semvec/pypi-packages huggingface dataset:
slidgnal 0.3.0b9
A Signal/XMPP gateway
Requires Python: >=3.11
Keywords: xmpp, gateway, bridge, instant messaging, chat, signal

# slidgnal

A
[feature-rich](https://slidge.im/docs/slidgnal/main/user/features.html)
[Signal](https://signal.org) to
[XMPP](https://xmpp.org/) puppeteering
[gateway](https://xmpp.org/extensions/xep-0100.html), based on
[slidge](https://slidge.im) and
[signalmeow](https://github.com/mautrix/signal/tree/main/pkg/signalmeow).

[![CI pipeline status](https://ci.codeberg.org/api/badges/14065/status.svg)](https://ci.codeberg.org/repos/14065)
[![Chat](https://rooms.slidge.im:5281/muc_badge/support@rooms.slidge.im)](https://slidge.im/xmpp-web/#/guest?join=support@rooms.slidge.im)
[![PyPI package version](https://badge.fury.io/py/slidgnal.svg)](https://pypi.org/project/slidgnal/)




slidgnal lets you chat with users of Signal without leaving your favorite XMPP client.

## Quickstart

```sh
docker run codeberg.org/slidge/slidgnal \  # works with podman too
    --jid signal.example.org \  # can be whatever you want it to be
    --secret some-secret \  # must match your XMPP server config
    --home-dir /somewhere/writeable  # for data persistence
```

Use the `:latest-amd64` tag for the latest release, `:vX.X.X-amd64` for release X.X.X, and `:main-amd64`
for the bleeding edge.`-arm64` images are also available.

If you do not like containers, other installation methods are detailed
[in the docs](https://slidge.im/docs/slidgnal/main/admin/install.html).

## Documentation

Hosted on [codeberg pages](https://slidge.im/docs/slidgnal/main/).

## Contributing

Contributions are **very** welcome, and we tried our best to make it easy
to start hacking on slidgnal. See [CONTRIBUTING.md](./CONTRIBUTING.md).
mysharelib 1.0.4
My share library
Requires Python: <3.13,>=3.11


# mysharelib

A Python library for financial data analysis and utilities, focused on Hong Kong stock market data.

## Features

- Fetch Hong Kong stock information and financial reports from EastMoney
- Analyze major shareholders and financial statements
- Scrape Hong Kong stock news from Sina Finance
- Utility functions for logging, caching, and data handling

## Directory Structure

- `src/mysharelib/em/`: EastMoney data fetchers (stock info, balance sheet, cash flow, income, shareholder analysis)
- `src/mysharelib/sina/`: News scraping for HK stocks
- `src/mysharelib/tools.py`: Logging and utility functions
- `log/`: Cached financial data in JSON format
- `tests/`: Pytest-based unit tests

## Installation

Requires Python 3.11–3.12.

```sh
pip install .
```

Or with Poetry:

```sh
poetry install
```

## Dependencies

- openbb-core
- chinese-calendar
- akshare

## Usage Example

```python
from mysharelib.em.get_hk_info_em import get_hk_info_em
df_basic, df_compare = get_hk_info_em("01088.HK")
```

## Development

- Use the `dev` branch for development and `main` for production.
- Run tests with `pytest`.
jws-voice-assistant 1.0.2
智能语音助手系统 - 类似钢铁侠中的贾维斯（JARVIS）
Requires Python: >=3.9
Keywords: voice assistant, jarvis, speech recognition, macos, automation, ai

# 🤖 Jws - 智能语音助手系统

## 项目简介

Jws 是一个类似钢铁侠中贾维斯（JARVIS）的智能语音助手系统，运行在 macOS 上，具有以下核心功能：

- 🎤 **语音识别**：听懂你说的话
- 🧠 **智能理解**：理解你的意图和指令
- ⚡ **系统控制**：在系统上所有app内执行操作
- 🔐 **最高权限**：具有除你之外的最高系统权限
- 🎯 **指示级操作**：你说什么，它就能做到什么

## 核心特性

### 1. 语音交互
- 实时语音识别
- 自然语言理解
- 语音反馈（TTS）

### 2. 系统控制
- 应用启动和切换
- 文件操作
- 系统设置控制
- GUI自动化

### 3. 智能助手
- 上下文理解
- 多轮对话
- 任务规划
- 自动化执行

## 技术栈

- **Python 3.9+** - 主要开发语言
- **SpeechRecognition** - 语音识别
- **pyttsx3 / gTTS** - 语音合成
- **AppleScript** - macOS 系统控制
- **PyAutoGUI** - GUI自动化
- **OpenAI API** (可选) - 高级NLP理解
- **macOS Accessibility API** - 系统权限

## 项目结构

```
Jws/
├── src/                    # 源代码
│   ├── core/              # 核心功能
│   │   ├── voice_recognition.py    # 语音识别
│   │   ├── command_parser.py       # 指令解析
│   │   ├── system_controller.py    # 系统控制
│   │   └── app_controller.py       # 应用控制
│   ├── utils/             # 工具函数
│   │   ├── audio.py      # 音频处理
│   │   └── permissions.py # 权限管理
│   └── main.py           # 主程序入口
├── config/                # 配置文件
│   └── settings.json     # 系统配置
├── requirements.txt       # 依赖包
├── setup.py              # 安装脚本
└── README.md             # 项目说明
```

## 快速开始

### 安装依赖

```bash
pip install -r requirements.txt
```

### 运行

```bash
python src/main.py
```

## 权限配置

Jws 需要以下 macOS 权限：
- ✅ 辅助功能权限（控制其他应用）
- ✅ 屏幕录制权限（GUI自动化）
- ✅ 麦克风权限（语音识别）
- ✅ 完全磁盘访问权限（文件操作）

## 使用示例

```
你: "打开Safari浏览器"
Jws: "正在打开Safari..."

你: "帮我写一封邮件给张三，主题是项目进度"
Jws: "正在打开邮件应用，准备编写邮件..."

你: "切换到Chrome，打开GitHub"
Jws: "已切换到Chrome，正在打开GitHub..."
```

## 开发计划

- [x] 项目初始化
- [ ] 语音识别模块
- [ ] 指令解析模块
- [ ] 系统控制模块
- [ ] 应用控制模块
- [ ] 权限管理
- [ ] 用户界面
- [ ] 配置系统

## 注意事项

⚠️ **安全提示**：
- Jws 具有系统最高权限，请妥善保管
- 建议设置启动密码或生物识别验证
- 定期更新和检查系统安全

## 许可证

MIT License
reinforcenow 10.0.1
This package has been renamed to 'rnow'. Please install 'rnow' instead.
Requires Python: >=3.7

# reinforcenow

## This package has been renamed!

Please install **rnow** instead:

```bash
pip uninstall reinforcenow
pip install rnow
```

The `reinforcenow` package name is deprecated. All development continues under the `rnow` package.
pypith-cli 0.1.2
Wrap any CLI with agent-friendly progressive discovery
Requires Python: >=3.10
Keywords: agent, ai, cli, command-line, llm, progressive-discovery, wrapper

# pypith-cli

Wrapper CLI that turns existing tools into agent-friendly experiences.

- Capture help text, analyze it, and emit Pith schemas
- Generate Bash/PowerShell/CMD wrappers
- Optional LLM providers (Anthropic, OpenAI, Ollama) with heuristic fallback

## Installation

```bash
pip install pypith-cli

# With LLM providers
pip install pypith-cli[anthropic]
pip install pypith-cli[openai]
pip install pypith-cli[ollama]
```

## Quick Start

```bash
# Configure LLM provider (optional)
pith init --provider anthropic

# Wrap your tools
pith wrap kubectl terraform docker

# Activate in shell
eval "$(pith activate)"

# Now they're agent-friendly
kubectl                    # Shows progressive discovery tiers
```

## Commands

| Command | Description |
|---------|-------------|
| `pith init` | Configure LLM provider and settings |
| `pith wrap <tool>` | Wrap a CLI with progressive discovery |
| `pith unwrap <tool>` | Remove wrapper |
| `pith list` | List all wrapped tools |
| `pith refresh <tool>` | Re-analyze after tool upgrade |
| `pith activate` | Print PATH activation command |
| `pith find <query>` | Semantic search across tools |
| `pith export <tool>` | Export schema for sharing |
| `pith import <file>` | Import pre-made schema |
pypith 0.1.2
Build agent-native Python CLIs with progressive discovery
Requires Python: >=3.10
Keywords: agent, ai, cli, command-line, llm, progressive-discovery, typer-alternative

# pypith

Decorator-based library for building agent-native Python CLIs with progressive discovery.

- Define commands with `@app.command()` and attach intents and hints
- Auto-generated `pith` discovery subcommand with tiers 0-3
- Built-in core schema, rendering, and optional semantic search
- Schema export compatible with `pypith-cli`

## Installation

```bash
pip install pypith

# With semantic search support
pip install pypith[semantic]
```

## Quick Start

```python
from pith import Pith, Argument, Option
from pathlib import Path

app = Pith(name="fileops", pith="File manipulation utilities")

@app.command()
@app.intents("copy files", "duplicate", "backup files")
def copy(
    src: Path = Argument(..., pith="Source file or directory"),
    dest: Path = Argument(..., pith="Destination path"),
    recursive: bool = Option(False, "-r", "--recursive", pith="Copy directories recursively"),
):
    """Copy files or directories to a destination."""
    import shutil
    if src.is_dir() and recursive:
        shutil.copytree(src, dest)
    else:
        shutil.copy2(src, dest)

if __name__ == "__main__":
    app.run()
```

## Core Module

The library includes the core schema and rendering utilities:

```python
from pith.core import PithSchema, Command, Tier1, Tier2, Tier3
from pith.core import render_tier0, build_run_line, search_commands
```