semvec/pypi-packages huggingface dataset:
chuk-mcp-virtual-fs 0.1.0
MCP Virtual Filesystem
Requires Python: >=3.11

# chuk-mcp-virtual-fs

MCP (Mission Control Platform) server for the Virtual FileSystem. This package provides a set of tools for managing files and directories in a virtual filesystem through the MCP framework.

## Features

- File and directory operations (create, read, write, delete, copy, move)
- Directory listing and file searching
- Filesystem snapshot management (create, restore, export, import)
- Storage statistics
- Support for different storage backends through Virtual FileSystem (local, S3, etc.)

## Installation

```bash
pip install chuk-mcp-virtual-fs
```

## Configuration

Create a `config.yaml` file with the following settings:

```yaml
host:
  name: "chuk-mcp-virtual-fs"
  log_level: "INFO"

server:
  type: "stdio"  # or "websocket" for network-based communication

mcp_servers:
  virtual_fs:
    enabled: true
    location: "."
    tools:
      enabled: true
      module: "chuk_mcp_virtual_fs.tools"
```

## Environment Variables

The following environment variables can be set to configure the virtual filesystem:

### For S3 Provider
- `VIRTUAL_FS_PROVIDER`: Set to "s3" to use S3 storage (default if not specified)
- `S3_BUCKET_NAME`: Name of the S3 bucket to use
- `S3_PREFIX`: Prefix for all files within the bucket
- `AWS_ENDPOINT_URL_S3`: Custom endpoint URL for S3-compatible storage
- `AWS_REGION`: AWS region to use

### For Local Provider
- `VIRTUAL_FS_PROVIDER`: Set to "local" to use local filesystem
- `LOCAL_FS_ROOT`: Root directory for the local filesystem

### For Memory Provider
- `VIRTUAL_FS_PROVIDER`: Set to "memory" to use in-memory filesystem
- `MEMORY_FS_ID`: Optional identifier for the memory filesystem (defaults to "default")

## Usage

Start the MCP server:

```bash
mcp-virtual-fs
```

Then use the MCP client to interact with the virtual filesystem tools.

## Available Tools

- `list_directory`: List contents of a directory
- `read_file`: Read file content
- `write_file`: Write content to a file
- `mkdir`: Create a directory
- `delete`: Delete a file or directory
- `copy`: Copy a file or directory
- `move`: Move a file or directory
- `find`: Find files matching a pattern
- `get_storage_stats`: Get storage statistics
- `create_snapshot`: Create a filesystem snapshot
- `restore_snapshot`: Restore from a filesystem snapshot
- `list_snapshots`: List available snapshots
- `export_snapshot`: Export a snapshot to a file
- `import_snapshot`: Import a snapshot from a file

## Development

### Prerequisites

- Python 3.11 or higher
- Required packages: boto3, pydantic, chuk-mcp-runtime, mcp, chuk-virtual-fs

### Setup Development Environment

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

## License

[MIT](LICENSE)
sr.comp.cli 1.12.0
Command line tools for interacting with the state of the Student Robotics Competition
Requires Python: >=3.8

SRComp CLI
==========

|Build Status| |Docs Status|

A set of command-line tools for operating SRComp at a competition and for
working with compstate repositories.

Usage
-----

**Install**:

.. code:: shell

    pip install -U pip setuptools wheel
    pip install sr.comp.cli

Bash completions are also available, see the ``bash-completion`` file in the
root of the repo.

Development
-----------

**Install**:

.. code:: shell

    pip install -e . -r dev-requirements.txt


**Test**:
``./run-tests``


.. |Build Status| image:: https://circleci.com/gh/PeterJCLaw/srcomp-cli.svg?style=svg
   :target: https://circleci.com/gh/PeterJCLaw/srcomp-cli

.. |Docs Status| image:: https://readthedocs.org/projects/srcomp-cli/badge/?version=latest
   :target: https://srcomp-cli.readthedocs.org/
salesforce-agentforce 0.1.9
A Python SDK for interacting with the Agentforce Agents
Requires Python: >=3.7

# Agentforce SDK
        
        A Python SDK for interacting with the Agentforce API.
        
        ## Connected app
        You must create a Connected App for your Agentforce Agent(s) to use it with this SDK. Here are the instructions: https://developer.salesforce.com/docs/einstein/genai/guide/agent-api-get-started.html
        
        
        ## Installation
        
        ```bash
        pip install salesforce-agentforce
        ```
        
        ## Usage
        
        ```python
        from agentforce.agents import Agentforce
        
        # Initialize the client
        agentforce = Agentforce()
        
        # Authenticate
        agentforce.authenticate(
            salesforce_org="your-salesforce-org",
            client_id="your-client-id",
            client_secret="your-client-secret"
        )
        
        # Start a session
        session = agentforce.start_session(agent_id="your-agent-id")
        
        # Send a message
        agentforce.add_message_text("Hello, how can you help me?")
        response = agentforce.send_message(session_id=session.sessionId)
        
        # End the session
        end_response = agentforce.end_session(session_id=session.sessionId)
        ```
        
        ## Features
        
        - Authentication with Salesforce
        - Session management (start/end)
        - Message sending (text and reply)
        - Type-safe response objects
        
        ## License
        
        MIT
fundamentus-scraper 0.1.0
Web Scraper para dados do Fundamentus
Requires Python: >=3.6

# Fundamentus Scraper

Pacote Python para coleta de dados do site Fundamentus.com.br

## Instalação

```bash
pip install fundamentus-scraper
```

## Uso Básico

```python
from fundamentus_scraper import FundamentusScraper

scraper = FundamentusScraper()

# Obter todos os dados
dados = scraper.get_company_data("PETR4")

# Obter um dado específico
p_l = scraper.get_single_data("PETR4", "p_l")

# Exportar para Excel
scraper.export_to_excel("PETR4", "petr4.xlsx")
```

## Campos Disponíveis

Consulte o mapeamento completo de campos em `FIELD_MAPPING`

## Licença

MIT
plixel 0.0.1
A python package for data analysis and visualization
Requires Python: >=3.10

# A simple Automation tool for data analysis
![Python Tests](https://github.com/XChaitanyaX/plixel/actions/workflows/python-package.yml/badge.svg)

- Still in development stage
- Should help in analysing certain data-sheets, generating reports, graphs, etc.
- Main focus is on plotting graphs.
- More features will be added in future.
- This is a simple package, not a full fledged software.

# How to contribute
- Fork the repository
- Clone the repository
- Create a new branch
- Make changes
- Push changes to your fork
- Create a pull request, make sure to give a proper description of changes made by you.
- check [contributing.md](contributing.md) for more details
mcp_lightpdf 0.1.30
LightPDF AI助手 MCP Server
Requires Python: >=3.12

# MCP_LightPDF

MCP_LightPDF 是一个基于 MCP (Model Control Protocol) 的文档格式转换工具，支持多种文档格式之间的相互转换。该工具需要在支持 MCP 功能的软件（如 Cursor）中配置使用。

## 配置说明

在 Cursor 中配置 MCP_LightPDF 工具需要修改 `~/.cursor/mcp.json` 文件。添加以下配置：

```json
{
  "mcpServers": {
    "lightpdf": {
      "command": "uvx",
      "args": [
        "mcp_lightpdf@latest"
      ],
      "env": {
        "API_KEY": "your_api_key_here"
      }
    }
  }
}
```

配置说明：
- `command`: 使用 `uvx` 命令运行工具
- `args`: 命令行参数
  - `-n`: 直接运行wheel包
  - wheel包路径：指向下载的 MCP_LightPDF wheel 包
- `env`: 环境变量配置
  - `API_KEY`: 你的API密钥

配置完成后，重启 Cursor 使配置生效。

## 功能特性

- 支持多种文档格式的转换
- 支持本地文件和网络URL
- 支持批量转换
- 并发处理，提高转换效率
- 详细的转换进度和结果报告
- 灵活的输出目录配置
- PDF水印去除功能

## 支持的格式

### PDF转换为其他格式
- Word (DOCX)
- Excel (XLSX)
- PowerPoint (PPTX)
- 图片 (JPG, JPEG, PNG, BMP, GIF)
- HTML
- 文本 (TXT)

### 其他格式转换为PDF
- Word (DOCX)
- Excel (XLSX)
- PowerPoint (PPTX)
- 图片 (JPG, JPEG, PNG, BMP, GIF)
- CAD (DWG)
- CAJ
- OFD

### PDF水印去除
- 支持去除PDF文档中的水印
- 保持原始文档质量和格式
- 支持批量处理多个PDF文件
- 输出格式为PDF文档

## 使用方法

1. 确保你使用的软件支持 MCP 功能（如 Cursor）
2. 在软件中完成 MCP_LightPDF 工具的配置
3. 调用工具时，指定：
   - 输入文件路径或URL
   - 目标转换格式
   - 输出目录（可选）

### 格式转换
使用 `convert_document` 工具，指定输入文件和目标格式。

### 去除水印
使用 `remove_watermark` 工具，指定需要处理的PDF文件路径。工具会自动使用特殊的`doc-repair`格式处理文件，并输出为无水印的PDF文档。

## 参数说明

### 格式转换工具
- `file_paths`: 要转换的文件路径或URL列表
- `format`: 目标格式，支持：
  - `pdf`: 转换为PDF格式
  - `docx`: 转换为Word格式
  - `xlsx`: 转换为Excel格式
  - `pptx`: 转换为PowerPoint格式
  - `jpg`/`jpeg`: 转换为JPG格式
  - `png`: 转换为PNG格式
  - `bmp`: 转换为BMP格式
  - `gif`: 转换为GIF格式
  - `html`: 转换为HTML格式
  - `txt`: 转换为文本格式

### 去除水印工具
- `file_paths`: 要处理的PDF文件路径或URL列表

## 注意事项

1. 确保有足够的磁盘空间用于文件转换
2. 对于网络URL，确保URL可访问且文件大小在合理范围内
3. 批量转换时会自动控制并发数，避免过度占用系统资源
4. 某些格式转换可能需要较长时间，请耐心等待
5. 水印去除功能仅适用于PDF格式文件
6. 复杂水印可能无法完全去除，效果取决于水印类型

## 错误处理

工具会提供详细的错误信息，常见的错误包括：

- API密钥未配置或无效
- 文件格式不支持
- 文件不存在或无法访问
- 网络连接问题
- 输出目录无写入权限

## 许可证

MIT License
libvcell 0.0.13
This is a python package which wraps a subset of VCell Java code as a native python package.
Requires Python: <4.0,>=3.11

# libvcell

[![Release](https://img.shields.io/github/v/release/virtualcell/libvcell)](https://img.shields.io/github/v/release/virtualcell/libvcell)
[![Build status](https://img.shields.io/github/actions/workflow/status/virtualcell/libvcell/main.yml?branch=main)](https://github.com/virtualcell/libvcell/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/virtualcell/libvcell/branch/main/graph/badge.svg)](https://codecov.io/gh/virtualcell/libvcell)
[![Commit activity](https://img.shields.io/github/commit-activity/m/virtualcell/libvcell)](https://img.shields.io/github/commit-activity/m/virtualcell/libvcell)
[![License](https://img.shields.io/github/license/virtualcell/libvcell)](https://img.shields.io/github/license/virtualcell/libvcell)

libvcell is a subset of VCell algorithms intended to support the [pyvcell](https://pypi.org/project/pyvcell/) python package.

- **Github repository**: <https://github.com/virtualcell/libvcell/>
- **Documentation** <https://virtualcell.github.io/libvcell/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

```bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:virtualcell/libvcell.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with

```bash
make install
```

You are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPI or Artifactory, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/codecov/).

## Releasing a new version

- Create an API Token on [PyPI](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting [this page](https://github.com/virtualcell/libvcell/settings/secrets/actions/new).
- Create a [new release](https://github.com/virtualcell/libvcell/releases/new) on Github.
- Create a new tag in the form `*.*.*`.
- For more details, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-poetry](https://github.com/fpgmaas/cookiecutter-poetry).
cdn-dl 2.4
通过cdn 下载文件
Requires Python: >=3.8
Keywords: cdn-dl, cdn 文件下载器

# CDN 下载器

一键下载文件by cdn

## cdn-dl

help:

```shell
cdn-dl -h
usage: cdn-dl [-h] -u URL -o OUT [-ua USE_AGENT] [-ts TRUNK_SIZE] [-t TIMEOUT] [-r RETRY] [-d] cdn [cdn ...]

cdn-dl 下载配置

positional arguments:
  cdn                   cdn configs配置,支持ip| ip:port |ip:port:host 字串或文本或host文件

optional arguments:
  -h, --help            show this help message and exit
  -u URL, --url URL     文件下载url
  -o OUT, --out OUT     文件下载路径
  -ua USE_AGENT, --use_agent USE_AGENT
                        是否使用user agent
  -ts TRUNK_SIZE, --trunk_size TRUNK_SIZE
                        下载使用的trunk size, 默认8192
  -t TIMEOUT, --timeout TIMEOUT
                        下载请求超时时间, 默认10s
  -r RETRY, --retry RETRY
                        下载请求重试次数, 默认3
  -d, --debug           是否打印调试信息
```

eg:

```shell
cdn-dl -u https://download.docker.com/linux/static/stable/x86_64/docker-27.2.1.tgz -o test.tgz docker.hosts
```

## cdn-get

help:

```shell
cdn-get -h
usage: cdn-get [-h] [-o OUT] [-c CDN [CDN ...]] [-T THREAD] [-t TIMEOUT] [-r RETRY] [--api API] [-d] domain [domain ...]

cdn-get 配置

positional arguments:
  domain                需要获取cdn的域名或者文本

optional arguments:
  -h, --help            show this help message and exit
  -o OUT, --out OUT     输出hosts 文件路径
  -c CDN [CDN ...], --cdn CDN [CDN ...]
                        cdn configs配置,支持ip| ip:port |ip:port:host 字串或文本或host文件
  -T THREAD, --thread THREAD
                        多线程数量
  -t TIMEOUT, --timeout TIMEOUT
                        下载请求超时时间, 默认10s
  -r RETRY, --retry RETRY
                        下载请求重试次数, 默认3
  --api API             dns api, 默认ali, 使用CF 使用cf dns
  -d, --debug           是否打印调试信息
```

eg:

```shell
cdn-get download.docker.com -o docker.hosts
```