semvec/pypi-packages huggingface dataset:
agent-arcade 1.1.3
Play fun arcade games while waiting on AI agent tasks
License: MIT
Requires Python: <4.0,>=3.9
Keywords: ai, games, terminal, productivity, tmux, textual

# Agent Arcade

**Play fun arcade games while waiting on AI agent tasks.**

Stop context-switching to your phone or social media while waiting for Claude Code or Codex to finish. Stay in the terminal, stay productive!

## Installation

### macOS

```bash
brew install tmux pipx
pipx install agent-arcade
```

### Linux

```bash
# Ubuntu/Debian
sudo apt-get install tmux
pipx install agent-arcade

# RedHat/CentOS
sudo yum install tmux
pipx install agent-arcade
```

### Windows (WSL)

```bash
# Install WSL first: wsl --install
# Then in your WSL terminal:
sudo apt-get install tmux
pipx install agent-arcade
```

## Quick Start

1. Launch Agent Arcade in your project directory:
   ```bash
   agent-arcade
   ```

2. Select your AI agent

3. Switch between agent/game view:
   - `Ctrl+Space`

4. Give your agent tasks and then play games while you wait!

## Supported AI Agents

- Claude Code
- Cursor

Want to add more agents? Submit a PR.

## Games

### Snake

Classic Snake game. Eat food, grow longer, avoid walls and yourself!

### In progress games

More games are coming soon. I'm currently working on:

- 2048
- Minesweeper
- Pong
- Sudoku

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Credits

- Built with [Textual](https://textual.textualize.io/) - Modern Python TUI framework
- Powered by [tmux](https://github.com/tmux/tmux) - Terminal multiplexer

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

### Development Setup

```bash
# Install Poetry
curl -sSL https://install.python-poetry.org | python3 -

# Clone and setup
git clone https://github.com/anthonygore/agent-arcade
cd agent-arcade
poetry install

# Run in dev mode (uses ~/.agent-arcade-dev for data)
poetry run agent-arcade
```

## Support

- **Issues**: [GitHub Issues](https://github.com/anthonygore/agent-arcade/issues)
- **Discussions**: [GitHub Discussions](https://github.com/anthonygore/agent-arcade/discussions)
solveclosure 0.1.0
A package that solves the closure problem for the dual-continuum model published by Paten et al.
License: MIT
Requires Python: >=3.8

# solveclosure

Solves the closure problem for the dual-continuum model published by Paten et. al. See the following two articles for more information: 

https://doi.org/10.1149/1945-7111/ae335f
https://doi.org/10.1149/1945-7111/ae3527

## 🚀 Installing solveclosure

solveclosure is available on GNU/Linux.
It is recommended to install solveclosure into a virtual environement. 

### Using pip

```bash
pip install solveclosure
```


## 💻 Using solveclosure

The simplest form of script to run solveclosure: 

```python
import solveclosure

img_path = "electrode_image.tif" # the path to your electrode image, electrolyte labelled as 0, active material 1, and CBD 2. 
label_map_path = "label_map.tif" # to path to a label map of active material particles (beginning at 1).

case_dir = "case_dir/" # am empty directory where OpenFOAM cases will be built. 

load_of_cmd = "source /usr/lib/openfoam/openfoam2412/etc/bashrc" # the command specific for your system to load an OpenFOAM terminal.

voxel = 1e-7 # the electrode image voxel size in meters.

cbd_surface_porosity = 1.0 # the surface porosity of CBD. Set to 1 if CBD is not present. 

D_s = 4e-14 # the diffusivity of active material in m2.s-1.


solveclosure.solve_closure_multiparticle(case_dir, img_path, label_map_path, load_of_cmd, voxel, cbd_surface_porosity, D_s)

```