Metadata-Version: 2.4
Name: term-rules
Version: 0.1.0
Summary: Transparent Easy Rule Model (credit scoring rules)
Project-URL: Homepage, https://github.com/yourname/term-rules
Project-URL: Issues, https://github.com/yourname/term-rules/issues
Author-email: Your Name <you@example.com>
License: MIT License
        
        Copyright (c) 2025 朱孟宇
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the “Software”), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice (including the next
        paragraph) shall be included in all copies or substantial portions of the
        Software.
        
        THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
        THE SOFTWARE.
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: bitarray>=2.5.1
Requires-Dist: catboost>=1.2
Requires-Dist: eventlet>=0.33.3
Requires-Dist: gmpy2>=2.1.2
Requires-Dist: lightgbm>=4.0
Requires-Dist: mpmath>=1.3.0
Requires-Dist: numpy>=1.22.3
Requires-Dist: pandas>=1.5.3
Requires-Dist: plotly>=5.0
Requires-Dist: scikit-learn>=1.2.2
Requires-Dist: scipy>=1.8.0
Requires-Dist: tqdm>=4.65.0
Requires-Dist: xgboost>=1.7.6
Description-Content-Type: text/markdown

# term-rules

Transparent Easy Rule Model（基于树模型的规则抽取与评估，German Credit 示例）。

> 安装（包名）：`pip install term-rules`  
> 导入（代码包）：`import term`（因为源码目录叫 `term/`）

## 快速开始
```python
from term import Rule
r = Rule("CreditHistory <= 3.5 & Duration > 11.5 & Savings <= 1.5")
mask = r(df)  # True 表示命中该规则
