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Python, R & Julia packages

The easiest way to use sTiles, no compiler and no manual download. Python and Julia fetch the right libstiles binary automatically on first use; R asks first, or installs it when you call sTiles_install_library().

pip install sTiles

remotes::install_github(
  "esmail-abdulfattah/sTiles",
  subdir = "R/sTiles")

pkg> add https://github.com/esmail-abdulfattah/sTiles:julia

Pre-built binaries

Latest release v2026.9.24 · built 2026-09-24 · every archive carries a BUILDINFO with the exact compiler, flags and library versions

Pick the build that matches your platform. Each archive contains libstiles, the C header, a pkg-config file and a BUILDINFO record. Nothing else needs installing: the Linux builds embed their BLAS (MKL or OpenBLAS), and the macOS Intel and Windows builds ship their runtime libraries alongside.

The x86_64 builds need a CPU with AVX2 (Intel Haswell 2013+ / AMD Excavator+); the library reports this clearly rather than crashing if your machine is older.

Other builds. Each GitHub Release also carries variants for specific hardware and toolchains — newest GCC with x86-64-v3 code, ARM Performance Libraries for armv8.2 servers (Graviton2+, Ampere, Grace), and GCC-built macOS libraries for linking into GCC programs. The Python and R packages use the five above by default; on Linux arm64 they pick the best one for your CPU automatically (SVE2 or armv8.2 where present); set STILES_VARIANT=none to force the portable build, or name any asset suffix to pin one.

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