# Installation

> NumKong for Python

From PyPI:

```sh
python -m pip install numkong
```

From a local checkout:

```sh
python -m pip install .
```

Quick runtime check:

```sh
python -c "import numkong as nk; print(repr(nk.cpu_capabilities_enabled()))"
```

### Wheel Compatibility and Building from Source

Pre-built wheels are available on PyPI for Linux (x86_64, aarch64, riscv64, plus i686, ppc64le, s390x), macOS (x86_64, arm64), and Windows (AMD64, ARM64).
Python 3.12 through 3.15 is supported, including the free-threaded 3.14t and 3.15t.
Every wheel compiles each capability the toolchain supports and picks among them at runtime, so a single wheel covers all CPU generations on a given architecture.

When building from source, the compiler requirements depend on the platform.
On macOS x86 only AVX2 is available; on macOS ARM NEON is always present, but SME requires Apple M4+ with Xcode 16+ (AppleClang 16+).
RISC-V builds require Clang and LLD because GCC lacks `zvfh`, `zvfbfwma`, and `zvbb` support.
On Windows, MSVC 19.44+ (Visual Studio 2022 17.14+) is recommended for full AVX-512 with FP16/BF16/VNNI.
Build parallelism is controlled by `CMAKE_BUILD_PARALLEL_LEVEL`, which should be lowered in memory-constrained containers.
There is no OpenMP dependency.
Python-side parallelism uses the `threads=` argument on the GIL-free kernels, or `concurrent.futures` around them.

```sh
CMAKE_BUILD_PARALLEL_LEVEL=2 pip install . --no-build-isolation
```