semvec/pypi-packages huggingface dataset:
stable-worldmodel 0.0.4
World Model Research Made Simple
Requires Python: >=3.10

[![Documentation](https://img.shields.io/badge/Docs-blue.svg)](https://galilai-group.github.io/stable-worldmodel/)
![Tests](https://img.shields.io/github/actions/workflow/status/galilai-group/stable-worldmodel/tests.yaml?label=Tests)
[![PyPI](https://img.shields.io/pypi/v/stable-worldmodel.svg)](https://pypi.python.org/pypi/stable-worldmodel/#history)
[![PyTorch](https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white)](https://pytorch.org/get-started/locally/)
[![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)

# stable-worldmodel

World model research made simple. From data collection to training and evaluation.

```bash
pip install stable-worldmodel
```

> **Note:** The library is still in active development.

See the full documentation at [here](https://galilai-group.github.io/stable-worldmodel/).


## Quick Example

```python
import stable_worldmodel as swm
from stable_worldmodel.data import HDF5Dataset
from stable_worldmodel.policy import WorldModelPolicy, PlanConfig
from stable_worldmodel.solver import CEMSolver

# collect a dataset
world = swm.World('swm/PushT-v1', num_envs=8)
world.set_policy(your_expert_policy)
world.record_dataset(dataset_name='pusht_demo', episodes=100)

# load dataset and train your world model
dataset = HDF5Dataset(name='pusht_demo', num_steps=16)
world_model = ...  # your world-model

# evaluate with model predictive control
solver = CEMSolver(model=world_model, num_samples=300)
policy = WorldModelPolicy(solver=solver, config=PlanConfig(horizon=10))

world.set_policy(policy)
results = world.evaluate(episodes=50)
print(f"Success Rate: {results['success_rate']:.1f}%")
```

## Supported Environments

<p align="center">
  <img src="docs/assets/envs_grid_1.gif" alt="Environments Grid 1">
  <br>
  <img src="docs/assets/envs_grid_2.gif" alt="Environments Grid 2">
</p>

## Contributing

Setup your codebase:

```bash
uv venv --python=3.10
source .venv/bin/activate
uv sync --all-extras --group dev
```

## Questions

If you have a question, please [file an issue](https://github.com/galilai-group/stable-worldmodel/issues).


## Citation

```bibtex
@misc{maes_lelidec2026swm-1,
      title={stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation}, 
      author = {Lucas Maes and Quentin Le Lidec and Dan Haramati and
                Nassim Massaudi and Damien Scieur and Yann LeCun and
                Randall Balestriero},
      year={2026},
      eprint={2602.08968},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2602.08968}, 
}
```
coherent.build 0.36.1
A zero-config Python project build backend
Requires Python: >=3.10

[![](https://img.shields.io/pypi/v/coherent.build)](https://pypi.org/project/coherent.build)

![](https://img.shields.io/pypi/pyversions/coherent.build)

[![](https://github.com/coherent-oss/coherent.build/actions/workflows/main.yml/badge.svg)](https://github.com/coherent-oss/coherent.build/actions?query=workflow%3A%22tests%22)

[![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)

[![Coherent Software Development System](https://img.shields.io/badge/coherent%20system-informational)](https://github.com/coherent-oss/system)

A PEP 517 backend for the [Coherent Software Development System](https://github.com/coherent-oss/system/blob/main/README.md).

Put your source in a repo and then build it with:

```
python -m coherent.build
```
crisscross-kit 1.2.3
Unified CAD and scripting packages for megastructure design, handle library generation and visualization.
Requires Python: >=3.10

# Crisscross Kit Python Library

[![PyPI version](https://img.shields.io/pypi/v/crisscross_kit.svg)](https://pypi.org/project/crisscross_kit/)
[![Documentation](https://img.shields.io/badge/docs-Read%20the%20Docs-blue)](https://hash-cad.readthedocs.io/python-api/)

Python library for DNA megastructure design, complementing the #-CAD desktop application. Provides programmatic access to design manipulation, handle evolution, and Echo Liquid Handler export.

## Installation

```bash
pip install crisscross_kit
```

Optional dependencies for 3D graphics and Blender:
```bash
pip install crisscross_kit[3d]
pip install crisscross_kit[blender]
```

For the orthogonal sequence generator (`orthoseq_generator`), you'll also need [NUPACK 4.x](https://www.nupack.org/download/overview).

## Quick Example

```python
from crisscross.core_functions import Megastructure

# Load a design created in #-CAD
mega = Megastructure(import_design_file="my_design.xlsx")

# Access slat data
print(f"Design has {len(mega.slats)} slats")

# Generate graphics
mega.create_standard_graphical_report('output_folder/')
```

## Documentation

**Full documentation**: [https://hash-cad.readthedocs.io/](https://hash-cad.readthedocs.io/python-api/)

## Developer Installation

Clone and install in editable mode:

```bash
git clone https://github.com/mattaq31/Hash-CAD.git
cd Hash-CAD/crisscross_kit
pip install -e .
```

## License

MIT License - see [LICENSE](../LICENSE) for details.
resource-api-monitor 0.0.1
A simple API to check the cpu and memory usage of an instance
Requires Python: >=3.13

# Resource Checker API

## This is a simple application that checks the resource usage of your server via API

## Requires

+ python = ">=3.13"

## Installation

```bash
pip3 install resource-api-monitor
```

You can also download the .whl package and install from there.

## Usage

Run:

```bash
monitor-server
```

Then just curl to endpoint:8000/cpu or endpoint:8000/memory.

## API Reference

| Endpoint | Method | Description |
| :--- | :--- | :--- |
| `/memory` | GET | Returns RAM usage and swap statistics. |
| `/cpu` | GET | Returns average CPU usage (0.3s duration between samples). |

### Example CPU Output

{
  "total_cpu_usage": 0.15,
  "usage_per_cpu": [0.12, 0.18, 0.14, 0.16]
}
codex-local-sdk-python 0.1.4
Python SDK wrapper around codex exec with bundled skill/docs scaffolding CLI.
Requires Python: >=3.10

# codex-local-sdk-python

[![PyPI Version](https://img.shields.io/pypi/v/codex-local-sdk-python.svg)](https://pypi.org/project/codex-local-sdk-python/)
[![Python Versions](https://img.shields.io/pypi/pyversions/codex-local-sdk-python.svg)](https://pypi.org/project/codex-local-sdk-python/)
[![Unit Tests](https://img.shields.io/github/actions/workflow/status/maestromaximo/codex-local-sdk-python/unit.yml?label=unit%20tests)](https://github.com/maestromaximo/codex-local-sdk-python/actions/workflows/unit.yml)
[![License](https://img.shields.io/github/license/maestromaximo/codex-local-sdk-python)](https://github.com/maestromaximo/codex-local-sdk-python/blob/main/LICENSE)

`codex-local-sdk-python` packages this repository's local `codex_local_sdk` module as an installable
PyPI distribution and adds a companion CLI:

- `codex-sdk skill` copies the bundled `codex-local-sdk-usage` skill to `.agents/skills/`.
- `codex-sdk docs` copies bundled documentation to `codex-sdk-documentation/`.

Project policies:

- Contributing: `CONTRIBUTING.md`
- Security: `SECURITY.md`
- License: `LICENSE` (MIT)

## Install

```bash
pip install codex-local-sdk-python
```

## Python usage

```python
from codex_local_sdk import CodexExecRequest, CodexLocalClient

client = CodexLocalClient()
result = client.run(CodexExecRequest(prompt="Summarize this repo"), timeout_seconds=120)
print(result.final_message)
```

## CLI

```bash
codex-sdk --help
codex-sdk skill
codex-sdk docs
```

Command details:

- `codex-sdk skill` copies `codex-local-sdk-usage` to `.agents/skills/`
- `codex-sdk docs` copies docs to `codex-sdk-documentation/`
- use `--output <dir>` to choose destination root
- use `--force` to overwrite existing files

Examples:

```bash
codex-sdk skill --output .
codex-sdk docs --output .
codex-sdk skill --output /path/to/project --force
```