def query_sz50_stocks():
rs = bs.query_sz50_stocks()
while Stock.retried_num < Stock.RETRY_MAX_NUM and rs.error_code != '0':
sleep(Stock.RETRY_DELAY_S)
rs = bs.query_sz50_stocks()
Stock.retried_num += 1
if '0' == rs.error_code:
Stock.retried_num = 0
return Stock.rs_to_list(rs)
def query_sz50_stocks():
rs = bs.query_sz50_stocks()
while BaoStock.retried_num < BaoStock.RETRY_MAX_NUM and rs.error_code != '0':
sleep(BaoStock.RETRY_DELAY_S)
rs = bs.query_sz50_stocks()
BaoStock.retried_num += 1
assert('0' == rs.error_code)
BaoStock.retried_num = 0
return BaoStock.rs_to_list(rs)
def getStockList(type: str = "default", date: str = ""):
result = []
data: DataFrame
if type == "sz50":
data = BaoStock.query_sz50_stocks(date).get_data()
elif type == "hs300":
data = BaoStock.query_hs300_stocks(date).get_data()
elif type == "zz500":
data = BaoStock.query_zz500_stocks(date).get_data()
elif type == "default":
path = Path(__file__).parent.absolute()/"list.json"
file = open(str(path), "r", encoding="utf8")
return Json.loads(file.read())
else:
data = BaoStock.query_stock_basic().get_data()
keys = data.keys()
data = [x[1]
for x in BaoStock.query_stock_basic().get_data().iterrows()]
if type == "index":
data = [x for x in data if x["type"] == "2"]
elif type == "stock":
data = [x for x in data if x["type"] == "1"]
for row in data:
result.append({getStockListMap[key][0]: row[key]
for key in keys if key in getStockListMap})
return result
for row in data.iterrows():
result.append({getStockListMap[key][0]: row[1][key]
for key in data.keys() if key in getStockListMap})
return result
def query_sz50_stocks(self):
# 登陆系统
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
# 获取上证50成分股
rs = bs.query_sz50_stocks()
print('query_sz50 error_code:' + rs.error_code)
print('query_sz50 error_msg:' + rs.error_msg)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
# 结果集输出到csv文件
result.to_csv(self.path + "sz50_stocks.csv",
encoding="gbk",
index=False)
#print(result)
# 登出系统
bs.logout()
return result
def get_sz50_stocks():
"""
获取上证50成分股数据
"""
#删除数据
BS_SZ50_Stocks.del_all_data()
# 登陆系统
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
# 获取上证50成分股
rs = bs.query_sz50_stocks()
print('query_sz50 error_code:' + rs.error_code)
print('query_sz50 error_msg:' + rs.error_msg)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
result.to_sql('odl_bs_sz50_stocks',
engine,
schema=CQ_Config.DB_SCHEMA,
if_exists='append',
index=False)
# 登出系统
bs.logout()
def get_code_list():
lg = bs.login()
# 获取上证50成分股
rs = bs.query_sz50_stocks()
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
# 结果集输出到csv文件
result.to_csv("D:/sz50_stocks.csv", encoding="GB2312", index=False)
code=result['code']
name=result['code_name']
#print(code)
code_list=[]
for i in code:
code_list.append(i.split('sh.')[1])
#print(code_list)
name_list=[]
for i in name:
name_list.append(i)
bs.logout()
return dict(zip(code_list,name_list))
def querySZ50Stocks(date=''):
rs = bs.query_sz50_stocks(date)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
def get_sz50_stocks():
rs = BS.query_sz50_stocks()
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
sz50_stocks.append(rs.get_row_data())
result = PD.DataFrame(sz50_stocks, columns=rs.fields)
print(result)
return result
def get_sz50_stocks_code(date=None):
# 登陆系统
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
rs = bs.query_sz50_stocks(date)
df = rs.get_data()
bs.logout()
return df[['code', 'code_name']].to_dict('record')
def get_constituent_stock(i):
basepath = os.path.dirname(__file__)
basicpath = 'static/morestock/' + i + '-stock'
show_time = today_time()
param = request.form
show_code = ""
if param and (param['code'] or param['code'] == ""):
code = param['code']
show_code = stock_com(code)
if show_code == "":
# baostock相关设置
lg = bs.login()
if i == "hs300":
rs = bs.query_hs300_stocks()
elif i == "sz":
rs = bs.query_sz50_stocks()
elif i == "zz":
rs = bs.query_zz500_stocks()
result = res_data(rs)
# 创建个股文件夹
create_file(basicpath)
# 存储csv、excel、josn文件
parsed = save_all(basicpath, i, show_time, result, 'data')
# 从json获取数据(all)
all_len = len(parsed)
type_name = i + "Stock"
show_obj = {"data": parsed, "total": all_len, "type": type_name}
# baostock登出
bs.logout()
return show_obj
else:
jsonpath = basicpath + '/json/' + i + '_' + show_time + '.json'
joson_file = os.path.join(basepath, jsonpath)
jsonFlag = "0"
search_arr = []
with open(joson_file, 'r+', encoding="utf-8") as load_f:
load_file = load_f.read()
home_file = json.loads(load_file, strict=False)
if show_code == "-1":
search_arr = home_file['data']
elif show_code == "-2":
search_arr = []
else:
for item in home_file['data']:
if item['code'] == show_code or item[
'code_name'] == show_code:
jsonFlag = "1"
search_arr.append(item)
all_len = len(search_arr)
type_name = i + "Stock"
show_obj = {"data": search_arr, "total": all_len, "type": type_name}
return show_obj
def get_50_codes(self, date='2017-01-01'):
# 获取上证50成分股
rs = bs.query_sz50_stocks(date)
print('query_sz50 error_code:' + rs.error_code)
print('query_sz50 error_msg:' + rs.error_msg)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
return result
def query_sz50_stocks(self,date = None):
'''
date：查询日期，格式XXXX-XX-XX，为空时默认最新日期。
'''
rs = bs.query_sz50_stocks(date = date)
self.log('query_sz50 error_msg:', rs)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
return result
def main():
# 沪深300
rs = bs.query_hs300_stocks()
# 获取上证50成分股
rs1 = bs.query_sz50_stocks()
# 获取中证500成分股
rs2 = bs.query_zz500_stocks()
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
re = Combine(rs.get_row_data()[1])
if re:
datalist.append(re)
result = pd.DataFrame(datalist)
result.to_csv("/tmp/a.csv", index=False)
def bs_save_sz50_stocks():
'''
获取上证50成分股信息
:return:
'''
bs.login()
rs = bs.query_sz50_stocks()
data_list = []
while (rs.error_code == '0') & rs.next():
data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
engine = create_engine(
'mysql+pymysql://root:root@localhost:3306/stock_quant?charset=utf8')
result.to_sql('bs_sz50_stocks', engine, index=True)
bs.logout()
def get_sz50_stocks(date=today):
# 获取上证50成分股
rs = bs.query_sz50_stocks(date=date)
if rs.error_code != '0':
print('query_sz50 respond error_code::' + rs.error_msg)
login()
return get_sz50_stocks(date)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
return result
def dispatch_request(self):
post_data = request.get_json()
date = post_data.get('date', '')
attr_fields = post_data.get('attr_fields', None)
rs = bs.query_sz50_stocks(date=date)
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
sz50_stocks.append(rs.get_row_data())
fields = ['updateDate', 'code', 'code_name']
data = jsonWrapper(sz50_stocks, fields)
result = {
'code': 200 if rs.error_code == '0' else rs.error_code,
'data': list(map(lambda x: { attr: x.get(attr, '') for attr in attr_fields }, data)) if attr_fields else data,
'msg': rs.error_msg
}
self.logout()
return jsonify(result)
def get_sz50_stocks():
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
#### 获取交易日信息 ####
rs = bs.query_sz50_stocks()
print('query_trade_dates respond error_code:' + rs.error_code)
print('query_trade_dates respond error_msg:' + rs.error_msg)
#### 打印结果集 ####
data_list = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
bs.logout()
return result
def query_sz50_stocks(date=None):
"""
上证50成分股
方法说明：通过API接口获取上证50成分股信息，更新频率：每周一更新。
返回类型：pandas的DataFrame类型。
参数含义：
date：查询日期，格式XXXX-XX-XX，为空时默认最新日期。
"""
lg = bs.login()
if lg.error_code != '0':
logger.error('login respond error_msg:' + lg.error_msg)
rs = bs.query_sz50_stocks(date)
if rs.error_code != '0':
logger.error('query_sz50_stocks respond error_msg:' +
rs.error_msg)
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
bs.logout()
return result
def download_sample_stocks(sample_name='sz50'):
if sample_name == 'sz50':
filename = FILE_PATH + "sz50_stocks.csv"
rs = bs.query_sz50_stocks()
elif sample_name == 'hs300':
filename = FILE_PATH + "hs300_stocks.csv"
rs = bs.query_hs300_stocks()
elif sample_name == 'zz500':
filename = FILE_PATH + "zz500_stocks.csv"
rs = bs.query_zz500_stocks()
elif sample_name == 'all':
filename = FILE_PATH + "all_stocks.csv"
# 取前七天的成分股信息，如果取当前天的，可能当天没有更新
trade_cal = get_trade_cal()
trade_day = trade_cal[(
trade_cal['is_trading_day'] == 1)]['calendar_date'].values
rs = bs.query_all_stock()
stocks = []
while (rs.error_code == '0') & rs.next():
stocks.append(rs.get_row_data())
result = pd.DataFrame(stocks, columns=rs.fields)
result.to_csv(filename, encoding="gbk", index=False)
logger.debug("将成分股%s保存至%s" % (sample_name, filename))
def sz50(self):
'''上证50'''
return get_data(bs.query_sz50_stocks())
import baostock as bs
import pandas as pd
# 登陆系统
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
# 获取上证50成分股
rs = bs.query_sz50_stocks(date="2018-08-10")
print('query_sz50 error_code:' + rs.error_code)
print('query_sz50 error_msg:' + rs.error_msg)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
# 结果集输出到csv文件
result.to_csv("D:/sz50_stocks.csv", encoding="gbk", index=False)
print(result)
# 登出系统
bs.logout()
import baostock as bs
import pandas as pd
# 登陆系统
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:'+lg.error_code)
print('login respond error_msg:'+lg.error_msg)
# 获取上证50成分股
rs = bs.query_sz50_stocks()
print('query_sz50 error_code:'+rs.error_code)
print('query_sz50 error_msg:'+rs.error_msg)
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
# 结果集输出到csv文件
result.to_csv("D:/sz50_stocks.csv", encoding="gbk", index=False)
print(result)
# 登出系统
bs.logout()
def getA50StockList(self):
try:
self.initMysqlConn()
# 查询当前所有正常上市交易的股票列表
df = ts.get_sz50s() # 不能用了？返回值是none
# 登陆系统
lg = bs.login()
rs = bs.query_sz50_stocks()
# 打印结果集
sz50_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
sz50_stocks.append(rs.get_row_data())
result = pd.DataFrame(sz50_stocks, columns=rs.fields)
# result['code']='\t'+result['code'].str[3:]
# ex=os.path.isfile('sz50s')
# if ex==False:
result.to_csv('G:\\stockData\\sz50s.csv',
encoding='utf_8_sig') #指数直接覆盖掉
rs = bs.query_hs300_stocks()
# 打印结果集
hs300_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
hs300_stocks.append(rs.get_row_data())
result1 = pd.DataFrame(hs300_stocks, columns=rs.fields)
# result1['code']=result1['code'].str[3:]
# ex=os.path.isfile('sz50s')
# if ex==False:
result1.to_csv('G:\\stockData\\hs300s.csv',
encoding='utf_8_sig') #指数直接覆盖掉
# result1.to_csv('G:\\stockData\\hs300s.csv',encoding='gbk')#指数直接覆盖掉
rs = bs.query_zz500_stocks()
# 打印结果集
zz500_stocks = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
zz500_stocks.append(rs.get_row_data())
result2 = pd.DataFrame(zz500_stocks, columns=rs.fields)
# result2['code']=result2['code'].str[3:]#没有t的话会丢掉前面的0
# ex=os.path.isfile('sz50s')
# if ex==False:
result2.to_csv('G:\\stockData\\zz500s.csv',
encoding='utf_8_sig') #指数直接覆盖掉
# 登出系统
bs.logout()
print('getsz50StockList & hs300s & zz500s Finished!')
return
c_len = 0
if (df == None):
df = result
c_len = df.shape[0] # 行数
except Exception as aa:
print(aa)
print('get error')
for j in range(c_len): # 按行读取股票列表
resu0 = list(df.loc[c_len - 1 - j])
resu = []
for k in range(len(resu0)): # 读取股票的字段
if str(resu0[k]) == 'nan':
resu.append(-1)
else:
resu.append(resu0[k])
try:
sql_insert = "INSERT INTO sz50StockList(date,code,name) VALUES ('%s', '%s', '%s')" % (
str(resu[0]), str(resu[1]), str(resu[2]))
self.cursor.execute(sql_insert)
self.db.commit()
except Exception as err:
continue
self.cursor.close()
self.db.close()
# 登出系统
bs.logout()
print('getsz50StockList Finished!')
def sz50_stocks(self):
self.getStockInstance()
rs = bs.query_sz50_stocks()
self._test_rs(rs)
return rs