semvec/pypi-packages huggingface dataset:
actuator 0.3.6
Python interface for controlling various robotic actuators
Requires Python: >=3.11

# actuator

Defines a package to make it easy and performant to control actuators.

> [!WARNING]
> The Python bindings for this package are currently in an experimental state and may be unstable or subject to breaking changes.

![System Architecture](./docs/architecture.png)

## Getting Started

See the documentation [here](https://docs.kscale.dev/docs/actuator-package) for instructions on getting started with this package.

## Build Requirements

### Linux
This package requires Linux for building due to dependencies on Linux-specific CAN bus libraries.

If you're developing on other platforms, consider using a Linux virtual machine or container for building.
mu-pipelines-configuration-provider 0.2.0a0
mu_pipelines_configuration_provider
Requires Python: >=3.12
Keywords: data movement, spark, etl

# mu_pipelines_configuration_provider

## Features


## Tools

### (Lint)
```
pipenv run flake8
pipenv run mypy
pipenv run black .
pipenv run isort .

```

### (Unit Tests)
```
pipenv run pytest --cov --cov-fail-under=80
```

### Pre-Commit Hooks

#### Install the hook
```
pipenv run pre-commit install
```
ray-tpu 0.0.5
An utility for running Ray with Cloud TPUs
Requires Python: >=3.8

# Ray TPU

This is a repository containing utilities for running [Ray](https://www.ray.io/)
on Cloud TPUs. For more information about TPUs, please check out the official
Google Cloud documentation [here](https://cloud.google.com/tpu).

## Why this package?

TPUs are different from other accelerators like GPUs because they are
"pod-centric". Scheduling jobs and workloads on TPUs require awareness of slice
topologies and other factors. This package introduces higher level utilities
that simplify running Ray workloads on TPU pod slices as if they were single
nodes.

## Installation

Run the following command to install the package:
```
pip install ray-tpu
```

Check out the [tutorials section](https://github.com/AI-Hypercomputer/ray-tpu/tree/main/tutorials/) for more details.
organizze-mcp 0.1.12
Add your description here
Requires Python: >=3.11

# Organizze MCP

A Python-based integration for Organizze financial management platform using FastMCP.

## Description

This project provides a Multi-Call Protocol (MCP) server for the Organizze financial management platform, allowing operations like viewing transactions and managing categories.

## Features

- List transactions within a date range
- List available categories
- Set categories for transactions

## Installation

This project uses Poetry for dependency management.

```bash
# Clone the repository
git clone https://github.com/yourusername/organizze-mcp.git
cd organizze-mcp

# Install dependencies
poetry install
```

## Configuration

Create a `.env` file in the root directory with the following variables:

```
ORGANIZZE_EMAIL=your_organizze_email
ORGANIZZE_TOKEN=your_organizze_api_token
```

You can obtain your API token from your Organizze account settings.

## Usage

Run the MCP server:

```bash
poetry run python src/organizze-mcp/main.py
```

## Requirements

- Python 3.12+
- fastmcp 2.3.3+
- requests 2.32.3+

## License

[Add your license here]

## Author

Diego (dccarbone@gmail.com)