semvec/pypi-packages huggingface dataset:
safe-ds 0.31.0
A user-friendly library for Data Science in Python.
License: MIT
Requires Python: <3.14,>=3.12
Keywords: data-science, machine-learning, usability, learnability

# Safe-DS Python Library

[![PyPI](https://img.shields.io/pypi/v/safe-ds)](https://pypi.org/project/safe-ds)
[![Main](https://github.com/Safe-DS/Library/actions/workflows/main.yml/badge.svg)](https://github.com/Safe-DS/Library/actions/workflows/main.yml)
[![codecov](https://codecov.io/gh/Safe-DS/Library/branch/main/graph/badge.svg?token=HVRP1633B1)](https://codecov.io/gh/Safe-DS/Library)
[![Documentation Status](https://readthedocs.org/projects/safe-ds-stdlib/badge/?version=stable)](https://library.safeds.com)

A user-friendly library for Data Science (DS) in Python.

Our goal is to make DS more accessible to a wider audience by providing a simple, intuitive, and consistent API to solve
common tasks on small to moderately sized datasets. As such, a major focus is to provide a learning tool for DS novices.

Instead of implementing DS methods from scratch, we use established DS libraries under the hood such as:

* [polars](https://docs.pola.rs/) for manipulation of tabular data,
* [scikit-learn](https://scikit-learn.org) for classical machine learning,
* [torch](https://pytorch.org) for deep learning, and
* [matplotlib](https://matplotlib.org/) for visualization.

For more specialized tasks, we recommend using these or other DS libraries directly.

Note that this library is still in development and not yet ready for production. Expect breaking changes in the future
without a major version bump (while in the `0.y.z` version range). Feedback is very welcome, however! If you have a
suggestion or find a bug, please [open an issue](https://github.com/Safe-DS/Library/issues/new/choose). If you have a
question, please [use our discussion forum][forum].

## Installation

Get the latest version from [PyPI](https://pypi.org/project/safe-ds):

```shell
pip install safe-ds
```

On a Windows PC with an NVIDIA graphics card, you may also want to install the CUDA versions of `torch` and
`torchvision`:

```shell
pip install --upgrade torch torchvision --index-url https://download.pytorch.org/whl/cu128
```

## Documentation

You can find the full documentation [here](https://library.safeds.com).

## Contributing

We welcome contributions from everyone. As a starting point, check the following resources:

* [Setting up a development environment](https://library.safeds.com/en/latest/development/environment/)
* [Project guidelines](https://library.safeds.com/en/latest/development/guidelines/design/)
* [Contributing page](https://github.com/Safe-DS/Library/contribute)

If you need further help, please [use our discussion forum][forum].

[forum]: https://github.com/orgs/Safe-DS/discussions
modular-mcp 0.3.0
A modular companion package for the Model Context Protocol SDK, designed to extend functionality with a clean and decoupled architecture.
License: MIT
Requires Python: >=3.13
Keywords: automation, git, llm, mcp, modular

# Modular MCP (Model Context Protocol Companion)

**Modular MCP** is a standalone Python package designed to extend and organize MCP servers in a clean and scalable way. It is **not a fork**, but a **modular companion** to the [Model Context Protocol SDK](https://github.com/modelcontextprotocol/python-sdk), developed and maintained by **Damyan Dimitrov** ([GitHub](https://github.com/DamyanBG)).

---

## ✨ Purpose

The purpose of this package is to enable **modular development of MCP servers** by introducing a `Bundle` system, similar in spirit to FastAPI's `APIRouter`. It provides:

- Clean separation of tools, resources, and prompts  
- Easy composition of multiple components  
- Scalable, maintainable codebases for MCP servers  

This package works **independently**, but when used together with the `mcp` SDK, it unlocks powerful features like `ModularFastMCP`.

---

## 📦 Installation

To install `modular-mcp`:

```bash
uv add modular-mcp
```

To use it with the official `mcp` SDK (as an optional dependency):

```bash
uv add "modular-mcp[mcp]"
```

---

## 🛠 Usage

Example of running a server using `uv`:

```bash
uv venv
uv add -e .[mcp]
uv run mcp
```

You can define and include multiple bundles to organize your project by domain or feature set.

---

## 📚 Learn More

For background on the MCP SDK and ecosystem:

👉 [Model Context Protocol Python SDK](https://github.com/modelcontextprotocol/python-sdk)

---

## 📝 License

MIT License — same as the original MCP SDK.