ttdatasdk 0.0.3

Ticker Trading Factors data access, Backtest and Trading.

ttdatasdk

介绍

Ticker Trading Factors data access, Backtest and Trading.

安装方法

# 首次安装, 在项目的根目录下添加requirements.txt文件，增加内容如下：

Cython==0.29.34

ply==3.11

msgpack>=0.4.7

pandas==1.4.4

setuptools==66.0.0

six==1.16.0

thriftpy2==0.4.16

wheel==0.38.4

ttdatasdk==0.0.1



# 在命令行执行：

pip install -r requirements.txt

# 如果安装失败，请指定官方镜像源

pip install -r requirements.txt -i https://pypi.org/simple



# 安装指定的版本： pip install ttdatasdk==<version>

pip install ttdatasdk==0.0.2



# 升级版本

pip install -U ttdatasdk

# 如果安装失败，请指定官方镜像源

pip install -U ttdatasdk -i https://pypi.org/simple

使用方法

import ttdatasdk



"""账号认证"""

ttdatasdk.auth(username, password)



"""使用 token 认证账号"""

ttdatasdk.auth_by_token(token="")



# 获取因子数据

factor_list = ['float_share', 'pe', 'pe_ttm', 'ma_5', 'ema_5', 'dv_ratio']

df = ttdatasdk.get_factor(stock_pool=['000300.SH'], trade_date='2023-03-29', factor_list=factor_list)

print(df)

                            open        high  ...      volume       amount

sec_code  trade_date                          ...                         

000001.SZ 2023-03-29       12.73       12.74  ...   596064.33   750687.551

000002.SZ 2023-03-29       15.41       15.62  ...   654848.26  1012734.687

000063.SZ 2023-03-29   34.435106   34.553575  ...   782218.36  2685933.703

000069.SZ 2023-03-29         4.7        4.75  ...   324836.19   152639.669

000100.SZ 2023-03-29    3.989899    4.044431  ...  1604844.15   707678.236

...                          ...         ...  ...         ...          ...

688363.SH 2023-03-29  111.999999  113.159999  ...    30500.33   341085.693

688396.SH 2023-03-29   59.307833   61.559399  ...    75640.44   458018.471

688561.SH 2023-03-29   72.570005   72.570005  ...    87323.24   605371.703

688599.SH 2023-03-29   51.750011   52.490011  ...    149553.3   768914.461

688981.SH 2023-03-29   49.189988   50.319988  ...   708926.22  3496451.834



[300 rows x 6 columns]

                                    open   high  ...  volume      amount

sec_code  datetime                               ...                    

000001.SZ 2023-03-29 14:56:00  12.529999  12.54  ...  3274.0   4103280.0

          2023-03-29 14:57:00      12.54  12.54  ...  5943.0   7450969.0

          2023-03-29 14:58:00      12.54  12.54  ...   122.0    152976.0

          2023-03-29 14:59:00      12.54  12.54  ...     0.0         0.0

          2023-03-29 15:00:00      12.54  12.54  ...  9497.0  11900655.0



[5 rows x 6 columns]