partition stringclasses 3 values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1 value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
train | QA_Account.get_history | 返回历史成交
Arguments:
start {str} -- [description]
end {str]} -- [description] | QUANTAXIS/QAARP/QAAccount.py | def get_history(self, start, end):
"""返回历史成交
Arguments:
start {str} -- [description]
end {str]} -- [description]
"""
return self.history_table.set_index(
'datetime',
drop=False
).loc[slice(pd.Timestamp(start),
pd.Timestamp(end))] | def get_history(self, start, end):
"""返回历史成交
Arguments:
start {str} -- [description]
end {str]} -- [description]
"""
return self.history_table.set_index(
'datetime',
drop=False
).loc[slice(pd.Timestamp(start),
pd.Timestamp(end))] | [
"返回历史成交"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAAccount.py#L1868-L1879 | [
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train | QA_SU_save_order | 存储order_handler的order_status
Arguments:
orderlist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE}) | QUANTAXIS/QASU/save_orderhandler.py | def QA_SU_save_order(orderlist, client=DATABASE):
"""存储order_handler的order_status
Arguments:
orderlist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
if isinstance(orderlist, pd.DataFrame):
collection = client.order
collection.create_index(
[('account_cookie',
ASCENDING),
('realorder_id',
ASCENDING)],
unique=True
)
try:
orderlist = QA_util_to_json_from_pandas(orderlist.reset_index())
for item in orderlist:
if item:
#item['date']= QA_util_get_order_day()
collection.update_one(
{
'account_cookie': item.get('account_cookie'),
'realorder_id': item.get('realorder_id')
},
{'$set': item},
upsert=True
)
except Exception as e:
print(e)
pass | def QA_SU_save_order(orderlist, client=DATABASE):
"""存储order_handler的order_status
Arguments:
orderlist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
if isinstance(orderlist, pd.DataFrame):
collection = client.order
collection.create_index(
[('account_cookie',
ASCENDING),
('realorder_id',
ASCENDING)],
unique=True
)
try:
orderlist = QA_util_to_json_from_pandas(orderlist.reset_index())
for item in orderlist:
if item:
#item['date']= QA_util_get_order_day()
collection.update_one(
{
'account_cookie': item.get('account_cookie'),
'realorder_id': item.get('realorder_id')
},
{'$set': item},
upsert=True
)
except Exception as e:
print(e)
pass | [
"存储order_handler的order_status"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_orderhandler.py#L31-L67 | [
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train | QA_SU_save_deal | 存储order_handler的deal_status
Arguments:
dealist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE}) | QUANTAXIS/QASU/save_orderhandler.py | def QA_SU_save_deal(dealist, client=DATABASE):
"""存储order_handler的deal_status
Arguments:
dealist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
if isinstance(dealist, pd.DataFrame):
collection = client.deal
collection.create_index(
[('account_cookie',
ASCENDING),
('trade_id',
ASCENDING)],
unique=True
)
try:
dealist = QA_util_to_json_from_pandas(dealist.reset_index())
collection.insert_many(dealist, ordered=False)
except Exception as e:
pass | def QA_SU_save_deal(dealist, client=DATABASE):
"""存储order_handler的deal_status
Arguments:
dealist {[dataframe]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
if isinstance(dealist, pd.DataFrame):
collection = client.deal
collection.create_index(
[('account_cookie',
ASCENDING),
('trade_id',
ASCENDING)],
unique=True
)
try:
dealist = QA_util_to_json_from_pandas(dealist.reset_index())
collection.insert_many(dealist, ordered=False)
except Exception as e:
pass | [
"存储order_handler的deal_status"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_orderhandler.py#L70-L96 | [
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train | QA_SU_save_order_queue | 增量存储order_queue
Arguments:
order_queue {[type]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE}) | QUANTAXIS/QASU/save_orderhandler.py | def QA_SU_save_order_queue(order_queue, client=DATABASE):
"""增量存储order_queue
Arguments:
order_queue {[type]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
collection = client.order_queue
collection.create_index(
[('account_cookie',
ASCENDING),
('order_id',
ASCENDING)],
unique=True
)
for order in order_queue.values():
order_json = order.to_dict()
try:
collection.update_one(
{
'account_cookie': order_json.get('account_cookie'),
'order_id': order_json.get('order_id')
},
{'$set': order_json},
upsert=True
)
except Exception as e:
print(e) | def QA_SU_save_order_queue(order_queue, client=DATABASE):
"""增量存储order_queue
Arguments:
order_queue {[type]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
collection = client.order_queue
collection.create_index(
[('account_cookie',
ASCENDING),
('order_id',
ASCENDING)],
unique=True
)
for order in order_queue.values():
order_json = order.to_dict()
try:
collection.update_one(
{
'account_cookie': order_json.get('account_cookie'),
'order_id': order_json.get('order_id')
},
{'$set': order_json},
upsert=True
)
except Exception as e:
print(e) | [
"增量存储order_queue"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_orderhandler.py#L99-L128 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | SMA | 威廉SMA算法
本次修正主要是对于返回值的优化,现在的返回值会带上原先输入的索引index
2018/5/3
@yutiansut | QUANTAXIS/QAIndicator/base.py | def SMA(Series, N, M=1):
"""
威廉SMA算法
本次修正主要是对于返回值的优化,现在的返回值会带上原先输入的索引index
2018/5/3
@yutiansut
"""
ret = []
i = 1
length = len(Series)
# 跳过X中前面几个 nan 值
while i < length:
if np.isnan(Series.iloc[i]):
i += 1
else:
break
preY = Series.iloc[i] # Y'
ret.append(preY)
while i < length:
Y = (M * Series.iloc[i] + (N - M) * preY) / float(N)
ret.append(Y)
preY = Y
i += 1
return pd.Series(ret, index=Series.tail(len(ret)).index) | def SMA(Series, N, M=1):
"""
威廉SMA算法
本次修正主要是对于返回值的优化,现在的返回值会带上原先输入的索引index
2018/5/3
@yutiansut
"""
ret = []
i = 1
length = len(Series)
# 跳过X中前面几个 nan 值
while i < length:
if np.isnan(Series.iloc[i]):
i += 1
else:
break
preY = Series.iloc[i] # Y'
ret.append(preY)
while i < length:
Y = (M * Series.iloc[i] + (N - M) * preY) / float(N)
ret.append(Y)
preY = Y
i += 1
return pd.Series(ret, index=Series.tail(len(ret)).index) | [
"威廉SMA算法"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/base.py#L50-L74 | [
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train | CROSS | A<B then A>B A上穿B B下穿A
Arguments:
A {[type]} -- [description]
B {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAIndicator/base.py | def CROSS(A, B):
"""A<B then A>B A上穿B B下穿A
Arguments:
A {[type]} -- [description]
B {[type]} -- [description]
Returns:
[type] -- [description]
"""
var = np.where(A < B, 1, 0)
return (pd.Series(var, index=A.index).diff() < 0).apply(int) | def CROSS(A, B):
"""A<B then A>B A上穿B B下穿A
Arguments:
A {[type]} -- [description]
B {[type]} -- [description]
Returns:
[type] -- [description]
"""
var = np.where(A < B, 1, 0)
return (pd.Series(var, index=A.index).diff() < 0).apply(int) | [
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train | COUNT | 2018/05/23 修改
参考https://github.com/QUANTAXIS/QUANTAXIS/issues/429
现在返回的是series | QUANTAXIS/QAIndicator/base.py | def COUNT(COND, N):
"""
2018/05/23 修改
参考https://github.com/QUANTAXIS/QUANTAXIS/issues/429
现在返回的是series
"""
return pd.Series(np.where(COND, 1, 0), index=COND.index).rolling(N).sum() | def COUNT(COND, N):
"""
2018/05/23 修改
参考https://github.com/QUANTAXIS/QUANTAXIS/issues/429
现在返回的是series
"""
return pd.Series(np.where(COND, 1, 0), index=COND.index).rolling(N).sum() | [
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train | LAST | 表达持续性
从前N1日到前N2日一直满足COND条件
Arguments:
COND {[type]} -- [description]
N1 {[type]} -- [description]
N2 {[type]} -- [description] | QUANTAXIS/QAIndicator/base.py | def LAST(COND, N1, N2):
"""表达持续性
从前N1日到前N2日一直满足COND条件
Arguments:
COND {[type]} -- [description]
N1 {[type]} -- [description]
N2 {[type]} -- [description]
"""
N2 = 1 if N2 == 0 else N2
assert N2 > 0
assert N1 > N2
return COND.iloc[-N1:-N2].all() | def LAST(COND, N1, N2):
"""表达持续性
从前N1日到前N2日一直满足COND条件
Arguments:
COND {[type]} -- [description]
N1 {[type]} -- [description]
N2 {[type]} -- [description]
"""
N2 = 1 if N2 == 0 else N2
assert N2 > 0
assert N1 > N2
return COND.iloc[-N1:-N2].all() | [
"表达持续性",
"从前N1日到前N2日一直满足COND条件"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/base.py#L160-L172 | [
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train | AVEDEV | 平均绝对偏差 mean absolute deviation
修正: 2018-05-25
之前用mad的计算模式依然返回的是单值 | QUANTAXIS/QAIndicator/base.py | def AVEDEV(Series, N):
"""
平均绝对偏差 mean absolute deviation
修正: 2018-05-25
之前用mad的计算模式依然返回的是单值
"""
return Series.rolling(N).apply(lambda x: (np.abs(x - x.mean())).mean(), raw=True) | def AVEDEV(Series, N):
"""
平均绝对偏差 mean absolute deviation
修正: 2018-05-25
之前用mad的计算模式依然返回的是单值
"""
return Series.rolling(N).apply(lambda x: (np.abs(x - x.mean())).mean(), raw=True) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/base.py#L179-L186 | [
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train | MACD | macd指标 仅适用于Series
对于DATAFRAME的应用请使用QA_indicator_macd | QUANTAXIS/QAIndicator/base.py | def MACD(Series, FAST, SLOW, MID):
"""macd指标 仅适用于Series
对于DATAFRAME的应用请使用QA_indicator_macd
"""
EMAFAST = EMA(Series, FAST)
EMASLOW = EMA(Series, SLOW)
DIFF = EMAFAST - EMASLOW
DEA = EMA(DIFF, MID)
MACD = (DIFF - DEA) * 2
DICT = {'DIFF': DIFF, 'DEA': DEA, 'MACD': MACD}
VAR = pd.DataFrame(DICT)
return VAR | def MACD(Series, FAST, SLOW, MID):
"""macd指标 仅适用于Series
对于DATAFRAME的应用请使用QA_indicator_macd
"""
EMAFAST = EMA(Series, FAST)
EMASLOW = EMA(Series, SLOW)
DIFF = EMAFAST - EMASLOW
DEA = EMA(DIFF, MID)
MACD = (DIFF - DEA) * 2
DICT = {'DIFF': DIFF, 'DEA': DEA, 'MACD': MACD}
VAR = pd.DataFrame(DICT)
return VAR | [
"macd指标",
"仅适用于Series",
"对于DATAFRAME的应用请使用QA_indicator_macd"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/base.py#L189-L200 | [
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train | BBI | 多空指标 | QUANTAXIS/QAIndicator/base.py | def BBI(Series, N1, N2, N3, N4):
'多空指标'
bbi = (MA(Series, N1) + MA(Series, N2) +
MA(Series, N3) + MA(Series, N4)) / 4
DICT = {'BBI': bbi}
VAR = pd.DataFrame(DICT)
return VAR | def BBI(Series, N1, N2, N3, N4):
'多空指标'
bbi = (MA(Series, N1) + MA(Series, N2) +
MA(Series, N3) + MA(Series, N4)) / 4
DICT = {'BBI': bbi}
VAR = pd.DataFrame(DICT)
return VAR | [
"多空指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/base.py#L213-L220 | [
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train | BARLAST | 支持MultiIndex的cond和DateTimeIndex的cond
条件成立 yes= True 或者 yes=1 根据不同的指标自己定
Arguments:
cond {[type]} -- [description] | QUANTAXIS/QAIndicator/base.py | def BARLAST(cond, yes=True):
"""支持MultiIndex的cond和DateTimeIndex的cond
条件成立 yes= True 或者 yes=1 根据不同的指标自己定
Arguments:
cond {[type]} -- [description]
"""
if isinstance(cond.index, pd.MultiIndex):
return len(cond)-cond.index.levels[0].tolist().index(cond[cond != yes].index[-1][0])-1
elif isinstance(cond.index, pd.DatetimeIndex):
return len(cond)-cond.index.tolist().index(cond[cond != yes].index[-1])-1 | def BARLAST(cond, yes=True):
"""支持MultiIndex的cond和DateTimeIndex的cond
条件成立 yes= True 或者 yes=1 根据不同的指标自己定
Arguments:
cond {[type]} -- [description]
"""
if isinstance(cond.index, pd.MultiIndex):
return len(cond)-cond.index.levels[0].tolist().index(cond[cond != yes].index[-1][0])-1
elif isinstance(cond.index, pd.DatetimeIndex):
return len(cond)-cond.index.tolist().index(cond[cond != yes].index[-1])-1 | [
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"或者",
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"=",
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train | get_today_all | today all
Returns:
[type] -- [description] | QUANTAXIS/QAFetch/realtime.py | def get_today_all(output='pd'):
"""today all
Returns:
[type] -- [description]
"""
data = []
today = str(datetime.date.today())
codes = QA_fetch_get_stock_list('stock').code.tolist()
bestip = select_best_ip()['stock']
for code in codes:
try:
l = QA_fetch_get_stock_day(
code, today, today, '00', ip=bestip)
except:
bestip = select_best_ip()['stock']
l = QA_fetch_get_stock_day(
code, today, today, '00', ip=bestip)
if l is not None:
data.append(l)
res = pd.concat(data)
if output in ['pd']:
return res
elif output in ['QAD']:
return QA_DataStruct_Stock_day(res.set_index(['date', 'code'], drop=False)) | def get_today_all(output='pd'):
"""today all
Returns:
[type] -- [description]
"""
data = []
today = str(datetime.date.today())
codes = QA_fetch_get_stock_list('stock').code.tolist()
bestip = select_best_ip()['stock']
for code in codes:
try:
l = QA_fetch_get_stock_day(
code, today, today, '00', ip=bestip)
except:
bestip = select_best_ip()['stock']
l = QA_fetch_get_stock_day(
code, today, today, '00', ip=bestip)
if l is not None:
data.append(l)
res = pd.concat(data)
if output in ['pd']:
return res
elif output in ['QAD']:
return QA_DataStruct_Stock_day(res.set_index(['date', 'code'], drop=False)) | [
"today",
"all"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/realtime.py#L35-L61 | [
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train | QA_SU_save_stock_day | save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用 | QUANTAXIS/QASU/save_tdx_parallelism.py | def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll_stock_day = client.stock_day
coll_stock_day.create_index(
[("code",
pymongo.ASCENDING),
("date_stamp",
pymongo.ASCENDING)]
)
err = []
# saveing result
def __gen_param(stock_list, coll_stock_day, ip_list=[]):
results = []
count = len(ip_list)
total = len(stock_list)
for item in range(len(stock_list)):
try:
code = stock_list[item]
QA_util_log_info(
'##JOB01 Now Saving STOCK_DAY==== {}'.format(str(code)),
ui_log
)
# 首选查找数据库 是否 有 这个代码的数据
search_cond = {'code': str(code)[0:6]}
ref = coll_stock_day.find(search_cond)
end_date = str(now_time())[0:10]
ref_count = coll_stock_day.count_documents(search_cond)
# 当前数据库已经包含了这个代码的数据， 继续增量更新
# 加入这个判断的原因是因为如果股票是刚上市的 数据库会没有数据 所以会有负索引问题出现
if ref_count > 0:
# 接着上次获取的日期继续更新
start_date = ref[ref_count - 1]['date']
# print("ref[ref.count() - 1]['date'] {} {}".format(ref.count(), coll_stock_day.count_documents({'code': str(code)[0:6]})))
else:
# 当前数据库中没有这个代码的股票数据， 从1990-01-01 开始下载所有的数据
start_date = '1990-01-01'
QA_util_log_info(
'UPDATE_STOCK_DAY \n Trying updating {} from {} to {}'
.format(code,
start_date,
end_date),
ui_log
)
if start_date != end_date:
# 更新过的，不更新
results.extend([(code, start_date, end_date, '00', 'day', ip_list[item % count]['ip'],
ip_list[item % count]['port'], item, total, ui_log, ui_progress)])
except Exception as error0:
print('Exception:{}'.format(error0))
err.append(code)
return results
ips = get_ip_list_by_multi_process_ping(stock_ip_list, _type='stock')[:cpu_count() * 2 + 1]
param = __gen_param(stock_list, coll_stock_day, ips)
ps = QA_SU_save_stock_day_parallelism(processes=cpu_count() if len(ips) >= cpu_count() else len(ips),
client=client, ui_log=ui_log)
ps.add(do_saving_work, param)
ps.run()
if len(err) < 1:
QA_util_log_info('SUCCESS save stock day ^_^', ui_log)
else:
QA_util_log_info('ERROR CODE \n ', ui_log)
QA_util_log_info(err, ui_log) | def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll_stock_day = client.stock_day
coll_stock_day.create_index(
[("code",
pymongo.ASCENDING),
("date_stamp",
pymongo.ASCENDING)]
)
err = []
# saveing result
def __gen_param(stock_list, coll_stock_day, ip_list=[]):
results = []
count = len(ip_list)
total = len(stock_list)
for item in range(len(stock_list)):
try:
code = stock_list[item]
QA_util_log_info(
'##JOB01 Now Saving STOCK_DAY==== {}'.format(str(code)),
ui_log
)
# 首选查找数据库 是否 有 这个代码的数据
search_cond = {'code': str(code)[0:6]}
ref = coll_stock_day.find(search_cond)
end_date = str(now_time())[0:10]
ref_count = coll_stock_day.count_documents(search_cond)
# 当前数据库已经包含了这个代码的数据， 继续增量更新
# 加入这个判断的原因是因为如果股票是刚上市的 数据库会没有数据 所以会有负索引问题出现
if ref_count > 0:
# 接着上次获取的日期继续更新
start_date = ref[ref_count - 1]['date']
# print("ref[ref.count() - 1]['date'] {} {}".format(ref.count(), coll_stock_day.count_documents({'code': str(code)[0:6]})))
else:
# 当前数据库中没有这个代码的股票数据， 从1990-01-01 开始下载所有的数据
start_date = '1990-01-01'
QA_util_log_info(
'UPDATE_STOCK_DAY \n Trying updating {} from {} to {}'
.format(code,
start_date,
end_date),
ui_log
)
if start_date != end_date:
# 更新过的，不更新
results.extend([(code, start_date, end_date, '00', 'day', ip_list[item % count]['ip'],
ip_list[item % count]['port'], item, total, ui_log, ui_progress)])
except Exception as error0:
print('Exception:{}'.format(error0))
err.append(code)
return results
ips = get_ip_list_by_multi_process_ping(stock_ip_list, _type='stock')[:cpu_count() * 2 + 1]
param = __gen_param(stock_list, coll_stock_day, ips)
ps = QA_SU_save_stock_day_parallelism(processes=cpu_count() if len(ips) >= cpu_count() else len(ips),
client=client, ui_log=ui_log)
ps.add(do_saving_work, param)
ps.run()
if len(err) < 1:
QA_util_log_info('SUCCESS save stock day ^_^', ui_log)
else:
QA_util_log_info('ERROR CODE \n ', ui_log)
QA_util_log_info(err, ui_log) | [
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train | QA_user_sign_in | 用户登陆
不使用 QAUSER库
只返回 TRUE/FALSE | QUANTAXIS/QASU/user.py | def QA_user_sign_in(username, password):
"""用户登陆
不使用 QAUSER库
只返回 TRUE/FALSE
"""
#user = QA_User(name= name, password=password)
cursor = DATABASE.user.find_one(
{'username': username, 'password': password})
if cursor is None:
QA_util_log_info('SOMETHING WRONG')
return False
else:
return True | def QA_user_sign_in(username, password):
"""用户登陆
不使用 QAUSER库
只返回 TRUE/FALSE
"""
#user = QA_User(name= name, password=password)
cursor = DATABASE.user.find_one(
{'username': username, 'password': password})
if cursor is None:
QA_util_log_info('SOMETHING WRONG')
return False
else:
return True | [
"用户登陆",
"不使用",
"QAUSER库",
"只返回",
"TRUE",
"/",
"FALSE"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/user.py#L31-L43 | [
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train | QA_user_sign_up | 只做check! 具体逻辑需要在自己的函数中实现
参见:QAWEBSERVER中的实现
Arguments:
name {[type]} -- [description]
password {[type]} -- [description]
client {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QASU/user.py | def QA_user_sign_up(name, password, client):
"""只做check! 具体逻辑需要在自己的函数中实现
参见:QAWEBSERVER中的实现
Arguments:
name {[type]} -- [description]
password {[type]} -- [description]
client {[type]} -- [description]
Returns:
[type] -- [description]
"""
coll = client.user
if (coll.find({'username': name}).count() > 0):
print(name)
QA_util_log_info('user name is already exist')
return False
else:
return True | def QA_user_sign_up(name, password, client):
"""只做check! 具体逻辑需要在自己的函数中实现
参见:QAWEBSERVER中的实现
Arguments:
name {[type]} -- [description]
password {[type]} -- [description]
client {[type]} -- [description]
Returns:
[type] -- [description]
"""
coll = client.user
if (coll.find({'username': name}).count() > 0):
print(name)
QA_util_log_info('user name is already exist')
return False
else:
return True | [
"只做check!",
"具体逻辑需要在自己的函数中实现"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/user.py#L46-L66 | [
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train | QA_Broker.warp | 对order/market的封装
[description]
Arguments:
order {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAMarket/QABroker.py | def warp(self, order):
"""对order/market的封装
[description]
Arguments:
order {[type]} -- [description]
Returns:
[type] -- [description]
"""
# 因为成交模式对时间的封装
if order.order_model == ORDER_MODEL.MARKET:
if order.frequence is FREQUENCE.DAY:
# exact_time = str(datetime.datetime.strptime(
# str(order.datetime), '%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1))
order.date = order.datetime[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
elif order.frequence in [FREQUENCE.ONE_MIN,
FREQUENCE.FIVE_MIN,
FREQUENCE.FIFTEEN_MIN,
FREQUENCE.THIRTY_MIN,
FREQUENCE.SIXTY_MIN]:
exact_time = str(
datetime.datetime
.strptime(str(order.datetime),
'%Y-%m-%d %H:%M:%S') +
datetime.timedelta(minutes=1)
)
order.date = exact_time[0:10]
order.datetime = exact_time
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = (
float(self.market_data["high"]) +
float(self.market_data["low"])
) * 0.5
elif order.order_model == ORDER_MODEL.NEXT_OPEN:
try:
exact_time = str(
datetime.datetime
.strptime(str(order.datetime),
'%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1)
)
order.date = exact_time[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
except:
order.datetime = '{} 15:00:00'.format(order.date)
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = float(self.market_data["close"])
elif order.order_model == ORDER_MODEL.CLOSE:
try:
order.datetime = self.market_data.datetime
except:
if len(str(order.datetime)) == 19:
pass
else:
order.datetime = '{} 15:00:00'.format(order.date)
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = float(self.market_data["close"])
elif order.order_model == ORDER_MODEL.STRICT:
'加入严格模式'
if order.frequence is FREQUENCE.DAY:
exact_time = str(
datetime.datetime
.strptime(order.datetime,
'%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1)
)
order.date = exact_time[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
elif order.frequence in [FREQUENCE.ONE_MIN,
FREQUENCE.FIVE_MIN,
FREQUENCE.FIFTEEN_MIN,
FREQUENCE.THIRTY_MIN,
FREQUENCE.SIXTY_MIN]:
exact_time = str(
datetime.datetime
.strptime(order.datetime,
'%Y-%m-%d %H-%M-%S') +
datetime.timedelta(minute=1)
)
order.date = exact_time[0:10]
order.datetime = exact_time
self.market_data = self.get_market(order)
if self.market_data is None:
return order
if order.towards == 1:
order.price = float(self.market_data["high"])
else:
order.price = float(self.market_data["low"])
return order | def warp(self, order):
"""对order/market的封装
[description]
Arguments:
order {[type]} -- [description]
Returns:
[type] -- [description]
"""
# 因为成交模式对时间的封装
if order.order_model == ORDER_MODEL.MARKET:
if order.frequence is FREQUENCE.DAY:
# exact_time = str(datetime.datetime.strptime(
# str(order.datetime), '%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1))
order.date = order.datetime[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
elif order.frequence in [FREQUENCE.ONE_MIN,
FREQUENCE.FIVE_MIN,
FREQUENCE.FIFTEEN_MIN,
FREQUENCE.THIRTY_MIN,
FREQUENCE.SIXTY_MIN]:
exact_time = str(
datetime.datetime
.strptime(str(order.datetime),
'%Y-%m-%d %H:%M:%S') +
datetime.timedelta(minutes=1)
)
order.date = exact_time[0:10]
order.datetime = exact_time
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = (
float(self.market_data["high"]) +
float(self.market_data["low"])
) * 0.5
elif order.order_model == ORDER_MODEL.NEXT_OPEN:
try:
exact_time = str(
datetime.datetime
.strptime(str(order.datetime),
'%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1)
)
order.date = exact_time[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
except:
order.datetime = '{} 15:00:00'.format(order.date)
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = float(self.market_data["close"])
elif order.order_model == ORDER_MODEL.CLOSE:
try:
order.datetime = self.market_data.datetime
except:
if len(str(order.datetime)) == 19:
pass
else:
order.datetime = '{} 15:00:00'.format(order.date)
self.market_data = self.get_market(order)
if self.market_data is None:
return order
order.price = float(self.market_data["close"])
elif order.order_model == ORDER_MODEL.STRICT:
'加入严格模式'
if order.frequence is FREQUENCE.DAY:
exact_time = str(
datetime.datetime
.strptime(order.datetime,
'%Y-%m-%d %H-%M-%S') + datetime.timedelta(day=1)
)
order.date = exact_time[0:10]
order.datetime = '{} 09:30:00'.format(order.date)
elif order.frequence in [FREQUENCE.ONE_MIN,
FREQUENCE.FIVE_MIN,
FREQUENCE.FIFTEEN_MIN,
FREQUENCE.THIRTY_MIN,
FREQUENCE.SIXTY_MIN]:
exact_time = str(
datetime.datetime
.strptime(order.datetime,
'%Y-%m-%d %H-%M-%S') +
datetime.timedelta(minute=1)
)
order.date = exact_time[0:10]
order.datetime = exact_time
self.market_data = self.get_market(order)
if self.market_data is None:
return order
if order.towards == 1:
order.price = float(self.market_data["high"])
else:
order.price = float(self.market_data["low"])
return order | [
"对order",
"/",
"market的封装"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QABroker.py#L191-L294 | [
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train | get_filename | get_filename | QUANTAXIS/QAFetch/QAfinancial.py | def get_filename():
"""
get_filename
"""
return [(l[0],l[1]) for l in [line.strip().split(",") for line in requests.get(FINANCIAL_URL).text.strip().split('\n')]] | def get_filename():
"""
get_filename
"""
return [(l[0],l[1]) for l in [line.strip().split(",") for line in requests.get(FINANCIAL_URL).text.strip().split('\n')]] | [
"get_filename"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QAfinancial.py#L78-L82 | [
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train | download_financialzip | 会创建一个download/文件夹 | QUANTAXIS/QAFetch/QAfinancial.py | def download_financialzip():
"""
会创建一个download/文件夹
"""
result = get_filename()
res = []
for item, md5 in result:
if item in os.listdir(download_path) and md5==QA_util_file_md5('{}{}{}'.format(download_path,os.sep,item)):
print('FILE {} is already in {}'.format(item, download_path))
else:
print('CURRENTLY GET/UPDATE {}'.format(item[0:12]))
r = requests.get('http://down.tdx.com.cn:8001/fin/{}'.format(item))
file = '{}{}{}'.format(download_path, os.sep, item)
with open(file, "wb") as code:
code.write(r.content)
res.append(item)
return res | def download_financialzip():
"""
会创建一个download/文件夹
"""
result = get_filename()
res = []
for item, md5 in result:
if item in os.listdir(download_path) and md5==QA_util_file_md5('{}{}{}'.format(download_path,os.sep,item)):
print('FILE {} is already in {}'.format(item, download_path))
else:
print('CURRENTLY GET/UPDATE {}'.format(item[0:12]))
r = requests.get('http://down.tdx.com.cn:8001/fin/{}'.format(item))
file = '{}{}{}'.format(download_path, os.sep, item)
with open(file, "wb") as code:
code.write(r.content)
res.append(item)
return res | [
"会创建一个download",
"/",
"文件夹"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QAfinancial.py#L89-L108 | [
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train | QAHistoryFinancialReader.get_df | 读取历史财务数据文件，并返回pandas结果 ， 类似gpcw20171231.zip格式，具体字段含义参考
https://github.com/rainx/pytdx/issues/133
:param data_file: 数据文件地址， 数据文件类型可以为 .zip 文件，也可以为解压后的 .dat
:return: pandas DataFrame格式的历史财务数据 | QUANTAXIS/QAFetch/QAfinancial.py | def get_df(self, data_file):
"""
读取历史财务数据文件，并返回pandas结果 ， 类似gpcw20171231.zip格式，具体字段含义参考
https://github.com/rainx/pytdx/issues/133
:param data_file: 数据文件地址， 数据文件类型可以为 .zip 文件，也可以为解压后的 .dat
:return: pandas DataFrame格式的历史财务数据
"""
crawler = QAHistoryFinancialCrawler()
with open(data_file, 'rb') as df:
data = crawler.parse(download_file=df)
return crawler.to_df(data) | def get_df(self, data_file):
"""
读取历史财务数据文件，并返回pandas结果 ， 类似gpcw20171231.zip格式，具体字段含义参考
https://github.com/rainx/pytdx/issues/133
:param data_file: 数据文件地址， 数据文件类型可以为 .zip 文件，也可以为解压后的 .dat
:return: pandas DataFrame格式的历史财务数据
"""
crawler = QAHistoryFinancialCrawler()
with open(data_file, 'rb') as df:
data = crawler.parse(download_file=df)
return crawler.to_df(data) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QAfinancial.py#L60-L75 | [
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train | QA_fetch_get_sh_margin | return shanghai margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data | QUANTAXIS/QAFetch/QACrawler.py | def QA_fetch_get_sh_margin(date):
"""return shanghai margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data
"""
if date in trade_date_sse:
data= pd.read_excel(_sh_url.format(QA_util_date_str2int
(date)), 1).assign(date=date).assign(sse='sh')
data.columns=['code','name','leveraged_balance','leveraged_buyout','leveraged_payoff','margin_left','margin_sell','margin_repay','date','sse']
return data
else:
pass | def QA_fetch_get_sh_margin(date):
"""return shanghai margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data
"""
if date in trade_date_sse:
data= pd.read_excel(_sh_url.format(QA_util_date_str2int
(date)), 1).assign(date=date).assign(sse='sh')
data.columns=['code','name','leveraged_balance','leveraged_buyout','leveraged_payoff','margin_left','margin_sell','margin_repay','date','sse']
return data
else:
pass | [
"return",
"shanghai",
"margin",
"data"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QACrawler.py#L34-L49 | [
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train | QA_fetch_get_sz_margin | return shenzhen margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data | QUANTAXIS/QAFetch/QACrawler.py | def QA_fetch_get_sz_margin(date):
"""return shenzhen margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data
"""
if date in trade_date_sse:
return pd.read_excel(_sz_url.format(date)).assign(date=date).assign(sse='sz') | def QA_fetch_get_sz_margin(date):
"""return shenzhen margin data
Arguments:
date {str YYYY-MM-DD} -- date format
Returns:
pandas.DataFrame -- res for margin data
"""
if date in trade_date_sse:
return pd.read_excel(_sz_url.format(date)).assign(date=date).assign(sse='sz') | [
"return",
"shenzhen",
"margin",
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QACrawler.py#L52-L63 | [
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train | QA_Market.upcoming_data | 更新市场数据
broker 为名字，
data 是市场数据
被 QABacktest 中run 方法调用 upcoming_data | QUANTAXIS/QAMarket/QAMarket.py | def upcoming_data(self, broker, data):
'''
更新市场数据
broker 为名字，
data 是市场数据
被 QABacktest 中run 方法调用 upcoming_data
'''
# main thread'
# if self.running_time is not None and self.running_time!= data.datetime[0]:
# for item in self.broker.keys():
# self._settle(item)
self.running_time = data.datetime[0]
for account in self.session.values():
account.run(QA_Event(
event_type=ENGINE_EVENT.UPCOMING_DATA,
# args 附加的参数
market_data=data,
broker_name=broker,
send_order=self.insert_order, # 🛠todo insert_order = insert_order
query_data=self.query_data_no_wait,
query_order=self.query_order,
query_assets=self.query_assets,
query_trade=self.query_trade
)) | def upcoming_data(self, broker, data):
'''
更新市场数据
broker 为名字，
data 是市场数据
被 QABacktest 中run 方法调用 upcoming_data
'''
# main thread'
# if self.running_time is not None and self.running_time!= data.datetime[0]:
# for item in self.broker.keys():
# self._settle(item)
self.running_time = data.datetime[0]
for account in self.session.values():
account.run(QA_Event(
event_type=ENGINE_EVENT.UPCOMING_DATA,
# args 附加的参数
market_data=data,
broker_name=broker,
send_order=self.insert_order, # 🛠todo insert_order = insert_order
query_data=self.query_data_no_wait,
query_order=self.query_order,
query_assets=self.query_assets,
query_trade=self.query_trade
)) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L103-L126 | [
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train | QA_Market.start_order_threading | 开启查询子线程(实盘中用) | QUANTAXIS/QAMarket/QAMarket.py | def start_order_threading(self):
"""开启查询子线程(实盘中用)
"""
self.if_start_orderthreading = True
self.order_handler.if_start_orderquery = True
self.trade_engine.create_kernel('ORDER', daemon=True)
self.trade_engine.start_kernel('ORDER')
self.sync_order_and_deal() | def start_order_threading(self):
"""开启查询子线程(实盘中用)
"""
self.if_start_orderthreading = True
self.order_handler.if_start_orderquery = True
self.trade_engine.create_kernel('ORDER', daemon=True)
self.trade_engine.start_kernel('ORDER')
self.sync_order_and_deal() | [
"开启查询子线程",
"(",
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L172-L181 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_Market.login | login 登录到交易前置
2018-07-02 在实盘中,登录到交易前置后,需要同步资产状态
Arguments:
broker_name {[type]} -- [description]
account_cookie {[type]} -- [description]
Keyword Arguments:
account {[type]} -- [description] (default: {None})
Returns:
[type] -- [description] | QUANTAXIS/QAMarket/QAMarket.py | def login(self, broker_name, account_cookie, account=None):
"""login 登录到交易前置
2018-07-02 在实盘中,登录到交易前置后,需要同步资产状态
Arguments:
broker_name {[type]} -- [description]
account_cookie {[type]} -- [description]
Keyword Arguments:
account {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
res = False
if account is None:
if account_cookie not in self.session.keys():
self.session[account_cookie] = QA_Account(
account_cookie=account_cookie,
broker=broker_name
)
if self.sync_account(broker_name, account_cookie):
res = True
if self.if_start_orderthreading and res:
#
self.order_handler.subscribe(
self.session[account_cookie],
self.broker[broker_name]
)
else:
if account_cookie not in self.session.keys():
account.broker = broker_name
self.session[account_cookie] = account
if self.sync_account(broker_name, account_cookie):
res = True
if self.if_start_orderthreading and res:
#
self.order_handler.subscribe(
account,
self.broker[broker_name]
)
if res:
return res
else:
try:
self.session.pop(account_cookie)
except:
pass
return False | def login(self, broker_name, account_cookie, account=None):
"""login 登录到交易前置
2018-07-02 在实盘中,登录到交易前置后,需要同步资产状态
Arguments:
broker_name {[type]} -- [description]
account_cookie {[type]} -- [description]
Keyword Arguments:
account {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
res = False
if account is None:
if account_cookie not in self.session.keys():
self.session[account_cookie] = QA_Account(
account_cookie=account_cookie,
broker=broker_name
)
if self.sync_account(broker_name, account_cookie):
res = True
if self.if_start_orderthreading and res:
#
self.order_handler.subscribe(
self.session[account_cookie],
self.broker[broker_name]
)
else:
if account_cookie not in self.session.keys():
account.broker = broker_name
self.session[account_cookie] = account
if self.sync_account(broker_name, account_cookie):
res = True
if self.if_start_orderthreading and res:
#
self.order_handler.subscribe(
account,
self.broker[broker_name]
)
if res:
return res
else:
try:
self.session.pop(account_cookie)
except:
pass
return False | [
"login",
"登录到交易前置"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L193-L245 | [
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train | QA_Market.sync_account | 同步账户信息
Arguments:
broker_id {[type]} -- [description]
account_cookie {[type]} -- [description] | QUANTAXIS/QAMarket/QAMarket.py | def sync_account(self, broker_name, account_cookie):
"""同步账户信息
Arguments:
broker_id {[type]} -- [description]
account_cookie {[type]} -- [description]
"""
try:
if isinstance(self.broker[broker_name], QA_BacktestBroker):
pass
else:
self.session[account_cookie].sync_account(
self.broker[broker_name].query_positions(account_cookie)
)
return True
except Exception as e:
print(e)
return False | def sync_account(self, broker_name, account_cookie):
"""同步账户信息
Arguments:
broker_id {[type]} -- [description]
account_cookie {[type]} -- [description]
"""
try:
if isinstance(self.broker[broker_name], QA_BacktestBroker):
pass
else:
self.session[account_cookie].sync_account(
self.broker[broker_name].query_positions(account_cookie)
)
return True
except Exception as e:
print(e)
return False | [
"同步账户信息"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L254-L271 | [
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train | QA_Market._trade | 内部函数 | QUANTAXIS/QAMarket/QAMarket.py | def _trade(self, event):
"内部函数"
print('==================================market enging: trade')
print(self.order_handler.order_queue.pending)
print('==================================')
self.order_handler._trade()
print('done') | def _trade(self, event):
"内部函数"
print('==================================market enging: trade')
print(self.order_handler.order_queue.pending)
print('==================================')
self.order_handler._trade()
print('done') | [
"内部函数"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L585-L591 | [
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train | QA_Market.settle_order | 交易前置结算
1. 回测: 交易队列清空,待交易队列标记SETTLE
2. 账户每日结算
3. broker结算更新 | QUANTAXIS/QAMarket/QAMarket.py | def settle_order(self):
"""交易前置结算
1. 回测: 交易队列清空,待交易队列标记SETTLE
2. 账户每日结算
3. broker结算更新
"""
if self.if_start_orderthreading:
self.order_handler.run(
QA_Event(
event_type=BROKER_EVENT.SETTLE,
event_queue=self.trade_engine.kernels_dict['ORDER'].queue
)
) | def settle_order(self):
"""交易前置结算
1. 回测: 交易队列清空,待交易队列标记SETTLE
2. 账户每日结算
3. broker结算更新
"""
if self.if_start_orderthreading:
self.order_handler.run(
QA_Event(
event_type=BROKER_EVENT.SETTLE,
event_queue=self.trade_engine.kernels_dict['ORDER'].queue
)
) | [
"交易前置结算"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAMarket.py#L644-L659 | [
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train | QA_util_to_json_from_pandas | 需要对于datetime 和date 进行转换, 以免直接被变成了时间戳 | QUANTAXIS/QAUtil/QATransform.py | def QA_util_to_json_from_pandas(data):
"""需要对于datetime 和date 进行转换, 以免直接被变成了时间戳"""
if 'datetime' in data.columns:
data.datetime = data.datetime.apply(str)
if 'date' in data.columns:
data.date = data.date.apply(str)
return json.loads(data.to_json(orient='records')) | def QA_util_to_json_from_pandas(data):
"""需要对于datetime 和date 进行转换, 以免直接被变成了时间戳"""
if 'datetime' in data.columns:
data.datetime = data.datetime.apply(str)
if 'date' in data.columns:
data.date = data.date.apply(str)
return json.loads(data.to_json(orient='records')) | [
"需要对于datetime",
"和date",
"进行转换",
"以免直接被变成了时间戳"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QATransform.py#L32-L38 | [
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train | QA_util_code_tostr | 将所有沪深股票从数字转化到6位的代码
因为有时候在csv等转换的时候,诸如 000001的股票会变成office强制转化成数字1 | QUANTAXIS/QAUtil/QACode.py | def QA_util_code_tostr(code):
"""
将所有沪深股票从数字转化到6位的代码
因为有时候在csv等转换的时候,诸如 000001的股票会变成office强制转化成数字1
"""
if isinstance(code, int):
return "{:>06d}".format(code)
if isinstance(code, str):
# 聚宽股票代码格式 '600000.XSHG'
# 掘金股票代码格式 'SHSE.600000'
# Wind股票代码格式 '600000.SH'
# 天软股票代码格式 'SH600000'
if len(code) == 6:
return code
if len(code) == 8:
# 天软数据
return code[-6:]
if len(code) == 9:
return code[:6]
if len(code) == 11:
if code[0] in ["S"]:
return code.split(".")[1]
return code.split(".")[0]
raise ValueError("错误的股票代码格式")
if isinstance(code, list):
return QA_util_code_to_str(code[0]) | def QA_util_code_tostr(code):
"""
将所有沪深股票从数字转化到6位的代码
因为有时候在csv等转换的时候,诸如 000001的股票会变成office强制转化成数字1
"""
if isinstance(code, int):
return "{:>06d}".format(code)
if isinstance(code, str):
# 聚宽股票代码格式 '600000.XSHG'
# 掘金股票代码格式 'SHSE.600000'
# Wind股票代码格式 '600000.SH'
# 天软股票代码格式 'SH600000'
if len(code) == 6:
return code
if len(code) == 8:
# 天软数据
return code[-6:]
if len(code) == 9:
return code[:6]
if len(code) == 11:
if code[0] in ["S"]:
return code.split(".")[1]
return code.split(".")[0]
raise ValueError("错误的股票代码格式")
if isinstance(code, list):
return QA_util_code_to_str(code[0]) | [
"将所有沪深股票从数字转化到6位的代码"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QACode.py#L29-L56 | [
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train | QA_util_code_tolist | 转换code==> list
Arguments:
code {[type]} -- [description]
Keyword Arguments:
auto_fill {bool} -- 是否自动补全(一般是用于股票/指数/etf等6位数,期货不适用) (default: {True})
Returns:
[list] -- [description] | QUANTAXIS/QAUtil/QACode.py | def QA_util_code_tolist(code, auto_fill=True):
"""转换code==> list
Arguments:
code {[type]} -- [description]
Keyword Arguments:
auto_fill {bool} -- 是否自动补全(一般是用于股票/指数/etf等6位数,期货不适用) (default: {True})
Returns:
[list] -- [description]
"""
if isinstance(code, str):
if auto_fill:
return [QA_util_code_tostr(code)]
else:
return [code]
elif isinstance(code, list):
if auto_fill:
return [QA_util_code_tostr(item) for item in code]
else:
return [item for item in code] | def QA_util_code_tolist(code, auto_fill=True):
"""转换code==> list
Arguments:
code {[type]} -- [description]
Keyword Arguments:
auto_fill {bool} -- 是否自动补全(一般是用于股票/指数/etf等6位数,期货不适用) (default: {True})
Returns:
[list] -- [description]
"""
if isinstance(code, str):
if auto_fill:
return [QA_util_code_tostr(code)]
else:
return [code]
elif isinstance(code, list):
if auto_fill:
return [QA_util_code_tostr(item) for item in code]
else:
return [item for item in code] | [
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train | QA_User.subscribe_strategy | 订阅一个策略
会扣减你的积分
Arguments:
strategy_id {str} -- [description]
last {int} -- [description]
Keyword Arguments:
today {[type]} -- [description] (default: {datetime.date.today()})
cost_coins {int} -- [description] (default: {10}) | QUANTAXIS/QAARP/QAUser.py | def subscribe_strategy(
self,
strategy_id: str,
last: int,
today=datetime.date.today(),
cost_coins=10
):
"""订阅一个策略
会扣减你的积分
Arguments:
strategy_id {str} -- [description]
last {int} -- [description]
Keyword Arguments:
today {[type]} -- [description] (default: {datetime.date.today()})
cost_coins {int} -- [description] (default: {10})
"""
if self.coins > cost_coins:
order_id = str(uuid.uuid1())
self._subscribed_strategy[strategy_id] = {
'lasttime':
last,
'start':
str(today),
'strategy_id':
strategy_id,
'end':
QA_util_get_next_day(
QA_util_get_real_date(str(today),
towards=1),
last
),
'status':
'running',
'uuid':
order_id
}
self.coins -= cost_coins
self.coins_history.append(
[
cost_coins,
strategy_id,
str(today),
last,
order_id,
'subscribe'
]
)
return True, order_id
else:
# return QAERROR.
return False, 'Not Enough Coins' | def subscribe_strategy(
self,
strategy_id: str,
last: int,
today=datetime.date.today(),
cost_coins=10
):
"""订阅一个策略
会扣减你的积分
Arguments:
strategy_id {str} -- [description]
last {int} -- [description]
Keyword Arguments:
today {[type]} -- [description] (default: {datetime.date.today()})
cost_coins {int} -- [description] (default: {10})
"""
if self.coins > cost_coins:
order_id = str(uuid.uuid1())
self._subscribed_strategy[strategy_id] = {
'lasttime':
last,
'start':
str(today),
'strategy_id':
strategy_id,
'end':
QA_util_get_next_day(
QA_util_get_real_date(str(today),
towards=1),
last
),
'status':
'running',
'uuid':
order_id
}
self.coins -= cost_coins
self.coins_history.append(
[
cost_coins,
strategy_id,
str(today),
last,
order_id,
'subscribe'
]
)
return True, order_id
else:
# return QAERROR.
return False, 'Not Enough Coins' | [
"订阅一个策略"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L213-L267 | [
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train | QA_User.unsubscribe_stratgy | 取消订阅某一个策略
Arguments:
strategy_id {[type]} -- [description] | QUANTAXIS/QAARP/QAUser.py | def unsubscribe_stratgy(self, strategy_id):
"""取消订阅某一个策略
Arguments:
strategy_id {[type]} -- [description]
"""
today = datetime.date.today()
order_id = str(uuid.uuid1())
if strategy_id in self._subscribed_strategy.keys():
self._subscribed_strategy[strategy_id]['status'] = 'canceled'
self.coins_history.append(
[0,
strategy_id,
str(today),
0,
order_id,
'unsubscribe']
) | def unsubscribe_stratgy(self, strategy_id):
"""取消订阅某一个策略
Arguments:
strategy_id {[type]} -- [description]
"""
today = datetime.date.today()
order_id = str(uuid.uuid1())
if strategy_id in self._subscribed_strategy.keys():
self._subscribed_strategy[strategy_id]['status'] = 'canceled'
self.coins_history.append(
[0,
strategy_id,
str(today),
0,
order_id,
'unsubscribe']
) | [
"取消订阅某一个策略"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L269-L288 | [
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train | QA_User.subscribing_strategy | 订阅一个策略
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QAUser.py | def subscribing_strategy(self):
"""订阅一个策略
Returns:
[type] -- [description]
"""
res = self.subscribed_strategy.assign(
remains=self.subscribed_strategy.end.apply(
lambda x: pd.Timestamp(x) - pd.Timestamp(datetime.date.today())
)
)
#res['left'] = res['end_time']
# res['remains']
res.assign(
status=res['remains'].apply(
lambda x: 'running'
if x > datetime.timedelta(days=0) else 'timeout'
)
)
return res.query('status=="running"') | def subscribing_strategy(self):
"""订阅一个策略
Returns:
[type] -- [description]
"""
res = self.subscribed_strategy.assign(
remains=self.subscribed_strategy.end.apply(
lambda x: pd.Timestamp(x) - pd.Timestamp(datetime.date.today())
)
)
#res['left'] = res['end_time']
# res['remains']
res.assign(
status=res['remains'].apply(
lambda x: 'running'
if x > datetime.timedelta(days=0) else 'timeout'
)
)
return res.query('status=="running"') | [
"订阅一个策略"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L301-L321 | [
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train | QA_User.new_portfolio | 根据 self.user_cookie 创建一个 portfolio
:return:
如果存在 返回 新建的 QA_Portfolio
如果已经存在 返回 这个portfolio | QUANTAXIS/QAARP/QAUser.py | def new_portfolio(self, portfolio_cookie=None):
'''
根据 self.user_cookie 创建一个 portfolio
:return:
如果存在 返回 新建的 QA_Portfolio
如果已经存在 返回 这个portfolio
'''
_portfolio = QA_Portfolio(
user_cookie=self.user_cookie,
portfolio_cookie=portfolio_cookie
)
if _portfolio.portfolio_cookie not in self.portfolio_list.keys():
self.portfolio_list[_portfolio.portfolio_cookie] = _portfolio
return _portfolio
else:
print(
" prortfolio with user_cookie ",
self.user_cookie,
" already exist!!"
)
return self.portfolio_list[portfolio_cookie] | def new_portfolio(self, portfolio_cookie=None):
'''
根据 self.user_cookie 创建一个 portfolio
:return:
如果存在 返回 新建的 QA_Portfolio
如果已经存在 返回 这个portfolio
'''
_portfolio = QA_Portfolio(
user_cookie=self.user_cookie,
portfolio_cookie=portfolio_cookie
)
if _portfolio.portfolio_cookie not in self.portfolio_list.keys():
self.portfolio_list[_portfolio.portfolio_cookie] = _portfolio
return _portfolio
else:
print(
" prortfolio with user_cookie ",
self.user_cookie,
" already exist!!"
)
return self.portfolio_list[portfolio_cookie] | [
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train | QA_User.get_account | 直接从二级目录拿到account
Arguments:
portfolio_cookie {str} -- [description]
account_cookie {str} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QAUser.py | def get_account(self, portfolio_cookie: str, account_cookie: str):
"""直接从二级目录拿到account
Arguments:
portfolio_cookie {str} -- [description]
account_cookie {str} -- [description]
Returns:
[type] -- [description]
"""
try:
return self.portfolio_list[portfolio_cookie][account_cookie]
except:
return None | def get_account(self, portfolio_cookie: str, account_cookie: str):
"""直接从二级目录拿到account
Arguments:
portfolio_cookie {str} -- [description]
account_cookie {str} -- [description]
Returns:
[type] -- [description]
"""
try:
return self.portfolio_list[portfolio_cookie][account_cookie]
except:
return None | [
"直接从二级目录拿到account"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L369-L383 | [
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train | QA_User.generate_simpleaccount | make a simple account with a easier way
如果当前user中没有创建portfolio, 则创建一个portfolio,并用此portfolio创建一个account
如果已有一个或多个portfolio,则使用第一个portfolio来创建一个account | QUANTAXIS/QAARP/QAUser.py | def generate_simpleaccount(self):
"""make a simple account with a easier way
如果当前user中没有创建portfolio, 则创建一个portfolio,并用此portfolio创建一个account
如果已有一个或多个portfolio,则使用第一个portfolio来创建一个account
"""
if len(self.portfolio_list.keys()) < 1:
po = self.new_portfolio()
else:
po = list(self.portfolio_list.values())[0]
ac = po.new_account()
return ac, po | def generate_simpleaccount(self):
"""make a simple account with a easier way
如果当前user中没有创建portfolio, 则创建一个portfolio,并用此portfolio创建一个account
如果已有一个或多个portfolio,则使用第一个portfolio来创建一个account
"""
if len(self.portfolio_list.keys()) < 1:
po = self.new_portfolio()
else:
po = list(self.portfolio_list.values())[0]
ac = po.new_account()
return ac, po | [
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train | QA_User.register_account | 注册一个account到portfolio组合中
account 也可以是一个策略类，实现其 on_bar 方法
:param account: 被注册的account
:return: | QUANTAXIS/QAARP/QAUser.py | def register_account(self, account, portfolio_cookie=None):
'''
注册一个account到portfolio组合中
account 也可以是一个策略类，实现其 on_bar 方法
:param account: 被注册的account
:return:
'''
# 查找 portfolio
if len(self.portfolio_list.keys()) < 1:
po = self.new_portfolio()
elif portfolio_cookie is not None:
po = self.portfolio_list[portfolio_cookie]
else:
po = list(self.portfolio_list.values())[0]
# 把account 添加到 portfolio中去
po.add_account(account)
return (po, account) | def register_account(self, account, portfolio_cookie=None):
'''
注册一个account到portfolio组合中
account 也可以是一个策略类，实现其 on_bar 方法
:param account: 被注册的account
:return:
'''
# 查找 portfolio
if len(self.portfolio_list.keys()) < 1:
po = self.new_portfolio()
elif portfolio_cookie is not None:
po = self.portfolio_list[portfolio_cookie]
else:
po = list(self.portfolio_list.values())[0]
# 把account 添加到 portfolio中去
po.add_account(account)
return (po, account) | [
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train | QA_User.save | 将QA_USER的信息存入数据库
ATTENTION:
在save user的时候, 需要同时调用 user/portfolio/account链条上所有的实例化类 同时save | QUANTAXIS/QAARP/QAUser.py | def save(self):
"""
将QA_USER的信息存入数据库
ATTENTION:
在save user的时候, 需要同时调用 user/portfolio/account链条上所有的实例化类 同时save
"""
if self.wechat_id is not None:
self.client.update(
{'wechat_id': self.wechat_id},
{'$set': self.message},
upsert=True
)
else:
self.client.update(
{
'username': self.username,
'password': self.password
},
{'$set': self.message},
upsert=True
)
# user ==> portfolio 的存储
# account的存储在 portfolio.save ==> account.save 中
for portfolio in list(self.portfolio_list.values()):
portfolio.save() | def save(self):
"""
将QA_USER的信息存入数据库
ATTENTION:
在save user的时候, 需要同时调用 user/portfolio/account链条上所有的实例化类 同时save
"""
if self.wechat_id is not None:
self.client.update(
{'wechat_id': self.wechat_id},
{'$set': self.message},
upsert=True
)
else:
self.client.update(
{
'username': self.username,
'password': self.password
},
{'$set': self.message},
upsert=True
)
# user ==> portfolio 的存储
# account的存储在 portfolio.save ==> account.save 中
for portfolio in list(self.portfolio_list.values()):
portfolio.save() | [
"将QA_USER的信息存入数据库"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L445-L473 | [
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train | QA_User.sync | 基于账户/密码去sync数据库 | QUANTAXIS/QAARP/QAUser.py | def sync(self):
"""基于账户/密码去sync数据库
"""
if self.wechat_id is not None:
res = self.client.find_one({'wechat_id': self.wechat_id})
else:
res = self.client.find_one(
{
'username': self.username,
'password': self.password
}
)
if res is None:
if self.client.find_one({'username': self.username}) is None:
self.client.insert_one(self.message)
return self
else:
raise RuntimeError('账户名已存在且账户密码不匹配')
else:
self.reload(res)
return self | def sync(self):
"""基于账户/密码去sync数据库
"""
if self.wechat_id is not None:
res = self.client.find_one({'wechat_id': self.wechat_id})
else:
res = self.client.find_one(
{
'username': self.username,
'password': self.password
}
)
if res is None:
if self.client.find_one({'username': self.username}) is None:
self.client.insert_one(self.message)
return self
else:
raise RuntimeError('账户名已存在且账户密码不匹配')
else:
self.reload(res)
return self | [
"基于账户",
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train | QA_User.reload | 恢复方法
Arguments:
message {[type]} -- [description] | QUANTAXIS/QAARP/QAUser.py | def reload(self, message):
"""恢复方法
Arguments:
message {[type]} -- [description]
"""
self.phone = message.get('phone')
self.level = message.get('level')
self.utype = message.get('utype')
self.coins = message.get('coins')
self.wechat_id = message.get('wechat_id')
self.coins_history = message.get('coins_history')
self.money = message.get('money')
self._subscribed_strategy = message.get('subuscribed_strategy')
self._subscribed_code = message.get('subscribed_code')
self.username = message.get('username')
self.password = message.get('password')
self.user_cookie = message.get('user_cookie')
#
portfolio_list = [item['portfolio_cookie'] for item in DATABASE.portfolio.find(
{'user_cookie': self.user_cookie}, {'portfolio_cookie': 1, '_id': 0})]
# portfolio_list = message.get('portfolio_list')
if len(portfolio_list) > 0:
self.portfolio_list = dict(
zip(
portfolio_list,
[
QA_Portfolio(
user_cookie=self.user_cookie,
portfolio_cookie=item
) for item in portfolio_list
]
)
)
else:
self.portfolio_list = {} | def reload(self, message):
"""恢复方法
Arguments:
message {[type]} -- [description]
"""
self.phone = message.get('phone')
self.level = message.get('level')
self.utype = message.get('utype')
self.coins = message.get('coins')
self.wechat_id = message.get('wechat_id')
self.coins_history = message.get('coins_history')
self.money = message.get('money')
self._subscribed_strategy = message.get('subuscribed_strategy')
self._subscribed_code = message.get('subscribed_code')
self.username = message.get('username')
self.password = message.get('password')
self.user_cookie = message.get('user_cookie')
#
portfolio_list = [item['portfolio_cookie'] for item in DATABASE.portfolio.find(
{'user_cookie': self.user_cookie}, {'portfolio_cookie': 1, '_id': 0})]
# portfolio_list = message.get('portfolio_list')
if len(portfolio_list) > 0:
self.portfolio_list = dict(
zip(
portfolio_list,
[
QA_Portfolio(
user_cookie=self.user_cookie,
portfolio_cookie=item
) for item in portfolio_list
]
)
)
else:
self.portfolio_list = {} | [
"恢复方法"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAUser.py#L540-L577 | [
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train | QA_util_format_date2str | 对输入日期进行格式化处理，返回格式为 "%Y-%m-%d" 格式字符串
支持格式包括:
1. str: "%Y%m%d" "%Y%m%d%H%M%S", "%Y%m%d %H:%M:%S",
"%Y-%m-%d", "%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H%M%S"
2. datetime.datetime
3. pd.Timestamp
4. int -> 自动在右边加 0 然后转换，譬如 '20190302093' --> "2019-03-02"
:param cursor_date: str/datetime.datetime/int 日期或时间
:return: str 返回字符串格式日期 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_format_date2str(cursor_date):
"""
对输入日期进行格式化处理，返回格式为 "%Y-%m-%d" 格式字符串
支持格式包括:
1. str: "%Y%m%d" "%Y%m%d%H%M%S", "%Y%m%d %H:%M:%S",
"%Y-%m-%d", "%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H%M%S"
2. datetime.datetime
3. pd.Timestamp
4. int -> 自动在右边加 0 然后转换，譬如 '20190302093' --> "2019-03-02"
:param cursor_date: str/datetime.datetime/int 日期或时间
:return: str 返回字符串格式日期
"""
if isinstance(cursor_date, datetime.datetime):
cursor_date = str(cursor_date)[:10]
elif isinstance(cursor_date, str):
try:
cursor_date = str(pd.Timestamp(cursor_date))[:10]
except:
raise ValueError('请输入正确的日期格式, 建议 "%Y-%m-%d"')
elif isinstance(cursor_date, int):
cursor_date = str(pd.Timestamp("{:<014d}".format(cursor_date)))[:10]
else:
raise ValueError('请输入正确的日期格式，建议 "%Y-%m-%d"')
return cursor_date | def QA_util_format_date2str(cursor_date):
"""
对输入日期进行格式化处理，返回格式为 "%Y-%m-%d" 格式字符串
支持格式包括:
1. str: "%Y%m%d" "%Y%m%d%H%M%S", "%Y%m%d %H:%M:%S",
"%Y-%m-%d", "%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H%M%S"
2. datetime.datetime
3. pd.Timestamp
4. int -> 自动在右边加 0 然后转换，譬如 '20190302093' --> "2019-03-02"
:param cursor_date: str/datetime.datetime/int 日期或时间
:return: str 返回字符串格式日期
"""
if isinstance(cursor_date, datetime.datetime):
cursor_date = str(cursor_date)[:10]
elif isinstance(cursor_date, str):
try:
cursor_date = str(pd.Timestamp(cursor_date))[:10]
except:
raise ValueError('请输入正确的日期格式, 建议 "%Y-%m-%d"')
elif isinstance(cursor_date, int):
cursor_date = str(pd.Timestamp("{:<014d}".format(cursor_date)))[:10]
else:
raise ValueError('请输入正确的日期格式，建议 "%Y-%m-%d"')
return cursor_date | [
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train | QA_util_get_next_trade_date | 得到下 n 个交易日 (不包含当前交易日)
:param date:
:param n: | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_next_trade_date(cursor_date, n=1):
"""
得到下 n 个交易日 (不包含当前交易日)
:param date:
:param n:
"""
cursor_date = QA_util_format_date2str(cursor_date)
if cursor_date in trade_date_sse:
# 如果指定日期为交易日
return QA_util_date_gap(cursor_date, n, "gt")
real_pre_trade_date = QA_util_get_real_date(cursor_date)
return QA_util_date_gap(real_pre_trade_date, n, "gt") | def QA_util_get_next_trade_date(cursor_date, n=1):
"""
得到下 n 个交易日 (不包含当前交易日)
:param date:
:param n:
"""
cursor_date = QA_util_format_date2str(cursor_date)
if cursor_date in trade_date_sse:
# 如果指定日期为交易日
return QA_util_date_gap(cursor_date, n, "gt")
real_pre_trade_date = QA_util_get_real_date(cursor_date)
return QA_util_date_gap(real_pre_trade_date, n, "gt") | [
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train | QA_util_get_pre_trade_date | 得到前 n 个交易日 (不包含当前交易日)
:param date:
:param n: | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_pre_trade_date(cursor_date, n=1):
"""
得到前 n 个交易日 (不包含当前交易日)
:param date:
:param n:
"""
cursor_date = QA_util_format_date2str(cursor_date)
if cursor_date in trade_date_sse:
return QA_util_date_gap(cursor_date, n, "lt")
real_aft_trade_date = QA_util_get_real_date(cursor_date)
return QA_util_date_gap(real_aft_trade_date, n, "lt") | def QA_util_get_pre_trade_date(cursor_date, n=1):
"""
得到前 n 个交易日 (不包含当前交易日)
:param date:
:param n:
"""
cursor_date = QA_util_format_date2str(cursor_date)
if cursor_date in trade_date_sse:
return QA_util_date_gap(cursor_date, n, "lt")
real_aft_trade_date = QA_util_get_real_date(cursor_date)
return QA_util_date_gap(real_aft_trade_date, n, "lt") | [
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train | QA_util_if_tradetime | 时间是否交易 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_if_tradetime(
_time=datetime.datetime.now(),
market=MARKET_TYPE.STOCK_CN,
code=None
):
'时间是否交易'
_time = datetime.datetime.strptime(str(_time)[0:19], '%Y-%m-%d %H:%M:%S')
if market is MARKET_TYPE.STOCK_CN:
if QA_util_if_trade(str(_time.date())[0:10]):
if _time.hour in [10, 13, 14]:
return True
elif _time.hour in [
9
] and _time.minute >= 15: # 修改成9:15 加入 9:15-9:30的盘前竞价时间
return True
elif _time.hour in [11] and _time.minute <= 30:
return True
else:
return False
else:
return False
elif market is MARKET_TYPE.FUTURE_CN:
date_today=str(_time.date())
date_yesterday=str((_time-datetime.timedelta(days=1)).date())
is_today_open=QA_util_if_trade(date_today)
is_yesterday_open=QA_util_if_trade(date_yesterday)
#考虑周六日的期货夜盘情况
if is_today_open==False: #可能是周六或者周日
if is_yesterday_open==False or (_time.hour > 2 or _time.hour == 2 and _time.minute > 30):
return False
shortName = "" # i , p
for i in range(len(code)):
ch = code[i]
if ch.isdigit(): # ch >= 48 and ch <= 57:
break
shortName += code[i].upper()
period = [
[9, 0, 10, 15],
[10, 30, 11, 30],
[13, 30, 15, 0]
]
if (shortName in ["IH", 'IF', 'IC']):
period = [
[9, 30, 11, 30],
[13, 0, 15, 0]
]
elif (shortName in ["T", "TF"]):
period = [
[9, 15, 11, 30],
[13, 0, 15, 15]
]
if 0<=_time.weekday<=4:
for i in range(len(period)):
p = period[i]
if ((_time.hour > p[0] or (_time.hour == p[0] and _time.minute >= p[1])) and (_time.hour < p[2] or (_time.hour == p[2] and _time.minute < p[3]))):
return True
#最新夜盘时间表_2019.03.29
nperiod = [
[
['AU', 'AG', 'SC'],
[21, 0, 2, 30]
],
[
['CU', 'AL', 'ZN', 'PB', 'SN', 'NI'],
[21, 0, 1, 0]
],
[
['RU', 'RB', 'HC', 'BU','FU','SP'],
[21, 0, 23, 0]
],
[
['A', 'B', 'Y', 'M', 'JM', 'J', 'P', 'I', 'L', 'V', 'PP', 'EG', 'C', 'CS'],
[21, 0, 23, 0]
],
[
['SR', 'CF', 'RM', 'MA', 'TA', 'ZC', 'FG', 'IO', 'CY'],
[21, 0, 23, 30]
],
]
for i in range(len(nperiod)):
for j in range(len(nperiod[i][0])):
if nperiod[i][0][j] == shortName:
p = nperiod[i][1]
condA = _time.hour > p[0] or (_time.hour == p[0] and _time.minute >= p[1])
condB = _time.hour < p[2] or (_time.hour == p[2] and _time.minute < p[3])
# in one day
if p[2] >= p[0]:
if ((_time.weekday >= 0 and _time.weekday <= 4) and condA and condB):
return True
else:
if (((_time.weekday >= 0 and _time.weekday <= 4) and condA) or ((_time.weekday >= 1 and _time.weekday <= 5) and condB)):
return True
return False
return False | def QA_util_if_tradetime(
_time=datetime.datetime.now(),
market=MARKET_TYPE.STOCK_CN,
code=None
):
'时间是否交易'
_time = datetime.datetime.strptime(str(_time)[0:19], '%Y-%m-%d %H:%M:%S')
if market is MARKET_TYPE.STOCK_CN:
if QA_util_if_trade(str(_time.date())[0:10]):
if _time.hour in [10, 13, 14]:
return True
elif _time.hour in [
9
] and _time.minute >= 15: # 修改成9:15 加入 9:15-9:30的盘前竞价时间
return True
elif _time.hour in [11] and _time.minute <= 30:
return True
else:
return False
else:
return False
elif market is MARKET_TYPE.FUTURE_CN:
date_today=str(_time.date())
date_yesterday=str((_time-datetime.timedelta(days=1)).date())
is_today_open=QA_util_if_trade(date_today)
is_yesterday_open=QA_util_if_trade(date_yesterday)
#考虑周六日的期货夜盘情况
if is_today_open==False: #可能是周六或者周日
if is_yesterday_open==False or (_time.hour > 2 or _time.hour == 2 and _time.minute > 30):
return False
shortName = "" # i , p
for i in range(len(code)):
ch = code[i]
if ch.isdigit(): # ch >= 48 and ch <= 57:
break
shortName += code[i].upper()
period = [
[9, 0, 10, 15],
[10, 30, 11, 30],
[13, 30, 15, 0]
]
if (shortName in ["IH", 'IF', 'IC']):
period = [
[9, 30, 11, 30],
[13, 0, 15, 0]
]
elif (shortName in ["T", "TF"]):
period = [
[9, 15, 11, 30],
[13, 0, 15, 15]
]
if 0<=_time.weekday<=4:
for i in range(len(period)):
p = period[i]
if ((_time.hour > p[0] or (_time.hour == p[0] and _time.minute >= p[1])) and (_time.hour < p[2] or (_time.hour == p[2] and _time.minute < p[3]))):
return True
#最新夜盘时间表_2019.03.29
nperiod = [
[
['AU', 'AG', 'SC'],
[21, 0, 2, 30]
],
[
['CU', 'AL', 'ZN', 'PB', 'SN', 'NI'],
[21, 0, 1, 0]
],
[
['RU', 'RB', 'HC', 'BU','FU','SP'],
[21, 0, 23, 0]
],
[
['A', 'B', 'Y', 'M', 'JM', 'J', 'P', 'I', 'L', 'V', 'PP', 'EG', 'C', 'CS'],
[21, 0, 23, 0]
],
[
['SR', 'CF', 'RM', 'MA', 'TA', 'ZC', 'FG', 'IO', 'CY'],
[21, 0, 23, 30]
],
]
for i in range(len(nperiod)):
for j in range(len(nperiod[i][0])):
if nperiod[i][0][j] == shortName:
p = nperiod[i][1]
condA = _time.hour > p[0] or (_time.hour == p[0] and _time.minute >= p[1])
condB = _time.hour < p[2] or (_time.hour == p[2] and _time.minute < p[3])
# in one day
if p[2] >= p[0]:
if ((_time.weekday >= 0 and _time.weekday <= 4) and condA and condB):
return True
else:
if (((_time.weekday >= 0 and _time.weekday <= 4) and condA) or ((_time.weekday >= 1 and _time.weekday <= 5) and condB)):
return True
return False
return False | [
"时间是否交易"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7205-L7306 | [
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train | QA_util_get_real_date | 获取真实的交易日期,其中,第三个参数towards是表示向前/向后推
towards=1 日期向后迭代
towards=-1 日期向前迭代
@ yutiansut | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_real_date(date, trade_list=trade_date_sse, towards=-1):
"""
获取真实的交易日期,其中,第三个参数towards是表示向前/向后推
towards=1 日期向后迭代
towards=-1 日期向前迭代
@ yutiansut
"""
date = str(date)[0:10]
if towards == 1:
while date not in trade_list:
date = str(
datetime.datetime.strptime(str(date)[0:10],
'%Y-%m-%d') +
datetime.timedelta(days=1)
)[0:10]
else:
return str(date)[0:10]
elif towards == -1:
while date not in trade_list:
date = str(
datetime.datetime.strptime(str(date)[0:10],
'%Y-%m-%d') -
datetime.timedelta(days=1)
)[0:10]
else:
return str(date)[0:10] | def QA_util_get_real_date(date, trade_list=trade_date_sse, towards=-1):
"""
获取真实的交易日期,其中,第三个参数towards是表示向前/向后推
towards=1 日期向后迭代
towards=-1 日期向前迭代
@ yutiansut
"""
date = str(date)[0:10]
if towards == 1:
while date not in trade_list:
date = str(
datetime.datetime.strptime(str(date)[0:10],
'%Y-%m-%d') +
datetime.timedelta(days=1)
)[0:10]
else:
return str(date)[0:10]
elif towards == -1:
while date not in trade_list:
date = str(
datetime.datetime.strptime(str(date)[0:10],
'%Y-%m-%d') -
datetime.timedelta(days=1)
)[0:10]
else:
return str(date)[0:10] | [
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train | QA_util_get_real_datelist | 取数据的真实区间,返回的时候用 start,end=QA_util_get_real_datelist
@yutiansut
2017/8/10
当start end中间没有交易日 返回None, None
@yutiansut/ 2017-12-19 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_real_datelist(start, end):
"""
取数据的真实区间,返回的时候用 start,end=QA_util_get_real_datelist
@yutiansut
2017/8/10
当start end中间没有交易日 返回None, None
@yutiansut/ 2017-12-19
"""
real_start = QA_util_get_real_date(start, trade_date_sse, 1)
real_end = QA_util_get_real_date(end, trade_date_sse, -1)
if trade_date_sse.index(real_start) > trade_date_sse.index(real_end):
return None, None
else:
return (real_start, real_end) | def QA_util_get_real_datelist(start, end):
"""
取数据的真实区间,返回的时候用 start,end=QA_util_get_real_datelist
@yutiansut
2017/8/10
当start end中间没有交易日 返回None, None
@yutiansut/ 2017-12-19
"""
real_start = QA_util_get_real_date(start, trade_date_sse, 1)
real_end = QA_util_get_real_date(end, trade_date_sse, -1)
if trade_date_sse.index(real_start) > trade_date_sse.index(real_end):
return None, None
else:
return (real_start, real_end) | [
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train | QA_util_get_trade_range | 给出交易具体时间 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_trade_range(start, end):
'给出交易具体时间'
start, end = QA_util_get_real_datelist(start, end)
if start is not None:
return trade_date_sse[trade_date_sse
.index(start):trade_date_sse.index(end) + 1:1]
else:
return None | def QA_util_get_trade_range(start, end):
'给出交易具体时间'
start, end = QA_util_get_real_datelist(start, end)
if start is not None:
return trade_date_sse[trade_date_sse
.index(start):trade_date_sse.index(end) + 1:1]
else:
return None | [
"给出交易具体时间"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7387-L7394 | [
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train | QA_util_get_trade_gap | 返回start_day到end_day中间有多少个交易天 算首尾 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_trade_gap(start, end):
'返回start_day到end_day中间有多少个交易天 算首尾'
start, end = QA_util_get_real_datelist(start, end)
if start is not None:
return trade_date_sse.index(end) + 1 - trade_date_sse.index(start)
else:
return 0 | def QA_util_get_trade_gap(start, end):
'返回start_day到end_day中间有多少个交易天 算首尾'
start, end = QA_util_get_real_datelist(start, end)
if start is not None:
return trade_date_sse.index(end) + 1 - trade_date_sse.index(start)
else:
return 0 | [
"返回start_day到end_day中间有多少个交易天",
"算首尾"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7397-L7403 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_util_date_gap | :param date: 字符串起始日 类型 str eg: 2018-11-11
:param gap: 整数 间隔多数个交易日
:param methods: gt大于 ，gte 大于等于， 小于lt ，小于等于lte ， 等于===
:return: 字符串 eg：2000-01-01 | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_date_gap(date, gap, methods):
'''
:param date: 字符串起始日 类型 str eg: 2018-11-11
:param gap: 整数 间隔多数个交易日
:param methods: gt大于 ，gte 大于等于， 小于lt ，小于等于lte ， 等于===
:return: 字符串 eg：2000-01-01
'''
try:
if methods in ['>', 'gt']:
return trade_date_sse[trade_date_sse.index(date) + gap]
elif methods in ['>=', 'gte']:
return trade_date_sse[trade_date_sse.index(date) + gap - 1]
elif methods in ['<', 'lt']:
return trade_date_sse[trade_date_sse.index(date) - gap]
elif methods in ['<=', 'lte']:
return trade_date_sse[trade_date_sse.index(date) - gap + 1]
elif methods in ['==', '=', 'eq']:
return date
except:
return 'wrong date' | def QA_util_date_gap(date, gap, methods):
'''
:param date: 字符串起始日 类型 str eg: 2018-11-11
:param gap: 整数 间隔多数个交易日
:param methods: gt大于 ，gte 大于等于， 小于lt ，小于等于lte ， 等于===
:return: 字符串 eg：2000-01-01
'''
try:
if methods in ['>', 'gt']:
return trade_date_sse[trade_date_sse.index(date) + gap]
elif methods in ['>=', 'gte']:
return trade_date_sse[trade_date_sse.index(date) + gap - 1]
elif methods in ['<', 'lt']:
return trade_date_sse[trade_date_sse.index(date) - gap]
elif methods in ['<=', 'lte']:
return trade_date_sse[trade_date_sse.index(date) - gap + 1]
elif methods in ['==', '=', 'eq']:
return date
except:
return 'wrong date' | [
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train | QA_util_get_trade_datetime | 交易的真实日期
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_trade_datetime(dt=datetime.datetime.now()):
"""交易的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt.date())
else:
return QA_util_get_real_date(str(dt.date()), trade_date_sse, 1) | def QA_util_get_trade_datetime(dt=datetime.datetime.now()):
"""交易的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt.date())
else:
return QA_util_get_real_date(str(dt.date()), trade_date_sse, 1) | [
"交易的真实日期"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7429-L7441 | [
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train | QA_util_get_order_datetime | 委托的真实日期
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_get_order_datetime(dt):
"""委托的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
dt = datetime.datetime.strptime(str(dt)[0:19], '%Y-%m-%d %H:%M:%S')
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt)
else:
# print('before')
# print(QA_util_date_gap(str(dt.date()),1,'lt'))
return '{} {}'.format(
QA_util_date_gap(str(dt.date()),
1,
'lt'),
dt.time()
) | def QA_util_get_order_datetime(dt):
"""委托的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
dt = datetime.datetime.strptime(str(dt)[0:19], '%Y-%m-%d %H:%M:%S')
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt)
else:
# print('before')
# print(QA_util_date_gap(str(dt.date()),1,'lt'))
return '{} {}'.format(
QA_util_date_gap(str(dt.date()),
1,
'lt'),
dt.time()
) | [
"委托的真实日期"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7444-L7464 | [
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train | QA_util_future_to_tradedatetime | 输入是真实交易时间,返回按期货交易所规定的时间* 适用于tb/文华/博弈的转换
Arguments:
real_datetime {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_future_to_tradedatetime(real_datetime):
"""输入是真实交易时间,返回按期货交易所规定的时间* 适用于tb/文华/博弈的转换
Arguments:
real_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
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:
dt = datetime.datetime.strptime(
str(real_datetime)[0:16],
'%Y-%m-%d %H:%M'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_next_datetime(dt,
1) | def QA_util_future_to_tradedatetime(real_datetime):
"""输入是真实交易时间,返回按期货交易所规定的时间* 适用于tb/文华/博弈的转换
Arguments:
real_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
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:
dt = datetime.datetime.strptime(
str(real_datetime)[0:16],
'%Y-%m-%d %H:%M'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_next_datetime(dt,
1) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7467-L7493 | [
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train | QA_util_future_to_realdatetime | 输入是交易所规定的时间,返回真实时间*适用于通达信的时间转换
Arguments:
trade_datetime {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QADate_trade.py | def QA_util_future_to_realdatetime(trade_datetime):
"""输入是交易所规定的时间,返回真实时间*适用于通达信的时间转换
Arguments:
trade_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
if len(str(trade_datetime)) == 19:
dt = datetime.datetime.strptime(
str(trade_datetime)[0:19],
'%Y-%m-%d %H:%M:%S'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_last_datetime(dt,
1)
elif len(str(trade_datetime)) == 16:
dt = datetime.datetime.strptime(
str(trade_datetime)[0:16],
'%Y-%m-%d %H:%M'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_last_datetime(dt,
1) | def QA_util_future_to_realdatetime(trade_datetime):
"""输入是交易所规定的时间,返回真实时间*适用于通达信的时间转换
Arguments:
trade_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
if len(str(trade_datetime)) == 19:
dt = datetime.datetime.strptime(
str(trade_datetime)[0:19],
'%Y-%m-%d %H:%M:%S'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_last_datetime(dt,
1)
elif len(str(trade_datetime)) == 16:
dt = datetime.datetime.strptime(
str(trade_datetime)[0:16],
'%Y-%m-%d %H:%M'
)
return dt if dt.time(
) < datetime.time(21,
0) else QA_util_get_last_datetime(dt,
1) | [
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"返回真实时间",
"*",
"适用于通达信的时间转换"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADate_trade.py#L7496-L7522 | [
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train | QA_util_make_hour_index | 创建股票的小时线的index
Arguments:
day {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QABar.py | def QA_util_make_hour_index(day, type_='1h'):
"""创建股票的小时线的index
Arguments:
day {[type]} -- [description]
Returns:
[type] -- [description]
"""
if QA_util_if_trade(day) is True:
return pd.date_range(
str(day) + ' 09:30:00',
str(day) + ' 11:30:00',
freq=type_,
closed='right'
).append(
pd.date_range(
str(day) + ' 13:00:00',
str(day) + ' 15:00:00',
freq=type_,
closed='right'
)
)
else:
return pd.DataFrame(['No trade']) | def QA_util_make_hour_index(day, type_='1h'):
"""创建股票的小时线的index
Arguments:
day {[type]} -- [description]
Returns:
[type] -- [description]
"""
if QA_util_if_trade(day) is True:
return pd.date_range(
str(day) + ' 09:30:00',
str(day) + ' 11:30:00',
freq=type_,
closed='right'
).append(
pd.date_range(
str(day) + ' 13:00:00',
str(day) + ' 15:00:00',
freq=type_,
closed='right'
)
)
else:
return pd.DataFrame(['No trade']) | [
"创建股票的小时线的index"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QABar.py#L96-L121 | [
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train | QA_util_time_gap | 分钟线回测的时候的gap | QUANTAXIS/QAUtil/QABar.py | def QA_util_time_gap(time, gap, methods, type_):
'分钟线回测的时候的gap'
min_len = int(240 / int(str(type_).split('min')[0]))
day_gap = math.ceil(gap / min_len)
if methods in ['>', 'gt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] > time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['>=', 'gte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] >= time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['<', 'lt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] < time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['<=', 'lte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] <= time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['==', '=', 'eq']:
return time | def QA_util_time_gap(time, gap, methods, type_):
'分钟线回测的时候的gap'
min_len = int(240 / int(str(type_).split('min')[0]))
day_gap = math.ceil(gap / min_len)
if methods in ['>', 'gt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] > time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['>=', 'gte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] >= time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['<', 'lt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] < time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['<=', 'lte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] <= time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['==', '=', 'eq']:
return time | [
"分钟线回测的时候的gap"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QABar.py#L124-L217 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_util_save_csv | QA_util_save_csv(data,name,column,location)
将list保存成csv
第一个参数是list
第二个参数是要保存的名字
第三个参数是行的名称(可选)
第四个是保存位置(可选)
@yutiansut | QUANTAXIS/QAUtil/QACsv.py | def QA_util_save_csv(data, name, column=None, location=None):
# 重写了一下保存的模式
# 增加了对于可迭代对象的判断 2017/8/10
"""
QA_util_save_csv(data,name,column,location)
将list保存成csv
第一个参数是list
第二个参数是要保存的名字
第三个参数是行的名称(可选)
第四个是保存位置(可选)
@yutiansut
"""
assert isinstance(data, list)
if location is None:
path = './' + str(name) + '.csv'
else:
path = location + str(name) + '.csv'
with open(path, 'w', newline='') as f:
csvwriter = csv.writer(f)
if column is None:
pass
else:
csvwriter.writerow(column)
for item in data:
if isinstance(item, list):
csvwriter.writerow(item)
else:
csvwriter.writerow([item]) | def QA_util_save_csv(data, name, column=None, location=None):
# 重写了一下保存的模式
# 增加了对于可迭代对象的判断 2017/8/10
"""
QA_util_save_csv(data,name,column,location)
将list保存成csv
第一个参数是list
第二个参数是要保存的名字
第三个参数是行的名称(可选)
第四个是保存位置(可选)
@yutiansut
"""
assert isinstance(data, list)
if location is None:
path = './' + str(name) + '.csv'
else:
path = location + str(name) + '.csv'
with open(path, 'w', newline='') as f:
csvwriter = csv.writer(f)
if column is None:
pass
else:
csvwriter.writerow(column)
for item in data:
if isinstance(item, list):
csvwriter.writerow(item)
else:
csvwriter.writerow([item]) | [
"QA_util_save_csv",
"(",
"data",
"name",
"column",
"location",
")"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QACsv.py#L28-L59 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_SPEBroker.query_positions | 查询现金和持仓
Arguments:
accounts {[type]} -- [description]
Returns:
dict-- {'cash_available':xxx,'hold_available':xxx} | QUANTAXIS/QAMarket/QAShipaneBroker.py | def query_positions(self, accounts):
"""查询现金和持仓
Arguments:
accounts {[type]} -- [description]
Returns:
dict-- {'cash_available':xxx,'hold_available':xxx}
"""
try:
data = self.call("positions", {'client': accounts})
if data is not None:
cash_part = data.get('subAccounts', {}).get('人民币', False)
if cash_part:
cash_available = cash_part.get('可用金额', cash_part.get('可用'))
position_part = data.get('dataTable', False)
if position_part:
res = data.get('dataTable', False)
if res:
hold_headers = res['columns']
hold_headers = [
cn_en_compare[item] for item in hold_headers
]
hold_available = pd.DataFrame(
res['rows'],
columns=hold_headers
)
if len(hold_available) == 1 and hold_available.amount[0] in [
None,
'',
0
]:
hold_available = pd.DataFrame(
data=None,
columns=hold_headers
)
return {
'cash_available':
cash_available,
'hold_available':
hold_available.assign(
amount=hold_available.amount.apply(float)
).loc[:,
['code',
'amount']].set_index('code').amount
}
else:
print(data)
return False, 'None ACCOUNT'
except:
return False | def query_positions(self, accounts):
"""查询现金和持仓
Arguments:
accounts {[type]} -- [description]
Returns:
dict-- {'cash_available':xxx,'hold_available':xxx}
"""
try:
data = self.call("positions", {'client': accounts})
if data is not None:
cash_part = data.get('subAccounts', {}).get('人民币', False)
if cash_part:
cash_available = cash_part.get('可用金额', cash_part.get('可用'))
position_part = data.get('dataTable', False)
if position_part:
res = data.get('dataTable', False)
if res:
hold_headers = res['columns']
hold_headers = [
cn_en_compare[item] for item in hold_headers
]
hold_available = pd.DataFrame(
res['rows'],
columns=hold_headers
)
if len(hold_available) == 1 and hold_available.amount[0] in [
None,
'',
0
]:
hold_available = pd.DataFrame(
data=None,
columns=hold_headers
)
return {
'cash_available':
cash_available,
'hold_available':
hold_available.assign(
amount=hold_available.amount.apply(float)
).loc[:,
['code',
'amount']].set_index('code').amount
}
else:
print(data)
return False, 'None ACCOUNT'
except:
return False | [
"查询现金和持仓"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAShipaneBroker.py#L215-L266 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_SPEBroker.query_clients | 查询clients
Returns:
[type] -- [description] | QUANTAXIS/QAMarket/QAShipaneBroker.py | def query_clients(self):
"""查询clients
Returns:
[type] -- [description]
"""
try:
data = self.call("clients", {'client': 'None'})
if len(data) > 0:
return pd.DataFrame(data).drop(
['commandLine',
'processId'],
axis=1
)
else:
return pd.DataFrame(
None,
columns=[
'id',
'name',
'windowsTitle',
'accountInfo',
'status'
]
)
except Exception as e:
return False, e | def query_clients(self):
"""查询clients
Returns:
[type] -- [description]
"""
try:
data = self.call("clients", {'client': 'None'})
if len(data) > 0:
return pd.DataFrame(data).drop(
['commandLine',
'processId'],
axis=1
)
else:
return pd.DataFrame(
None,
columns=[
'id',
'name',
'windowsTitle',
'accountInfo',
'status'
]
)
except Exception as e:
return False, e | [
"查询clients"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAShipaneBroker.py#L268-L295 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_SPEBroker.query_orders | 查询订单
Arguments:
accounts {[type]} -- [description]
Keyword Arguments:
status {str} -- 'open' 待成交 'filled' 成交 (default: {'filled'})
Returns:
[type] -- [description] | QUANTAXIS/QAMarket/QAShipaneBroker.py | def query_orders(self, accounts, status='filled'):
"""查询订单
Arguments:
accounts {[type]} -- [description]
Keyword Arguments:
status {str} -- 'open' 待成交 'filled' 成交 (default: {'filled'})
Returns:
[type] -- [description]
"""
try:
data = self.call("orders", {'client': accounts, 'status': status})
if data is not None:
orders = data.get('dataTable', False)
order_headers = orders['columns']
if ('成交状态' in order_headers
or '状态说明' in order_headers) and ('备注' in order_headers):
order_headers[order_headers.index('备注')] = '废弃'
order_headers = [cn_en_compare[item] for item in order_headers]
order_all = pd.DataFrame(
orders['rows'],
columns=order_headers
).assign(account_cookie=accounts)
order_all.towards = order_all.towards.apply(
lambda x: trade_towards_cn_en[x]
)
if 'order_time' in order_headers:
# 这是order_status
order_all['status'] = order_all.status.apply(
lambda x: order_status_cn_en[x]
)
if 'order_date' not in order_headers:
order_all.order_time = order_all.order_time.apply(
lambda x: QA_util_get_order_datetime(
dt='{} {}'.format(datetime.date.today(),
x)
)
)
else:
order_all = order_all.assign(
order_time=order_all.order_date
.apply(QA_util_date_int2str) + ' ' +
order_all.order_time
)
if 'trade_time' in order_headers:
order_all.trade_time = order_all.trade_time.apply(
lambda x: '{} {}'.format(datetime.date.today(),
x)
)
if status is 'filled':
return order_all.loc[:,
self.dealstatus_headers].set_index(
['account_cookie',
'realorder_id']
).sort_index()
else:
return order_all.loc[:,
self.orderstatus_headers].set_index(
['account_cookie',
'realorder_id']
).sort_index()
else:
print('response is None')
return False
except Exception as e:
print(e)
return False | def query_orders(self, accounts, status='filled'):
"""查询订单
Arguments:
accounts {[type]} -- [description]
Keyword Arguments:
status {str} -- 'open' 待成交 'filled' 成交 (default: {'filled'})
Returns:
[type] -- [description]
"""
try:
data = self.call("orders", {'client': accounts, 'status': status})
if data is not None:
orders = data.get('dataTable', False)
order_headers = orders['columns']
if ('成交状态' in order_headers
or '状态说明' in order_headers) and ('备注' in order_headers):
order_headers[order_headers.index('备注')] = '废弃'
order_headers = [cn_en_compare[item] for item in order_headers]
order_all = pd.DataFrame(
orders['rows'],
columns=order_headers
).assign(account_cookie=accounts)
order_all.towards = order_all.towards.apply(
lambda x: trade_towards_cn_en[x]
)
if 'order_time' in order_headers:
# 这是order_status
order_all['status'] = order_all.status.apply(
lambda x: order_status_cn_en[x]
)
if 'order_date' not in order_headers:
order_all.order_time = order_all.order_time.apply(
lambda x: QA_util_get_order_datetime(
dt='{} {}'.format(datetime.date.today(),
x)
)
)
else:
order_all = order_all.assign(
order_time=order_all.order_date
.apply(QA_util_date_int2str) + ' ' +
order_all.order_time
)
if 'trade_time' in order_headers:
order_all.trade_time = order_all.trade_time.apply(
lambda x: '{} {}'.format(datetime.date.today(),
x)
)
if status is 'filled':
return order_all.loc[:,
self.dealstatus_headers].set_index(
['account_cookie',
'realorder_id']
).sort_index()
else:
return order_all.loc[:,
self.orderstatus_headers].set_index(
['account_cookie',
'realorder_id']
).sort_index()
else:
print('response is None')
return False
except Exception as e:
print(e)
return False | [
"查询订单"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAShipaneBroker.py#L297-L372 | [
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train | QA_SPEBroker.send_order | [summary]
Arguments:
accounts {[type]} -- [description]
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
Keyword Arguments:
order_direction {[type]} -- [description] (default: {ORDER_DIRECTION.BUY})
order_model {[type]} -- [description] (default: {ORDER_MODEL.LIMIT})
priceType 可选择： 上海交易所：
0 - 限价委托
4 - 五档即时成交剩余撤销
6 - 五档即时成交剩余转限
深圳交易所：
0 - 限价委托
1 - 对手方最优价格委托
2 - 本方最优价格委托
3 - 即时成交剩余撤销委托
4 - 五档即时成交剩余撤销
5 - 全额成交或撤销委托
Returns:
[type] -- [description] | QUANTAXIS/QAMarket/QAShipaneBroker.py | def send_order(
self,
accounts,
code='000001',
price=9,
amount=100,
order_direction=ORDER_DIRECTION.BUY,
order_model=ORDER_MODEL.LIMIT
):
"""[summary]
Arguments:
accounts {[type]} -- [description]
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
Keyword Arguments:
order_direction {[type]} -- [description] (default: {ORDER_DIRECTION.BUY})
order_model {[type]} -- [description] (default: {ORDER_MODEL.LIMIT})
priceType 可选择： 上海交易所：
0 - 限价委托
4 - 五档即时成交剩余撤销
6 - 五档即时成交剩余转限
深圳交易所：
0 - 限价委托
1 - 对手方最优价格委托
2 - 本方最优价格委托
3 - 即时成交剩余撤销委托
4 - 五档即时成交剩余撤销
5 - 全额成交或撤销委托
Returns:
[type] -- [description]
"""
try:
#print(code, price, amount)
return self.call_post(
'orders',
{
'client': accounts,
"action": 'BUY' if order_direction == 1 else 'SELL',
"symbol": code,
"type": order_model,
"priceType": 0 if order_model == ORDER_MODEL.LIMIT else 4,
"price": price,
"amount": amount
}
)
except json.decoder.JSONDecodeError:
print(RuntimeError('TRADE ERROR'))
return None | def send_order(
self,
accounts,
code='000001',
price=9,
amount=100,
order_direction=ORDER_DIRECTION.BUY,
order_model=ORDER_MODEL.LIMIT
):
"""[summary]
Arguments:
accounts {[type]} -- [description]
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
Keyword Arguments:
order_direction {[type]} -- [description] (default: {ORDER_DIRECTION.BUY})
order_model {[type]} -- [description] (default: {ORDER_MODEL.LIMIT})
priceType 可选择： 上海交易所：
0 - 限价委托
4 - 五档即时成交剩余撤销
6 - 五档即时成交剩余转限
深圳交易所：
0 - 限价委托
1 - 对手方最优价格委托
2 - 本方最优价格委托
3 - 即时成交剩余撤销委托
4 - 五档即时成交剩余撤销
5 - 全额成交或撤销委托
Returns:
[type] -- [description]
"""
try:
#print(code, price, amount)
return self.call_post(
'orders',
{
'client': accounts,
"action": 'BUY' if order_direction == 1 else 'SELL',
"symbol": code,
"type": order_model,
"priceType": 0 if order_model == ORDER_MODEL.LIMIT else 4,
"price": price,
"amount": amount
}
)
except json.decoder.JSONDecodeError:
print(RuntimeError('TRADE ERROR'))
return None | [
"[",
"summary",
"]"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QAShipaneBroker.py#L374-L431 | [
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train | QA_DataStruct_Indicators.get_indicator | 获取某一时间的某一只股票的指标 | QUANTAXIS/QAData/QAIndicatorStruct.py | def get_indicator(self, time, code, indicator_name=None):
"""
获取某一时间的某一只股票的指标
"""
try:
return self.data.loc[(pd.Timestamp(time), code), indicator_name]
except:
raise ValueError('CANNOT FOUND THIS DATE&CODE') | def get_indicator(self, time, code, indicator_name=None):
"""
获取某一时间的某一只股票的指标
"""
try:
return self.data.loc[(pd.Timestamp(time), code), indicator_name]
except:
raise ValueError('CANNOT FOUND THIS DATE&CODE') | [
"获取某一时间的某一只股票的指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/QAIndicatorStruct.py#L47-L54 | [
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train | QA_DataStruct_Indicators.get_timerange | 获取某一段时间的某一只股票的指标 | QUANTAXIS/QAData/QAIndicatorStruct.py | def get_timerange(self, start, end, code=None):
"""
获取某一段时间的某一只股票的指标
"""
try:
return self.data.loc[(slice(pd.Timestamp(start), pd.Timestamp(end)), slice(code)), :]
except:
return ValueError('CANNOT FOUND THIS TIME RANGE') | def get_timerange(self, start, end, code=None):
"""
获取某一段时间的某一只股票的指标
"""
try:
return self.data.loc[(slice(pd.Timestamp(start), pd.Timestamp(end)), slice(code)), :]
except:
return ValueError('CANNOT FOUND THIS TIME RANGE') | [
"获取某一段时间的某一只股票的指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/QAIndicatorStruct.py#L65-L72 | [
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train | QA_SU_save_stock_terminated | 获取已经被终止上市的股票列表，数据从上交所获取，目前只有在上海证券交易所交易被终止的股票。
collection：
code：股票代码 name：股票名称 oDate:上市日期 tDate:终止上市日期
:param client:
:return: None | QUANTAXIS/QASU/save_tushare.py | def QA_SU_save_stock_terminated(client=DATABASE):
'''
获取已经被终止上市的股票列表，数据从上交所获取，目前只有在上海证券交易所交易被终止的股票。
collection：
code：股票代码 name：股票名称 oDate:上市日期 tDate:终止上市日期
:param client:
:return: None
'''
# 🛠todo 已经失效从wind 资讯里获取
# 这个函数已经失效
print("！！！ tushare 这个函数已经失效！！！")
df = QATs.get_terminated()
#df = QATs.get_suspended()
print(
" Get stock terminated from tushare,stock count is %d (终止上市股票列表)" %
len(df)
)
coll = client.stock_terminated
client.drop_collection(coll)
json_data = json.loads(df.reset_index().to_json(orient='records'))
coll.insert(json_data)
print(" 保存终止上市股票列表 到 stock_terminated collection， OK") | def QA_SU_save_stock_terminated(client=DATABASE):
'''
获取已经被终止上市的股票列表，数据从上交所获取，目前只有在上海证券交易所交易被终止的股票。
collection：
code：股票代码 name：股票名称 oDate:上市日期 tDate:终止上市日期
:param client:
:return: None
'''
# 🛠todo 已经失效从wind 资讯里获取
# 这个函数已经失效
print("！！！ tushare 这个函数已经失效！！！")
df = QATs.get_terminated()
#df = QATs.get_suspended()
print(
" Get stock terminated from tushare,stock count is %d (终止上市股票列表)" %
len(df)
)
coll = client.stock_terminated
client.drop_collection(coll)
json_data = json.loads(df.reset_index().to_json(orient='records'))
coll.insert(json_data)
print(" 保存终止上市股票列表 到 stock_terminated collection， OK") | [
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train | QA_SU_save_stock_info_tushare | 获取 股票的 基本信息，包含股票的如下信息
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved,公积金
reservedPerShare,每股公积金
esp,每股收益
bvps,每股净资
pb,市净率
timeToMarket,上市日期
undp,未分利润
perundp, 每股未分配
rev,收入同比(%)
profit,利润同比(%)
gpr,毛利率(%)
npr,净利润率(%)
holders,股东人数
add by tauruswang
在命令行工具 quantaxis 中输入 save stock_info_tushare 中的命令
:param client:
:return: | QUANTAXIS/QASU/save_tushare.py | def QA_SU_save_stock_info_tushare(client=DATABASE):
'''
获取 股票的 基本信息，包含股票的如下信息
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved,公积金
reservedPerShare,每股公积金
esp,每股收益
bvps,每股净资
pb,市净率
timeToMarket,上市日期
undp,未分利润
perundp, 每股未分配
rev,收入同比(%)
profit,利润同比(%)
gpr,毛利率(%)
npr,净利润率(%)
holders,股东人数
add by tauruswang
在命令行工具 quantaxis 中输入 save stock_info_tushare 中的命令
:param client:
:return:
'''
df = QATs.get_stock_basics()
print(" Get stock info from tushare,stock count is %d" % len(df))
coll = client.stock_info_tushare
client.drop_collection(coll)
json_data = json.loads(df.reset_index().to_json(orient='records'))
coll.insert(json_data)
print(" Save data to stock_info_tushare collection， OK") | def QA_SU_save_stock_info_tushare(client=DATABASE):
'''
获取 股票的 基本信息，包含股票的如下信息
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved,公积金
reservedPerShare,每股公积金
esp,每股收益
bvps,每股净资
pb,市净率
timeToMarket,上市日期
undp,未分利润
perundp, 每股未分配
rev,收入同比(%)
profit,利润同比(%)
gpr,毛利率(%)
npr,净利润率(%)
holders,股东人数
add by tauruswang
在命令行工具 quantaxis 中输入 save stock_info_tushare 中的命令
:param client:
:return:
'''
df = QATs.get_stock_basics()
print(" Get stock info from tushare,stock count is %d" % len(df))
coll = client.stock_info_tushare
client.drop_collection(coll)
json_data = json.loads(df.reset_index().to_json(orient='records'))
coll.insert(json_data)
print(" Save data to stock_info_tushare collection， OK") | [
"获取",
"股票的",
"基本信息，包含股票的如下信息"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_tushare.py#L143-L183 | [
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train | QA_SU_save_stock_day | save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用 | QUANTAXIS/QASU/save_tushare.py | def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list()
# TODO: 重命名stock_day_ts
coll_stock_day = client.stock_day_ts
coll_stock_day.create_index(
[("code",
pymongo.ASCENDING),
("date_stamp",
pymongo.ASCENDING)]
)
err = []
num_stocks = len(stock_list)
for index, ts_code in enumerate(stock_list):
QA_util_log_info('The {} of Total {}'.format(index, num_stocks))
strProgressToLog = 'DOWNLOAD PROGRESS {} {}'.format(
str(float(index / num_stocks * 100))[0:4] + '%',
ui_log
)
intProgressToLog = int(float(index / num_stocks * 100))
QA_util_log_info(
strProgressToLog,
ui_log=ui_log,
ui_progress=ui_progress,
ui_progress_int_value=intProgressToLog
)
_saving_work(ts_code,
coll_stock_day,
ui_log=ui_log,
err=err)
# 日线行情每分钟内最多调取200次，超过5000积分无限制
time.sleep(0.005)
if len(err) < 1:
QA_util_log_info('SUCCESS save stock day ^_^', ui_log)
else:
QA_util_log_info('ERROR CODE \n ', ui_log)
QA_util_log_info(err, ui_log) | def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list()
# TODO: 重命名stock_day_ts
coll_stock_day = client.stock_day_ts
coll_stock_day.create_index(
[("code",
pymongo.ASCENDING),
("date_stamp",
pymongo.ASCENDING)]
)
err = []
num_stocks = len(stock_list)
for index, ts_code in enumerate(stock_list):
QA_util_log_info('The {} of Total {}'.format(index, num_stocks))
strProgressToLog = 'DOWNLOAD PROGRESS {} {}'.format(
str(float(index / num_stocks * 100))[0:4] + '%',
ui_log
)
intProgressToLog = int(float(index / num_stocks * 100))
QA_util_log_info(
strProgressToLog,
ui_log=ui_log,
ui_progress=ui_progress,
ui_progress_int_value=intProgressToLog
)
_saving_work(ts_code,
coll_stock_day,
ui_log=ui_log,
err=err)
# 日线行情每分钟内最多调取200次，超过5000积分无限制
time.sleep(0.005)
if len(err) < 1:
QA_util_log_info('SUCCESS save stock day ^_^', ui_log)
else:
QA_util_log_info('ERROR CODE \n ', ui_log)
QA_util_log_info(err, ui_log) | [
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train | QA_util_dict_remove_key | 输入一个dict 返回删除后的 | QUANTAXIS/QAUtil/QADict.py | def QA_util_dict_remove_key(dicts, key):
"""
输入一个dict 返回删除后的
"""
if isinstance(key, list):
for item in key:
try:
dicts.pop(item)
except:
pass
else:
try:
dicts.pop(key)
except:
pass
return dicts | def QA_util_dict_remove_key(dicts, key):
"""
输入一个dict 返回删除后的
"""
if isinstance(key, list):
for item in key:
try:
dicts.pop(item)
except:
pass
else:
try:
dicts.pop(key)
except:
pass
return dicts | [
"输入一个dict",
"返回删除后的"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADict.py#L26-L42 | [
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train | QA_util_sql_async_mongo_setting | 异步mongo示例
Keyword Arguments:
uri {str} -- [description] (default: {'mongodb://localhost:27017/quantaxis'})
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QASql.py | def QA_util_sql_async_mongo_setting(uri='mongodb://localhost:27017/quantaxis'):
"""异步mongo示例
Keyword Arguments:
uri {str} -- [description] (default: {'mongodb://localhost:27017/quantaxis'})
Returns:
[type] -- [description]
"""
# loop = asyncio.new_event_loop()
# asyncio.set_event_loop(loop)
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# async def client():
return AsyncIOMotorClient(uri, io_loop=loop) | def QA_util_sql_async_mongo_setting(uri='mongodb://localhost:27017/quantaxis'):
"""异步mongo示例
Keyword Arguments:
uri {str} -- [description] (default: {'mongodb://localhost:27017/quantaxis'})
Returns:
[type] -- [description]
"""
# loop = asyncio.new_event_loop()
# asyncio.set_event_loop(loop)
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# async def client():
return AsyncIOMotorClient(uri, io_loop=loop) | [
"异步mongo示例"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QASql.py#L41-L59 | [
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train | QA_Portfolio.add_account | portfolio add a account/stratetgy | QUANTAXIS/QAARP/QAPortfolio.py | def add_account(self, account):
'portfolio add a account/stratetgy'
if account.account_cookie not in self.account_list:
if self.cash_available > account.init_cash:
account.portfolio_cookie = self.portfolio_cookie
account.user_cookie = self.user_cookie
self.cash.append(self.cash_available - account.init_cash)
self.account_list.append(account.account_cookie)
account.save()
return account
else:
pass | def add_account(self, account):
'portfolio add a account/stratetgy'
if account.account_cookie not in self.account_list:
if self.cash_available > account.init_cash:
account.portfolio_cookie = self.portfolio_cookie
account.user_cookie = self.user_cookie
self.cash.append(self.cash_available - account.init_cash)
self.account_list.append(account.account_cookie)
account.save()
return account
else:
pass | [
"portfolio",
"add",
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"account",
"/",
"stratetgy"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L196-L207 | [
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train | QA_Portfolio.drop_account | 删除一个account
Arguments:
account_cookie {[type]} -- [description]
Raises:
RuntimeError -- [description] | QUANTAXIS/QAARP/QAPortfolio.py | def drop_account(self, account_cookie):
"""删除一个account
Arguments:
account_cookie {[type]} -- [description]
Raises:
RuntimeError -- [description]
"""
if account_cookie in self.account_list:
res = self.account_list.remove(account_cookie)
self.cash.append(
self.cash[-1] + self.get_account_by_cookie(res).init_cash)
return True
else:
raise RuntimeError(
'account {} is not in the portfolio'.format(account_cookie)
) | def drop_account(self, account_cookie):
"""删除一个account
Arguments:
account_cookie {[type]} -- [description]
Raises:
RuntimeError -- [description]
"""
if account_cookie in self.account_list:
res = self.account_list.remove(account_cookie)
self.cash.append(
self.cash[-1] + self.get_account_by_cookie(res).init_cash)
return True
else:
raise RuntimeError(
'account {} is not in the portfolio'.format(account_cookie)
) | [
"删除一个account"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L209-L227 | [
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train | QA_Portfolio.new_account | 创建一个新的Account
Keyword Arguments:
account_cookie {[type]} -- [description] (default: {None})
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QAPortfolio.py | def new_account(
self,
account_cookie=None,
init_cash=1000000,
market_type=MARKET_TYPE.STOCK_CN,
*args,
**kwargs
):
"""创建一个新的Account
Keyword Arguments:
account_cookie {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
if account_cookie is None:
"""创建新的account
Returns:
[type] -- [description]
"""
# 如果组合的cash_available>创建新的account所需cash
if self.cash_available >= init_cash:
temp = QA_Account(
user_cookie=self.user_cookie,
portfolio_cookie=self.portfolio_cookie,
init_cash=init_cash,
market_type=market_type,
*args,
**kwargs
)
if temp.account_cookie not in self.account_list:
#self.accounts[temp.account_cookie] = temp
self.account_list.append(temp.account_cookie)
temp.save()
self.cash.append(self.cash_available - init_cash)
return temp
else:
return self.new_account()
else:
if self.cash_available >= init_cash:
if account_cookie not in self.account_list:
acc = QA_Account(
portfolio_cookie=self.portfolio_cookie,
user_cookie=self.user_cookie,
init_cash=init_cash,
market_type=market_type,
account_cookie=account_cookie,
*args,
**kwargs
)
acc.save()
self.account_list.append(acc.account_cookie)
self.cash.append(self.cash_available - init_cash)
return acc
else:
return self.get_account_by_cookie(account_cookie) | def new_account(
self,
account_cookie=None,
init_cash=1000000,
market_type=MARKET_TYPE.STOCK_CN,
*args,
**kwargs
):
"""创建一个新的Account
Keyword Arguments:
account_cookie {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
if account_cookie is None:
"""创建新的account
Returns:
[type] -- [description]
"""
# 如果组合的cash_available>创建新的account所需cash
if self.cash_available >= init_cash:
temp = QA_Account(
user_cookie=self.user_cookie,
portfolio_cookie=self.portfolio_cookie,
init_cash=init_cash,
market_type=market_type,
*args,
**kwargs
)
if temp.account_cookie not in self.account_list:
#self.accounts[temp.account_cookie] = temp
self.account_list.append(temp.account_cookie)
temp.save()
self.cash.append(self.cash_available - init_cash)
return temp
else:
return self.new_account()
else:
if self.cash_available >= init_cash:
if account_cookie not in self.account_list:
acc = QA_Account(
portfolio_cookie=self.portfolio_cookie,
user_cookie=self.user_cookie,
init_cash=init_cash,
market_type=market_type,
account_cookie=account_cookie,
*args,
**kwargs
)
acc.save()
self.account_list.append(acc.account_cookie)
self.cash.append(self.cash_available - init_cash)
return acc
else:
return self.get_account_by_cookie(account_cookie) | [
"创建一个新的Account"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L229-L290 | [
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train | QA_Portfolio.get_account_by_cookie | 'give the account_cookie and return the account/strategy back'
:param cookie:
:return: QA_Account with cookie if in dict
None not in list | QUANTAXIS/QAARP/QAPortfolio.py | def get_account_by_cookie(self, cookie):
'''
'give the account_cookie and return the account/strategy back'
:param cookie:
:return: QA_Account with cookie if in dict
None not in list
'''
try:
return QA_Account(
account_cookie=cookie,
user_cookie=self.user_cookie,
portfolio_cookie=self.portfolio_cookie,
auto_reload=True
)
except:
QA_util_log_info('Can not find this account')
return None | def get_account_by_cookie(self, cookie):
'''
'give the account_cookie and return the account/strategy back'
:param cookie:
:return: QA_Account with cookie if in dict
None not in list
'''
try:
return QA_Account(
account_cookie=cookie,
user_cookie=self.user_cookie,
portfolio_cookie=self.portfolio_cookie,
auto_reload=True
)
except:
QA_util_log_info('Can not find this account')
return None | [
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train | QA_Portfolio.get_account | check the account whether in the protfolio dict or not
:param account: QA_Account
:return: QA_Account if in dict
None not in list | QUANTAXIS/QAARP/QAPortfolio.py | def get_account(self, account):
'''
check the account whether in the protfolio dict or not
:param account: QA_Account
:return: QA_Account if in dict
None not in list
'''
try:
return self.get_account_by_cookie(account.account_cookie)
except:
QA_util_log_info(
'Can not find this account with cookies %s' %
account.account_cookie
)
return None | def get_account(self, account):
'''
check the account whether in the protfolio dict or not
:param account: QA_Account
:return: QA_Account if in dict
None not in list
'''
try:
return self.get_account_by_cookie(account.account_cookie)
except:
QA_util_log_info(
'Can not find this account with cookies %s' %
account.account_cookie
)
return None | [
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train | QA_Portfolio.message | portfolio 的cookie | QUANTAXIS/QAARP/QAPortfolio.py | def message(self):
"""portfolio 的cookie
"""
return {
'user_cookie': self.user_cookie,
'portfolio_cookie': self.portfolio_cookie,
'account_list': list(self.account_list),
'init_cash': self.init_cash,
'cash': self.cash,
'history': self.history
} | def message(self):
"""portfolio 的cookie
"""
return {
'user_cookie': self.user_cookie,
'portfolio_cookie': self.portfolio_cookie,
'account_list': list(self.account_list),
'init_cash': self.init_cash,
'cash': self.cash,
'history': self.history
} | [
"portfolio",
"的cookie"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L330-L340 | [
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train | QA_Portfolio.send_order | 基于portfolio对子账户下单
Arguments:
account_cookie {str} -- [description]
Keyword Arguments:
code {[type]} -- [description] (default: {None})
amount {[type]} -- [description] (default: {None})
time {[type]} -- [description] (default: {None})
towards {[type]} -- [description] (default: {None})
price {[type]} -- [description] (default: {None})
money {[type]} -- [description] (default: {None})
order_model {[type]} -- [description] (default: {None})
amount_model {[type]} -- [description] (default: {None})
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QAPortfolio.py | def send_order(
self,
account_cookie: str,
code=None,
amount=None,
time=None,
towards=None,
price=None,
money=None,
order_model=None,
amount_model=None,
*args,
**kwargs
):
"""基于portfolio对子账户下单
Arguments:
account_cookie {str} -- [description]
Keyword Arguments:
code {[type]} -- [description] (default: {None})
amount {[type]} -- [description] (default: {None})
time {[type]} -- [description] (default: {None})
towards {[type]} -- [description] (default: {None})
price {[type]} -- [description] (default: {None})
money {[type]} -- [description] (default: {None})
order_model {[type]} -- [description] (default: {None})
amount_model {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
return self.get_account_by_cookie(account_cookie).send_order(
code=code,
amount=amount,
time=time,
towards=towards,
price=price,
money=money,
order_model=order_model,
amount_model=amount_model
) | def send_order(
self,
account_cookie: str,
code=None,
amount=None,
time=None,
towards=None,
price=None,
money=None,
order_model=None,
amount_model=None,
*args,
**kwargs
):
"""基于portfolio对子账户下单
Arguments:
account_cookie {str} -- [description]
Keyword Arguments:
code {[type]} -- [description] (default: {None})
amount {[type]} -- [description] (default: {None})
time {[type]} -- [description] (default: {None})
towards {[type]} -- [description] (default: {None})
price {[type]} -- [description] (default: {None})
money {[type]} -- [description] (default: {None})
order_model {[type]} -- [description] (default: {None})
amount_model {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
return self.get_account_by_cookie(account_cookie).send_order(
code=code,
amount=amount,
time=time,
towards=towards,
price=price,
money=money,
order_model=order_model,
amount_model=amount_model
) | [
"基于portfolio对子账户下单"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L342-L384 | [
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train | QA_Portfolio.save | 存储过程 | QUANTAXIS/QAARP/QAPortfolio.py | def save(self):
"""存储过程
"""
self.client.update(
{
'portfolio_cookie': self.portfolio_cookie,
'user_cookie': self.user_cookie
},
{'$set': self.message},
upsert=True
) | def save(self):
"""存储过程
"""
self.client.update(
{
'portfolio_cookie': self.portfolio_cookie,
'user_cookie': self.user_cookie
},
{'$set': self.message},
upsert=True
) | [
"存储过程"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QAPortfolio.py#L527-L537 | [
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train | QA_Risk.market_value | 每日每个股票持仓市值表
Returns:
pd.DataFrame -- 市值表 | QUANTAXIS/QAARP/QARisk.py | def market_value(self):
"""每日每个股票持仓市值表
Returns:
pd.DataFrame -- 市值表
"""
if self.account.daily_hold is not None:
if self.if_fq:
return (
self.market_data.to_qfq().pivot('close').fillna(
method='ffill'
) * self.account.daily_hold.apply(abs)
).fillna(method='ffill')
else:
return (
self.market_data.pivot('close').fillna(method='ffill') *
self.account.daily_hold.apply(abs)
).fillna(method='ffill')
else:
return None | def market_value(self):
"""每日每个股票持仓市值表
Returns:
pd.DataFrame -- 市值表
"""
if self.account.daily_hold is not None:
if self.if_fq:
return (
self.market_data.to_qfq().pivot('close').fillna(
method='ffill'
) * self.account.daily_hold.apply(abs)
).fillna(method='ffill')
else:
return (
self.market_data.pivot('close').fillna(method='ffill') *
self.account.daily_hold.apply(abs)
).fillna(method='ffill')
else:
return None | [
"每日每个股票持仓市值表"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L212-L232 | [
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train | QA_Risk.max_dropback | 最大回撤 | QUANTAXIS/QAARP/QARisk.py | def max_dropback(self):
"""最大回撤
"""
return round(
float(
max(
[
(self.assets.iloc[idx] - self.assets.iloc[idx::].min())
/ self.assets.iloc[idx]
for idx in range(len(self.assets))
]
)
),
2
) | def max_dropback(self):
"""最大回撤
"""
return round(
float(
max(
[
(self.assets.iloc[idx] - self.assets.iloc[idx::].min())
/ self.assets.iloc[idx]
for idx in range(len(self.assets))
]
)
),
2
) | [
"最大回撤"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L252-L266 | [
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train | QA_Risk.total_commission | 总手续费 | QUANTAXIS/QAARP/QARisk.py | def total_commission(self):
"""总手续费
"""
return float(
-abs(round(self.account.history_table.commission.sum(),
2))
) | def total_commission(self):
"""总手续费
"""
return float(
-abs(round(self.account.history_table.commission.sum(),
2))
) | [
"总手续费"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L269-L275 | [
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train | QA_Risk.total_tax | 总印花税 | QUANTAXIS/QAARP/QARisk.py | def total_tax(self):
"""总印花税
"""
return float(-abs(round(self.account.history_table.tax.sum(), 2))) | def total_tax(self):
"""总印花税
"""
return float(-abs(round(self.account.history_table.tax.sum(), 2))) | [
"总印花税"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L278-L283 | [
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train | QA_Risk.profit_construct | 利润构成
Returns:
dict -- 利润构成表 | QUANTAXIS/QAARP/QARisk.py | def profit_construct(self):
"""利润构成
Returns:
dict -- 利润构成表
"""
return {
'total_buyandsell':
round(
self.profit_money - self.total_commission - self.total_tax,
2
),
'total_tax':
self.total_tax,
'total_commission':
self.total_commission,
'total_profit':
self.profit_money
} | def profit_construct(self):
"""利润构成
Returns:
dict -- 利润构成表
"""
return {
'total_buyandsell':
round(
self.profit_money - self.total_commission - self.total_tax,
2
),
'total_tax':
self.total_tax,
'total_commission':
self.total_commission,
'total_profit':
self.profit_money
} | [
"利润构成"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L286-L305 | [
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train | QA_Risk.profit_money | 盈利额
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QARisk.py | def profit_money(self):
"""盈利额
Returns:
[type] -- [description]
"""
return float(round(self.assets.iloc[-1] - self.assets.iloc[0], 2)) | def profit_money(self):
"""盈利额
Returns:
[type] -- [description]
"""
return float(round(self.assets.iloc[-1] - self.assets.iloc[0], 2)) | [
"盈利额"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L308-L315 | [
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train | QA_Risk.annualize_return | 年化收益
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QARisk.py | def annualize_return(self):
"""年化收益
Returns:
[type] -- [description]
"""
return round(
float(self.calc_annualize_return(self.assets,
self.time_gap)),
2
) | def annualize_return(self):
"""年化收益
Returns:
[type] -- [description]
"""
return round(
float(self.calc_annualize_return(self.assets,
self.time_gap)),
2
) | [
"年化收益"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L334-L345 | [
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train | QA_Risk.benchmark_data | 基准组合的行情数据(一般是组合,可以调整) | QUANTAXIS/QAARP/QARisk.py | def benchmark_data(self):
"""
基准组合的行情数据(一般是组合,可以调整)
"""
return self.fetch[self.benchmark_type](
self.benchmark_code,
self.account.start_date,
self.account.end_date
) | def benchmark_data(self):
"""
基准组合的行情数据(一般是组合,可以调整)
"""
return self.fetch[self.benchmark_type](
self.benchmark_code,
self.account.start_date,
self.account.end_date
) | [
"基准组合的行情数据",
"(",
"一般是组合",
"可以调整",
")"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L396-L404 | [
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train | QA_Risk.benchmark_assets | 基准组合的账户资产队列 | QUANTAXIS/QAARP/QARisk.py | def benchmark_assets(self):
"""
基准组合的账户资产队列
"""
return (
self.benchmark_data.close /
float(self.benchmark_data.close.iloc[0])
* float(self.assets[0])
) | def benchmark_assets(self):
"""
基准组合的账户资产队列
"""
return (
self.benchmark_data.close /
float(self.benchmark_data.close.iloc[0])
* float(self.assets[0])
) | [
"基准组合的账户资产队列"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L407-L415 | [
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train | QA_Risk.benchmark_annualize_return | 基准组合的年化收益
Returns:
[type] -- [description] | QUANTAXIS/QAARP/QARisk.py | def benchmark_annualize_return(self):
"""基准组合的年化收益
Returns:
[type] -- [description]
"""
return round(
float(
self.calc_annualize_return(
self.benchmark_assets,
self.time_gap
)
),
2
) | def benchmark_annualize_return(self):
"""基准组合的年化收益
Returns:
[type] -- [description]
"""
return round(
float(
self.calc_annualize_return(
self.benchmark_assets,
self.time_gap
)
),
2
) | [
"基准组合的年化收益"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L425-L440 | [
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train | QA_Risk.beta | beta比率 组合的系统性风险 | QUANTAXIS/QAARP/QARisk.py | def beta(self):
"""
beta比率 组合的系统性风险
"""
try:
res = round(
float(
self.calc_beta(
self.profit_pct.dropna(),
self.benchmark_profitpct.dropna()
)
),
2
)
except:
print('贝塔计算错误。。')
res = 0
return res | def beta(self):
"""
beta比率 组合的系统性风险
"""
try:
res = round(
float(
self.calc_beta(
self.profit_pct.dropna(),
self.benchmark_profitpct.dropna()
)
),
2
)
except:
print('贝塔计算错误。。')
res = 0
return res | [
"beta比率",
"组合的系统性风险"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L450-L468 | [
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train | QA_Risk.alpha | alpha比率 与市场基准收益无关的超额收益率 | QUANTAXIS/QAARP/QARisk.py | def alpha(self):
"""
alpha比率 与市场基准收益无关的超额收益率
"""
return round(
float(
self.calc_alpha(
self.annualize_return,
self.benchmark_annualize_return,
self.beta,
0.05
)
),
2
) | def alpha(self):
"""
alpha比率 与市场基准收益无关的超额收益率
"""
return round(
float(
self.calc_alpha(
self.annualize_return,
self.benchmark_annualize_return,
self.beta,
0.05
)
),
2
) | [
"alpha比率",
"与市场基准收益无关的超额收益率"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L471-L485 | [
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train | QA_Risk.sharpe | 夏普比率 | QUANTAXIS/QAARP/QARisk.py | def sharpe(self):
"""
夏普比率
"""
return round(
float(
self.calc_sharpe(self.annualize_return,
self.volatility,
0.05)
),
2
) | def sharpe(self):
"""
夏普比率
"""
return round(
float(
self.calc_sharpe(self.annualize_return,
self.volatility,
0.05)
),
2
) | [
"夏普比率"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L488-L500 | [
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train | QA_Risk.plot_assets_curve | 资金曲线叠加图
@Roy T.Burns 2018/05/29 修改百分比显示错误 | QUANTAXIS/QAARP/QARisk.py | def plot_assets_curve(self, length=14, height=12):
"""
资金曲线叠加图
@Roy T.Burns 2018/05/29 修改百分比显示错误
"""
plt.style.use('ggplot')
plt.figure(figsize=(length, height))
plt.subplot(211)
plt.title('BASIC INFO', fontsize=12)
plt.axis([0, length, 0, 0.6])
plt.axis('off')
i = 0
for item in ['account_cookie', 'portfolio_cookie', 'user_cookie']:
plt.text(
i,
0.5,
'{} : {}'.format(item,
self.message[item]),
fontsize=10,
rotation=0,
wrap=True
)
i += (length / 2.8)
i = 0
for item in ['benchmark_code', 'time_gap', 'max_dropback']:
plt.text(
i,
0.4,
'{} : {}'.format(item,
self.message[item]),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += (length / 2.8)
i = 0
for item in ['annualize_return', 'bm_annualizereturn', 'profit']:
plt.text(
i,
0.3,
'{} : {} %'.format(item,
self.message.get(item,
0) * 100),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += length / 2.8
i = 0
for item in ['init_cash', 'last_assets', 'volatility']:
plt.text(
i,
0.2,
'{} : {} '.format(item,
self.message[item]),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += length / 2.8
i = 0
for item in ['alpha', 'beta', 'sharpe']:
plt.text(
i,
0.1,
'{} : {}'.format(item,
self.message[item]),
ha='left',
fontsize=10,
rotation=0,
wrap=True
)
i += length / 2.8
plt.subplot(212)
self.assets.plot()
self.benchmark_assets.xs(self.benchmark_code, level=1).plot()
asset_p = mpatches.Patch(
color='red',
label='{}'.format(self.account.account_cookie)
)
asset_b = mpatches.Patch(
label='benchmark {}'.format(self.benchmark_code)
)
plt.legend(handles=[asset_p, asset_b], loc=0)
plt.title('ASSET AND BENCKMARK')
return plt | def plot_assets_curve(self, length=14, height=12):
"""
资金曲线叠加图
@Roy T.Burns 2018/05/29 修改百分比显示错误
"""
plt.style.use('ggplot')
plt.figure(figsize=(length, height))
plt.subplot(211)
plt.title('BASIC INFO', fontsize=12)
plt.axis([0, length, 0, 0.6])
plt.axis('off')
i = 0
for item in ['account_cookie', 'portfolio_cookie', 'user_cookie']:
plt.text(
i,
0.5,
'{} : {}'.format(item,
self.message[item]),
fontsize=10,
rotation=0,
wrap=True
)
i += (length / 2.8)
i = 0
for item in ['benchmark_code', 'time_gap', 'max_dropback']:
plt.text(
i,
0.4,
'{} : {}'.format(item,
self.message[item]),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += (length / 2.8)
i = 0
for item in ['annualize_return', 'bm_annualizereturn', 'profit']:
plt.text(
i,
0.3,
'{} : {} %'.format(item,
self.message.get(item,
0) * 100),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += length / 2.8
i = 0
for item in ['init_cash', 'last_assets', 'volatility']:
plt.text(
i,
0.2,
'{} : {} '.format(item,
self.message[item]),
fontsize=10,
ha='left',
rotation=0,
wrap=True
)
i += length / 2.8
i = 0
for item in ['alpha', 'beta', 'sharpe']:
plt.text(
i,
0.1,
'{} : {}'.format(item,
self.message[item]),
ha='left',
fontsize=10,
rotation=0,
wrap=True
)
i += length / 2.8
plt.subplot(212)
self.assets.plot()
self.benchmark_assets.xs(self.benchmark_code, level=1).plot()
asset_p = mpatches.Patch(
color='red',
label='{}'.format(self.account.account_cookie)
)
asset_b = mpatches.Patch(
label='benchmark {}'.format(self.benchmark_code)
)
plt.legend(handles=[asset_p, asset_b], loc=0)
plt.title('ASSET AND BENCKMARK')
return plt | [
"资金曲线叠加图"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L643-L733 | [
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train | QA_Risk.plot_signal | 使用热力图画出买卖信号 | QUANTAXIS/QAARP/QARisk.py | def plot_signal(self, start=None, end=None):
"""
使用热力图画出买卖信号
"""
start = self.account.start_date if start is None else start
end = self.account.end_date if end is None else end
_, ax = plt.subplots(figsize=(20, 18))
sns.heatmap(
self.account.trade.reset_index().drop(
'account_cookie',
axis=1
).set_index('datetime').loc[start:end],
cmap="YlGnBu",
linewidths=0.05,
ax=ax
)
ax.set_title(
'SIGNAL TABLE --ACCOUNT: {}'.format(self.account.account_cookie)
)
ax.set_xlabel('Code')
ax.set_ylabel('DATETIME')
return plt | def plot_signal(self, start=None, end=None):
"""
使用热力图画出买卖信号
"""
start = self.account.start_date if start is None else start
end = self.account.end_date if end is None else end
_, ax = plt.subplots(figsize=(20, 18))
sns.heatmap(
self.account.trade.reset_index().drop(
'account_cookie',
axis=1
).set_index('datetime').loc[start:end],
cmap="YlGnBu",
linewidths=0.05,
ax=ax
)
ax.set_title(
'SIGNAL TABLE --ACCOUNT: {}'.format(self.account.account_cookie)
)
ax.set_xlabel('Code')
ax.set_ylabel('DATETIME')
return plt | [
"使用热力图画出买卖信号"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L775-L796 | [
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train | QA_Performance.pnl_lifo | 使用后进先出法配对成交记录 | QUANTAXIS/QAARP/QARisk.py | def pnl_lifo(self):
"""
使用后进先出法配对成交记录
"""
X = dict(
zip(
self.target.code,
[LifoQueue() for i in range(len(self.target.code))]
)
)
pair_table = []
for _, data in self.target.history_table_min.iterrows():
while True:
if X[data.code].qsize() == 0:
X[data.code].put((data.datetime, data.amount, data.price))
break
else:
l = X[data.code].get()
if (l[1] * data.amount) < 0:
# 原有多仓/ 平仓 或者原有空仓/平仓
if abs(l[1]) > abs(data.amount):
temp = (l[0], l[1] + data.amount, l[2])
X[data.code].put_nowait(temp)
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
abs(data.amount),
data.price,
l[2]
]
)
break
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
abs(data.amount),
l[2],
data.price
]
)
break
elif abs(l[1]) < abs(data.amount):
data.amount = data.amount + l[1]
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
l[1],
data.price,
l[2]
]
)
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
l[1],
l[2],
data.price
]
)
else:
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
abs(data.amount),
data.price,
l[2]
]
)
break
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
abs(data.amount),
l[2],
data.price
]
)
break
else:
X[data.code].put_nowait(l)
X[data.code].put_nowait(
(data.datetime,
data.amount,
data.price)
)
break
pair_title = [
'code',
'sell_date',
'buy_date',
'amount',
'sell_price',
'buy_price'
]
pnl = pd.DataFrame(pair_table, columns=pair_title).set_index('code')
pnl = pnl.assign(
unit=pnl.code.apply(lambda x: self.market_preset.get_unit(x)),
pnl_ratio=(pnl.sell_price / pnl.buy_price) - 1,
sell_date=pd.to_datetime(pnl.sell_date),
buy_date=pd.to_datetime(pnl.buy_date)
)
pnl = pnl.assign(
pnl_money=(pnl.sell_price - pnl.buy_price) * pnl.amount * pnl.unit,
hold_gap=abs(pnl.sell_date - pnl.buy_date),
if_buyopen=(pnl.sell_date -
pnl.buy_date) > datetime.timedelta(days=0)
)
pnl = pnl.assign(
openprice=pnl.if_buyopen.apply(
lambda pnl: 1 if pnl else 0) * pnl.buy_price + pnl.if_buyopen.apply(lambda pnl: 0 if pnl else 1) * pnl.sell_price,
opendate=pnl.if_buyopen.apply(
lambda pnl: 1 if pnl else 0) * pnl.buy_date.map(str) + pnl.if_buyopen.apply(lambda pnl: 0 if pnl else 1) * pnl.sell_date.map(str),
closeprice=pnl.if_buyopen.apply(
lambda pnl: 0 if pnl else 1) * pnl.buy_price + pnl.if_buyopen.apply(lambda pnl: 1 if pnl else 0) * pnl.sell_price,
closedate=pnl.if_buyopen.apply(
lambda pnl: 0 if pnl else 1) * pnl.buy_date.map(str) + pnl.if_buyopen.apply(lambda pnl: 1 if pnl else 0) * pnl.sell_date.map(str))
return pnl.set_index('code') | def pnl_lifo(self):
"""
使用后进先出法配对成交记录
"""
X = dict(
zip(
self.target.code,
[LifoQueue() for i in range(len(self.target.code))]
)
)
pair_table = []
for _, data in self.target.history_table_min.iterrows():
while True:
if X[data.code].qsize() == 0:
X[data.code].put((data.datetime, data.amount, data.price))
break
else:
l = X[data.code].get()
if (l[1] * data.amount) < 0:
# 原有多仓/ 平仓 或者原有空仓/平仓
if abs(l[1]) > abs(data.amount):
temp = (l[0], l[1] + data.amount, l[2])
X[data.code].put_nowait(temp)
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
abs(data.amount),
data.price,
l[2]
]
)
break
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
abs(data.amount),
l[2],
data.price
]
)
break
elif abs(l[1]) < abs(data.amount):
data.amount = data.amount + l[1]
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
l[1],
data.price,
l[2]
]
)
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
l[1],
l[2],
data.price
]
)
else:
if data.amount < 0:
pair_table.append(
[
data.code,
data.datetime,
l[0],
abs(data.amount),
data.price,
l[2]
]
)
break
else:
pair_table.append(
[
data.code,
l[0],
data.datetime,
abs(data.amount),
l[2],
data.price
]
)
break
else:
X[data.code].put_nowait(l)
X[data.code].put_nowait(
(data.datetime,
data.amount,
data.price)
)
break
pair_title = [
'code',
'sell_date',
'buy_date',
'amount',
'sell_price',
'buy_price'
]
pnl = pd.DataFrame(pair_table, columns=pair_title).set_index('code')
pnl = pnl.assign(
unit=pnl.code.apply(lambda x: self.market_preset.get_unit(x)),
pnl_ratio=(pnl.sell_price / pnl.buy_price) - 1,
sell_date=pd.to_datetime(pnl.sell_date),
buy_date=pd.to_datetime(pnl.buy_date)
)
pnl = pnl.assign(
pnl_money=(pnl.sell_price - pnl.buy_price) * pnl.amount * pnl.unit,
hold_gap=abs(pnl.sell_date - pnl.buy_date),
if_buyopen=(pnl.sell_date -
pnl.buy_date) > datetime.timedelta(days=0)
)
pnl = pnl.assign(
openprice=pnl.if_buyopen.apply(
lambda pnl: 1 if pnl else 0) * pnl.buy_price + pnl.if_buyopen.apply(lambda pnl: 0 if pnl else 1) * pnl.sell_price,
opendate=pnl.if_buyopen.apply(
lambda pnl: 1 if pnl else 0) * pnl.buy_date.map(str) + pnl.if_buyopen.apply(lambda pnl: 0 if pnl else 1) * pnl.sell_date.map(str),
closeprice=pnl.if_buyopen.apply(
lambda pnl: 0 if pnl else 1) * pnl.buy_price + pnl.if_buyopen.apply(lambda pnl: 1 if pnl else 0) * pnl.sell_price,
closedate=pnl.if_buyopen.apply(
lambda pnl: 0 if pnl else 1) * pnl.buy_date.map(str) + pnl.if_buyopen.apply(lambda pnl: 1 if pnl else 0) * pnl.sell_date.map(str))
return pnl.set_index('code') | [
"使用后进先出法配对成交记录"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L1015-L1155 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_Performance.plot_pnlratio | 画出pnl比率散点图 | QUANTAXIS/QAARP/QARisk.py | def plot_pnlratio(self):
"""
画出pnl比率散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_ratio)
plt.gcf().autofmt_xdate()
return plt | def plot_pnlratio(self):
"""
画出pnl比率散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_ratio)
plt.gcf().autofmt_xdate()
return plt | [
"画出pnl比率散点图"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L1313-L1320 | [
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train | QA_Performance.plot_pnlmoney | 画出pnl盈亏额散点图 | QUANTAXIS/QAARP/QARisk.py | def plot_pnlmoney(self):
"""
画出pnl盈亏额散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_money)
plt.gcf().autofmt_xdate()
return plt | def plot_pnlmoney(self):
"""
画出pnl盈亏额散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_money)
plt.gcf().autofmt_xdate()
return plt | [
"画出pnl盈亏额散点图"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L1322-L1328 | [
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train | QA_Performance.win_rate | 胜率
胜率
盈利次数/总次数 | QUANTAXIS/QAARP/QARisk.py | def win_rate(self):
"""胜率
胜率
盈利次数/总次数
"""
data = self.pnl
try:
return round(len(data.query('pnl_money>0')) / len(data), 2)
except ZeroDivisionError:
return 0 | def win_rate(self):
"""胜率
胜率
盈利次数/总次数
"""
data = self.pnl
try:
return round(len(data.query('pnl_money>0')) / len(data), 2)
except ZeroDivisionError:
return 0 | [
"胜率"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAARP/QARisk.py#L1346-L1356 | [
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"ZeroDivisionErr... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | CronTabItem.next_time | Get the local time of the next schedule time this job will run.
:param bool asc: Format the result with ``time.asctime()``
:returns: The epoch time or string representation of the epoch time that
the job should be run next | QUANTAXIS/QASetting/crontab.py | def next_time(self, asc=False):
"""Get the local time of the next schedule time this job will run.
:param bool asc: Format the result with ``time.asctime()``
:returns: The epoch time or string representation of the epoch time that
the job should be run next
"""
_time = time.localtime(time.time() + self.next())
if asc:
return time.asctime(_time)
return time.mktime(_time) | def next_time(self, asc=False):
"""Get the local time of the next schedule time this job will run.
:param bool asc: Format the result with ``time.asctime()``
:returns: The epoch time or string representation of the epoch time that
the job should be run next
"""
_time = time.localtime(time.time() + self.next())
if asc:
return time.asctime(_time)
return time.mktime(_time) | [
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... | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASetting/crontab.py#L51-L62 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_fetch_get_future_transaction_realtime | 期货实时tick | QUANTAXIS/QAFetch/__init__.py | def QA_fetch_get_future_transaction_realtime(package, code):
"""
期货实时tick
"""
Engine = use(package)
if package in ['tdx', 'pytdx']:
return Engine.QA_fetch_get_future_transaction_realtime(code)
else:
return 'Unsupport packages' | def QA_fetch_get_future_transaction_realtime(package, code):
"""
期货实时tick
"""
Engine = use(package)
if package in ['tdx', 'pytdx']:
return Engine.QA_fetch_get_future_transaction_realtime(code)
else:
return 'Unsupport packages' | [
"期货实时tick"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/__init__.py#L272-L280 | [
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train | QA_indicator_MA | MA
Arguments:
DataFrame {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_MA(DataFrame,*args,**kwargs):
"""MA
Arguments:
DataFrame {[type]} -- [description]
Returns:
[type] -- [description]
"""
CLOSE = DataFrame['close']
return pd.DataFrame({'MA{}'.format(N): MA(CLOSE, N) for N in list(args)}) | def QA_indicator_MA(DataFrame,*args,**kwargs):
"""MA
Arguments:
DataFrame {[type]} -- [description]
Returns:
[type] -- [description]
"""
CLOSE = DataFrame['close']
return pd.DataFrame({'MA{}'.format(N): MA(CLOSE, N) for N in list(args)}) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L58-L69 | [
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train | QA_indicator_MACD | MACD CALC | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_MACD(DataFrame, short=12, long=26, mid=9):
"""
MACD CALC
"""
CLOSE = DataFrame['close']
DIF = EMA(CLOSE, short)-EMA(CLOSE, long)
DEA = EMA(DIF, mid)
MACD = (DIF-DEA)*2
return pd.DataFrame({'DIF': DIF, 'DEA': DEA, 'MACD': MACD}) | def QA_indicator_MACD(DataFrame, short=12, long=26, mid=9):
"""
MACD CALC
"""
CLOSE = DataFrame['close']
DIF = EMA(CLOSE, short)-EMA(CLOSE, long)
DEA = EMA(DIF, mid)
MACD = (DIF-DEA)*2
return pd.DataFrame({'DIF': DIF, 'DEA': DEA, 'MACD': MACD}) | [
"MACD",
"CALC"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L82-L92 | [
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train | QA_indicator_DMI | 趋向指标 DMI | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_DMI(DataFrame, M1=14, M2=6):
"""
趋向指标 DMI
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
OPEN = DataFrame.open
TR = SUM(MAX(MAX(HIGH-LOW, ABS(HIGH-REF(CLOSE, 1))),
ABS(LOW-REF(CLOSE, 1))), M1)
HD = HIGH-REF(HIGH, 1)
LD = REF(LOW, 1)-LOW
DMP = SUM(IFAND(HD>0,HD>LD,HD,0), M1)
DMM = SUM(IFAND(LD>0,LD>HD,LD,0), M1)
DI1 = DMP*100/TR
DI2 = DMM*100/TR
ADX = MA(ABS(DI2-DI1)/(DI1+DI2)*100, M2)
ADXR = (ADX+REF(ADX, M2))/2
return pd.DataFrame({
'DI1': DI1, 'DI2': DI2,
'ADX': ADX, 'ADXR': ADXR
}) | def QA_indicator_DMI(DataFrame, M1=14, M2=6):
"""
趋向指标 DMI
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
OPEN = DataFrame.open
TR = SUM(MAX(MAX(HIGH-LOW, ABS(HIGH-REF(CLOSE, 1))),
ABS(LOW-REF(CLOSE, 1))), M1)
HD = HIGH-REF(HIGH, 1)
LD = REF(LOW, 1)-LOW
DMP = SUM(IFAND(HD>0,HD>LD,HD,0), M1)
DMM = SUM(IFAND(LD>0,LD>HD,LD,0), M1)
DI1 = DMP*100/TR
DI2 = DMM*100/TR
ADX = MA(ABS(DI2-DI1)/(DI1+DI2)*100, M2)
ADXR = (ADX+REF(ADX, M2))/2
return pd.DataFrame({
'DI1': DI1, 'DI2': DI2,
'ADX': ADX, 'ADXR': ADXR
}) | [
"趋向指标",
"DMI"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L95-L118 | [
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"ope... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
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