semvec/pypi-packages huggingface dataset:
BDMLtools 0.4.5
Ml learning tools for busniess data mining

# BDMLtools

[![PyPI version](https://img.shields.io/pypi/pyversions/BDMLtools.svg)](https://pypi.python.org/pypi/BDMLtools)
[![License](https://img.shields.io/github/license/zk403/mlearn)](https://github.com/zk403/mlearn/blob/main/LICENSE)
[![Build Status](https://github.com/zk403/mlearn/actions/workflows/python-test.yml/badge.svg)](https://github.com/zk403/mlearn/actions/workflows/python-test.yml)
[![codecov](https://codecov.io/gh/zk403/mlearn/main/graphs/badge.svg)](https://app.codecov.io/gh/zk403/mlearn)
[![PyPI release](https://img.shields.io/pypi/v/BDMLtools.svg)](https://pypi.python.org/pypi/BDMLtools)

BDMLtools是适用于常见商业数据分析数据挖掘场景下，中小数据量的二分类模型的机器学习建模工具包。
本模组将集成商业分析场景中二分类模型中常用的机器学习模型，并使之能够兼顾模型开发效率、报告制作与建模流程标准化。
本模组涵盖数据清洗、数据探索、特征工程、评分卡制作、模型评估、统计学逐步回归、机器学习模型及其参数优化等内容

安装: 

+ github

```
pip install git+git://github.com/zk403/mlearn.git
```

+ pypi

```
pip install BDMLtools
```

卸载: 

```
pip uninstall BDMLtools
```

更新
```
v0.4.5
1.移除tunner中有关模型校准(calibration)内容
2.修复varGroupsPlot的bug
3.修改binSelector中参数iv_limit默认值
4.全面替换贝叶斯优化基础库由scikit-optimize为optuna
5.LgbmShapRFECVSelector中替换贝叶斯优化的scikit-optimize为随机网格搜索
6.移除tunner中的评估函数ks与lift，auc与logloss修改为sklearn.metrics默认
7.重构gridsearch、FLgridTuner、halvingcv代码，使其更加合理
8.更新单元测试脚本，更新部分代码说明
9.更新example
```
promsoft_dl_interface 0.1.21
Интерфейс HTTP API транспортной компании Деловые линии.
Requires Python: <4.0,>=3.10


Interfaces for API <a href="https://dev.dellin.ru/api/ordering/ltl-request/">Delovie linii</a> transport company.  

Usage:
```
from dl_interface import Counteragent

ca = Counteragent(form="0xb9090c56d0e15e524e2035fcea921d4d", name="Иванов Иван Иванович")  
print(f"As dict: {ca.dict()}")
```
DIYables-Pico-Joystick 0.1.0
Joystick Library for with Raspberry Pi Pico, created by DIYables
Requires Python: >=3.6

## Joystick Library for Raspberry Pi Pico - DIYables_Pico_Joystick
This MicroPython library is designed for Raspberry Pi Pico to make it easy to use with joystick. It is easy to use for not only beginners but also experienced users... 

It is created by DIYables to work with DIYables Joystick, but also work with products from other brands. Please consider purchasing products from [DIYables Store on Amazon](https://amazon.com/diyables) to support our works.



Features
----------------------------
* Works with any Raspberry Pi Pico board.

Product Link
----------------------------
* [Joystick](https://diyables.io/products/joystick)
* [Sensor Kit](https://diyables.io/products/sensor-kit)



Available Functions
----------------------------
* __init__(pin_x, pin_y, pin_button, mode=Pin.PULL_UP)
* read_x()	
* read_y()	
* read_button_state()
* is_pressed()
* is_released()
* get_press_count()
* set_press_count_mode(mode)
* reset_press_count()
* set_debounce_time(time_ms)
* loop()



Available Examples
----------------------------
* main.py



Tutorials
----------------------------
* [Raspberry Pi Pico - Joystick](https://newbiely.com/tutorials/raspberry-pico/raspberry-pi-pico-joystick)



References
----------------------------
* [Raspberry Pi Pico - Joystick Library](https://newbiely.com/tutorials/raspberry-pico/raspberry-pi-pico-joystick-library)
rag-engine 0.1.2
A Retrieval-Augmented Generation (RAG) Engine for managing embeddings and similarity search
Requires Python: >=3.7

# RAG Engine

[![Python Tests](https://github.com/slava-vishnyakov/rag_engine/actions/workflows/python-tests.yml/badge.svg)](https://github.com/slava-vishnyakov/rag_engine/actions/workflows/python-tests.yml)

RAG Engine is a Python package for implementing Retrieval-Augmented Generation (RAG) using OpenAI's embeddings and a SQLite database with vector search capabilities.

## Installation

You can install the RAG Engine package using pip:

```
pip install rag_engine
```

## Usage

Here's a quick example of how to use RAG Engine:

```python
import asyncio
from rag_engine import RAGEngine

async def main():
    # Initialize the RAG Engine
    rag = RAGEngine("database.sqlite")

    # Add some sentences
    sentences = ["This is a test sentence.", "Another example sentence."]
    rag.add(sentences)

    # Search for similar sentences
    results = rag.search("test sentence", n=2)
    print(results)

# Run the async function
asyncio.run(main())
```

## Features

- Supports multiple OpenAI embedding models: ADA_002, SMALL_3, and LARGE_3
- Asynchronous operations for better performance
- SQLite database with vector similarity search
- Flexible API for adding, searching, and deleting embeddings

## Development

To set up the development environment:

1. Clone the repository
2. Install the package with development dependencies:
   ```
   pip install -e .[dev]
   ```
3. Run the tests:
   ```
   pytest
   ```

Note: Tests require a valid OpenAI API key. Set the `OPENAI_API_KEY` environment variable before running the tests.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
plsp 0.261
A simple, easy to use, and powerful logging library for Python.

# Please Log Shit Please (or `plsp`)

## Notes

```text
`infoinject` is a module allowing you to 'compile' python source code with added debug information.
this means that the interesting parts of the code stay separate from printing and other debug code.
```

```text
=====================
Pieces of the puzzle.
=====================

Logger 			- The piece that does the logging.

Debug_Context 		- Use this along side with the logger to separate different areas of an application.
			- For example, you may have a rendering context and a physics context inside a game engine.

Debug_Mode 		- Use this to specify different levels of debug information.
			- For example, you may have a "info" mode and a "detail" mode.
			- If the "info" mode is active, any messages that are in the "detail" mode will not be printed.
			- This is because the "detail" mode extends from the "info" mode.
			- If the "detail" mode is active, any messages that are in the "info"
			-   and "detail" mode will be printed.

infoinject 		- The piece that injects the debug information into the source code.
			- Uses the Logger to log the debug information.

formatters/ 		- The pieces that format the debug information.
			- For example, you may want to have the time of the debug information to
			-   be formatted in a specific way.
			- You may also want to have the caller of the debug information to be formatted in a specific way.
			- The formatters may be added onto any specified debug context. Then, when the Logger is used
			-   by said context, the formatters will be used to format the debug information.



====================================
How the pieces relate to each other.
====================================

> Nodes A that is down from node B means that A depends on, or is used by, B.

	Logger
	/ \
	+  +--------------------+
	|                       |
	Debug_Context           Debug_Mode
	|
	formatters/
```

## V0.261 released on 6th/8/2024
Chopped infoinject