semvec/pypi-packages huggingface dataset:
pyerrorhelper 0.2.5
AI enabled error handling library
License: MIT
Requires Python: >=3.8
Keywords: error-handling, middleware, python, ai, ai-error-handling, ai-error-summarization

# pyerrorhelper

> 🧠 AI-enabled Python library for **runtime error explainability**.

---

## 📖 Description

`pyerrorhelper` is a Python library that brings **AI-powered error explainability** into your runtime environment.

### Why?
Developers typically use AI **before** running code (for generation) or **after** running code (for debugging).
This package enables AI **during execution**, so your running Python programs can leverage AI-driven insights in real time.

### Key Objectives
- **Runtime AI integration** – Make AI available inside the running program (starting with error explainability).
- **Retrofit older systems** – Allow existing Python systems to adopt AI workflows with minimal changes [this is the future i wanna build].
- **Free & local AI models** – Works with free AI solutions - using [Ollama](https://www.ollama.com).

---

## Architecture Diagram

![Architecture Digram](https://raw.githubusercontent.com/Satyamaadi/pyerrorhelper/refs/heads/main/pyerrorhelper.jpg)

## 🛠️ Working

There are two main components (class) in the system - 

- ErrorMananger (manager.py) -
    install - this method handles overriding sys.excepthook with custom method.
    process_exception - this method calls the second component (OllamaEmbedder) and helps in summarizing the error
    uninstall - this method makes the sys.excepthook as default error handling way

- OllamEmbedder (ollamaembedder.py) - 
    ensure_ollama_installed - this method ensures that Ollama is installed, if not - it tries installing it via curl command
    summarize - this method uses the Ollama supported GPT model to summarize the errors

## 🔀 Flow of control - 

- When we use install() of ErrorManager -> sys.excepthook is overridden
- and at the same time -> OllamaEmbedder is initialised and it checks for Ollama installation on local system
- if its not present -> it tries to install the Ollama backend
- After the installation of Ollama -> the system is activated, ready to catch any error and summarize it


## ⚙️ Installation

1. **Install Python**
   Download and install from [python.org](https://www.python.org/downloads/).

2. **Install pyerrorhelper**
   ```bash
   pip install pyerrorhelper
   ```

3. **Usage**
```
from pyerrorhelper import ErrorManager

class Test:
    def __init__(self):
        self.error_manager = ErrorManager()
        self.error_manager.install()
    
    def some_function(self):
        cause_some_error()
```
## 👨‍💻 About Me

Name: Shikhar Aditya

Email: satyamshikhar@gmail.com

Github Repo Link: [pyerrorhandler](https://github.com/Satyamaadi/pyerrorhelper)

GitHub Personal Profile: [Satyamaadi](https://github.com/Satyamaadi)

## 🤝 Contributing

Contributions are welcome! Feel free to fork, open issues, or submit pull requests.
mwbot 1.0.42
个性化封装的Python Mediawiki API库
License: MIT
Requires Python: <4.0,>=3.9
Keywords: Mediawiki, API, bot, auto

## mwbot(Python)
mwbot是一个基于Python的异步 Mediawiki API库，同时封装了用于[PRTS wiki](https://prts.wiki)的[部分方法](https://github.com/GuGuMur/mwbot/blob/main/mwbot/arktool.py)

## 快速使用
### 前备工作
#### 安装
    pip install mwbot -i https://pypi.org/simple/
#### 获取Bot应有的参数
1. 前往对应wiki的 特殊:版本 页面获取wiki的index.php, api.php的路径
2. 前往对应wiki的 特殊:BotPasswords 创建一套机器人密码

<details><summary>详细过程</summary>

1. 填入“机器人名称”。（如：BotName）

2. 选择下方的权限
    - 这将能够限制通过机器人密码登录后的账户权限，尤其是当你的人工账户和机器人是同一账户时，这将有效保护你的账户。
    - bot只能使用您选中的与您拥有的权限的交集。
    
3. 创建成功，获得机器人密码，你将有两种登录机器人的方式，任意一种都能登录至机器人账户：
    - 登录名为User@BotName，密码为BotPassword
    - 登录名为User，密码为BotName@BotPassword
</details>

### 开始使用
```python
from mwbot import Bot
import asyncio
async def main():
    bot = Bot(
            sitename="my_wiki", # 替换为你所在的Wiki名，便于参考
            api="api", # 替换为对应Wiki的api.php路径
            index="index", #替换为对应Wiki的index.php路径
            username="User",
            password="BotName@BotPassword")
            # 将username和password替换为你刚才获得的机器人登录名和密码
            # 你只能选择一种登录方式，并填入对应登录方式的登录名和密码
    await bot.login()
    
    # 样例：打印页面 用户:User 的内容
    r = await bot.get_page_text(title="用户:User")
    print(r)

if __name__ == "__main__":
    asyncio.run(main())
```
## 深入
* [示例](https://github.com/GuGuMur/mwbot/tree/main/examples)
* [文档](https://gugumur.github.io/mwbot)
nba-draft-utils 0.1.2
Utilities for NBA draft probability modeling: data loading, preprocessing, model training, evaluation, and Kaggle submission.
License: MIT
Requires Python: <3.12,>=3.11

# nba-draft-utils

Utilities for NBA draft probability modeling (data loading, preprocessing, model training/evaluation, and Kaggle submission).

## Install (local)
```bash
pip install -e .