semvec/pypi-packages huggingface dataset:
mcp-server-coding 0.1.1
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Requires Python: >=3.13

# Coding平台MCP服务

这是一个用于Coding平台的MCP（Model Context Protocol）服务，提供需求查询功能。

## 功能特性

- ✅ 查询Coding平台需求列表
- ✅ 支持多项目查询
- ✅ 可配置的分页和排序
- ✅ 环境变量配置

## 安装依赖

```bash
pip install -e .
```

## 环境变量配置

### 方法1：临时设置（当前终端会话）
```bash
# 设置必需的API访问令牌
export CODING_API_TOKEN="6ba7fa74ec2af91139e56a84960068b5c984b20a"

# 设置可选配置
export CODING_DEFAULT_PROJECT="gypaas"
export CODING_DEFAULT_LIMIT="10"

# 验证设置
echo "API Token: $CODING_API_TOKEN"
```

### 方法2：永久设置（推荐）
将环境变量添加到shell配置文件中（~/.bashrc, ~/.zshrc, 或 ~/.profile）：

```bash
# 编辑配置文件
nano ~/.zshrc

# 添加以下内容
export CODING_API_TOKEN="your_actual_coding_api_token"
export CODING_DEFAULT_PROJECT="your_project_name"
export CODING_DEFAULT_LIMIT="10"
export CODING_API_BASE_URL="https://it.devops.sinochem.com/open-api/"

# 重新加载配置
source ~/.zshrc
```

### 方法3：使用.env文件（推荐）
服务已配置为自动加载`.env`文件中的环境变量：

```bash
# 1. 安装python-dotenv（如果尚未安装）
pip install python-dotenv

# 2. 复制示例文件
cp .env.example .env

# 3. 编辑.env文件，填写实际值
nano .env

# 4. 启动服务（自动加载.env配置）
python main.py
```

**优势**：
- ✅ 配置与代码分离，更安全
- ✅ 无需手动设置环境变量
- ✅ 支持版本控制（可将.env.example提交到版本库）
- ✅ 多环境支持（开发、测试、生产使用不同的.env文件）

**.env文件示例**：
```bash
# 必需配置
CODING_API_TOKEN=your_actual_coding_api_token

# 可选配置  
CODING_DEFAULT_PROJECT=your_project_name
CODING_DEFAULT_LIMIT=10
```

### 方法4：脚本设置
使用提供的设置脚本：

```bash
# 修改setup_test_env.sh中的token值
nano setup_test_env.sh

# 运行设置脚本
source setup_test_env.sh

# 验证环境变量
env | grep CODING
```

### 环境变量说明

| 变量名 | 必需 | 默认值 | 说明 |
|--------|------|--------|------|
| `CODING_API_TOKEN` | ✅ | 无 | Coding平台API访问令牌 |
| `CODING_API_BASE_URL` | ❌ | `https://it.devops.sinochem.com/open-api/` | API基础URL |
| `CODING_DEFAULT_PROJECT` | ❌ | `gypaas` | 默认项目名称 |
| `CODING_DEFAULT_LIMIT` | ❌ | `10` | 默认查询条数 |
| `CODING_ISSUE_TYPE` | ❌ | `ALL` | 需求类型（ALL/REQUIREMENT/BUG/TASK） |
| `CODING_OFFSET` | ❌ | `0` | 分页偏移量 |
| `CODING_SORT_KEY` | ❌ | `CODE` | 排序字段 |
| `CODING_SORT_VALUE` | ❌ | `DESC` | 排序方式 |

## 使用方法

### 作为MCP服务器运行

```bash
python main.py
```

### 通过MCP客户端连接

配置你的MCP客户端（如Claude、Cursor等）连接到这个服务：

```json
{
  "mcpServers": {
    "coding-service": {
      "command": "python",
      "args": ["/path/to/main.py"]
    }
  }
}
```

## API说明

### get_requirements工具

查询Coding平台的需求列表：

- **参数**:
  - `project_name`: 项目名称（可选，默认为环境变量配置）
  - `limit`: 查询条数限制（可选，默认为环境变量配置）

- **返回**: 包含需求列表的JSON响应

## 开发说明

项目使用Python 3.13+，主要依赖：
- `mcp[cli]`: MCP协议实现
- `requests`: HTTP请求库

## 故障排除

1. **API令牌错误**: 确保`CODING_API_TOKEN`环境变量已正确设置
2. **网络连接问题**: 检查是否能访问Coding平台API
3. **权限问题**: 确认API令牌有足够的权限访问需求数据
pybotchi-files 0.2.1
PyBotchi implementation for manipulating file/s
Requires Python: <4.0,>=3.13.0

# PyBotchi Files

Dedicated agents for file/s content extraction and manipulation.

## Feel free to override/extend it's functionality to cater your requirements.

# Example Usage

- [FastAPI](https://github.com/amadolid/pybotchi/blob/master/agents/pybotchi-files/example_usage.py)
  - > uvicorn example_usage:app
configaroo 0.6.1
Bouncy handling of configuration files
Requires Python: >=3.11
Keywords: configuration, configuration-management, toml, json

# Configaroo - Bouncy Configuration Handling

[![Latest version](https://img.shields.io/pypi/v/configaroo.svg)](https://pypi.org/project/configaroo/)
[![Python versions](https://img.shields.io/pypi/pyversions/configaroo.svg)](https://pypi.org/project/configaroo/)
[![License](https://img.shields.io/pypi/l/configaroo.svg)](https://github.com/gahjelle/configaroo/blob/main/LICENSE)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Linted with Ruff](https://github.com/gahjelle/configaroo/actions/workflows/lint.yml/badge.svg?branch=main)](https://github.com/gahjelle/configaroo/actions/workflows/lint.yml)
[![Tested with Pytest](https://github.com/gahjelle/configaroo/actions/workflows/test.yml/badge.svg?branch=main)](https://github.com/gahjelle/configaroo/actions/workflows/test.yml)
[![Type checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)

Configaroo is a light configuration package for Python that offers the following features:

- Access configuration settings with dotted keys: `config.nested.key`
- Use different configuration file formats, including TOML and JSON
- Override key configuration settings with environment variables
- Validate a configuration based on a Pydantic model
- Convert the type of configuration values based on a Pydantic model
- Dynamically format certain configuration values
tollingvision-scsinfo 2.6.2
Python client for Tolling Vision
Requires Python: >=3.6

# Python Tolling Vision client

Python client for [Tolling Vision](https://tollingvision.com/).

## 📋 Introduction

The Tolling Vision client provides a seamless way to interact with the Tolling Vision Dockerized service, allowing tolling operators or image review companies to process and review images efficiently. This client supports features like license plate, make and model, and dangerous goods recognition.

## 💻 Prerequisites

Before installing, ensure you have the following prerequisites:

Python (>=3.6)

## 💁 How to Install

To install the Tolling Vision client along with the necessary dependencies, including **`grpcio-tools`**, run the following command:

```sh
pip install grpcio-tools tollingvision-scsinfo
```

If you need to upgrade to the latest version of the Tolling Vision client, you can do so by adding the **`--upgrade`** flag to the installation command:

```sh
pip install --upgrade tollingvision-scsinfo
```

## 📖 Usage

To see a working example of how to use this package, please refer to the sample project available on GitHub: [Python Example Program for Tolling Vision
](https://github.com/tollingvision/tollingvision-python-sample).

You can clone the repository and follow the instructions provided in the README file of the sample project to get started.
finder-enrichment-db-client 0.1.10
Client for the Finder Enrichment DB API
Requires Python: >=3.12

# Finder Enrichment DB Client

This package provides a Python client for interacting with the Finder Enrichment DB API.

## Features

- Complete API client for all endpoints
- Type-safe with Pydantic models
- Automatic authentication handling
- Comprehensive error handling
- Support for all enrichment operations

## Installation

```bash
pip install finder-enrichment-db-client
```

## Usage

```python
from finder_enrichment_db_client import FinderEnrichmentDBAPIClient

# Initialize client
client = FinderEnrichmentDBAPIClient(
    base_url="http://localhost:8200",
    api_key="your-api-key"
)

# Get listings
listings = client.get_listings()

# Create a new listing
# ... (see API documentation for full examples)
```

## Dependencies

- pydantic
- httpx
- finder-enrichment-db-contracts
flowcean 0.7.0b2
Automatic generation of models for cyber-physical systems.
Requires Python: <4.0,>=3.10

# Flowcean

[![Actions status](https://github.com/flowcean/flowcean/actions/workflows/ci.yml/badge.svg)](https://github.com/flowcean/flowcean/actions)
[![docs status](https://github.com/flowcean/flowcean/actions/workflows/pages.yml/badge.svg)](https://flowcean.me)
[![PyPI - Version](https://img.shields.io/pypi/v/flowcean)](https://pypi.python.org/pypi/flowcean)
[![License](https://img.shields.io/github/license/flowcean/flowcean)](https://github.com/flowcean/flowcean/blob/main/LICENSE)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/flowcean)](https://pypi.python.org/pypi/flowcean)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Pyright](https://img.shields.io/badge/types-Pyright-blue.svg)](https://github.com/microsoft/pyright)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

An advanced, versatile framework to streamline the automatic generation of models for cyber-physical systems.

## Highlights

- 🚀 automates the creation of models tailored to cyber-physical systems.
- 🧠 abstracts over learning frameworks
- ✔️ models for offline, incrementally, or active learning.
- 🗃️ integrates custom data sources.
- 🔍 evaluate models with standard metrics.
- 🐍 written in Python, easy connection via a gRPC interface

## Documentation

flowcean's documentation is available at [flowcean.me](https://flowcean.me).

## Contributing

We strive for open-source contributions that drive research forward and would love to see you get involved. See our [code of conduct](https://github.com/flowcean/flowcean/blob/main/CODE_OF_CONDUCT.md) to get started.

## License

flowcean is licensed under the 3-Clause BSD License ([LICENSE](https://github.com/flowcean/flowcean/blob/main/LICENSE) or [https://opensource.org/license/bsd-3-clause](https://opensource.org/license/bsd-3-clause)).