semvec/pypi-packages huggingface dataset:
khmer-time-format 0.1.0
Format 12/24 hour time into Khmer (digits or words).
License: MIT
Requires Python: >=3.8
Keywords: khmer, time, format

# khmer-time-format (Python)

Format 12-hour / 24-hour time (e.g. `1:22 PM`, `13:22`) into Khmer with **two options**:

1) **Khmer numerals (digits)**  
`ម៉ោង១ និង ២២ នាទី រសៀល`

2) **Khmer words (no digits)**  
`ម៉ោងមួយ និង ម្ភៃពីរ នាទី រសៀល`

## Install

```bash
pip install khmer-time-format
```

## Usage

```python
from khmer_time_format import format_time

print(format_time("1:22 PM", mode="digits"))
print(format_time("13:22", mode="words"))
```

## Development

```bash
python -m venv .venv
# Windows: .venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
pip install -e ".[dev]"
pytest
ruff check .
mypy src
```

## Build & publish (PyPI)

```bash
python -m build
python -m twine check dist/*
```

Push a version tag to publish to PyPI via GitHub Actions:

```bash
# tag value becomes package version
git tag v0.1.0
git push origin v0.1.0
```

Tag pushes matching `v*` trigger `.github/workflows/publish.yml`.

With this setup, you do not need to edit the version in `pyproject.toml` for each release.
harnessgg-blender 0.2.0
Bridge-first CLI for Blender automation
License: MIT
Requires Python: >=3.10
Keywords: blender, 3d, automation, ai-agent, cli

# harness-blender

Bridge-first Python package for agent-driven Blender automation through a JSON CLI.

## Install (local)

```bash
pip install -e .
```

## Quick Start

```bash
harness-blender bridge start
harness-blender doctor
harness-blender file new scene.blend --overwrite
harness-blender object add scene.blend CUBE --name CubeA
harness-blender camera add scene.blend --name CamMain
harness-blender camera set-active scene.blend CamMain
harness-blender render still scene.blend out.png
```

## Docs

- Human commands: `docs/human/commands.md`
- LLM command spec: `docs/llm/command-spec.md`
- Bridge protocol: `docs/llm/bridge-protocol.md`
- Error codes: `docs/llm/error-codes.md`
- Response schema: `docs/llm/response-schema.json`

## Publishing

Build and validate locally:

```bash
python -m pip install -e ".[dev]"
python -m build
twine check dist/*
```

Automated publish is configured in `.github/workflows/publish.yaml` using trusted publishing
(`environment: pypi` + OIDC).