semvec/pypi-packages huggingface dataset:
pineko 0.5.0
Combine PineAPPL grids and EKOs into FK tables
Requires Python: <3.13,>=3.9

<p align="center">
  <a href="https://pineko.readthedocs.io/"><img alt="PINEKO" src="https://raw.githubusercontent.com/N3PDF/pineko/main/docs/source/img/Logo.png" width=200></a>
</p>

<p align="center">
  <a href="https://github.com/N3PDF/pineko/actions/workflows/unittests.yml"><img alt="Tests" src="https://github.com/N3PDF/pineko/actions/workflows/unittests.yml/badge.svg" /></a>
  <a href="https://pineko.readthedocs.io/en/latest/?badge=latest"><img alt="Docs" src="https://readthedocs.org/projects/pineko/badge/?version=latest"></a>
  <a href="https://codecov.io/gh/NNPDF/pineko"><img src="https://codecov.io/gh/NNPDF/pineko/branch/main/graph/badge.svg" /></a>
  <a href="https://www.codefactor.io/repository/github/nnpdf/pineko"><img src="https://www.codefactor.io/repository/github/nnpdf/pineko/badge" alt="CodeFactor" /></a>
</p>

PINEKO is a Python module to produce fktables from interpolation grids and EKOs.

## Installation
PINEKO is available via
- PyPI: <a href="https://pypi.org/project/pineko/"><img alt="PyPI" src="https://img.shields.io/pypi/v/pineko"/></a>
```bash
pip install pineko
```

### Development

If you want to install from source you can run
```bash
git clone git@github.com:N3PDF/pineko.git
cd pineko
poetry install
```

To setup `poetry`, and other tools, see [Contribution
Guidelines](https://github.com/N3PDF/pineko/blob/main/.github/CONTRIBUTING.md).

## Documentation
- The documentation is available here: <a href="https://pineko.readthedocs.io/en/latest/"><img alt="Docs" src="https://readthedocs.org/projects/pineko/badge/?version=latest"></a>
- To build the documentation from source run
```bash
cd docs
poetry run make html
```

## Tests and benchmarks
- To run unit test you can do
```bash
poetry run pytest
```

## Contributing
- Your feedback is welcome! If you want to report a (possible) bug or want to ask for a new feature, please raise an issue: <a href="https://github.com/N3PDF/pineko/issues"><img alt="GitHub issues" src="https://img.shields.io/github/issues/N3PDF/pineko"/></a>
- Please follow our [Code of Conduct](https://github.com/N3PDF/pineko/blob/main/.github/CODE_OF_CONDUCT.md) and read the
  [Contribution Guidelines](https://github.com/N3PDF/pineko/blob/main/.github/CONTRIBUTING.md)
aem-instance-manager 0.6
An AEM instance management tool designed to simplify switching across multiple project environments.
Requires Python: >=3.6

# AEM Instance Manager

**AEM Instance Manager** is a Python-based CLI tool to help developers manage local Adobe Experience Manager (AEM) instances more easily. It allows you to start, stop, and monitor multiple AEM author/publish instances from a simple interface.

---

## 📦 Installation

First, clone the repository and navigate to the project directory:

```bash
pip3 install aem-instance-manager
```
## 📋 Dependencies
```
pandas
tkinter for GUI (usually comes with Python)
```

## 📂 Required AEM Project Structure
```
└── project1
    ├── author
    │   └── aem-author-p4502.jar
    ├── publish
    │   └── aem-publish-p4502.jar
    └── src
```

## Required Inputs

To function properly, aem-instance-manager needs the following input details:

| Input | Info |
| ------ | ------ |
| Project Name | You project name (e.g Project 1) |
| Author Port | any author port number (e.g 4502) |
| Publish Port |  any publish port number (e.g 4503) |
| Folder Path | project folder path (e.g. /Users/mayur/Desktop/aem/project1) |

## 🚀 Usage

In Mac

Setup for macOS Terminal
```
export PATH="$HOME/Library/Python/3.13/bin:$PATH"
export PATH="/Library/Frameworks/Python.framework/Versions/3.13/bin:$PATH"
```
Then apply the changes:
```
source ~/.zshrc
```
Once installed, you can launch the CLI tool with:
```
aem-instance-manager
```
Or directly using Python:
```
python3 -m aem_instance_manager.run
```

![aem-instance-manager gui window screenshot](https://raw.githubusercontent.com/mayursatav/aem_instance_manager/refs/heads/main/aem-instance-manager-screenshot.png)

## 🧠 Features
- 🧾 Manage multiple AEM instances (Author / Publish)
- ✅ Start/Stop/Restart selected instances
- 📊 Track status using pandas DataFrames
- 🖥️ Simple terminal interface (with optional GUI using tkinter)

## 📝 License
```
MIT License
```

## Created By
Mayur Satav
[www.mayursatav.in](https://www.mayursatav.in/)
WeiboBot 1.2.3
基于微博H5 API开发的机器人框架
Requires Python: >=3.11
Keywords: weibo, bot, weibo-bot, weibo-api, weibo-sdk

<div align="center">

# WeiboBot

_基于微博H5 API开发的爬虫框架_

<a href="https://pypi.org/project/WeiboBot/"><img alt="PyPI" src="https://img.shields.io/pypi/v/WeiboBot" /></a></td>
<a href="https://pypi.org/project/WeiboBot/"><img alt="Python Version" src="https://img.shields.io/pypi/pyversions/WeiboBot" /></a>
<a href="https://pypi.org/project/WeiboBot/"><img alt="Python Implementation" src="https://img.shields.io/pypi/implementation/WeiboBot" /></a>

<a href="https://github.com/MerlinCN/WeiboBot/blob/master/LICENSE"><img alt="License" src="https://img.shields.io/github/license/MerlinCN/WeiboBot"></a>

</div>



WeiboBot 是一个基于微博H5 API开发的爬虫框架，提供了简单的接口，包括了一些指令，比如：转评赞，回复消息等
可以选择直接获取数据，也可以持续运行

## 安装

### 普通安装

```bash
pip install WeiboBot
```

### 带截图功能

```bash
pip install WeiboBot[screenshot]
```

### 源码安装（推荐使用uv）

```bash
uv sync --all-extras
```

## 开始使用(生命周期)

```python
from loguru import logger

from WeiboBot import Bot, ChatDetail, Comment, Weibo

bot = Bot()


@bot.onNewMsg()  # 被私信的时候触发
async def on_msg(chat: ChatDetail):
    for msg in chat.msgs:  # 消息列表
        logger.info(f"{msg.sender_screen_name}:{msg.text}")


@bot.onNewWeibo()  # 首页刷到新微博时触发
async def on_weibo(weibo: Weibo):
    weibo = await bot.weibo_info(weibo.mid)  # 获取微博详细信息(长微博才需要)
    logger.info(f"{weibo.text}")


@bot.onMentionCmt()  # 提及我的评论时触发
async def on_mention_cmt(cmt: Comment):
    logger.info(f"收到{cmt.mid}的评论")


@bot.onTick()  # 每次循环触发
async def on_tick():
    logger.info("tick")


if __name__ == "__main__":
    bot.run()

```

## 开始使用(仅调用)

```python
import asyncio

from loguru import logger

import WeiboBot.const as const
from WeiboBot import NetTool


async def main():
    async with NetTool() as nettool:
        user = await nettool.user_info(nettool.mid)
        logger.info(user)
        weibo_example1 = await nettool.weibo_info(123456)  # 获取微博
        weibo_example2 = await nettool.post_weibo(
            "发一条微博", visible=const.VISIBLE.ONLY_ME
        )
    # ...... 其他操作


if __name__ == "__main__":
    asyncio.run(main())
```

## 更新路线图

目前项目仍在重构中

- [x]  对旧API的整合
- [ ]  扩展更加多的API
- [x]  提升登录的健壮性
- [ ]  增加更多测试用例和自动化
- [ ]  去掉 logger

## 示例

[好康Bot](https://github.com/MerlinCN/WeiboWatchdog)

正在重构中

> 一个转发小姐姐的Bot