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#UPDATE to 1.2.6
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#UPDATE to 1.2.6
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@yutiansut
yutiansut authored Jan 7, 2019
2 parents 6064c57 + f62349a commit f6071e5
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17 changes: 17 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -72,6 +72,23 @@
- [1.0.25](#1025)

<!-- /TOC -->
## 1.2.6

1. 优化QADOCKER文档
2. 增加QAORDER文档
3. 优化了QALog模块在打印大量日志的时候无法知道其用途的问题

现在的quantaxis log 会以这个模式作为name:
```
'quantaxis_{}-{}-.log'.format(get_config(), os.sep, os.path.basename(sys.argv[0]).split('.py')[0], str(datetime.datetime.now().strftime(
'%Y-%m-%d-%H-%M-%S')))
```
4. 修改了QAUser的注册模块逻辑
5. 增加了 QA_DataStruct_Min 和 QA_DataStruct_Day两个基类模型
6. 修复settle的一个bug



## 1.2.5

1. 对于QA.QA_util_code_tostr 增加 原先为list类型的支持 现在支持自动补全的 int/list/str 类型转 str
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98 changes: 56 additions & 42 deletions QUANTAXIS/QAData/data_resample.py
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Expand Up @@ -26,8 +26,8 @@

import pandas as pd

def QA_data_tick_resample_1min(tick, type_='1min', if_drop=True):

def QA_data_tick_resample_1min(tick, type_='1min', if_drop=True):
"""
tick 采样为 分钟数据
1. 仅使用将 tick 采样为 1 分钟数据
Expand All @@ -52,36 +52,50 @@ def QA_data_tick_resample_1min(tick, type_='1min', if_drop=True):
# do fix on the first and last bar
# 某些股票某些日期没有集合竞价信息，譬如 002468 在 2017 年 6 月 5 日的数据
if len(_data.loc[time(9, 25): time(9, 25)]) > 0:
_data1.loc[time(9, 31): time(9, 31), 'open'] = _data1.loc[time(9, 26): time(9, 26), 'open'].values
_data1.loc[time(9, 31): time(9, 31), 'high'] = _data1.loc[time(9, 26): time(9, 31), 'high'].max()
_data1.loc[time(9, 31): time(9, 31), 'low'] = _data1.loc[time(9, 26): time(9, 31), 'low'].min()
_data1.loc[time(9, 31): time(9, 31), 'vol'] = _data1.loc[time(9, 26): time(9, 31), 'vol'].sum()
_data1.loc[time(9, 31): time(9, 31), 'amount'] = _data1.loc[time(9, 26): time(9, 31), 'amount'].sum()
_data1.loc[time(9, 31): time(9, 31), 'open'] = _data1.loc[time(
9, 26): time(9, 26), 'open'].values
_data1.loc[time(9, 31): time(9, 31), 'high'] = _data1.loc[time(
9, 26): time(9, 31), 'high'].max()
_data1.loc[time(9, 31): time(9, 31), 'low'] = _data1.loc[time(
9, 26): time(9, 31), 'low'].min()
_data1.loc[time(9, 31): time(9, 31), 'vol'] = _data1.loc[time(
9, 26): time(9, 31), 'vol'].sum()
_data1.loc[time(9, 31): time(9, 31), 'amount'] = _data1.loc[time(
9, 26): time(9, 31), 'amount'].sum()
# 通达信分笔数据有的有 11:30 数据，有的没有
if len(_data.loc[time(11, 30): time(11, 30)]) > 0:
_data1.loc[time(11, 30): time(11, 30), 'high'] = _data1.loc[time(11, 30): time(11, 31), 'high'].max()
_data1.loc[time(11, 30): time(11, 30), 'low'] = _data1.loc[time(11, 30): time(11, 31), 'low'].min()
_data1.loc[time(11, 30): time(11, 30), 'close'] = _data1.loc[time(11, 31): time(11, 31), 'close'].values
_data1.loc[time(11, 30): time(11, 30), 'vol'] = _data1.loc[time(11, 30): time(11, 31), 'vol'].sum()
_data1.loc[time(11, 30): time(11, 30), 'amount'] = _data1.loc[time(11, 30): time(11, 31), 'amount'].sum()
_data1.loc[time(11, 30): time(11, 30), 'high'] = _data1.loc[time(
11, 30): time(11, 31), 'high'].max()
_data1.loc[time(11, 30): time(11, 30), 'low'] = _data1.loc[time(
11, 30): time(11, 31), 'low'].min()
_data1.loc[time(11, 30): time(11, 30), 'close'] = _data1.loc[time(
11, 31): time(11, 31), 'close'].values
_data1.loc[time(11, 30): time(11, 30), 'vol'] = _data1.loc[time(
11, 30): time(11, 31), 'vol'].sum()
_data1.loc[time(11, 30): time(11, 30), 'amount'] = _data1.loc[time(
11, 30): time(11, 31), 'amount'].sum()
_data1 = _data1.loc[time(9, 31): time(11, 30)]

# afternoon min bar
_data2 = _data[time(13,0): time(15,0)].resample(
type_, closed='left', base=30, loffset=type_).apply({'price': 'ohlc', 'vol': 'sum', 'code': 'last', 'amount': 'sum'})
_data2 = _data[time(13, 0): time(15, 0)].resample(
type_, closed='left', base=30, loffset=type_).apply({'price': 'ohlc', 'vol': 'sum', 'code': 'last', 'amount': 'sum'})

_data2.columns = _data2.columns.droplevel(0)
# 沪市股票在 2018-08-20 起，尾盘 3 分钟集合竞价
if (pd.Timestamp(date) < pd.Timestamp('2018-08-20')) and (tick.code.iloc[0][0] == '6'):
# 避免出现 tick 数据没有 1:00 的值
if len(_data.loc[time(13, 0): time(13, 0)]) > 0:
_data2.loc[time(15, 0): time(15, 0), 'high'] = _data2.loc[time(15, 0): time(15, 1), 'high'].max()
_data2.loc[time(15, 0): time(15, 0), 'low'] = _data2.loc[time(15, 0): time(15, 1), 'low'].min()
_data2.loc[time(15, 0): time(15, 0), 'close'] = _data2.loc[time(15, 1): time(15, 1), 'close'].values
_data2.loc[time(15, 0): time(15, 0), 'high'] = _data2.loc[time(
15, 0): time(15, 1), 'high'].max()
_data2.loc[time(15, 0): time(15, 0), 'low'] = _data2.loc[time(
15, 0): time(15, 1), 'low'].min()
_data2.loc[time(15, 0): time(15, 0), 'close'] = _data2.loc[time(
15, 1): time(15, 1), 'close'].values
else:
# 避免出现 tick 数据没有 15:00 的值
if len(_data.loc[time(13, 0): time(13, 0)]) > 0:
_data2.loc[time(15, 0): time(15, 0)] = _data2.loc[time(15, 1): time(15, 1)].values
_data2.loc[time(15, 0): time(15, 0)] = _data2.loc[time(
15, 1): time(15, 1)].values
_data2 = _data2.loc[time(13, 1): time(15, 0)]
resx = resx.append(_data1).append(_data2)
resx['vol'] = resx['vol'] * 100.0
Expand Down Expand Up @@ -172,31 +186,6 @@ def QA_data_min_resample(min_data, type_='5min'):
new_type {[type]} -- [description]
"""

# ohlc_data=min_data.loc[:,['open','high','low','close']].stack().reset_index().rename(columns={0:'price'}).drop(['level_2'],axis=1).set_index('datetime',drop=False)
# vol=min_data.assign(vol1=0,vol2=0,vol3=0)
# L2=vol.loc[:,['volume','vol1','vol2','vol3']].stack().reset_index().rename(columns={0:'vol'}).drop(['level_2'],axis=1).set_index('datetime')
# tick=pd.concat([ohlc_data,L2.vol],axis=1)
# data = tick['price'].resample(
# type_, label='right', closed='left').ohlc()

# data['volume'] = tick['vol'].resample(
# type_, label='right', closed='left').sum()
# data['code'] = tick.code.iloc[1]
# if 'date' not in tick.columns:
# tick=tick.assign(date=tick.datetime.apply(lambda x: str(x)[0:10]))

# resx=pd.DataFrame()
# _temp = tick.drop_duplicates('date')['date']
# for item in _temp:
# _data = data[item]
# _data = _data[time(9, 31):time(11, 30)].append(
# _data[time(13, 1):time(15, 0)])
# resx = resx.append(_data)
# resx=resx.reset_index()
# data=resx.assign(date=resx['datetime'].apply(lambda x: str(x)[0:10]))

# return data.fillna(method='ffill').set_index(['datetime', 'code'], drop=False).drop_duplicates()

try:
min_data = min_data.reset_index().set_index('datetime', drop=False)
except:
Expand All @@ -208,15 +197,40 @@ def QA_data_min_resample(min_data, type_='5min'):

for item in set(min_data.index.date):
min_data_p = min_data.loc[str(item)]
n = min_data_p['{} 21:00:00'.format(item):].resample(
type_, base=30, closed='right', loffset=type_).apply(CONVERSION)

d = min_data_p[:'{} 11:30:00'.format(item)].resample(
type_, base=30, closed='right', loffset=type_).apply(CONVERSION)
f = min_data_p['{} 13:00:00'.format(item):].resample(
type_, closed='right', loffset=type_).apply(CONVERSION)

resx = resx.append(d).append(f)

return resx.dropna().reset_index().set_index(['datetime', 'code'])


def QA_data_futuremin_resample(min_data, type_='5min'):
"""期货分钟线采样成大周期
分钟线采样成子级别的分钟线
future:
vol ==> trade
amount X
"""

min_data.tradeime = pd.to_datetime(min_data.tradetime)

CONVERSION = {'code': 'first', 'open': 'first', 'high': 'max', 'low': 'min',
'close': 'last', 'trade': 'sum', 'tradetime': 'last', 'date': 'last'}
resx = min_data.resample(type_, closed='right',
loffset=type_).apply(CONVERSION)
return resx.dropna().reset_index().set_index(['datetime', 'code'])


def QA_data_day_resample(day_data, type_='w'):
"""日线降采样
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2 changes: 1 addition & 1 deletion QUANTAXIS/QAUtil/QADate_trade.py
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Expand Up @@ -473,7 +473,7 @@ def QA_util_future_to_tradedatetime(real_datetime):
Returns:
[type] -- [description]
"""
if len(str(real_datetime))==19:
if len(str(real_datetime))>=19:
dt = datetime.datetime.strptime(str(real_datetime)[0:19], '%Y-%m-%d %H:%M:%S')
return dt if dt.time()<datetime.time(21,0) else QA_util_get_next_datetime(dt,1)
elif len(str(real_datetime))==16:
Expand Down
23 changes: 14 additions & 9 deletions QUANTAXIS/QAUtil/QALogs.py
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Expand Up @@ -35,7 +35,7 @@
import configparser
import datetime
import os

import sys
from zenlog import logging

from QUANTAXIS.QASetting.QALocalize import log_path, setting_path
Expand Down Expand Up @@ -72,13 +72,18 @@ def get_config():

"""2019-01-03 升级到warning级别 不然大量别的代码的log会批量输出出来
"""
try:
_name = '{}{}quantaxis_{}-{}-.log'.format(get_config(), os.sep, os.path.basename(sys.argv[0]).split('.py')[0], str(datetime.datetime.now().strftime(
'%Y-%m-%d-%H-%M-%S')))
except:
_name = '{}{}quantaxis-{}-.log'.format(get_config(), os.sep, str(datetime.datetime.now().strftime(
'%Y-%m-%d-%H-%M-%S')))


logging.basicConfig(level=logging.WARNING,
format='%(asctime)s QUANTAXIS>>> %(message)s',
datefmt='%H:%M:%S',
filename='{}{}quantaxis-{}-.log'.format(get_config(), os.sep, str(datetime.datetime.now().strftime(
'%Y-%m-%d-%H-%M-%S'))),
filename=_name,
filemode='w',
)
console = logging.StreamHandler()
Expand All @@ -91,7 +96,7 @@ def get_config():
#logging.info('start QUANTAXIS')


def QA_util_log_debug(logs, ui_log = None, ui_progress = None):
def QA_util_log_debug(logs, ui_log=None, ui_progress=None):
"""
QUANTAXIS Log Module
@yutiansut
Expand All @@ -101,7 +106,7 @@ def QA_util_log_debug(logs, ui_log = None, ui_progress = None):
logging.debug(logs)


def QA_util_log_info(logs, ui_log = None, ui_progress = None, ui_progress_int_value = None):
def QA_util_log_info(logs, ui_log=None, ui_progress=None, ui_progress_int_value=None,):
"""
QUANTAXIS Log Module
@yutiansut
Expand All @@ -110,19 +115,19 @@ def QA_util_log_info(logs, ui_log = None, ui_progress = None, ui_progress_int_va
"""
logging.warning(logs)

#给GUI使用，更新当前任务到日志和进度
# 给GUI使用，更新当前任务到日志和进度
if ui_log is not None:
if isinstance(logs, str) :
if isinstance(logs, str):
ui_log.emit(logs)
if isinstance(logs, list) :
if isinstance(logs, list):
for iStr in logs:
ui_log.emit(iStr)

if ui_progress is not None and ui_progress_int_value is not None:
ui_progress.emit(ui_progress_int_value)


def QA_util_log_expection(logs, ui_log = None, ui_progress = None):
def QA_util_log_expection(logs, ui_log=None, ui_progress=None):
"""
QUANTAXIS Log Module
@yutiansut
Expand Down
2 changes: 1 addition & 1 deletion QUANTAXIS/__init__.py
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Expand Up @@ -32,7 +32,7 @@
2017/4/8
"""

__version__ = '1.2.6.dev1'
__version__ = '1.2.6'
__author__ = 'yutiansut'
logo = ' \n \
```````````````````````````````````````````````````````````````````````````````````````````````````````````````````````` \n \
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