def get_index_df(self, date):
# 沪深大盘指数
# 如果文件存在就读取已有的数据, 如果没有, 就缓存起来
if self.stock_code.endswith('SH'):
index_code = '000001.SH'
else:
index_code = '399001.SZ'
file_name = saver.get_csv_name(date, index_code, self.start_date, self.end_date)
if saver.check_file_existed(file_name):
print('---- 读取csv数据 ----')
df = saver.read_from_csv(file_name)
else:
if date == 'month':
df = pro.index_monthly(ts_code=index_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
elif date == 'week':
df = pro.index_weekly(ts_code=index_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
else:
df = pro.index_daily(ts_code=index_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
print('---- 保存csv数据 ----')
if len(df) != 0:
saver.save_csv(df, file_name)
return df
def get_filtered_stocks(self, pe=100, total_mv=1500000, turnover_rate=3):
# 如果文件存在就读取已有的数据, 如果没有, 就缓存起来
stock_name = saver.get_csv_data_name('stock_info',
'recommended',
end_date=self.last_bus_day)
if saver.check_file_existed(stock_name):
print('---- 读取csv数据 ----')
df = saver.read_from_csv(stock_name)
else:
df = pro.daily_basic(
ts_code='',
trade_date=self.last_bus_day,
fields='ts_code,trade_date,turnover_rate,pe,total_mv')
# ---------------------------------------
# 自定义过滤条件, pe 静态市盈率, total_mv 总市值, turnover_rate 换手率
df = df.drop(df[(df['pe'] < 0) | (df['pe'] > pe) |
(df['total_mv'] < total_mv) |
(df['turnover_rate'] < turnover_rate)].index)
# ---------------------------------------
# 删除有空NaN的行
df = df.dropna(axis=0, how='any')
if len(df) != 0:
saver.save_csv(df, stock_name)
return df
def get_stock_list(self):
# 股票列表
file_name = saver.get_csv_data_name('stock_info', 'stock_list', self.end_date)
if saver.check_file_existed(file_name):
print('---- 读取csv数据 ----')
df = saver.read_from_csv(file_name)
else:
df = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date')
print('---- 保存csv数据 ----')
if len(df) != 0:
saver.save_csv(df, file_name)
return df
def get_stock_info_df(self):
# 通用行情接口, 换手率tor，量比vr, 均线
# 如果文件存在就读取已有的数据, 如果没有, 就缓存起来
file_name = saver.get_csv_name('stock_info', self.stock_code, self.start_date, self.end_date)
if saver.check_file_existed(file_name):
print('---- 读取csv数据 ----')
df = saver.read_from_csv(file_name)
else:
# 换手率tor，量比vr, 均线
df = ts.pro_bar(ts_code=self.stock_code, start_date=self.start_date, end_date=self.end_date,
factors=['tor', 'vr'], ma=[5, 20, 60])
print('---- 保存csv数据 ----')
if len(df) != 0:
saver.save_csv(df, file_name)
return df
def get_all_stocks(self):
# 如果文件存在就读取已有的数据, 如果没有, 就缓存起来
stock_list_name = saver.get_csv_data_name('stocks',
'all',
end_date=self.last_bus_day)
if saver.check_file_existed(stock_list_name):
print('---- 读取csv数据 ----')
data_list = saver.read_from_csv(stock_list_name)
else:
data_list = pro.stock_basic(
exchange='',
list_status='L',
fields='ts_code,symbol,name,area,industry,list_date')
if len(data_list) != 0:
saver.save_csv(data_list, stock_list_name)
return data_list
def get_stock_df(self, date):
# 单个股票的数据
# 如果文件存在就读取已有的数据, 如果没有, 就缓存起来
file_name = saver.get_csv_name(date, self.stock_code, self.start_date, self.end_date)
if saver.check_file_existed(file_name):
print('---- 读取csv数据 ----')
df = saver.read_from_csv(file_name)
else:
if date == 'month':
df = pro.monthly(ts_code=self.stock_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
elif date == 'week':
df = pro.weekly(ts_code=self.stock_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
else:
df = pro.daily(ts_code=self.stock_code, start_date=self.start_date, end_date=self.end_date,
fields=self.fields)
print('---- 保存csv数据 ----')
if len(df) != 0:
saver.save_csv(df, file_name)
return df