semvec/pypi-packages huggingface dataset:
pmmv 0.4.0
PMMV - Python Mass Move: A tool for batch renaming/moving files with an interactive editor
License: MIT
Requires Python: >=3.11

# PMMV - Python Mass Move

PMMV is a tool for batch renaming/moving files with an interactive editor. Most
useful when you need to rename a huge amount of files and could benefit from
scripted macros. Works best with [fd](https://github.com/sharkdp/fd).

Features:

 - Rename files in the comfort of your favourite editor.
 - .pmmv.undo files allow you to undo your last renaming!
 - Git integration for renaming files.

## Installation

Install using pip:

```bash
uv tool install pmmv
```

## Usage

This was built with vim in mind, though any editor will work. The script will
look at the `EDITOR` variable to determine which editor to use. For instance,
`export EDITOR=code` would open vscode.

```bash
uvx pmmv *.txt readme.md
# Or include a full directory
uvx pmmv my_dir/
```

Or pipe files from another command:

```bash
find . -name "*.txt" | uvx pmmv -
# Or try the much faster fd-find
fd -e txt | uvx pmmv -
```

## Development

Setup with uv.

```
uv venv
. .venv/bin/activate
uv pip sync
```

Tests are run through pytest.

```
uv run pytest tests/ -v
```

## Acknowledgements

This is my first project that's almost entirely vibe-coded. I used an initial
prompt to claude sonnet 4.5 which can be seen at `docs/initial_prompt.txt`. I
then used qwen3-coder-30b-a3 from
[cpatonn](https://huggingface.co/cpatonn/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit)
through vllm 0.11.0 and Qwen Code 0.0.14 to iterate further on the code.
mcp-cuc-ztc 0.1.0
An MCP Server that provides a tool to get the current time with optional timezone support
License: MIT
Requires Python: <4.0,>=3.10

# MCP Time Server

An MCP Server that provides a tool to get the current time with optional timezone support.

## Features

- Provides a `get_current_time` tool to retrieve the current time
- Supports optional timezone parameter
- Simple and lightweight implementation
- Built using the Model Context Protocol (MCP)

## Installation

```bash
pip install mcp-time-server
```

## Usage

### Running the Server

```bash
mcp-time-server
```

This will start the MCP Server using the STDIO transport, which is suitable for local process communication.

### Using the `get_current_time` Tool

The server exposes a single tool called `get_current_time` that can be used by MCP clients.

#### Parameters

- `timezone` (optional): A timezone string, e.g., "Asia/Shanghai", "America/New_York"
  - If not provided, the system's default timezone will be used

#### Return Value

A formatted string representing the current time in the format: `YYYY-MM-DD HH:MM:SS.SSSSSS TIMEZONE`

#### Examples

```python
# Get current time in system default timezone
result = await mcp_client.call_tool("get_current_time")
# Example output: "2023-12-25 13:45:30.123456 EST"

# Get current time in a specific timezone
result = await mcp_client.call_tool("get_current_time", timezone="Asia/Shanghai")
# Example output: "2023-12-26 02:45:30.123456 CST"
```

## Project Structure

```
mcp-time-server/
├── mcp_time_server/
│   ├── __init__.py      # Package initialization
│   └── main.py          # Main server implementation
├── pyproject.toml       # Project configuration
├── README.md            # This file
├── LICENSE              # License file
└── .gitignore           # Git ignore file
```

## License

MIT License - see the LICENSE file for details.

## About MCP

The Model Context Protocol (MCP) is an open-source standard for connecting AI applications to external systems. For more information, visit [modelcontextprotocol.io](https://modelcontextprotocol.io).
artificer-workflows 0.1.0a18
A library for developing workflow graphs that run as MCP (Model Context Protocol) servers
License: MIT
Requires Python: >=3.10
Keywords: ai, llm, mcp, model-context-protocol, workflow

# artificer-workflows

Build multi-step workflows that guide AI agents through complex tasks exposed as MCP tools.

> **Alpha Release** - APIs may change.

## How it works

Define workflows as Python classes with typed steps. The library registers them as tools with your FastMCP server that agents can call to execute the workflow step by step. Each step provides instructions to the agent and validates outputs using Pydantic schemas.

When an agent calls a workflow tool, it receives structured instructions for what to do. After completing the work, the agent calls back with results that are validated against the step's schema. The workflow then transitions to the next step or completes.

## Installation

```bash
pip install artificer-workflows
```

## Quick example

```python
from pydantic import BaseModel, Field
from fastmcp import FastMCP
from artificer.workflows import Workflow

mcp = FastMCP(name="my-workflows")


class BuildFeature(Workflow):
   ...


class GatherRequirementsStep(BuildFeature.Step, start=True):
    class OutputModel(BaseModel):
        summary: str = Field(description="Summary of requirements")

    def start(self, previous_result=None) -> str:
        # return instructions
        return "Gather requirements from the user and document them."

    def complete(self, output: OutputModel) -> type["PlanStep"]:
        # returns next step
        return PlanStep


class PlanStep(BuildFeature.Step):
    class OutputModel(BaseModel):
        tasks: list[str] = Field(description="List of tasks to implement")

    def start(self, previous_result: GatherRequirementsStep.OutputModel=None) -> str:
        return f"Create an implementation plan based on: {previous_result.summary}"

    def complete(self, output: OutputModel) -> None:
        # return None to complete the workflow
        return None


BuildFeature.register(mcp)


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

```

Run the server and connect it to your agent. The agent can now call:
- `BuildFeature__start_workflow` - Start a new workflow
- `BuildFeature__complete_step` - Complete a step and move to the next
- `BuildFeature__generate_diagram` - Generate a Mermaid diagram of the workflow

## Features

- **Type-safe step outputs** - Pydantic schemas validate agent responses
- **Automatic MCP tool generation** - Steps become callable tools
- **Workflow state persistence** - Workflows can rewound and restarted from any step
- **Error handling and retries** - Steps can fail and retry with configurable limits
- **Template support** - Use Jinja2 templates for step instructions
- **Branching workflows** - Steps can conditionally route to different next steps
- **Mermaid Diagram** - Generate a mermaid diagram of your workflow

## License

MIT
qqmusic-api-python 0.4.1
QQ音乐API封装库
License: MIT
Requires Python: >=3.10
Keywords: api, music, qqmusic, tencentmusic

<div align="center">
    <a>
        <img src="https://socialify.git.ci/l-1124/QQMusicApi/image?description=1&font=Source%20Code%20Pro&language=1&logo=https%3A%2F%2Fy.qq.com%2Fmediastyle%2Fmod%2Fmobile%2Fimg%2Flogo.svg&name=1&pattern=Overlapping%20Hexagons&theme=Auto">
    </a>
    <a href="https://www.python.org">
        <img src="https://img.shields.io/badge/Python-3.10|3.11|3.12|3.13-blue" alt="Python">
    </a>
    <a href="https://github.com/l-1124/QQMusicApi?tab=MIT-1-ov-file">
        <img src="https://img.shields.io/github/license/l-1124/QQMusicApi" alt="GitHub license">
    </a>
    <a href="https://github.com/l-1124/QQMusicApi/stargazers">
        <img src="https://img.shields.io/github/stars/l-1124/QQMusicApi?color=yellow&label=Github%20Stars" alt="STARS">
    </a>
    <a href="https://github.com/l-1124/QQMusicApi/actions/workflows/testing.yml">
        <img src="https://github.com/l-1124/QQMusicApi/actions/workflows/testing.yml/badge.svg?branch=main" alt="Testing">
    </a>
</div>

---

> [!IMPORTANT]
> 本仓库的所有内容仅供学习和参考之用，禁止用于商业用途
>
> **音乐平台不易，请尊重版权，支持正版。**

**文档**: <a href="https://l-1124.github.io/QQMusicApi" target="_blank">https://l-1124.github.io/QQMusicApi</a>

**源代码**: <a href="https://github.com/l-1124/QQMusicApi" target="_blank">https://github.com/l-1124/QQMusicApi</a>

## 介绍

使用 Python 编写的用于调用 [QQ音乐](https://y.qq.com/) 各种 API 的库.

## 特色

- 涵盖常见 API
- 调用简便，函数命名易懂，代码注释详细
- 完全异步操作

## 依赖

- Cryptography
- HTTPX
- orjson

## 快速上手

### 安装

```bash
pip install qqmusic-api-python
```

### 使用

```python
import asyncio

from qqmusic_api import search

async def main():
    # 搜索歌曲
    result = await search.search_by_type(keyword="周杰伦", num=20)
    # 打印结果
    print(result)

asyncio.run(main())
```

## [Web API](./web/README.md)

## License

本项目基于 **[MIT License](https://github.com/l-1124/QQMusicApi?tab=MIT-1-ov-file)** 许可证发行。

## 免责声明

由于使用本项目产生的包括由于本协议或由于使用或无法使用本项目而引起的任何性质的任何直接、间接、特殊、偶然或结果性损害（包括但不限于因商誉损失、停工、计算机故障或故障引起的损害赔偿，或任何及所有其他商业损害或损失）由使用者负责

## 贡献者

[![Contributor](https://contrib.rocks/image?repo=l-1124/QQMusicApi)](https://github.com/l-1124/QQMusicApi/graphs/contributors)
alethe 0.1.0
AI-powered code explainer and semantic diff tool
License: MIT
Requires Python: >=3.10

# Alethe

Alethe is an AI-powered code explainer and semantic diff tool. It generates human-readable markdown explanations for Python files and compares different versions to highlight semantic changes.

## Features

- Generate markdown explanations of Python code.
- Track file versions and compute semantic diffs between explanations.
- Works with local Hugging Face models or a stub mode for offline testing.
- CLI interface for easy usage.

## Installation

You can install Alethe from PyPI:

```bash
pip install alethe
```

## Usage

Basic CLI usage:

```bash
alethe explain path/to/file.py
alethe summary path/to/file.py
alethe diff path/to/file.py v1 v2
alethe list path/to/file.py
alethe rename old_file.py new_file.py
alethe getpath <file_id>
```

### Example

Generate an explanation for **example.py**:

```bash
alethe explain example.py
```