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 dump_sw_class1_list(file):
'''
Get the list of SW class1 list and save to file
:param file: the file containing indices that will be saved
:return:
'''
df, msg = swindex.get_index_list()
print(msg)
df_class_one = df[df['section_name'] == u'一级行业']
df_class_one.to_csv(file)
def swindex_get_index_list():
df, msg = swindex.get_index_list()
return df.to_json(orient='table')
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)
def get_heatmap_data(is_save: bool = False):
"""
热力图数据、散点图数据
申万一级行业涨跌幅、换手率与交易量，
数据格式：4or5 * n，n为申万一级行业个数，
每个数组中[x轴(换手率),y轴(涨跌幅),面积(交易量),行业名称,(可选)]
:param is_save:
:return:
"""
data = dict()
#
index_list, msg = swindex.get_index_list()
days_delta = 30
end_date = datetime.date.today()
start_date = end_date - datetime.timedelta(days=days_delta)
l1_industry = index_list[index_list['section_name'] == '一级行业'].set_index(
keys='index_code')
l1_codes = l1_industry.index.tolist()
#
data['trade_date'] = None
data['industry'] = l1_industry['index_name'].tolist()
data['heatmap'] = []
data['scatter'] = []
#
for i in range(0, len(l1_codes)):
kdaily, msg = swindex.get_index_daily(
index_code=l1_codes[i],
start_date=start_date.isoformat(),
end_date=end_date.isoformat())
daily_indi, msg = swindex.get_index_dailyindicator(
index_code=l1_codes[i],
start_date=start_date.isoformat(),
end_date=end_date.isoformat(),
freq='D')
daily_data = pd.merge(
left=kdaily,
right=daily_indi.drop(
['index_code', 'index_name', 'close', 'chg_pct', 'volume'],
axis=1),
on='date',
how='left')
daily_data.sort_values(by='date', inplace=True)
daily_data.reset_index(drop=True, inplace=True)
# 热力图纵轴索引
daily_data['ver_range'] = [i] * len(daily_data)
# 热力图横轴索引
daily_data['hor_range'] = range(0, len(daily_data))
# 单日涨跌
daily_data[['turn_rate', 'change_pct',
'vol']] = daily_data[['turn_rate', 'change_pct',
'vol']].astype('float')
# 累计涨跌
daily_data['change_sum'] = round(daily_data['change_pct'].cumsum(), 2)
if data['trade_date'] is None:
data['trade_date'] = daily_data['date'].map(
lambda x: to_date_str(x, only_date=True)).tolist()
# data[l1_codes[i]] = dict()
# data[l1_codes[i]]['index_name'] = l1_industry.loc[l1_codes[i], 'index_name']
# 热力图数据
heatmap_data = daily_data[[
'hor_range', 'ver_range', 'change_pct', 'change_sum'
]].values.tolist()
data['heatmap'].extend(heatmap_data)
# 散点图
scatter_data = [
daily_data.loc[len(daily_data) - 1,
['turn_rate', 'change_pct', 'vol', 'index_name']].
values.tolist()
]
data['scatter'].extend(scatter_data)
if is_save:
with open(PRO_PATH + '/data/heatmap.json', 'w') as f:
json.dump(data, f, indent=1, ensure_ascii=False)
return data
bounds = []
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}
#