zsasa Python Bindings
Python bindings for zsasa — a high-performance SASA calculator in Zig.
Installation
pip install zsasa
# or
uv add zsasa
The x86_64 wheels need a CPU with AVX2 and FMA (x86-64-v3, 2013 and later), and the macOS wheels need macOS 11 or later. On an older CPU, install from source with pip install --no-binary zsasa zsasa (needs Zig 0.16).
Optional Dependencies
pip install zsasa[gemmi] # Gemmi integration
pip install zsasa[biopython] # BioPython integration
pip install zsasa[biotite] # Biotite integration
pip install zsasa[all] # All integrations
Quick Start
import numpy as np
from zsasa import calculate_sasa
coords = np.array([[0.0, 0.0, 0.0], [3.0, 0.0, 0.0]])
radii = np.array([1.5, 1.5])
result = calculate_sasa(coords, radii)
print(f"Total SASA: {result.total_area:.2f} Ų")
# With structure file (gemmi)
from zsasa.integrations.gemmi import calculate_sasa_from_structure
result = calculate_sasa_from_structure("protein.cif")
print(f"Total: {result.total_area:.1f} Ų")
Features
- Two algorithms: Shrake-Rupley and Lee-Richards, with bitmask LUT optimization
- Selectable precision:
calculate_sasa_batchtakesprecision="f64"(default) or"f32" - Multi-threading: Automatic parallelization
- Atom classification: CCD, ProtOr, NACCESS, and OONS classifiers
- Analysis: Per-residue aggregation, RSA, polar/nonpolar classification
- Batch processing:
process_directory()for proteome-scale datasets - MD trajectory: MDTraj and MDAnalysis integrations; use pyztraj for direct trajectory-file I/O
- Integrations: Gemmi, BioPython, Biotite
See the full API reference for details.
Development
cd python
uv run --with pytest pytest tests/ -v # Tests
ruff format . && ruff check --fix . # Lint
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for zsasa 0.10.0
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| zsasa-0.10.0.tar.gz | 493.7 kB | Details |
Built distributions (wheels)
Total release size: 47.3 MB
Release files / zsasa-0.10.0.tar.gz
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