TianGong Quantitative Investment Research Analysis Client
Project description
tgtrader
天工量化投研分析客户端
- 提供开箱即用的分析工具
- 对于小白,可以直接使用可视化分析工具,零代码开启量化分析
- 对于有一定经验的开发者,结合使用sdk开发,更加灵活
安装
pip install tgtrader
如果网络不通,可以使用国内镜像源
pip install tgtrader -i https://mirrors.aliyun.com/pypi/simple/
更新日志
v0.1.0
- 支持获取国内ETF数据、股票数据(使用AKShare获取数据)
使用说明
获取数据
from tgtrader.data import DataGetter
from tgtrader.common import PriceAdjust, Period, SecurityType
symbols = [
'511260', # 十年国债ETF
'159915', # 创业板ETF
'510500', # 500ETF
'159919', # 沪深300ETF
'510880', # 红利ETF
'518880', # 黄金ETF
'513100', # 纳指ETF
]
data_getter = DataGetter()
df = data_getter.get_data(symbols,
"2010-01-01",
"2024-11-30",
period=Period.Day,
fields=["open","close","high","low","volume"],
security_type=SecurityType.ETF,
adjust=PriceAdjust.HFQ)
df
| 参数 | 类型 | 说明 | 示例值 |
|---|---|---|---|
| symbols | List[str] | 证券代码列表 | ['511260', '159915'] |
| start_date | str | 开始日期,格式为YYYY-MM-DD | '2010-01-01' |
| end_date | str | 结束日期,格式为YYYY-MM-DD | '2024-11-30' |
| period | Period | 数据周期,可选值:Day(日线)、Week(周线)、Month(月线) | Period.Day |
| fields | List[str] | 需要获取的字段,可选值:open、close、high、low、volume | ['open', 'close'] |
| security_type | SecurityType | 证券类型,可选值:ETF、Stock | SecurityType.ETF |
| adjust | PriceAdjust | 价格复权方式,可选值:None(不复权)、QFQ(前复权)、HFQ(后复权) | PriceAdjust.HFQ |
微信公众号: 天工量化
关注即可获取:
- tgtrader的最佳实践:如何用好tgtrader以提高投研效率
- 研报复现:各大券商研报复现,源码公开
- 策略分享:基于tg量化工具集,实现各类策略
- 实盘跟踪:已上线的实盘策略持续跟进
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