pyarrowspace

Python bindings for arrowspace-rs.

arrowspace is a graph-based analytics library for vector spaces, supported by a graph representation and a key-value store. The main use-cases targeted are: AI search capabilities as advanced vector similarity, graph characterisation analysis and search, indexing of high-dimensional vectors. Design principles described in this article.

For labs and tests please see tests/

Installation

Core library

The core library ships as a compiled Rust extension. It only requires numpy, pyarrow, pandas, and scikit-learn:

pip install arrowspace

Optional extras

Additional capabilities are available as optional extras:

Extra	Packages included	Use case
`embeddings`	`datasets`, `sentence-transformers`, `transformers[torch]<5.0`, `tsdae`	Generating embeddings from text via HuggingFace models; required for `test_1_quora_questions.py` and all tests above
`benchmarks`	`beir`, `nltk`	Running BEIR/MS-MARCO benchmark suites and NLP preprocessing
`viz`	`matplotlib`, `seaborn`, `tqdm`	Plotting results and progress bars in test scripts
`full`	all of the above	Full development and research environment

Install with one or more extras:

# Required to run test_1_quora_questions.py and above
pip install arrowspace[embeddings]

# Benchmarking + visualisation
pip install arrowspace[benchmarks,viz]

# Everything (for running the full test suite)
pip install arrowspace[full]

Note: tests/test_0_*.py only require the core install. All tests numbered test_1 and above require at minimum arrowspace[embeddings].

Build from source

If you have Cargo installed, you can compile and install locally using maturin:

pip install maturin[patchelf]
# quick development build
maturin develop
# optimised release build (recommended for large datasets)
maturin develop --release

Tests

test_0_*.py scripts only require the core install:

python tests/test_0_0.py

test_1 and above require the embeddings extra (pip install arrowspace[embeddings]):

python tests/test_1_quora_questions.py

Higher-numbered tests (test_3 and above) additionally require benchmarks and viz:

pip install arrowspace[full]
python tests/test_3_beir.py

Some tests require downloading a dataset separately or fine-tuning embeddings on a given dataset.

Simplest Example

from arrowspace import ArrowSpaceBuilder
import numpy as np

items: np.array = np.array(
    [[0.1, 0.2, 0.3], [0.0, 0.5, 0.1], [0.9, 0.1, 0.0]],
    dtype = np.float64
)

graph_params: dict = {
    "eps": 1.0,
    "k": 6,
    "topk": 3,
    "p": 2.0,
    "sigma": 1.0,
}

# Create an ArrowSpace instance, returning the computed
# signal graph and lambdas
aspace, gl = ArrowSpaceBuilder().build(graph_params, items)

# Search comparable items
# defaults: k = nitems, alpha = 0.9, beta = 0.1
query: np.array = np.array(
    [0.05, 0.2, 0.25],
    dtype = np.float64
)

tau: float = 1.0
hits: list = aspace.search(query, gl, tau)

# Search returns a list of `(index, score`) tuples, where
# expected value from the code above show the first index
# having the top score, i.e., being nearest.

print(hits)
# [ (0, 0.989743318610787), (1, 0.7565344158360029), (2, 0.22151940739207396) ]

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

arrowspace-0.27.2.tar.gz (18.7 MB view details)

Uploaded Sep 2, 2026 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

arrowspace-0.27.2-cp313-cp313-macosx_11_0_arm64.whl (3.3 MB view details)

Uploaded Sep 2, 2026 CPython 3.13macOS 11.0+ ARM64

File details

Details for the file arrowspace-0.27.2.tar.gz.

File metadata

Download URL: arrowspace-0.27.2.tar.gz
Upload date: Sep 2, 2026
Size: 18.7 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for arrowspace-0.27.2.tar.gz
Algorithm	Hash digest
SHA256	`2222738c61beb2b4230cc6f556d1cd12021e7619b1a70d398482dbe0e01035d3`
MD5	`caf14003094d151c58732de86f830959`
BLAKE2b-256	`705e19dd712f841bcf71ecaceaa9bc0f198276697040fe485b99708cbc3477d7`

See more details on using hashes here.

File details

Details for the file arrowspace-0.27.2-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

Download URL: arrowspace-0.27.2-cp313-cp313-macosx_11_0_arm64.whl
Upload date: Sep 2, 2026
Size: 3.3 MB
Tags: CPython 3.13, macOS 11.0+ ARM64
Uploaded using Trusted Publishing? No
Uploaded via: uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for arrowspace-0.27.2-cp313-cp313-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`02d42265ab736b1bfc735f9d22bb5c5bd628692e165c8db79241f75edd4bd15b`
MD5	`f3cace412883f3fcd0329f8b1ed87e0e`
BLAKE2b-256	`a813385420305b700b8ed2a96db59f5b70d9ee57d14306cfed5ac91020550d90`