pyomq

Python binding for omq.rs, a Rust libzmq port. Drop-in pyzmq replacement on the common path.

Install

uv pip install pyomq
uv pip install 'pyomq[test]'   # adds pytest, pyzmq for the interop suite

The published wheel includes optional features: plain, curve, lz4. Use pyomq.has("curve") at runtime to check availability.

Usage

import pyomq as zmq  # drop-in for `import zmq` from pyzmq

ctx = zmq.Context()
push = ctx.socket(zmq.PUSH)
push.connect("tcp://127.0.0.1:5555")
push.send(b"hello")
push.close()
ctx.term()

For asynchronous code:

import pyomq
import pyomq.asyncio as zmq_async

ctx = zmq_async.Context()
sock = ctx.socket(pyomq.PUSH)
await sock.connect("tcp://127.0.0.1:5555")
await sock.send(b"hello")
await sock.close()

Status

Sync and asyncio APIs both ship in this release. All 20 ZMTP socket types are wired:

  • Standard (RFC 28 + 47): PAIR, PUB, SUB, REQ, REP, DEALER, ROUTER, PULL, PUSH, XPUB, XSUB, STREAM.
  • Draft: SERVER, CLIENT (RFC 41), RADIO, DISH (RFC 48), GATHER, SCATTER (RFC 49), PEER, CHANNEL (RFC 51).

Transports: tcp://, ipc://, inproc://, and udp:// (RADIO/DISH only). Optional features built into the wheel: plain, curve, blake3zmq, lz4.

DISH groups: use socket.join(b"group") / socket.leave(b"group") to manage subscriptions; messages are sent as multipart [group, body].

Backend

pyomq is built on omq-tokio (multi-threaded tokio runtime). The runtime runs on a dedicated background thread; every Python call releases the GIL across the runtime trip.

Performance

See BENCHMARKS.md for full tables.

pyomq vs pyzmq performance

2-process loopback throughput and latency vs pyzmq, measured on Linux 6.12 (Debian 13), Intel i7-8700B 3.2 GHz, Rust 1.95.0.

zmq.proxy() forwarding (128 B, TCP)

pyomq pyzmq ratio
PUSH/PULL msg/s 2.62 M/s 1.52 M/s 1.72×
REQ/REP rt/s 7,013/s 4,437/s 1.58×

pyomq's proxy() forwards directly between sockets on the tokio runtime, no Python per-message overhead. pyzmq's zmq.proxy() calls libzmq's C-level zmq_proxy. PUSH/PULL forwarding is throughput-bound and pyomq is ~1.4x faster. REQ/REP proxy is latency-bound (4 TCP hops per round-trip); pyomq is ~1.7x faster thanks to direct socket forwarding.

Run scripts/update_perf.py (after maturin develop --release) to re-measure, regenerate the chart, and update the proxy table.

Compression transports

OMQ.rs adds a transparent LZ4 compression transport on top of TCP: lz4+tcp://. Swap the scheme in your endpoint string and everything else stays the same:

push = ctx.socket(zmq.PUSH)
push.bind("lz4+tcp://127.0.0.1:5555")

pull = ctx.socket(zmq.PULL)
pull.connect("lz4+tcp://127.0.0.1:5555")

Both peers must use a matching compression endpoint. Payloads below ~512 B are sent as-is (the codec detects that compression would expand them).

lz4+tcp:// supports dictionary auto-training (off by default). When enabled, it samples the first 100 outbound messages, builds a 2 KiB dict, and ships it to the peer once. After that the compression threshold drops from 512 B to 128 B, so small structured messages start compressing too. Pure Rust (lz4rip), no C compiler required.

See BENCHMARKS_COMPRESSION.md for throughput charts and benchmark details.

CURVE authentication

CURVE encrypts traffic and authenticates the server to the client. To also authenticate clients to the server, call set_curve_auth() before bind()/connect():

server_pub, server_sec = zmq.curve_keypair()
client_pub, client_sec = zmq.curve_keypair()

pull = ctx.socket(zmq.PULL)
pull.curve_server = 1
pull.curve_publickey = server_pub
pull.curve_secretkey = server_sec

# Option 1: allow specific client keys (checked in Rust, no GIL overhead)
pull.set_curve_auth([client_pub])

# Option 2: custom callback receiving a PeerInfo with a .public_key (Z85 bytes)
pull.set_curve_auth(lambda peer: peer.public_key in allowed_keys)

# Option 3: accept any valid CURVE client (the default)
pull.set_curve_auth(None)

No ZAP, no filesystem key management. The callback runs during the CURVE handshake; returning a falsy value rejects the client.

BLAKE3ZMQ authentication

BLAKE3ZMQ is an omq-native encryption mechanism using BLAKE3 key derivation and ChaCha20 encryption. Keys are raw 32-byte X25519 keypairs (not Z85-encoded like CURVE). Setup mirrors CURVE:

server_pub, server_sec = zmq.blake3zmq_keypair()
client_pub, client_sec = zmq.blake3zmq_keypair()

pull = ctx.socket(zmq.PULL)
pull.blake3zmq_server = 1
pull.blake3zmq_publickey = server_pub
pull.blake3zmq_secretkey = server_sec

push = ctx.socket(zmq.PUSH)
push.blake3zmq_serverkey = server_pub
push.blake3zmq_publickey = client_pub
push.blake3zmq_secretkey = client_sec

# Client authentication (same three options as CURVE)
pull.set_blake3zmq_auth([client_pub])                         # allow list
pull.set_blake3zmq_auth(lambda peer: peer.public_key in ok)   # callback
pull.set_blake3zmq_auth(None)                                 # accept all

The callback receives a PeerInfo with a .public_key attribute (raw 32-byte bytes). Requires the blake3zmq feature (pyomq.has("blake3zmq")).

[!WARNING] BLAKE3ZMQ has not been independently security audited. It's an omq-native construction (Noise XX + BLAKE3 + X25519 + ChaCha20-BLAKE3) and should not be relied on for anything that matters until it has had third-party review. Use CURVE (RFC 26) for production / regulated workloads.

Develop

cd bindings/pyomq
uv venv && source .venv/bin/activate
uv pip install maturin pytest pyzmq
maturin develop --release
pytest -v

Project links

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Key dates

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  • Released:
Newer release available (0.20.1)

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Avatar for paddorpy from gravatar.com paddorpy

Credits

Author: Patrik Wenger

GitHub Statistics

Data verified by PyPI on Jul 10, 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

ISC License (ISCL) (ISC)

Requires

Python >=3.9

Tags

zeromq omq messaging pyzmq zmq

Classifiers

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