hashcodecs

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SIMD-accelerated Base64, MurmurHash3, and XXH3 for Python and Rust.

Move byte-heavy work into Rust without changing your Python inputs. hashcodecs accepts bytes, bytearray, and memoryview, selects the best available SIMD backend, and exposes batch and reusable-buffer APIs.

Features

  • Base64 encode and decode with standard, URL-safe, padded, unpadded, wrapped, and canonical modes.
  • MurmurHash3 x86-32, x86-128, and x64-128 with one-shot and incremental APIs.
  • Bit-for-bit compatible XXH3-64 and XXH3-128 with one-shot and native batch APIs.
  • Caller-managed *_into outputs for allocation-sensitive workloads.
  • Runtime dispatch across AVX-512, AVX2, SSE4.1, SSSE3, NEON, and scalar implementations where applicable.
  • Direct CPython buffer handling for bytes, bytearray, and memoryview inputs.
  • Install wheels for CPython 3.10 through 3.15 and free-threaded CPython 3.14t and 3.15t on Linux, macOS, and Windows.

Citation

If you use hashcodecs, cite CITATION.cff.

Installation

pip3 install hashcodecs

Compatibility

Version 1.x keeps the documented Python API stable under the compatibility policy. Release wheels target CPython 3.10 through 3.15 on manylinux x86-64, macOS 11+ ARM64, and Windows x86-64. CPython 3.14t and 3.15t receive free-threaded wheels on the same platforms.

The Rust crate and Python package share one release version. Before 1.0, minor releases may contain breaking Rust API changes; the documented Python API follows the compatibility policy below. See Security Policy for vulnerability reporting.

Performance snapshot

On the benchmark host, hashcodecs.xxh3_64 processes a 1 MiB input at 78.83 GiB/s. The operator pinned one logical CPU and measured hashcodecs alone. At 256 B items in batches of 64, the Base64 batch API reaches 8.56 GiB/s for encode and 7.60 GiB/s for decode. The per-item loop reaches 4.41 and 3.39 GiB/s. Read the benchmark details and raw results.

Python

The Base64 module follows familiar Python conventions while adding explicit padding, canonical validation, batch, and reusable-buffer operations.

import hashcodecs.base64 as base64
from hashcodecs import murmur3_32, xxh3_64, xxh3_128_batch

assert base64.b64encode(b'hello') == b'aGVsbG8='
assert base64.b64decode(b'aGVsbG8=') == b'hello'
assert base64.urlsafe_b64encode(b'hello', padded=False) == b'aGVsbG8'

assert murmur3_32(b'hello') == 0x248BFA47
assert xxh3_64(b'') == 0x2D06800538D394C2
assert xxh3_128_batch([b'hello', b'world']) == [
    0xB5E9C1AD071B3E7FC779CFAA5E523818,
    0xFA0D38A9B38280D0891E4985BDB2583E,
]

Reusable outputs

*_into functions write into caller-managed bytearray storage and return the number of bytes written. XXH3 batch outputs are packed little-endian digests.

import hashcodecs.base64 as base64
from hashcodecs import xxh3_64_batch_into

payload = b'hello'
encoded = bytearray(4 * ((len(payload) + 2) // 3))
encoded_len = base64.b64encode_into(payload, encoded)
assert encoded[:encoded_len] == b'aGVsbG8='

hashes = bytearray(2 * 8)
written = xxh3_64_batch_into([b'hello', b'world'], hashes, seed=42)
assert written == 16

Incremental hashing

from hashcodecs import murmur3_x64_128

hasher = murmur3_x64_128(seed=42)
hasher.update(b'hello')
snapshot = hasher.copy()
hasher.update(b' world')

assert snapshot.hexdigest() == snapshot.digest().hex()
assert hasher.digest() != snapshot.digest()

Rust

The Rust API exposes the same core algorithms without the Python binding layer.

cargo add hashcodecs

let encoded = hashcodecs::base64::b64encode(b"hello");
assert_eq!(encoded, "aGVsbG8=");

let mut output = [0_u8; 8];
let written = hashcodecs::base64::b64encode_into(b"hello", &mut output).unwrap();
assert_eq!(&output[..written], b"aGVsbG8=");

assert_eq!(
    hashcodecs::murmur3::murmur3_x86_32(b"hello", 0),
    0x248b_fa47
);
assert_eq!(
    hashcodecs::xxhash::xxh3_64(b"", 0),
    0x2d06_8005_38d3_94c2
);

Architecture

The Rust core owns algorithm behavior and SIMD dispatch. A thin CPython layer handles argument parsing, buffer ownership, reusable outputs, and GIL decisions; root-level Python modules provide typed public exports without adding per-call wrappers.

See docs/ARCHITECTURE.md for the module layout, dispatch model, algorithm data flows, CPython boundary, and safety invariants.

Benchmarks

Run the suite on Windows 10 x64 with an Intel Core Ultra 7 265K. Pin one logical CPU and run each case in one thread. Collect 50 Rust samples and 15 Python samples. Higher throughput wins.

Base64: Rust

Rust Base64 throughput

MurmurHash3: Rust

Rust MurmurHash3 throughput

XXH3: Rust

Link hashcodecs with xxHash 0.8.3 through xxhash-c-sys. Build the C baseline with AVX2. Batch cases pass 32 equal-size inputs and include result-vector allocation.

Rust XXH3 throughput

Base64: Python

Pass bytes to Rust without an input copy. Python decoding uses validate=True.

Python Base64 throughput

MurmurHash3: Python

Python MurmurHash3 throughput

XXH3: Python

Pass 32 equal-size inputs to each batch case. Compare one native hashcodecs call with a loop over the upstream xxhash extension.

Python XXH3 throughput

Read the focused cases, commands, and values in BENCHMARK.md. Read raw chart values in docs/benchmarks/results.csv.

Reproduce

Comparison crates and Python packages are development-only dependencies and are not included in consumer builds.

cargo bench --bench base64
cargo bench --bench murmur3
cargo bench --bench xxhash

uv sync --group benchmark --no-install-project
uv run --no-project --with . python benchmarks/python_base64.py
uv run --no-project --with . python benchmarks/python_base64_batch.py
uv run --no-project --with . python benchmarks/python_murmur3.py
uv run --no-project --with . python benchmarks/python_xxhash.py

The Python benchmarks expose focused modes such as --into, --bytearray-input, --memoryview-input, --incremental, --large, and --hashcodecs-only. Use --help on a benchmark script for its supported modes.

For the same-ISA Windows XXH3 comparison shown above, rebuild the C baseline with:

$env:CFLAGS='/O2 /arch:AVX2'
cargo clean -p xxhash-c-sys
cargo bench --bench xxhash

Development

Build the Python wheel and source distribution:

uv build

Run the primary local checks:

cargo fmt --check
cargo clippy --all-targets --features python -- -D warnings
cargo test --features python
uv run --frozen --no-sync ruff check . --no-cache
uv run --frozen --no-sync ruff format --check .
uv run --frozen --no-sync pytest tests --cov=hashcodecs --cov-branch --cov-fail-under=100

Optimized paths are also checked with differential fuzzing, Kani, strict-provenance Miri, AddressSanitizer, and MemorySanitizer in CI.

References

The Base64 SIMD implementation follows the approach described in Faster Base64 Encoding and Decoding using AVX2 Instructions, extended with runtime-selected AVX-512 VBMI and AArch64 NEON backends.

License

Licensed under either of the following, at your option:

Project links

Data verified by PyPI on Aug 22, 2026
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Key dates

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  • Released:
Newer release available (1.4.1)

1 maintainer

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Avatar for kozistr from gravatar.com kozistr

Credits

Author: kozistr

GitHub Statistics

Data verified by PyPI on Aug 22, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT OR Apache-2.0
View SPDX License List

Requires

Python >=3.10

Tags

base64 murmur3 rust simd xxhash

Classifiers

Report project as malware

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BLAKE2b-256 1b5f0ed53bf1053698b001c44d4bc8334e85aafa3fbf0dfcbcd61b302d9cee40

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Provenance

The following attestation bundles were made for hashcodecs-1.0.0-cp310-cp310-macosx_11_0_arm64.whl:

Publisher: release.yml on kozistr/hashcodecs-rs

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

1.4.1

25 files

1.4.0

25 files

1.3.0

25 files

1.2.1

25 files

1.2.0

25 files

1.1.0

25 files

This release

1.0.0 This release

25 files

0.6.1

19 files

0.6.0

19 files

0.5.0

4 files

0.4.0

4 files

0.3.0

4 files

0.2.0

4 files

0.1.0

4 files

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