semvec/pypi-packages huggingface dataset:
BahaviorPattern 0.0.2
The tool is designed to mine behavior patterns
Requires Python: >=3.6

BahaviorTool是一个Python包，提供了CombinePattern、ContinuePattern和SequencePattern三个类的实现行为模式挖掘。

## 安装

你可以使用pip安装BahaviorPattern：

```
pip install BahaviorPattern
```

## 使用

在你的Python代码中引入类，例如：

```python
from BahaviorPattern import CombinePattern, ContinuePattern, SequencePattern

#--------------------------------- 组合行为模式挖掘 ---------------------------------#
use_behavior = []
del_behavior = []
# 创建实例
behavior = CombinePattern(data=data, 
                          use_behavior=use_behavior, 
                          del_behavior=del_behavior, 
                          min_support=0.1, 
                          min_confidence=0.5, 
                          min_length=3, 
                          max_length=7, 
                          sep='@') 
# 运行模型，返回pattern结果和使用的行为列表
combine, combine_use_behavior = behavior.run() 
# 筛选lift符合要求的pattern
combine_result = combine[combine['lift'] > 6] 


#--------------------------------- 连续行为模式挖掘 ---------------------------------#
use_behavior = []
del_behavior = []
# 创建实例
behavior = ContinuePattern(data=data, 
                           use_behavior=use_behavior, 
                           del_behavior=del_behavior, 
                           min_support=0.1, 
                           min_length=3, 
                           max_length=6, 
                           sep='@') 
# 运行模型，返回pattern结果和使用的行为列表
continues, continue_use_behavior = behavior.run() 
# 筛选lift符合要求的pattern
continues_result = continues[continues['lift'] > 6] 


#--------------------------------- 序列行为模式挖掘 ---------------------------------#
use_behavior = []
del_behavior = []
# 创建实例
behavior = SequencePattern(data=data, 
                           use_behavior=use_behavior, 
                           del_behavior=del_behavior, 
                           min_support=0.1,
                           min_length=3, 
                           max_length=7, 
                           sep='@') 
# 运行模型，返回pattern结果和使用的行为列表
sequence, seq_use_behavior = behavior.run() 
# 筛选lift符合要求的pattern
sequence_result = sequence[sequence['lift'] > 6] 
```

## 依赖

BahaviorPattern依赖以下Python库：

- numpy
- pandas
- efficient_apriori
- tqdm
- prefixspan

完整的依赖列表可以在setup.py中找到。

## 贡献

如果你发现任何bugs，请提交Issue或Pull Request进行更正

## 作者

MyPackage由Chen Chen编写和维护。

## 致谢

感谢以下Python包的开发者：

- numpy
- pandas
- efficient_apriori
- tqdm
- prefixspan

这些开发者对该项目发展做出了重要贡献。
jaraco.env 1.0.0
Facilities for environment variables
Requires Python: >=3.7

.. image:: https://img.shields.io/pypi/v/jaraco.env.svg
   :target: https://pypi.org/project/jaraco.env

.. image:: https://img.shields.io/pypi/pyversions/jaraco.env.svg

.. image:: https://github.com/jaraco/jaraco.env/workflows/tests/badge.svg
   :target: https://github.com/jaraco/jaraco.env/actions?query=workflow%3A%22tests%22
   :alt: tests

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
   :target: https://github.com/psf/black
   :alt: Code style: Black

.. .. image:: https://readthedocs.org/projects/jaracoenv/badge/?version=latest
..    :target: https://jaracoenv.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/badge/skeleton-2023-informational
   :target: https://blog.jaraco.com/skeleton


This library facilitates handling of environment variables.


Check
=====

Use ``Check`` to act as a boolean gate on an environment variable.