def get_zh_info():
ts.set_token(config.get('tushare', 'token'))
pro = ts.pro_api()
df = pro.stock_basic()
df.rename(columns={'symbol': 'code'}, inplace=True)
table = 'zh_stocks_info'
columns = [
'code', 'ts_code', 'name', 'industry', 'area', 'market', 'list_date'
]
df = df[columns]
df = df[df['code'].str.isdigit()]
mydb.upsert_table(table, columns, df)
df, msg = swindex.get_index_list()
df1 = df.loc[df['section_name'] == "一级行业"]
ind1_list = df1.index_code
sw_columns = ['code', 'name', 'sw_ind1', 'sw_ind1_weight']
j = 0
for i in ind1_list:
j = j + 1
print('processing [' + str(j) + '/' + str(ind1_list.size) + '] : ' + i)
stock_data, msg = swindex.get_index_cons(i)
stock_data.rename(columns={
'stock_code': 'code',
'stock_name': 'name',
'weight': 'sw_ind1_weight'
},
inplace=True)
stock_data.loc[:, 'sw_ind1'] = df1.query(
'index_code == "{}"'.format(i)).index_name.values[0]
stock_data = stock_data[sw_columns]
upsert_table(table, sw_columns, stock_data)
def get_sw_weight(self, code):
'''
获取申万指数的权重
:param code: sw code
:return: df
'''
df, msg = swindex.get_index_cons(code)
def dump_components(index_file, sleeptime=0.0, stop=100):
'''
dump all components of indices
:param index_file:
:param sleeptime:
:param stop:
:return:
'''
class1_list = get_class1_info(index_file)
count = 0
cnt_comp = 0
for class1 in class1_list:
a_item = class1
code = a_item[1]
df_comp, msg = swindex.get_index_cons(str(code))
leng_df = len(df_comp.index)
cnt_comp += leng_df
print(
f'current{code} has components of {leng_df}/{cnt_comp}(in total)')
fn = str(a_item[1]) + f'_components.csv'
df_comp.to_csv("data/comp/" + fn)
count += 1
if count > stop:
break
if sleeptime > 0.0:
sleep(sleeptime)
def _sw_weight(self):
res = pd.DataFrame()
# 获取申万一级行业成份股
for index_code, index_name in INDUSTRY_SW.items():
temp = swindex.get_index_cons(index_code)[0]
temp.rename(columns={'index_code': 'code', 'index_name': 'name'}, inplace=True)
temp['index_code'] = index_code + '.SI'
temp['index_name'] = index_name
res = res.append(temp, ignore_index=True)
res['code'] = [i + '.SH' if i[0] == '6' else i + '.SZ' for i in res['code']]
res['update_time'] = self.today
return res
from opendatatools import swindex
if __name__ == '__main__':
#df, msg = swindex.get_index_list()
#print(df)
#df, msg = swindex.get_index_cons('801030')
#print(df)
df, msg = swindex.get_index_daily('801003', '2000-01-01', '2018-11-02')
df, msg = swindex.get_index_cons('801060')
print(df)
# freq 'D', 'W', 'M'
#df, msg = swindex.get_index_dailyindicator('801040', '2000-01-01', '2018-11-02', 'W')
#print(df)
def swindex_get_index_cons():
df, msg = swindex.get_index_cons(index_code=request.form['index_code'])
return df.to_json(orient='table')
df.rename(columns={'symbol': 'code'}, inplace=True)
table = 'zh_stocks_info'
columns = [
'code', 'ts_code', 'name', 'industry', 'area', 'market', 'list_date'
]
df = df[columns]
df = df[df['code'].str.isdigit()]
mydb.upsert_table(table, columns, df)
df, msg = swindex.get_index_list()
df1 = df.loc[df['section_name'] == "一级行业"]
ind1_list = df1.index_code
sw_columns = ['code', 'name', 'sw_ind1', 'sw_ind1_weight']
j = 0
for i in ind1_list:
j = j + 1
print('processing [' + str(j) + '/' + str(ind1_list.size) + '] : ' + i)
stock_data, msg = swindex.get_index_cons(i)
stock_data.rename(columns={
'stock_code': 'code',
'stock_name': 'name',
'weight': 'sw_ind1_weight'
},
inplace=True)
stock_data.loc[:, 'sw_ind1'] = df1.query(
'index_code == "{}"'.format(i)).index_name.values[0]
stock_data = stock_data[sw_columns]
upsert_table(table, sw_columns, stock_data)
initial_guess = None
def to_date(date):
return datetime.datetime.strptime(date, '%Y%m%d')
def to_time(date):
return datetime.datetime.strftime(date, '%Y%m%d')
# ------------------------------------- ------------------------------------ #
# ------------------------------------- Constrain ------------------------------------ #
# ------------------------------------- ------------------------------------ #
category, category_msg = swindex.get_index_list()
content, content_msg = swindex.get_index_cons('801040')
# class TrackingErrorLimit:
#
# def __init__(self, upper_limit, hard):
# """
# 追踪误差约束。基准为优化时指定的基准。
#
# :param upper_limit: 追踪误差上界
# :param hard: 软约束/硬约束
# """
# self.upper_limit = upper_limit
# self.hard = hard
# self.constraint = {'type': 'eq', 'fun': lambda x: sum(x) - 1}
#
# def goal(self, omega):