def show_result():
if len(count_dict) > 0:
console.write_blank()
for index in count_dict:
console.write_number(index, str(count_dict[index]))
reset()
return
def share_detail(code_list, reset_flag=False):
"""
将股票数据推送至influxdb
"""
f = h5py.File(conf.HDF5_FILE_SHARE, 'a')
for code in code_list:
code_prefix = code[0:3]
code_group_path = '/' + code_prefix + '/' + code
if f.get(code_group_path) is None:
console.write_msg(code + "目录不存在")
continue
console.write_head(conf.HDF5_OPERATE_PUSH, conf.HDF5_RESOURCE_TUSHARE,
code)
# 推送原始kline
measurement = conf.MEASUREMENT_SHARE
_raw_kline(f[code_prefix][code], measurement, code, reset_flag)
# 推送缠论kline
measurement = conf.MEASUREMENT_SHARE_WRAP
_wrap_kline(f[code_prefix][code], measurement, code, reset_flag)
# 推送基本面数据
measurement = conf.MEASUREMENT_SHARE_BASIC
_basic_info(f[code_prefix][code], measurement, code, reset_flag)
console.write_blank()
console.write_tail()
f.close()
return
def output(self):
"""
打印结果
"""
trend_now = self.small.iloc[-1]
phase_now = self.phase.iloc[-1]
# phase_pre = self.phase.iloc[-2]
side = self._get_side(phase_now[action.INDEX_PHASE_STATUS])
console.write_msg(
"【%s, %s, %s】" %
(self.code, trend_now[conf.HDF5_SHARE_DATE_INDEX], side))
if len(self.phase) > 1:
phase_pre = self.phase.iloc[-2]
msg = "上阶段，macd差值%f，price差值%d，连续%d次，dif位置%f"
console.write_msg(
msg % (phase_pre[phase.MACD_DIFF], phase_pre[phase.PRICE_END] -
phase_pre[phase.PRICE_START], phase_pre[phase.COUNT],
phase_pre[phase.DIF_END]))
msg = "建议价格%d - %d"
console.write_msg(msg %
(phase_now[phase.PRICE_START], trend_now["close"]))
msg = "medium级别背离情况：%s"
console.write_msg(msg % (self.medium_trend_reverse))
msg = "big级别背离情况：%s"
console.write_msg(msg % (self.big_trend_reverse))
console.write_blank()
return
def code_detail(code_list, start_date):
"""
将code的basic内容，整理至share文件下
"""
# 获取basic所有日期的detail，并遍历读取详细信息
f = h5py.File(conf.HDF5_FILE_BASIC, 'a')
f_share = h5py.File(conf.HDF5_FILE_SHARE, 'a')
console.write_head(conf.HDF5_OPERATE_ARRANGE, conf.HDF5_RESOURCE_TUSHARE,
conf.HDF5_BASIC_DETAIL)
path = '/' + conf.HDF5_BASIC_DETAIL
if f.get(path) is None:
return
code_basic_dict = dict()
for date in f[path]:
if start_date is not None and date < start_date:
console.write_msg(start_date + "起始日期大于基本数据的最大日期")
continue
df = tool.df_from_dataset(f[path], date, None)
df["code"] = df["code"].str.decode("utf-8")
df = df.set_index("code")
for code in df.index:
if code not in code_list:
continue
if code not in code_basic_dict:
code_basic_dict[code] = tool.init_empty_df(df.columns)
code_basic_dict[code].loc[date] = df.loc[code, :]
for code, code_df in code_basic_dict.items():
code_df.index.name = conf.HDF5_SHARE_DATE_INDEX
code_df = code_df.reset_index().sort_values(
by=[conf.HDF5_SHARE_DATE_INDEX])
code_prefix = code[0:3]
code_group_path = '/' + code_prefix + '/' + code
if f_share.get(code_group_path) is None:
console.write_msg(code + "的detail文件不存在")
continue
if start_date is None:
tool.delete_dataset(f_share[code_group_path],
conf.HDF5_BASIC_DETAIL)
tool.merge_df_dataset(f_share[code_group_path], conf.HDF5_BASIC_DETAIL,
code_df)
console.write_exec()
console.write_blank()
console.write_tail()
f_share.close()
f.close()
return
def code_exec(f, code):
"""
个股筛选
"""
MACD_DIVERSE_LIMIT = 5
code_prefix = code[0:3]
code_dict = dict()
code_dict["code"] = code
omit_flag = False
for ktype in ["D", "W", "M", "30", "5"]:
if f[code_prefix][code].get(ktype) is None:
console.write_blank()
console.write_msg(code + "阶段" + ktype + "的detail数据不存在")
return None
share_df = tool.df_from_dataset(f[code_prefix][code], ktype, None)
index_ds_name = conf.HDF5_INDEX_DETAIL + "_" + ktype
if f[code_prefix][code].get(index_ds_name) is None:
console.write_blank()
console.write_msg(code + "阶段" + ktype + "的macd与均线数据不存在")
return None
index_df = tool.df_from_dataset(f[code_prefix][code], index_ds_name,
None)
share_df = share_df.merge(index_df,
left_on=conf.HDF5_SHARE_DATE_INDEX,
right_on=conf.HDF5_SHARE_DATE_INDEX,
how='outer')
share_df[conf.HDF5_SHARE_DATE_INDEX] = share_df[
conf.HDF5_SHARE_DATE_INDEX].str.decode("utf-8")
# 检查macd的趋势
if ktype in ["D", "M", "W"]:
code_dict = _filter_trend(share_df.tail(50), code_dict, ktype)
if code_dict is None:
omit_flag = True
break
# 检查macd的背离
if ktype in ["D", "30"]:
code_dict = _filter_diverse(share_df.tail(100), code_dict, ktype)
# 如果日线不存在macd的上涨趋势，则忽略该股票
if omit_flag is True:
return None
# 如果日线、30min一个阶段内都不存在背离，忽略
if code_dict["30" +
INDEX_MACD_DIVERSE_COUNT] <= MACD_DIVERSE_LIMIT and code_dict[
"d" + INDEX_MACD_DIVERSE_COUNT] <= MACD_DIVERSE_LIMIT:
return None
return code_dict
def output(self):
now = self.trade.iloc[-1]
console.write_msg(
"【%s, %s, %s】" %
(self.code, now[conf.HDF5_SHARE_DATE_INDEX], now["type"]))
msg = "个股5min，趋势%s，连续%d次，macd趋势%f, macd差值%d%%"
console.write_msg(
msg %
(now[DF_FIVE + TRADE_STATUS], now[DF_FIVE + TRADE_TREND_COUNT],
now[DF_FIVE + TRADE_MACD_PHASE], now[DF_FIVE + TRADE_MACD_DIFF]))
dtype_dict = {
DF_THIRTY: "个股30min",
DF_BIG: "个股大趋势",
DF_INDEX: "指数30min",
}
for dtype in dtype_dict:
msg = "%s，趋势%s，连续%d次，macd趋势%f, macd差值%d%%"
console.write_msg(
msg %
(dtype_dict[dtype], now[dtype + TRADE_STATUS],
now[dtype + TRADE_TREND_COUNT], now[dtype + TRADE_MACD_PHASE],
now[dtype + TRADE_MACD_DIFF]))
# TODO 背离情况要计算两次买卖点trend_count的差值
trend_count = now[DF_FIVE + TRADE_TREND_COUNT]
upper_estimate = (trend_count + 1) * 5
lower_estimate = (trend_count - 1) * 5
if self.stype == conf.STYPE_ASHARE:
remain_seconds = tradetime.get_ashare_remain_second(
now[conf.HDF5_SHARE_DATE_INDEX])
remain_minutes = round(remain_seconds / 60, 0)
msg = "剩余时间%d分钟，下个交易点预估需要%d-%d分钟，模式%s"
if (upper_estimate * 60) <= remain_seconds:
trade_opportunity = "T+0"
else:
trade_opportunity = "T+1"
console.write_msg(msg % (remain_minutes, lower_estimate,
upper_estimate, trade_opportunity))
elif self.stype == conf.STYPE_BITMEX:
msg = "下个交易点预估需要%d-%d分钟"
console.write_msg(msg % (lower_estimate, upper_estimate))
console.write_msg("建议仓位：%d/3" % (now[TRADE_POSITIONS]))
console.write_blank()
return
def index_detail(reset_flag=False):
"""
将指数数据推送至influxdb
"""
f = h5py.File(conf.HDF5_FILE_INDEX, 'a')
for code in f:
console.write_head(conf.HDF5_OPERATE_PUSH, conf.HDF5_RESOURCE_TUSHARE,
code)
# 推送原始kline
measurement = conf.MEASUREMENT_INDEX
_raw_kline(f[code], measurement, code, reset_flag)
# 推送缠论kline
measurement = conf.MEASUREMENT_INDEX_WRAP
_wrap_kline(f[code], measurement, code, reset_flag)
console.write_blank()
console.write_tail()
f.close()
return
def all_share(omit_list, init_flag=True):
"""
获取所有股票的macd与所处均线等指标
"""
f = h5py.File(conf.HDF5_FILE_SHARE, 'a')
for code_prefix in f:
if code_prefix in omit_list:
continue
console.write_head(conf.HDF5_OPERATE_INDEX, conf.HDF5_RESOURCE_TUSHARE,
code_prefix)
for code in f[code_prefix]:
# 忽略停牌、退市、无法获取的情况
if f[code_prefix][code].attrs.get(
conf.HDF5_BASIC_QUIT) is not None:
continue
if f[code_prefix][code].attrs.get(conf.HDF5_BASIC_ST) is not None:
continue
code_group_path = '/' + code_prefix + '/' + code
for ktype in conf.HDF5_SHARE_KTYPE:
try:
if f.get(code_group_path) is None or f[code_prefix][
code].get(ktype) is None:
console.write_msg(code + "-" + ktype + "的detail不存在")
continue
df = tool.df_from_dataset(f[code_prefix][code], ktype,
None)
index_df = one_df(df, init_flag)
ds_name = conf.HDF5_INDEX_DETAIL + "_" + ktype
if init_flag is True:
tool.delete_dataset(f[code_prefix][code], ds_name)
tool.merge_df_dataset(f[code_prefix][code], ds_name,
index_df.reset_index())
except Exception as er:
print(str(er))
console.write_exec()
console.write_blank()
console.write_tail()
f.close()
return
def filter_share(code_list, start_date):
"""
整理筛选的股票缠论k线
"""
f = h5py.File(conf.HDF5_FILE_SHARE, 'a')
console.write_head(conf.HDF5_OPERATE_WRAP, conf.HDF5_RESOURCE_TUSHARE,
conf.HDF5_INDEX_WRAP)
for code in code_list:
code_prefix = code[0:3]
code_group_path = '/' + code_prefix + '/' + code
if f.get(code_group_path) is None:
continue
# 忽略停牌、退市、无法获取的情况
if f[code_prefix][code].attrs.get(
conf.HDF5_BASIC_QUIT
) is not None or f[code_prefix][code].attrs.get(
conf.HDF5_BASIC_ST) is not None:
continue
for ktype in conf.HDF5_SHARE_WRAP_KTYPE:
ds_name = ktype
if f[code_prefix][code].get(ds_name) is None:
continue
share_df = tool.df_from_dataset(f[code_prefix][code], ds_name,
None)
wrap_df = one_df(share_df)
if wrap_df is not None:
ds_name = conf.HDF5_INDEX_WRAP + "_" + ktype
if f[code_prefix][code].get(ds_name) is not None:
tool.delete_dataset(f[code_prefix][code], ds_name)
tool.create_df_dataset(f[code_prefix][code], ds_name, wrap_df)
console.write_exec()
else:
console.write_pass()
console.write_blank()
console.write_tail()
f.close()
return
def classify_detail(classify_list, reset_flag=False):
"""
将分类推送至influxdb
"""
f = h5py.File(conf.HDF5_FILE_CLASSIFY, 'a')
# 获取classify列表
for ctype in classify_list:
console.write_head(conf.HDF5_OPERATE_PUSH, conf.HDF5_RESOURCE_TUSHARE,
ctype)
for classify_name in f[ctype]:
# 推送原始kline
measurement = conf.MEASUREMENT_CLASSIFY + "_" + ctype
_raw_kline(f[ctype][classify_name], measurement, classify_name,
reset_flag)
# 推送缠论kline
measurement = conf.MEASUREMENT_CLASSIFY_WRAP + "_" + ctype
_wrap_kline(f[ctype][classify_name], measurement, classify_name,
reset_flag)
console.write_blank()
console.write_tail()
f.close()
return
def all_exec(omit_list):
"""
筛选出存在背离的股票
"""
# 筛选记录内容如下:
# 1. 月线macd趋势
# 2. 周线macd趋势
# 3. 日线macd趋势，是否背离，数值差距
# 4. 30min的macd趋势，是否背离，数值差距，震荡中枢数量
# 5. 5min的macd趋势，是否背离，数值差距，震荡中枢数量
console.write_head(conf.HDF5_OPERATE_SCREEN, conf.HDF5_RESOURCE_TUSHARE,
conf.STRATEGY_TREND_AND_REVERSE)
f = h5py.File(conf.HDF5_FILE_SHARE, 'a')
filter_df = tool.init_empty_df(_ini_filter_columns())
for code_prefix in f:
if code_prefix in omit_list:
continue
for code in f[code_prefix]:
code_group_path = '/' + code_prefix + '/' + code
if f.get(code_group_path) is None:
console.write_blank()
console.write_msg(code + "的tushare数据不存在")
continue
# 忽略停牌、退市、无法获取的情况
if f[code_prefix][code].attrs.get(
conf.HDF5_BASIC_QUIT
) is not None or f[code_prefix][code].attrs.get(
conf.HDF5_BASIC_ST) is not None:
console.write_blank()
console.write_msg(code + "已退市或停牌")
continue
try:
code_dict = code_exec(f, code)
if code_dict is None:
console.write_pass()
continue
else:
console.write_exec()
filter_df = filter_df.append(code_dict, ignore_index=True)
except Exception as er:
console.write_msg("[" + code + "]" + str(er))
f.close()
f_screen = h5py.File(conf.HDF5_FILE_SCREEN, 'a')
if f_screen.get(conf.STRATEGY_TREND_AND_REVERSE) is None:
f_screen.create_group(conf.STRATEGY_TREND_AND_REVERSE)
if f_screen[conf.STRATEGY_TREND_AND_REVERSE].get(
conf.SCREEN_SHARE_FILTER) is None:
f_screen[conf.STRATEGY_TREND_AND_REVERSE].create_group(
conf.SCREEN_SHARE_FILTER)
today_str = tradetime.get_today()
tool.delete_dataset(
f_screen[conf.STRATEGY_TREND_AND_REVERSE][conf.SCREEN_SHARE_FILTER],
today_str)
tool.merge_df_dataset(
f_screen[conf.STRATEGY_TREND_AND_REVERSE][conf.SCREEN_SHARE_FILTER],
today_str, filter_df)
f_screen.close()
console.write_blank()
console.write_tail()
return