def trade_date_into_db():
delete_table()
df = ak.tool_trade_date_hist_sina()
df['trade_date'] = df['trade_date'].apply(
lambda x: int(x[0:10].replace("-", "")))
df.to_sql("share_trade_date", engine, if_exists="append", index=False)
return "success"
def __init__(self):
self.database = Database()
# 获取从1990-12-19至2020-12-31股票交易日数据
self.trade_date = ak.tool_trade_date_hist_sina()["trade_date"].tolist()
self.label_range = {
3: "3DaysLabel",
5: "5DaysLabel",
10: "10DaysLabel",
15: "15DaysLabel",
30: "30DaysLabel",
60: "60DaysLabel"
}
def if_trade(selectday: date = datetime.now().date()):
"""判断当日是否交易日"""
import akshare as ak
try:
tool_trade_date_hist_sina_df = ak.tool_trade_date_hist_sina()
tradedays = tool_trade_date_hist_sina_df.trade_date.to_list()
except Exception as err:
print("获取akshare的交易日历失败：", err)
tradedays = [datetime.now().date()]
if selectday in tradedays or selectday.strftime("%Y-%m-%d") in tradedays:
return True
else:
return False
def __init__(self):
self.database = Database()
# 获取从1990-12-19至2020-12-31股票交易日数据
self.trade_date = ak.tool_trade_date_hist_sina()["trade_date"].tolist()
self.label_range = {3: "3DaysLabel",
5: "5DaysLabel",
10: "10DaysLabel",
15: "15DaysLabel",
30: "30DaysLabel",
60: "60DaysLabel"}
self.redis_client = redis.StrictRedis(host=config.REDIS_IP,
port=config.REDIS_PORT,
db=config.CACHE_NEWS_REDIS_DB_ID)
self.redis_client.set("today_date", datetime.datetime.now().strftime("%Y-%m-%d"))
self.redis_client.delete("stock_news_num_over_{}".format(config.MINIMUM_STOCK_NEWS_NUM_FOR_ML))
self._stock_news_nums_stat()
def __init__(self):
self.database = Database()
# 获取从1990-12-19至2020-12-31股票交易日数据
self.trade_date = ak.tool_trade_date_hist_sina()["trade_date"].tolist()
self.label_range = {
3: "3DaysLabel",
5: "5DaysLabel",
10: "10DaysLabel",
15: "15DaysLabel",
30: "30DaysLabel",
60: "60DaysLabel"
}
self.redis_client = redis.StrictRedis(host=config.REDIS_IP,
port=config.REDIS_PORT,
db=config.CACHE_NEWS_REDIS_DB_ID)
self.redis_client.set("today_date",
datetime.datetime.now().strftime("%Y-%m-%d"))
def spider(future):
vol = 'vol'
long = 'long_open_interest'
long_chg = 'long_open_interest_chg'
short = 'short_open_interest'
short_chg = 'short_open_interest_chg'
trade_calendar = ak.tool_trade_date_hist_sina()
nowdatetime = datetime.datetime.now()
if int(nowdatetime.strftime("%H%M"))>1630:
pass
else:
nowdatetime = nowdatetime-datetime.timedelta(days=1)
for counts in range(30):
if nowdatetime.strftime("%Y-%m-%d") in trade_calendar['trade_date'].values:
tradedate = nowdatetime.strftime("%Y%m%d")
break
else:
nowdatetime -= datetime.timedelta(days=1)
if counts == 29:
print("no trade day found!")
return
# get_ag_sum_daily_df = ak.get_rank_sum_daily(start_day='20201209',end_day='20201210',vars_list=['AG'])
# get_au_sum_daily_df = ak.get_rank_sum_daily(start_day='20201209',end_day='20201210',vars_list=['AU'])
ag_rank_table_df = ak.get_shfe_rank_table(date=tradedate,vars_list=[future])
ag = {long:0,short:0,long_chg:0,short_chg:0,vol:0}
for df in ag_rank_table_df.values():
ag[vol] += df.loc[20,vol]
ag[long] += df.loc[20,long]
ag[short] += df.loc[20,short]
ag[long_chg] += df.loc[20,long_chg]
ag[short_chg] += df.loc[20,short_chg]
stat = (ag[long]+ag[short])/ag[vol]
ts = (ag[long_chg]-ag[short_chg])/np.abs(ag[long_chg]+ag[short_chg])
# how to use TS?
print(ag)
print(stat,ts)
return ag
def __get_dates(self):
dates = ak.tool_trade_date_hist_sina()
dates.trade_date = pd.to_datetime(dates.trade_date)
return dates
def trade_date_hist():
df = ak.tool_trade_date_hist_sina()
return df