def QA_fetch_stock_day_adv(
code,
__start, __end,
if_drop_index=False,
collections=QA_Setting.client.quantaxis.stock_day):
'获取股票日线'
__start = str(__start)[0:10]
__end = str(__end)[0:10]
if isinstance(code, str):
print(code)
if QA_util_date_valid(__end) == True:
__data = []
for item in collections.find({
'code': str(code)[0:6], "date_stamp": {
"$lte": QA_util_date_stamp(__end),
"$gte": QA_util_date_stamp(__start)}}):
__data.append([str(item['code']), float(item['open']), float(item['high']), float(
item['low']), float(item['close']), float(item['vol']), item['date']])
__data = DataFrame(__data, columns=[
'code', 'open', 'high', 'low', 'close', 'volume', 'date'])
__data['date'] = pd.to_datetime(__data['date'])
return QA_DataStruct_Stock_day(__data.query('volume>1').set_index(['date', 'code'], drop=if_drop_index))
else:
QA_util_log_info('something wrong with date')
elif isinstance(code, list):
return QA_DataStruct_Stock_day(pd.concat(QA_fetch_stocklist_day(code, [__start, __end])).query('volume>1').set_index(['date', 'code'], drop=if_drop_index))
def QA_fetch_stock_day_adv(
code,
start='all', end=None,
if_drop_index=False,
collections=DATABASE.stock_day):
'获取股票日线'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
if start == 'all':
start = '1990-01-01'
end = str(datetime.date.today())
if isinstance(code, str):
if QA_util_date_valid(end) == True:
__data = []
for item in collections.find({
'code': str(code)[0:6], "date_stamp": {
"$lte": QA_util_date_stamp(end),
"$gte": QA_util_date_stamp(start)}}):
__data.append([str(item['code']), float(item['open']), float(item['high']), float(
item['low']), float(item['close']), float(item['vol']), float(item['amount']), item['date']])
__data = DataFrame(__data, columns=[
'code', 'open', 'high', 'low', 'close', 'volume', 'amount', 'date'])
__data['date'] = pd.to_datetime(__data['date'])
return QA_DataStruct_Stock_day(__data.query('volume>1').set_index(['date', 'code'], drop=if_drop_index).sort_index())
else:
QA_util_log_info('something wrong with date')
elif isinstance(code, list):
return QA_DataStruct_Stock_day(pd.concat(QA_fetch_stocklist_day(code, [start, end])).query('volume>1').set_index(['date', 'code'], drop=if_drop_index))
def QA_fetch_index_quant_pre_adv(code, start="all", end=None, format='pd'):
'获取股票量化机器学习数据查询接口'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
# code checking
if start == 'all' or start == None:
start = '2008-01-01'
end = QA_util_today_str()
data = QA_fetch_index_quant_pre(code, start, end)
return QA_DataStruct_Stock_day(data)
else:
data = QA_fetch_index_quant_pre(code, start, end)
return QA_DataStruct_Stock_day(data)
def get_stock_day_qfq_adv(self, codelist, start, end):
res = self.get_stock_day_qfq(codelist, start, end).reset_index()
return QA_DataStruct_Stock_day(
res.assign(amount=res.total_turnover,
code=res.order_book_id).set_index(['date', 'code']),
if_fq='qfq')
def QA_fetch_stocklist_day_adv(
code,
__start, __end,
if_drop_index=False,
collections=QA_Setting.client.quantaxis.stock_day):
'获取股票日线'
return QA_DataStruct_Stock_day(pd.concat(QA_fetch_stocklist_day(code, [__start, __end])).query('volume>1').set_index(['date', 'code'], drop=if_drop_index))
def QA_fetch_stock_day_adv(code,
start='all',
end=None,
if_drop_index=False,
collections=DATABASE.stock_day):
'''
:param code: 股票代码
:param start: 开始日期
:param end: 结束日期
:param if_drop_index:
:param collections: 默认数据库
:return: 如果股票代码不存 或者开始结束日期不存在 在返回 None ，合法返回 QA_DataStruct_Stock_day 数据
'''
'获取股票日线'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
if start == 'all':
start = '1990-01-01'
end = str(datetime.date.today())
res = QA_fetch_stock_day(code, start, end, format='pd')
if res is None:
print("code=%s , start=%s, end=%s QA_fetch_stock_day return None" %
(code, start, end))
return None
else:
return QA_DataStruct_Stock_day(
res.set_index(['date', 'code'], drop=if_drop_index))
def QA_fetch_stock_fianacial_adv(
code,
start='all',
end=None,
if_drop_index=True,
):
'获取财报TTM'
#code= [code] if isinstance(code,str) else code
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
if start == 'all':
start = '1990-01-01'
end = QA_util_today_str()
res = QA_fetch_stock_fianacial(code, start, end, format='pd')
if res is None:
# todo 报告是代码不合法，还是日期不合法
print(
"QA Error QA_fetch_stock_fianacial_adv parameter code=%s , start=%s, end=%s call QA_fetch_stock_fianacial_adv return None"
% (code, start, end))
return None
else:
res_reset_index = res.set_index(['date', 'code'], drop=if_drop_index)
# if res_reset_index is None:
# print("QA Error QA_fetch_stock_fianacial_adv set index 'datetime, code' return None")
# return
return QA_DataStruct_Stock_day(res_reset_index)
def QA_fetch_stock_day_adv(
code,
start='all', end=None,
if_drop_index=False,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.stock_day):
'''
:param code: 股票代码
:param start: 开始日期
:param end: 结束日期
:param if_drop_index:
:param collections: 默认数据库
:return: 如果股票代码不存 或者开始结束日期不存在 在返回 None ，合法返回 QA_DataStruct_Stock_day 数据
'''
'获取股票日线'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
if start == 'all':
start = '1990-01-01'
end = str(datetime.date.today())
res = QA_fetch_stock_day(code, start, end, format='pd')
if res is None:
# 🛠 todo 报告是代码不合法，还是日期不合法
print("💢 Error QA_fetch_stock_day_adv parameter code=%s , start=%s, end=%s call QA_fetch_stock_day return None"%(code,start,end))
return None
else:
res_reset_index = res.set_index(['date', 'code'], drop=if_drop_index)
# if res_reset_index is None:
# print("💢 Error QA_fetch_stock_day_adv set index 'datetime, code' return None")
# return None
return QA_DataStruct_Stock_day(res_reset_index)
def QA_fetch_stocklist_day_adv(
code,
start, end=None,
if_drop_index=False,
collections=DATABASE.stock_day):
'获取股票日线'
return QA_DataStruct_Stock_day(pd.concat(QA_fetch_stocklist_day(code, [start, end])).query('volume>1').set_index(['date', 'code'], drop=if_drop_index).sort_index())
def QA_fetch_stock_target_adv(code,
start="all",
end=None,
type='close',
format='pd'):
'获取股票量化机器学习数据查询接口'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
# code checking
if start == 'all' or start == None:
start = '2008-01-01'
end = QA_util_today_str()
data = QA_fetch_stock_target(code, start, end, type=type)
return QA_DataStruct_Stock_day(data)
else:
data = QA_fetch_stock_target(code, start, end, type=type)
return QA_DataStruct_Stock_day(data)
def QA_fetch_stocklist_day_adv(
code,
start='all', end=None,
if_drop_index=False,
collections=DATABASE.stock_day):
'获取股票日线'
if start == 'all':
start = '1990-01-01'
end = str(datetime.date.today())
return QA_DataStruct_Stock_day(pd.concat(QA_fetch_stocklist_day(code, [start, end])).query('volume>1').set_index(['date', 'code'], drop=if_drop_index).sort_index())
def QA_fetch_index_alpha_adv(code,
start="all",
end=None,
format='pd',
collections=DATABASE.index_alpha):
'获取股票财报日历'
#code= [code] if isinstance(code,str) else code
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
# code checking
if start == 'all' or start == None:
start = '2005-01-01'
end = QA_util_today_str()
data = QA_fetch_index_alpha(code, start, end)
return QA_DataStruct_Stock_day(data)
else:
data = QA_fetch_index_alpha(code, start, end)
return QA_DataStruct_Stock_day(data)
def QA_fetch_stock_quant_data_adv(code,
start="all",
end=None,
block=True,
format='pd',
collections=DATABASE.stock_quant_data):
'获取股票量化机器学习最终指标V1'
#code= [code] if isinstance(code,str) else code
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
# code checking
if start == 'all' or start == None:
start = '2008-01-01'
end = QA_util_today_str()
data = QA_fetch_stock_quant_data(code, start, end, block)
return QA_DataStruct_Stock_day(data)
else:
data = QA_fetch_stock_quant_data(code, start, end, block)
return QA_DataStruct_Stock_day(data)
def test_data_struct_stock(self):
code = '000001'
days = 365 * 1.2
start = datetime.datetime.now() - datetime.timedelta(days)
end = datetime.datetime.now() - datetime.timedelta(0)
df = qm.get(code, start, end)
if df is not None:
df = df.set_index(['date', 'code'], drop=True)
ds = qd().dataStruct(df)
ds2 = QA_DataStruct_Stock_day(df)
self.assertIsInstance(ds, QA_DataStruct_Stock_day)
self.assertIsInstance(ds2, QA_DataStruct_Stock_day)
def QA_fetch_get_stock_indicator(code, start_date, end_date, type='day'):
if type == 'day':
start = QA_util_get_pre_trade_date(start_date, 200)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA_fetch_stock_day_adv(code, start, end_date)
data = data.to_qfq()
except:
print("No data")
elif type == 'week':
start = QA_util_get_pre_trade_date(start_date, 200)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA_fetch_stock_day_adv(code, start, end_date)
data = data.to_qfq()
data = QA_DataStruct_Stock_day(
data.data.groupby('code', sort=True).apply(ohlc, 7))
except:
print("No data")
elif type == 'month':
start = QA_util_get_pre_trade_date(start_date, 220)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA_fetch_stock_day_adv(code, start, end_date)
data = data.to_qfq()
data = QA_DataStruct_Stock_day(
data.data.groupby('code', sort=True).apply(ohlc, 30))
except:
print("No data")
if data == None:
return None
else:
data = get_indicator(data, rng1)
return (data)
def QA_fetch_stock_day_full_adv(date):
'''
'返回全市场某一天的数据'
:param date:
:return: QA_DataStruct_Stock_day类 型数据
'''
# 🛠 todo 检查日期data参数
res = QA_fetch_stock_full(date, 'pd')
if res is None:
print("QA Error QA_fetch_stock_day_full_adv parameter date=%s call QA_fetch_stock_full return None" % (date))
return None
else:
res_set_index = res.set_index(['date', 'code'])
# if res_set_index is None:
# print("QA Error QA_fetch_stock_day_full set index 'date, code' return None")
return QA_DataStruct_Stock_day(res_set_index)
def QA_fetch_stock_day_adv(code,
start='all',
end=None,
if_drop_index=False,
collections=DATABASE.stock_day):
'获取股票日线'
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
if start == 'all':
start = '1990-01-01'
end = str(datetime.date.today())
return QA_DataStruct_Stock_day(
QA_fetch_stock_day(code, start, end,
format='pd').set_index(['date', 'code'],
drop=if_drop_index))
def QA_fetch_get_index_indicator(code, start_date, end_date, type='day'):
if type == 'day':
start = QA_util_get_pre_trade_date(start_date, 180)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA.QA_fetch_index_day(
code, start, end_date,
format='pd').reset_index(drop=True).set_index(['date', 'code'])
data = QA_DataStruct_Stock_day(data)
except:
print("No data")
elif type == 'week':
start = QA_util_get_pre_trade_date(start_date, 187)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA.QA_fetch_index_day(
code, start, end_date,
format='pd').reset_index(drop=True).set_index(['date', 'code'])
data = QA_DataStruct_Stock_day(
data.groupby('code', sort=True).apply(ohlc, 7))
except:
print("No data")
elif type == 'month':
start = QA_util_get_pre_trade_date(start_date, 210)
rng1 = pd.Series(pd.date_range(start_date, end_date,
freq='D')).apply(lambda x: str(x)[0:10])
try:
data = QA.QA_fetch_index_day(
code, start, end_date,
format='pd').reset_index(drop=True).set_index(['date', 'code'])
data = QA_DataStruct_Stock_day(
data.groupby('code', sort=True).apply(ohlc, 30))
except:
print("No data")
if data == None:
return None
else:
data = get_indicator(data, rng1)
return (data)
def get_stock_day(self, codelist, start, end):
codelist = promise_list(codelist)
if 'XS' not in codelist[0]:
codelist = pd.Series(codelist).apply(lambda x: x + '.XSHE' if x[
0] != '6' else x + '.XSHG').tolist()
columns_raw = [
'date', 'order_book_id', 'num_trades', 'limit_up', 'limit_down',
'open', 'high', 'low', 'close', 'volume', 'total_turnover'
]
res = self.client.query_dataframe(
"SELECT * FROM quantaxis.stock_cn_day WHERE ((`date` >= '{}')) \
AND (`date` <= '{}') AND (`order_book_id` IN ({}))".
format(start, end, "'{}'".format(
"','".join(codelist)))).loc[:, columns_raw].drop_duplicates(
['date', 'order_book_id'])
return QA_DataStruct_Stock_day(
res.assign(date=pd.to_datetime(res.date),
code=res.order_book_id,
amount=res.total_turnover).set_index(['date', 'code'
]).sort_index())
def QA_fetch_stock_day_full_adv(date):
'返回全市场某一天的数据'
return QA_DataStruct_Stock_day(QA_fetch_stock_full(date, 'pd').set_index(['date', 'code'], drop=False))
