| Crates.io | vector-ta |
| lib.rs | vector-ta |
| version | 0.1.2 |
| created_at | 2026-01-21 02:24:36.956351+00 |
| updated_at | 2026-01-21 02:49:19.78796+00 |
| description | High-performance technical analysis indicators with optional SIMD/CUDA and language bindings. |
| homepage | https://vectoralpha.dev/projects/ta |
| repository | https://github.com/VectorAlpha-dev/VectorTA |
| max_upload_size | |
| id | 2058067 |
| size | 34,903,680 |
VectorTA is a Rust crate of technical analysis indicators focused on speed and predictable allocations, with optional SIMD/CUDA acceleration and optional Python/WASM bindings.
Full documentation (indicator list, API reference, and guides): https://vectoralpha.dev/projects/ta
Example: ADX over HLC slices
use vector_ta::indicators::adx::{adx, AdxInput, AdxParams};
fn compute_adx(
high: &[f64],
low: &[f64],
close: &[f64],
) -> Result<Vec<f64>, Box<dyn std::error::Error>> {
let input = AdxInput::from_slices(high, low, close, AdxParams { period: Some(14) });
Ok(adx(&input)?.values)
}
cuda: GPU acceleration using prebuilt PTX (compute_89) shipped in the crate. Consumers do not need nvcc.cuda-build-ptx: Maintainer-only: compile PTX from kernels/cuda/** using nvcc.nightly-avx: Runtime-selected AVX2/AVX512 kernels on x86_64 (nightly required).python: PyO3 bindings (build from source via maturin).wasm: wasm-bindgen bindings (build from source via wasm-pack).Build + install into a virtualenv:
python3 -m venv .venv
source .venv/bin/activate
python -m pip install -U pip maturin numpy
maturin develop --release --features python
Build with wasm-pack:
rustup target add wasm32-unknown-unknown
wasm-pack build --target nodejs --release --features wasm
Enable:
[dependencies]
vector-ta = { version = "0.1.1", features = ["cuda"] }
Notes:
CUDA_FORCE_SKIP=1.VECTOR_TA_PREBUILT_PTX_DIR (see docs link above).Apache-2.0 (see LICENSE).