def calc_user_stock_cover_index():
"""
统计更新用户的持仓，计算持仓跟各大指数的重合度
Parameters
------
Return
-------
result 是否正常结束
"""
try:
# 用户持仓个股增加股票名称
param = {'list_status': 'L', 'exchange': '', 'fields': 'symbol,name'}
hs_df = basic.get_hs_stock_list(param)
globalStock = {}
for index, row in hs_df.iterrows():
globalStock[row['symbol']] = row['name']
_array = dal.queryMany(None, {
'_id': 1,
'samples': 1
}, 0, None, 'indexSample')
array = list(_array)
if len(array) == 0:
return None
_opt_stock_array = dal.queryMany(None, {
'_id': 1,
'stock': 1
}, 0, None, 'optStock')
opt_stock_array = list(_opt_stock_array)
if len(opt_stock_array) == 0:
return None
for opt_stock in opt_stock_array:
user_id = opt_stock['_id']
user_stock = opt_stock['stock']
user_quant = {}
user_quant['user'] = user_id
for index_sample in array:
index_name = index_sample['_id']
user_quant['index'] = index_name
user_quant['_id'] = f'{user_id}_{index_name}'
calc_opt_stock_in_index_sample(user_stock,
index_sample['samples'],
user_quant, globalStock)
dal.updateOne({'_id': user_quant['_id']}, 'optQuant',
user_quant, True)
logger.info(user_quant)
except Exception as exp:
logger.error(exp)
return None
return None
def calc_ma(code: str, diff_days: int):
"""
更新转债diff_days天内MA
Parameters
------
diff_days: 计算x天前的MA数据
Return
-------
result 是否正常结束
"""
try:
_array = dal.queryMany({'code': code}, {
'close': 1,
'_id': 0
}, diff_days, [('date', -1)], 'hisprice')
array = list(_array)
if len(array) == 0:
return None
narray = np.array([])
for price in array:
narray = np.append(narray, price['close'])
ma = talib.MA(narray, timeperiod=diff_days, matype=0)
if np.isnan(ma[-1]):
return None
else:
return ma[-1]
except Exception as exp:
logger.error(exp)
return None
return None
def query_stock_days_price_chg(code: str, diff_days: int):
"""
查询diff_days天内个股的价格波动率
Parameters
------
diff_days: 计算x天前
code: 个股代码 600030
Return
------- Data Frame
------- index date
------- pct
result dataFrame
"""
try:
_array = dal.queryMany({'code': code}, {
'pct_chg': 1,
'date': 1,
'_id': 0
}, diff_days + 1, [('date', -1)], 'hisprice')
array = list(_array)
if len(array) == 0:
return None
narray_pct = np.array([])
narray_date = np.array([])
narray_date.dtype = 'int32'
for price in array:
narray_pct = np.append(narray_pct, price['pct_chg'])
narray_date = np.append(narray_date, price['date'])
df = pd.DataFrame(narray_pct, index=narray_date, columns=['pct'])
return df
except Exception as exp:
logger.error(exp)
return None
def restoreRedisDataFromMongo(self):
try:
fundArray = dal.queryMany(None, None, 0, None, 'fund_outline')
fundArr = list(fundArray)
if len(fundArr) == 0:
return None
for fund in fundArr:
code = fund['Code']
logger.info(code)
redisRes = redisDal.redisSet(f'fund:{code}', json.dumps(fund))
except Exception as err:
logger.critical(err)
return -1
def scrawlFundTask(self):
try:
fundArray = dal.queryMany(None, {
'_id': 1,
'cxcode': 1
}, 0, None, 'fund_target')
fundArr = list(fundArray)
if len(fundArr) == 0:
return None
for fund in fundArr:
code = fund['_id']
cxcode = fund['cxcode']
if (code is None or cxcode is None):
continue
time.sleep(random.randint(15, 20))
logger.info(fund)
self.scrawlSingleFundInfo(cxcode, code)
except Exception as err:
logger.critical(err)
return -1
def calc_atr(code: str, diff_days: int):
"""
更新转债diff_days天内MA
Parameters
------
diff_days: 计算x天前的MA数据
Return
-------
result 是否正常结束
"""
try:
_array = dal.queryMany({'code': code}, {
'close': 1,
'high': 1,
'low': 1,
'_id': 0
}, diff_days + 1, [('date', -1)], 'hisprice')
array = list(_array)
if len(array) == 0:
return None
narray_high = np.array([])
narray_low = np.array([])
narray_close = np.array([])
for price in array:
narray_high = np.append(narray_high, price['high'])
narray_low = np.append(narray_low, price['low'])
narray_close = np.append(narray_close, price['close'])
atr = talib.ATR(narray_high,
narray_low,
narray_close,
timeperiod=diff_days)
if np.isnan(atr[-1]):
return None
else:
return atr[-1]
except Exception as exp:
logger.error(exp)
return None
return None
def calcIndustrySample():
"""
更新个股的国证二级、三级行业分类
Parameters
------
stock_code 股票代码
Return
-------
True 成功
False 失败
"""
try:
indSamples_ = dal.queryMany(None, {
'_id': 1,
'samples': 1
}, 0, None, 'industrySample')
indSamples = list(indSamples_)
for indSample in indSamples:
for stock_code in indSample['samples']:
redisData = redisDal.redisHGet('xueQiuStockSet', stock_code)
if redisData is None:
redisObj = {'code': stock_code}
else:
redisObj = json.loads(redisData)
ind = indSample['_id']
if len(ind) == 5:
redisObj['gz2'] = ind
elif len(ind) == 7:
redisObj['gz3'] = ind
redisDal.redisHSet('xueQiuStockSet', stock_code,
json.dumps(redisObj))
logger.info(f'calcIndustrySample {stock_code} --{ind}')
except Exception as err:
logger.critical(err)
return False
return True