def main2():
# 获取期权基础信息文件
df_info = get_opt_info('510050.SH.csv')
df_info_call = df_info[df_info['call_or_put'] == 'C']
df_info_put = df_info[df_info['call_or_put'] == 'P']
df_info_call.reset_index(inplace=True)
df_info_put.reset_index(inplace=True)
path = os.path.join(__CONFIG_TDX_STK_DIR__, 'vipdoc', 'ds', 'lday')
wind_codes = list(set(df_info_call['wind_code']))
wind_codes.sort()
df_volume = None
for wind_code in wind_codes:
print(wind_code)
try:
df_volume_ = get_price(wind_code, path=path, instrument_type='option',
fields=['Volume'])
except:
continue
if df_volume is None:
df_volume = df_volume_
else:
# 将所有数据合并成一个DataFrame太占用内存，读一个计算一个更快
df_volume = df_volume.add(df_volume_, fill_value=0)
path_csv = os.path.join(__CONFIG_H5_OPT_DIR__, 'data', 'call.csv')
df_volume.to_csv(path_csv)
wind_codes = list(set(df_info_put['wind_code']))
wind_codes.sort()
df_volume = None
for wind_code in wind_codes:
print(wind_code)
try:
df_volume_ = get_price(wind_code, path=path, instrument_type='option',
fields=['Volume'])
except:
continue
if df_volume is None:
df_volume = df_volume_
else:
df_volume = df_volume.add(df_volume_, fill_value=0)
path_csv = os.path.join(__CONFIG_H5_OPT_DIR__, 'data', 'put.csv')
df_volume.to_csv(path_csv)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
读取数据示例
"""
from kquant_data.api import get_price
pricing = get_price('600000.SH', instrument_type='stock')
print(pricing)
pricing = get_price(['600000.SH', '000001.SZ'], instrument_type='stock')
print(pricing)
pricing = get_price(['000001.SZ'],
instrument_type='stock',
start_date='2010-01-01')
print(pricing)
pricing = get_price(['000001.SZ'],
instrument_type='stock',
start_date='2010-01-01',
bar_size=300,
fields=['Close'])
print(pricing)
pricing = get_price(['000001.SZ'],
instrument_type='stock',
start_date='2010-01-01',
bar_size=86400)
print(pricing)
# 拿到的价格是原始价格，需要自己复权
# 向前复权
pricing['Close_forward_factor'] = pricing['Close'] * pricing['forward_factor']
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
读取数据示例
"""
from kquant_data.api import get_price
pricing = get_price('600000.SH')
print(pricing)
pricing = get_price(['600000.SH', '000001.SZ'])
print(pricing)
pricing = get_price(['000001.SZ'], start_date='2010-01-01')
print(pricing)
pricing = get_price(['000001.SZ'], start_date='2010-01-01', bar_size=300, fields=['Close'])
print(pricing)
pricing = get_price(['000001.SZ'], start_date='2010-01-01', bar_size=86400)
print(pricing)
# 拿到的价格是原始价格，需要自己复权
# 向前复权
pricing['Close_forward_factor'] = pricing['Close'] * pricing['forward_factor']
print(pricing)
# 向后复权
pricing['Close_backward_factor'] = pricing['Close'] * pricing['backward_factor']
print(pricing)
from kquant_data.api import get_price
from kquant_data.option.info import get_opt_info, get_opt_info_filtered_by_month
from kquant_data.processing.utils import read_fill_from_dir
from kquant_data.config import __CONFIG_H5_OPT_DIR__, __CONFIG_TDX_STK_DIR__
if __name__ == '__main__':
# 获取期权基础信息文件
df_info = get_opt_info('510050.SH.csv')
df_filtered = get_opt_info_filtered_by_month(df_info, 1806)
df_filtered = df_filtered[(df_filtered['listed_date'] <= '2018-04-10')]
path = os.path.join(__CONFIG_TDX_STK_DIR__, 'vipdoc', 'ds', 'lday')
pricing = get_price(list(df_filtered.index), path=path, instrument_type='option')
# print(df)
# 这是期权的价格，不是标的的价格
Close = pricing['Close']
# print(Close)
path = os.path.join(__CONFIG_H5_OPT_DIR__, 'optionchain', '510050.SH')
df_strike_price = pd.DataFrame(index=Close.index, columns=Close.columns)
df_strike_price = read_fill_from_dir(path, 'strike_price', df_strike_price)
df_strike_price.iloc[-1] = df_info['exercise_price']
df_strike_price.fillna(method='bfill', inplace=True)
df_multiplier = pd.DataFrame(index=Close.index, columns=Close.columns)
df_multiplier = read_fill_from_dir(path, 'multiplier', df_multiplier)
df_multiplier.iloc[-1] = df_info['contract_unit']
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
读取数据示例
"""
import os
from kquant_data.config import __CONFIG_H5_FUT_DIR__
from kquant_data.api import get_price
from kquant_data.option.info import read_optioncontractbasicinfo
get_price('sh')
root_path = os.path.join(__CONFIG_H5_FUT_DIR__, 'optioncontractbasicinfo',
'510050.SH.csv')
df_info = read_optioncontractbasicinfo(root_path)
# 排序一下，方便显示
df_info = df_info.sort_values(
by=['limit_month', 'call_or_put', 'exercise_price'])
df_info = df_info.reset_index()
# df_info = df_info.set_index(['limit_month', 'call_or_put', 'exercise_price', 'limit_month_m'])
df_info = df_info.set_index(['limit_month', 'call_or_put', 'exercise_price'])
# df_info.to_csv(r'd:\x.csv', encoding='utf-8-sig')
# 选择具体的到期月份，这下可以画T型报价图了
df_filtered = df_info[df_info.index.get_level_values('limit_month') == 1806]
df = get_price(list(df_filtered['wind_code']),
path=r'D:\shqqday',
instrument_type='option',
new_symbols=list(df_filtered['trade_code']))
print(df)