def load_index(index, query_func, data_path):
data_file = os.path.join(data_path, index, 'stocks.csv')
if os.path.exists(data_file):
return load_stocks_from_file(data_file)
lg = bs.login()
if lg.error_code != '0':
raise ValueError('baostock login failed:{}, {}'.format(lg.error_code, lg.error_msg))
try:
rs = query_func()
if rs.error_code != '0':
raise ValueError('baostock query {} failed:{}, {}'.format(index, rs.error_code, rs.error_msg))
index_stocks = []
while (rs.error_code == '0') & rs.next():
index_stocks.append(rs.get_row_data())
if rs.error_code != '0':
raise ValueError('baostock query {} failed:{}, {}'.format(index, rs.error_code, rs.error_msg))
result = pd.DataFrame(index_stocks, columns=rs.fields)
pathlib.Path(os.path.join(data_path, index)).mkdir(parents=True, exist_ok=True)
result.to_csv(data_file, encoding="utf-8", index=False)
return load_stocks_from_file(data_file)
finally:
bs.logout()
def refresh_all_stock_day_k_noadjust(start_date="2020-03-27",
current_date="2020-03-30"):
bs.login()
stock_rs = bs.query_all_stock(day=current_date)
stock_df = stock_rs.get_data()
data_list = []
for code in stock_df["code"]:
k_rs = bs.query_history_k_data_plus(
code,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
start_date=start_date,
end_date='',
frequency="d",
adjustflag="3")
while (k_rs.error_code == '0') & k_rs.next():
data_list.append(k_rs.get_row_data())
print('query_history_k_data_plus no adjust code:' + code)
bs.logout()
db_conn = create_engine(common.db_path_sqlalchemy)
db_conn.execute(
r'''
INSERT OR REPLACE INTO stock_day_k_noadjust VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
''', data_list)
def query_trade_dates(start_date, end_date):
"""
交易日查询：query_trade_dates()
方法说明：查询股票交易日信息信息，可以通过参数设置获取起止年份数据，提供2014-2018年数据。
返回类型：pandas的DataFrame类型。
"""
#### 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)
#### 获取交易日信息 ####
rs = bs.query_trade_dates(start_date=start_date, end_date=end_date)
#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)
#### 结果集输出到csv文件 ####
result.to_csv(path + "trade_dates.csv", encoding="gbk", index=False)
#### 登出系统 ####
bs.logout()
return
def get_stock_data(t1, t2, stock_name):
lg = bs.login()
print('login respond error_code:' + lg.error_code)
print('login respond error_msg:' + lg.error_msg)
#### 获取沪深A股历史K线数据 ####
# 详细指标参数，参见baostock
rs = bs.query_history_k_data(
stock_name,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
start_date=t1,
end_date=t2,
frequency="d",
adjustflag="3")
print('query_history_k_data respond error_code:' + rs.error_code)
print('query_history_k_data 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)
print(result)
#### 结果集输出到csv文件 ####
result.to_csv("history_A_stock_k_data.csv", index=False)
print(result)
#### 登出系统 ####
bs.logout()
result['date'] = pd.to_datetime(result['date'])
result.set_index("date", inplace=True)
return result
def download(stockCode, beginDate, endDate, fileName, isCsv):
#### 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)
#### 获取沪深A股历史K线数据 ####
# 详细指标参数，参见“历史行情指标参数”章节；“分钟线”参数与“日线”参数不同。
# 分钟线指标：date,time,code,open,high,low,close,volume,amount,adjustflag
# code：股票代码，sh或sz.+6位数字代码，或者指数代码，如：sh.601398。sh：上海；sz：深圳。此参数不可为空；
# fields：指示简称，支持多指标输入，以半角逗号分隔，填写内容作为返回类型的列。详细指标列表见历史行情指标参数章节，日线与分钟线参数不同。此参数不可为空；
# start：开始日期（包含），格式“YYYY-MM-DD”，为空时取2015-01-01；
# end：结束日期（包含），格式“YYYY-MM-DD”，为空时取最近一个交易日；
# frequency：数据类型，默认为d，日k线；d=日k线、w=周、m=月、5=5分钟、15=15分钟、30=30分钟、60=60分钟k线数据，不区分大小写；指数没有分钟线数据；周线每周最后一个交易日才可以获取，月线每月最后一个交易日才可以获取。
# adjustflag：复权类型，默认不复权：3；1：后复权；2：前复权。已支持分钟线、日线、周线、月线前后复权。 BaoStock提供的是涨跌幅复权算法复权因子，具体介绍见：
rs = bs.query_history_k_data_plus(
stockCode,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
start_date="2006-01-01",
end_date=endDate,
frequency="d",
adjustflag="2")
print('query_history_k_data_plus respond error_code:' + rs.error_code)
print('query_history_k_data_plus respond error_msg:' + rs.error_msg)
if isCsv:
saveToCsv(rs, fileName)
else:
saveToMysql(rs)
#### 登出系统 ####
bs.logout()
def start_tk_crawl():
global dm
dm = DBManager("history_k_data")
# 初始化baostock
bs.login()
# 获取股票代码列表
code_list = dm.get_code_list()
for item in code_list:
max_try = 8 # 失败重连次数
ticker = item["ticker"]
print("开始加载股票数据：" + str(ticker))
for tries in range(max_try):
rs = bs.query_history_k_data_plus(
ticker,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
start_date='2008-01-01',
end_date='2019-05-31',
frequency="d",
adjustflag="3")
if rs.error_code == '0':
parse_pager(rs, ticker) # 解析数据
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
print("加载股票数据失败：" + str(ticker))
print("加载股票数据完成")
bs.logout()
def Kget(stockcode, checkdate1, checkdate2):
import pandas as pd
import baostock as bs
#### 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)
#### 获取沪深A股历史K线数据 ####
# 详细指标参数，参见“历史行情指标参数”章节；“分钟线”参数与“日线”参数不同。
# 分钟线指标：date,time,code,open,high,low,close,volume,amount,adjustflag
rs = bs.query_history_k_data_plus(
stockcode,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM",
start_date=checkdate1,
end_date=checkdate2,
frequency="d",
adjustflag="3")
# print('query_history_k_data_plus respond error_code:'+rs.error_code)
# print('query_history_k_data_plus 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)
#### 结果集输出到csv文件 ####
result.to_csv("history_A_stock_k_data.csv", encoding="utf8", index=False)
# print(result)
#### 登=出系统 ####
bs.logout()
def getBasicInfoByName(name):
# 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)
# 获取证券基本资料
rs = bs.query_stock_basic(code_name=name) # 支持模糊查询
print('query_stock_basic respond error_code:' + rs.error_code)
print('query_stock_basic respond error_msg:' + rs.error_msg)
obj = {}
if (rs.error_code != '0'):
obj['error_code'] = rs.error_code
obj['error_msg'] = rs.error_msg
return obj
#print(type(rs))#<class 'baostock.data.resultset.ResultData'>
#打印结果集
data_list = []
while (rs.error_code == '0' and rs.next()):
#获取一条记录，将记录合并在一起
data_list.append(rs.get_row_data())
obj['error_code'] = '0'
obj['data_list'] = data_list
#登出系统
bs.logout()
return obj
def start_pe_crawl():
global dm, log
log = Logger()
dm = DBManager("em_pe_database")
log.logger.info("开始更新指数数据")
bs.login()
code_list = dm.get_code_list()
for item in code_list:
ticker = item["ticker"]
max_try = 8
for tries in range(max_try):
rs = bs.query_history_k_data(
ticker,
"date,code,close,peTTM,pbMRQ,psTTM,pcfNcfTTM",
frequency="d",
adjustflag="2")
if rs.error_code == "0":
parse_pager(rs, ticker)
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
log.logger.error("更新股票指数数据：" + str(ticker))
log.logger.info("结束更新指数数据")
bs.logout()
def update_stock_daily(history=False):
try:
et = utils.get_recently_trade_date()
st = et
if history:
st = settings.START_DATE
print(st, et)
# 登陆系统 ####
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code + ', error_msg:' +
lg.error_msg)
stock = redisUtils.get("Ashare")
stockJson = json.loads(stock)
for code in stockJson:
name = stockJson[code][1]
if "ST" in name:
continue
print("Downloading :" + code + " , name :" + name)
k_rs = bs.query_history_k_data_plus(code,
settings.STOCK_FIELDS,
start_date=st,
end_date=et)
# print(k_rs.get_data())
stock_records = k_rs.get_data().to_dict('records')
for record in stock_records:
rJsonStr = json.dumps(record, indent=4,
ensure_ascii=False).encode('utf-8')
r = redisUtils.sadd(code, rJsonStr)
print("{} redis add finish".format(code))
bs.logout()
except IOError:
print("Update Data Error ")
def update_trades():
try:
et = stock_utils.get_recently_trade_date()
st = ConfigUtils.get_stock("START_DATE")
# 登陆系统 ####
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:' + lg.error_code + ', error_msg:' +
lg.error_msg)
pd_names = pd.read_csv(ConfigUtils.get_stock("STOCK_NAME"))
data = list(pd_names.iterrows())
# multi processing
number_kernel = 1
size = int((len(data) + number_kernel - 1) / number_kernel)
p = Pool(number_kernel)
for i in range(number_kernel):
start = size * i
_end = size * (i + 1)
end = len(data) if _end > len(data) else _end
p.apply_async(loading_stock, args=(data[start:end], st, et))
p.close()
p.join()
print('all subprocesses done.')
bs.logout()
except IOError as e:
print("Update Data Error ", e)
def load_adjfactor(symbol, data_path):
adj_file = os.path.join(data_path, symbol, 'adj.csv')
if os.path.exists(adj_file):
return load_adjfactor_from_file(adj_file)
lg = bs.login('anonymous', '123456')
if lg.error_code != '0':
raise ValueError('baostock login failed:{}, {}'.format(lg.error_code, lg.error_msg))
rs_list = []
rs_factor = bs.query_adjust_factor(convert_symbol(symbol), start_date="1990-01-01", end_date="2199-12-31")
while (rs_factor.error_code == '0') & rs_factor.next():
rs_list.append(rs_factor.get_row_data())
if rs_factor.error_code != '0':
bs.logout()
raise ValueError('baostock read data failed:{}'.format(rs_factor.error_msg))
bs.logout()
result_factor = pd.DataFrame(rs_list, columns=rs_factor.fields)
result_factor.to_csv(adj_file, encoding="utf-8", index=False)
return load_adjfactor_from_file(adj_file)
def init_trade_date():
settings.init()
# 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)
# 获取交易日信息 ####
rs = bs.query_trade_dates(start_date=settings.START_DATE, end_date=settings.END_DATE)
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)
# 结果集输出到csv文件 ####
result.to_csv(settings.STOCKS_DATE, encoding="utf-8", index=False, header=True)
print(result)
# 登出系统 ####
bs.logout()
def start_tk_crawl():
global dm, log
log = Logger()
dm = DBManager("em_tk_database")
log.logger.info("开始更新股票数据")
bs.login()
code_list = dm.get_code_list()
for item in code_list:
ticker = item["ticker"]
max_try = 8
for tries in range(max_try):
rs = bs.query_history_k_data(
ticker,
"date,code,open,high,low,close,volume,amount,adjustflag,turn,"
"pctChg",
frequency="w",
adjustflag="3")
if rs.error_code == '0':
parse_pager(rs, ticker)
break
elif tries < (max_try - 1):
sleep(2)
continue
else:
log.logger.error("更新股票数据失败：" + str(ticker))
log.logger.info("结束更新股票数据")
bs.logout()
def get(self, request, *args, **kwargs):
queryset = SharesCategory.objects.all()
if len(queryset) <= 0:
lg = bs.login()
rs = bs.query_stock_industry()
# print(rs)
data_list = []
while (rs.error_code == '0') & rs.next():
data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
result1 = pd.DataFrame(result['industry'])
result1['count'] = pd.Series(np.random.randint(1, 2, 4061))
result1['industryClassification'] = result[
'industryClassification']
result1 = result1.groupby('industry').sum()
shares_cate_list = []
for index, row in result1.iterrows():
cate_obj = SharesCategory(industry=index,
industryClassification='申万一级行业',
count=row['count'])
cate_obj.save()
shares_cate_list.append({
'industry': index,
'industryClassification': '申万一级行业',
'count': float(row['count'])
})
bs.logout()
return JsonResponse(shares_cate_list, safe=False)
else:
return JsonResponse([], safe=False)
def all_stock_list():
#### 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)
#### 获取证券信息 ####
date = datetime.datetime.now()
print(date)
start_date = (date + datetime.timedelta(days=-5)).strftime('%Y-%m-%d')
rs = bs.query_all_stock(day='2020-07-16')
print('query_all_stock respond error_code:' + rs.error_code)
print('query_all_stock respond error_msg:' + rs.error_msg)
#### 登出系统 ####
bs.logout()
#### 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 = rs.get_row_data()
if data[1] != '0':
#data[0] = data[0].replace('.', '')
data_list.append(data)
result = pd.DataFrame(data_list, columns=rs.fields)
return result
def query_stock_k_data_plus(date):
#### 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)
date = date.strftime("%Y-%m-%d")
print(date)
stock_rs = bs.query_all_stock(date)
stock_df = stock_rs.get_data()
print(stock_df.empty)
if not (stock_df is None or stock_df.empty):
data_df = pd.DataFrame()
for code in stock_df["code"]:
k_rs = bs.query_history_k_data_plus(
code, "date,code,open,high,low,close,preclose,volume,"
"amount,adjustflag,turn,tradestatus,pctChg,peTTM,"
"pbMRQ,psTTM,pcfNcfTTM,isST", date, date)
data_df = data_df.append(k_rs.get_data())
data = data_df.drop_duplicates(subset={"date", "code"}, keep="last")
common.insert_db(data, "bs_stock_k_data", False, "`date`,`code`")
print(date + " done!")
else:
print(date + " no data .")
bs.logout()
def get_history_companies(self) -> pd.DataFrame:
"""
Returns
-------
pd.DataFrame:
symbol date type
SH600000 2019-11-11 add
SH600000 2020-11-10 remove
dtypes:
symbol: str
date: pd.Timestamp
type: str, value from ["add", "remove"]
"""
bs.login()
today = pd.datetime.now()
date_range = pd.DataFrame(
pd.date_range(start="2007-01-15", end=today, freq="7D"))[0].dt.date
ret_list = []
col = ["date", "symbol", "code_name"]
for date in tqdm(date_range, desc="Download CSI500"):
rs = bs.query_zz500_stocks(date=str(date))
zz500_stocks = []
while (rs.error_code == "0") & rs.next():
zz500_stocks.append(rs.get_row_data())
result = pd.DataFrame(zz500_stocks, columns=col)
result["symbol"] = result["symbol"].apply(
lambda x: x.replace(".", "").upper())
result = self.get_data_from_baostock(date)
ret_list.append(result[["date", "symbol"]])
bs.logout()
return pd.concat(ret_list, sort=False)
def growget(stackcode):
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)
# 查询季频估值指标盈利能力
growth_list = []
for y in range(2007, 2021):
qu = 4
if y == 2021:
qu = 1
for i in range(qu):
rs_profit = bs.query_growth_data(code=stackcode,
year=y,
quarter=i + 1)
while (rs_profit.error_code == '0') & rs_profit.next():
growth_list.append(rs_profit.get_row_data())
result_growth = pd.DataFrame(growth_list, columns=rs_profit.fields)
# 结果集输出到csv文件
result.to_csv("grow_data.csv", encoding="utf8", index=False)
# 登出系统
bs.logout()
def get_new_companies(self) -> pd.DataFrame:
"""
Returns
-------
pd.DataFrame:
symbol start_date end_date
SH600000 2000-01-01 2099-12-31
dtypes:
symbol: str
start_date: pd.Timestamp
end_date: pd.Timestamp
"""
logger.info("get new companies......")
today = datetime.date.today()
bs.login()
result = self.get_data_from_baostock(today)
bs.logout()
df = result[["date", "symbol"]]
df.columns = [self.END_DATE_FIELD, self.SYMBOL_FIELD_NAME]
df[self.END_DATE_FIELD] = pd.to_datetime(
df[self.END_DATE_FIELD].astype(str))
df[self.START_DATE_FIELD] = self.bench_start_date
logger.info("end of get new companies.")
return df
def get_his_trade_date(start_date="2018-01-27", end_date="2019-05-01"):
#### 登陆系统 ####
lg = bs.login(user_id="anonymous", password="******")
# 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_trade_dates(start_date=start_date, end_date=end_date)
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)
#### 登出系统 ####
bs.logout()
#### 结果集输出到csv文件 ####
#result.to_csv("/data/trade_datas.csv", encoding="gbk", index=False)
return result
def get_history_k_data(code,start_date,end_date,frequency,adjustflag):
bs.login()
rs = bs.query_history_k_data_plus(code,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
start_date=start_date, end_date=end_date,frequency=frequency,adjustflag=adjustflag)
data_list = []
while (rs.error_code == '0') & rs.next() :
data={}
# 获取一条记录，将记录合并在一起
rowdata = rs.get_row_data()
data['date']=rowdata[0]
data['code']=rowdata[1]
data['open']=rowdata[2]
data['high']=rowdata[3]
data['low']=rowdata[4]
data['close']=rowdata[5]
data['preclose']=rowdata[6]
data['volume']=rowdata[7]
data['amount']=rowdata[8]
data['adjustflag']=rowdata[10]
data['tradestatus']=rowdata[11]
data['pctChg']=rowdata[12]
data['isST']=rowdata[13]
data_list.append(data)
return data_list
bs.logout()
def Zijinmian():
today = datetime.datetime.today()
year = today.year
month = today.month
dic = {'m2': []}
# 登陆系统
lg = bs.login()
# 获取货币供应量
if month < 10:
enddate = str(year) + '-' + '0' + str(month)
else:
enddate = str(year) + '-' + str(month)
rs5 = bs.query_money_supply_data_month(start_date="2020-01",
end_date=enddate)
# 打印结果集
data_list = []
while (rs5.error_code == '0') & rs5.next():
# 获取一条记录，将记录合并在一起
data_list.append(rs5.get_row_data())
result = pd.DataFrame(data_list, columns=rs5.fields)
print(np.array(result['m2Month']))
# 登出系统
bs.logout()
dic['m2'] = np.array(result['m2Month']).tolist()
dic['m2'] = list(map(eval, dic['m2']))
return json.dumps(dic, ensure_ascii=False)
def create_stock_industry():
"""
BS-创建行业分类
"""
# 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)
# 获取行业分类数据
rs = bs.query_stock_industry()
print('query_stock_industry error_code:' + rs.error_code)
print('query_stock_industry respond error_msg:' + rs.error_msg)
# 打印结果集
industry_list = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
industry_list.append(rs.get_row_data())
result = pd.DataFrame(industry_list, columns=rs.fields)
dtype = {
'updateDate': String(10),
'code': String(9),
'code_name': String(10),
'industry': String(4),
'industryClassification': String(6)
}
result.to_sql('odl_bs_stock_industry', engine, schema=CQ_Config.DB_SCHEMA, if_exists='replace', index=False, dtype=dtype)
# 登出系统
bs.logout()
def refresh_all_stock_adjust(start_date="2020-03-27",
current_date="2020-03-30"):
bs.login()
db_conn = create_engine(common.db_path_sqlalchemy)
stock_rs = bs.query_all_stock(day=current_date)
stock_df = stock_rs.get_data()
rs_list = []
for code in stock_df["code"]:
if code.startswith("sh.6") | code.startswith(
"sz.00") | code.startswith("sz.300"):
print('query_stock_factor code:' + code)
rs_factor = bs.query_adjust_factor(code=code,
start_date=start_date,
end_date=current_date)
while (rs_factor.error_code == '0') & rs_factor.next():
rs_list.append(rs_factor.get_row_data())
factor_list = []
for d in rs_list:
code = d[0]
print("refresh all factor for " + code)
rs_factor = bs.query_adjust_factor(code=code,
start_date='2006-01-01',
end_date=current_date)
while (rs_factor.error_code == '0') & rs_factor.next():
factor_list.append(rs_factor.get_row_data())
if len(factor_list) > 0:
db_conn.execute(
r'''
INSERT OR REPLACE INTO stock_adjustfactor VALUES (?, ?, ?, ?, ?)
''', factor_list)
bs.logout()
def Fetch000001WithBaostock(startDate):
#### 登陆系统 ####
lg = bs.login()
# 详细指标参数，参见“历史行情指标参数”章节
rs = bs.query_history_k_data("sh.000001",
"date,open,high,low,close,volume",
start_date=Utils.DateForm1(startDate),
end_date='',
frequency="d",
adjustflag="3")
#### 打印结果集 ####
data_list = []
while (rs.error_code == '0') & rs.next():
data_list.append(rs.get_row_data())
df = pd.DataFrame(data_list, columns=rs.fields)
for index, row in df.iterrows():
row['date'] = row['date'].replace('-', '')
df.rename(columns={'date': 'trade_date', 'volume': 'vol'}, inplace=True)
dfInRange = df[(df['trade_date'] > str(startDate))]
bs.logout()
return dfInRange
def get_growth_data(stock_number,stock_name,year,quarter):
print('==========================================================')
print("开始进行: "+stock_name+"("+stock_number+")"+"的数据处理")
print("尝试登陆baostock")
#####login#####
lg=bs.login(user_id="anonymous",password="******")
if(lg.error_code == '0'):
print("登陆成功")
else:
print("登录失败")
#####get stock data#####
rs=bs.query_growth_data(code=stock_number,year=year,quarter=quarter)
print('请求历史数据返回代码:'+rs.error_code)
print('请求历史数据返回信息:'+rs.error_msg)
data_list=[]
while(rs.error_code=='0')&rs.next():
data_list.append(rs.get_row_data())
result=pd.DataFrame(data_list,columns=rs.fields)
bs.logout()
print(stock_name+"("+stock_number+")"+"的数据处理完成")
print('==========================================================')
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 logout(self):
'''
退出
'''
hide()
bs.logout()
show()
def data_download(self, start_date='2017-07-01', end_date='2020-12-31'):
#### 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)
#### 获取沪深A股历史K线数据 ####
rs = bs.query_history_k_data_plus(
self.code,
"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
start_date=start_date,
end_date=end_date,
frequency="d",
adjustflag="3")
print('query_history_k_data_plus respond error_code:' + rs.error_code)
print('query_history_k_data_plus 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())
self.mydata = pd.DataFrame(data_list, columns=rs.fields)
#### 登出系统 ####
bs.logout()
