semvec/pypi-packages huggingface dataset:
posebench-fast 0.1.4
Fast docking evaluation metrics: symmetry-corrected RMSD and PoseBusters filters
Requires Python: >=3.11
Keywords: docking, rmsd, posebusters, molecular-docking, benchmark

# posebench-fast

[![PyPI version](https://badge.fury.io/py/posebench-fast.svg)](https://pypi.org/project/posebench-fast/)
[![CI](https://github.com/LigandPro/posebench-fast/actions/workflows/ci.yml/badge.svg)](https://github.com/LigandPro/posebench-fast/actions/workflows/ci.yml)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)

Fast docking evaluation metrics: symmetry-corrected RMSD and lightweight PoseBusters filters.

## Installation

```bash
uv pip install posebench-fast
```

## Features

- **Symmetry-corrected RMSD** — accounts for molecular symmetry (benzene, carboxylates, etc.)
- **Fast PoseBusters filters** — 4 key checks in ~10ms instead of full 27-test suite (~1-2s)

## Usage

```python
from posebench_fast import compute_all_isomorphisms, get_symmetry_rmsd_with_isomorphisms

# Symmetry-corrected RMSD
isomorphisms = compute_all_isomorphisms(rdkit_mol)
rmsd = get_symmetry_rmsd_with_isomorphisms(true_coords, pred_coords, isomorphisms)
```

```python
from posebench_fast import check_intermolecular_distance

# Fast filters: not_too_far_away, no_clashes, no_volume_clash, no_internal_clash
results = check_intermolecular_distance(
    mol_orig=rdkit_mol,
    pos_pred=pred_positions,      # (n_samples, n_atoms, 3)
    pos_cond=protein_positions,   # (n_protein_atoms, 3)
    atom_names_pred=lig_atoms,
    atom_names_cond=prot_atoms,
)
```

## Related

- [PoseBench](https://github.com/BioinfoMachineLearning/PoseBench) — full benchmark suite
- [PoseBusters](https://github.com/maabuu/posebusters) — full 27-test validation
- [spyrmsd](https://github.com/RMeli/spyrmsd) — symmetry RMSD algorithms

## License

MIT
colorconv-cli 0.1.0
Convert between color formats - hex, RGB, HSL, and color names
Requires Python: >=3.8
Keywords: cli, color, converter, hex, hsl, palette, rgb

# colorcli

Convert between color formats - hex, RGB, HSL, and CSS named colors.

```bash
pip install colorcli
```

## Usage

```bash
# Convert any color format
colors convert "#ff5733"
colors convert "rgb(255, 87, 51)"
colors convert coral

# Specific format conversions
colors hex "#ff5733"
colors rgb 255 87 51
colors hsl 11 100 60
colors name coral

# Generate palettes
colors palette "#ff5733" 5 --type analogous
colors palette coral 3 --type triadic
colors palette "#336699" --type complementary

# Utility commands
colors blend "#ff0000" "#0000ff"
colors contrast "#ff5733"
colors names              # List all CSS color names
```

## Commands

| Command | Description |
|---------|-------------|
| `convert COLOR` | Convert any color to all formats |
| `hex HEX` | Convert hex to RGB/HSL |
| `rgb R G B` | Convert RGB to hex/HSL |
| `hsl H S L` | Convert HSL to hex/RGB |
| `name NAME` | Look up CSS named color |
| `names` | List all 140 CSS named colors |
| `palette COLOR [COUNT]` | Generate color palette |
| `blend COLOR1 COLOR2` | Mix two colors |
| `contrast COLOR` | Suggest text color for background |
| `random-gradient COLOR` | Generate CSS gradient |

## Palette Types

- `complementary` - Opposite on color wheel
- `analogous` - Adjacent colors (default)
- `triadic` - Three colors 120° apart
- `tetradic` - Four colors 90° apart
- `split` - Split-complementary
- `shades` - Darker versions
- `tints` - Lighter versions

## JSON Output

All commands support `--json` for machine-readable output:

```bash
colors convert "#ff5733" --json
```

```json
{
  "hex": "#ff5733",
  "rgb": {"r": 255, "g": 87, "b": 51},
  "rgb_string": "rgb(255, 87, 51)",
  "hsl": {"h": 11, "s": 100, "l": 60},
  "hsl_string": "hsl(11, 100%, 60%)",
  "name": null
}
```

## For AI Agents

See [SKILL.md](SKILL.md) for agent-optimized documentation.

## License

MIT
builtsimple-research 1.0.2
Unified API for PubMed, ArXiv, and Wikipedia semantic search
Keywords: api, arxiv, pubmed, research, semantic-search, wikipedia

# builtsimple-research

Unified API for searching PubMed, ArXiv, and Wikipedia.

## Installation

```bash
pip install builtsimple-research
```

## Usage

### Async (recommended)
```python
import asyncio
from builtsimple_research import search_pubmed, search_arxiv, search_wikipedia, search_all

async def main():
    # Search individual sources
    pubmed = await search_pubmed("cancer treatment", limit=5)
    arxiv = await search_arxiv("transformer attention", limit=5)
    wiki = await search_wikipedia("machine learning", limit=5)
    
    # Search all at once
    all_results = await search_all("neural networks", limit=5)
    
asyncio.run(main())
```

### Sync
```python
from builtsimple_research import search_pubmed_sync, search_arxiv_sync, search_wikipedia_sync

results = search_pubmed_sync("cancer treatment", limit=5)
```

## API

- `search_pubmed(query, limit=10)` - 4.5M+ biomedical articles
- `search_arxiv(query, limit=10)` - Scientific preprints
- `search_wikipedia(query, limit=10)` - 4.8M+ articles
- `search_all(query, limit=10)` - All sources in parallel

## License

MIT - Built-Simple.ai