Benchmark Results
8.77× faster than FreeSASA batch on E. coli AFDB and 9.70× faster on Human AFDB with bitmask f32 mode, while keeping peak RSS under 80 MiB. The pinned v0.6.0 suite also covers FreeSASA agreement, large structures, and MD trajectories.
See batch benchmarks →Zero Dependencies
Pure Zig with no external libraries. Single zig build command. Python wheels available on PyPI for Linux, macOS, and Windows.
Two Algorithms
Shrake-Rupley (fast, recommended) and Lee-Richards (precise). Selectable f64/f32 precision.
Multiple Formats
mmCIF, PDB, and JSON input. XTC and DCD trajectory support with automatic unit conversion.
Python Bindings
NumPy integration with Gemmi, BioPython, Biotite, MDTraj, and MDAnalysis support.
Analysis Tools
Per-residue aggregation, RSA calculation, and polar/nonpolar classification with three built-in classifiers.
Batch & Trajectory
Native directory batch processing and MD trajectory analysis. Proteome-scale datasets in seconds.
Cross-Platform
Linux, macOS, and Windows. CLI binary, Python package on PyPI, and native Zig library with interactive autodoc.