s4-codec 1.1.0

Python bindings for s4-codec — in-process CPU compression (zstd / gzip) for ML and ETL pipelines. GPU codecs are not exposed in Python in v1.0; route GPU workloads through the s4 server gateway.

s4-codec (Python bindings)

In-process CPU compression (zstd + gzip) from Python — no S4 gateway required. Wraps the same Rust s4-codec crate that powers the S4 S3-compatible storage gateway, so a Python notebook / Airflow task / Spark UDF can compress and decompress with the exact same byte format as objects sitting in an S4 bucket. (GPU codecs are intentionally NOT exposed in Python in v1.0 — they require a CUDA toolchain + GPU at runtime, which is a poor fit for pip install. Workloads that need GPU compression should route through the s4 server gateway instead. Python GPU exposure is a v1.x roadmap candidate.)

Install

pip install s4-codec        # CPU codecs only (zstd + gzip)

Example

from s4_codec import CpuZstd, CpuGzip, gpu_available

codec = CpuZstd(level=3)
data = b"hello squished s3 " * 10_000
compressed, original_size, crc = codec.compress(data)
roundtrip = codec.decompress(compressed, original_size, crc)
assert roundtrip == data

# RFC 1952 gzip output — decodable by any standard `gunzip`-aware client.
gz_compressed, *_ = CpuGzip(level=6).compress(data)
assert gz_compressed[:2] == b"\x1f\x8b"

print("GPU available:", gpu_available())

API

Class / function	Purpose
CpuZstd(level: int = 3)	CPU zstd, level 1..=22.
CpuGzip(level: int = 6)	CPU gzip (RFC 1952), level 0..=9.
<codec>.compress(data: bytes) -> (bytes, int, int)	Returns (compressed, original_size, crc32c).
<codec>.decompress(data, original_size, crc32c) -> bytes	Inverse of compress.
gpu_available() -> bool	True iff the wheel was built with --features nvcomp-gpu and a CUDA-capable GPU is reachable.

The (original_size, crc32c) tuple corresponds to the ChunkManifest.original_size / ChunkManifest.crc32c fields the Rust crate uses; round-trip them alongside the compressed payload (e.g. as JSON sidecar fields).

Build from source

pip install maturin
cd crates/s4-codec-py
maturin build --release
ls target/wheels/                          # *.whl is here

The --features nvcomp-gpu flag forwards to the underlying s4-codec-rs crate's GPU codecs at the Rust level, but the Python module does NOT expose Python classes for the GPU codecs in v1.0 (see the §Status note above). Building with --features nvcomp-gpu therefore only affects what gpu_available() reports, not which Python classes are importable.

maturin develop installs the wheel into the current virtualenv for iterative development.

Running tests

maturin develop
pip install -e ".[dev]"
pytest tests/

The --features nvcomp-gpu build flag forwards to the underlying s4-codec-rs GPU paths at the Rust level. In v1.0 this only affects what gpu_available() reports; the Python module does NOT add GPU codec classes when built with this feature (see the §Status note at the top of this file).

maturin develop --release --features nvcomp-gpu

The pytest suite covers CPU codec round-trips, RFC 1952 gzip compatibility, GIL-release threading, version inheritance, and the per-CodecError exception class hierarchy (v0.8.5 #85). A separate Rust-side test (tests/version_matches_workspace.rs) guards the workspace semver inherit.

Error handling

The binding raises a subclass tree per CodecError variant so callers can branch programmatically instead of string-matching:

Exception class	CodecError variant	Base class
S4Error	(base + TruncatedStream)	ValueError
S4CrcMismatchError	CrcMismatch	S4Error
S4SizeMismatchError	SizeMismatch	S4Error
S4CodecMismatchError	CodecMismatch	S4Error
S4UnregisteredCodecError	UnregisteredCodec	S4Error
S4ManifestSizeExceedsLimitError	ManifestSizeExceedsLimit	S4Error
S4ManifestSizeMismatchError	ManifestSizeMismatch	S4Error
S4BackendError	Backend / Join	RuntimeError
S4IoError	Io	OSError

S4Error inherits from ValueError for backward compat with code that caught the previous flat ValueError mapping. S4BackendError and S4IoError deliberately escape that hierarchy so existing retry-on-IOError middleware continues to fire on the right class.

Workspace integration

The crate ships a cdylib only and uses PyO3's extension-module feature, so cargo check -p s4-codec-py and cargo build --workspace succeed on a CI runner with no Python development headers installed — no libpython link is performed; the Python interpreter that loads the .so provides those symbols at runtime.

If you ever see a link error like undefined reference to PyExc_…, drop pyo3/extension-module from the features and you'll get the diagnostic build that does link libpython.

Threading / GIL

Both CpuZstd.compress() and CpuGzip.compress() (and their decompress() counterparts) release the Python GIL while running, so other Python threads make progress concurrently. This is safe for:

• Django / Flask workers
• ASGI / asyncio event loops (use asyncio.to_thread() to wrap the blocking call)
• multi-threaded data pipelines

Example (asyncio):

import asyncio
from s4_codec import CpuZstd

async def compress_async(data: bytes) -> bytes:
    codec = CpuZstd()
    compressed, orig_size, crc = await asyncio.to_thread(codec.compress, data)
    return compressed

Note: the methods themselves are synchronous — they don't return awaitables. The GIL release means another Python thread can run during the compress; it doesn't make the call async-aware.

Supported codecs

Codec	Default
CpuZstd	✓
CpuGzip	✓

The GPU codecs (nvcomp-zstd, nvcomp-bitcomp, nvcomp-gdeflate) are intentionally not exposed as Python classes in v1.0 — they require a CUDA toolchain at build time and a GPU at runtime, which is a poor fit for the pip install s4-codec packaging story. The nvcomp-gpu feature on the underlying Rust crate exists for the server path; the Python module's runtime classes are the two CPU codecs above. gpu_available() -> bool is exposed for clients that want to gate their own logic on GPU presence (e.g. to decide whether to route a workload through the s4 server gateway instead of the in-process Python decoder), but it does not enable any new Python class on its own. GPU codec exposure in Python is a v1.x roadmap candidate.

Publishing status

• PyPI publish is manual (no CI automation as of v0.8.5):

  cd crates/s4-codec-py
  maturin build --release
  twine upload target/wheels/*
  

• Workspace version inheritance was fixed in v0.8.5 #82 — the published wheel version now matches the gateway version.

target/wheels/ is gitignored — never commit .whl files.

License

Apache-2.0 — same as the rest of the S4 project.