def get_recent_dividend_share_stocks(diff_days: int = 5) -> []:
"""
获取最近进行分红除权的股票代码列表
Parameters
------
diff_days: int x天内是否个股进行过分红除权
Return
-------
array
ts_code ts股票代码
"""
param = {'list_status': 'L', 'exchange': '', 'fields': 'ts_code,sumbol'}
hs_df = get_hs_stock_list(param)
ret_jsons = None
stock_list = []
for index, row in hs_df.iterrows():
code = row['symbol']
try:
is_dividend = is_stock_recent_dividend(code, diff_days)
if is_dividend:
stock_list.append(row['ts_code'])
time.sleep(1)
except Exception as err:
logger.critical(err)
continue
logger.info('dividend stock list:')
logger.info(stock_list)
return stock_list
def test_stock_list_hs300():
df = basic.get_hs_stock_list({
'list_status': 'L',
'exchange': '',
'fields': 'ts_code,symbol,list_date'
})
assert df[df.ts_code == '399300.SZ']['symbol'].iloc[0] == '399300'
def run_his_stock_adj_price_task(past_diff_days, exchange=''):
"""
更新沪深股市上市公司前复权股票历史价格
Parameters
------
past_diff_days: 查询x天前的股票复权数据
exchange: 交易所 SSE上交所 SZSE深交所
Return
-------
result 是否正常结束
"""
param = {
'list_status': 'L',
'exchange': exchange,
'fields': 'ts_code,symbol,list_date'
}
hs_df = basic.get_hs_stock_list(param)
delta = datetime.timedelta(days=past_diff_days)
past_str = (datetime.date.today() - delta).strftime('%Y%m%d')
today_str = datetime.date.today().strftime('%Y%m%d')
for index, row in hs_df.iterrows():
ts_code = row['ts_code'].split('.')[0]
logger.info(f'{ts_code} start fqprice job {today_str}')
adj_price_df = price.get_adj_price({
'ts_code':
row['ts_code'],
'start_date':
past_str,
'end_date':
today_str,
'adj':
'qfq',
'freq':
'D',
'asset':
'I' if str(row['ts_code']).startswith('399') else 'E'
})
if adj_price_df is None:
continue
for index, row in adj_price_df.iterrows():
trade_date = row['trade_date']
_id = f'{ts_code}-{trade_date}'
data = {
'_id': _id,
'code': ts_code,
'date': int(row['trade_date']),
'open': float('%.2f' % row['open']),
'close': float('%.2f' % row['close']),
'high': float('%.2f' % row['high']),
'low': float('%.2f' % row['low']),
'pre_close': float('%.2f' % row['pre_close']),
'change': float('%.2f' % row['change']),
'pct_chg': float('%.2f' % row['pct_chg']),
'vol': float('%.2f' % row['vol']),
'amout': float('%.3f' % row['amount'])
}
res = dal.updateOne({'_id': _id}, 'hisprice', data, True)
time.sleep(1)
return True
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 run_stock_alpha_beta_task():
"""
更新沪深股市上市公司相对沪深300的alpha beta
Parameters
------
Return
-------
result 是否正常结束
"""
param = {'list_status': 'L', 'exchange': '', 'fields': 'symbol'}
hs_df = basic.get_hs_stock_list(param)
for index, row in hs_df.iterrows():
code = row['symbol']
quant.calc_alpha_beta(code, 460)
return True
def run_stock_52week_lowprice_task():
"""
更新沪深股市上市公司52周最低价
Parameters
------
Return
-------
result 是否正常结束
"""
param = {'list_status': 'L', 'exchange': '', 'fields': 'symbol'}
hs_df = basic.get_hs_stock_list(param)
for index, row in hs_df.iterrows():
code = row['symbol']
quant.manage52WeekLowestPrice({'code': code})
return True
def run_stock_insert_es_task():
"""
构建沪深上市公司代码和名称的es存储
Parameters
------
Return
-------
result 是否正常结束
"""
param = {'list_status': 'L', 'exchange': '', 'fields': 'symbol'}
hs_df = basic.get_hs_stock_list(param)
for index, row in hs_df.iterrows():
code = row['symbol']
name = row['name']
es_res = es.insert_document(
'stock',
json.dumps({
'stockcode': row['symbol'],
'stockname': row['name']
}), code)
logger.info(f'fetch stock es result {es_res} end')
return True
def run_stock_day_week_month_ma_task():
"""
构建沪深上市公司代码和名称的es存储
Parameters
------
Return
-------
result 是否正常结束
"""
param = {'list_status': 'L', 'exchange': '', 'fields': 'symbol'}
hs_df = basic.get_hs_stock_list(param)
for index, row in hs_df.iterrows():
try:
code = row['symbol']
name = row['name']
today = datetime.datetime.now().strftime("%Y%m%d")
two_year = int(time.strftime('%Y', time.localtime(
time.time()))) - 2
five_year = int(time.strftime('%Y', time.localtime(
time.time()))) - 5
eight_year = int(time.strftime('%Y', time.localtime(
time.time()))) - 11
month_day = time.strftime('%m%d', time.localtime(time.time()))
two_year_ago = '{}{}'.format(two_year, month_day)
five_year_ago = '{}{}'.format(five_year, month_day)
eight_year_ago = '{}{}'.format(eight_year, month_day)
param_day = {
'ts_code': row['ts_code'],
'start_date': two_year_ago,
'end_date': today,
'adj': 'qfq',
'freq': 'D',
'asset': 'E',
'ma': [20, 30, 60, 90, 120, 250]
}
day_df = price.get_adj_ma_price(param_day)
ma_data = day_df.fillna('').iloc[0]
ma_day = {
'trade_date': ma_data['trade_date'],
'ma20': ma_data['ma20'],
'ma30': ma_data['ma30'],
'ma60': ma_data['ma60'],
'ma90': ma_data['ma90'],
'ma120': ma_data['ma120'],
'ma250': ma_data['ma250']
}
param_week = {
'ts_code': row['ts_code'],
'start_date': five_year_ago,
'end_date': today,
'adj': 'qfq',
'freq': 'W',
'asset': 'E',
'ma': [20, 30, 60, 90, 120, 250]
}
week_df = price.get_adj_ma_price(param_week)
ma_week_data = week_df.fillna('').iloc[0]
ma_week = {
'trade_date': ma_week_data['trade_date'],
'ma20': ma_week_data['ma20'],
'ma30': ma_week_data['ma30'],
'ma60': ma_week_data['ma60'],
'ma90': ma_week_data['ma90'],
'ma120': ma_week_data['ma120'],
'ma250': ma_week_data['ma250']
}
param_month = {
'ts_code': row['ts_code'],
'start_date': eight_year_ago,
'end_date': today,
'adj': 'qfq',
'freq': 'M',
'asset': 'E',
'ma': [20, 30, 60, 90, 120]
}
month_df = price.get_adj_ma_price(param_month)
ma_month_data = month_df.fillna('').iloc[0]
ma_month = {
'trade_date': ma_month_data['trade_date'],
'ma20': ma_month_data['ma20'],
'ma30': ma_month_data['ma30'],
'ma60': ma_month_data['ma60'],
'ma90': ma_month_data['ma90'],
'ma120': ma_month_data['ma120']
}
redisObj = {
'code': code,
'ma_day': ma_day,
'ma_week': ma_week,
'ma_month': ma_month
}
# save
redisRes = redisDal.redisSet(f'ma:{code}', json.dumps(redisObj))
logger.info(f'{code} ma result:' + str(redisRes))
except Exception as exp:
logger.error(exp)
return True