item["ticker"],
"diff": round(diff_list[-1], 4),
"pe": float(pe_data_list[-1]["peTTM"])
})
print(result_list)
log.logger.info("结束分析数据：" + json.dumps(result_list))
# 生成分析报告
creat_report(result_list)
history_capital = list()
# 时间列表
def date_range(start, end, step=1, format="%Y-%m-%d"):
strptime, strftime = datetime.datetime.strptime, datetime.datetime.strftime
days = (strptime(end, format) - strptime(start, format)).days + 1
return [
strftime(strptime(start, format) + datetime.timedelta(i), format)
for i in range(0, days, step)
]
if __name__ == "__main__":
log = Logger()
dm_tk = DBManager("em_tk_database")
dm_pe = DBManager("em_pe_database")
date_list_table = [
date_range("2016-01-01", "2016-12-31"),
date_range("2017-01-01", "2017-12-31"),
date_range("2018-01-01", "2018-12-31")
]
code_list = [x for x in dm_tk.get_code_list()]
for date_list in date_list_table:
capital_base = 1000000
history_capital = list()
for index in range(len(date_list)):
cur_date = date_list[index]
if datetime.datetime.strptime(cur_date, "%Y-%m-%d").weekday() == 4: