pyzlc 2.2.4

A lightweight ZeroMQ-based framework for high-performance, cross-environment communication across Local Area Networks.

pyzlc

pyzlc is a lightweight, cross-environment communication framework designed for Python applications running on Local Area Networks (LAN). Built on top of ZeroMQ, it features automatic node discovery, enabling nodes to dynamically find and connect to sockets from other peers without manual configuration.

pyzlc eliminates the need for heavyweight frameworks like ROS or ROS2 when you simply need to establish quick, reliable communication—whether on the same host or distributed across different machines—while maintaining a minimal dependency footprint.

🚀 Key Features

Zero-Config Discovery: Nodes automatically discover and update each other on the LAN using multicast heartbeats—no master node or manual IP configuration required.

ROS-like API: Designed with a familiar workflow for ROS users. simply initialize a node, register your publishers/subscribers, and start communicating with minimal boilerplate.

Automatic Serialization: Native support for dictionaries, lists, and primitives via msgpack, removing the need to manually define encoders or decoders. Future support is planned for Protobuf and Flatbuffers.

Async-First Architecture: Built on top of Python’s asyncio and ZeroMQ for high-performance, non-blocking asynchronous applications.

Rich Logging: Integrated, color-coded logging system to simplify debugging and status monitoring.

📦 Installation

pip install pyzlc

⚡ Quick Start

1. Initialization Every script starts by initializing the singleton node.

import pyzlc

# Initialize the node with a unique name and your local IP
pyzlc.init(node_name="MyNode", node_ip="127.0.0.1")

2. Pub/Sub Pattern Publish messages to a specific topic and subscribe to updates.

Publisher:

import pyzlc
import time

pyzlc.init("PublisherNode", "127.0.0.1")
pub = pyzlc.Publisher("chat_room")

while True:
    # You can send strings, dicts, or lists directly!
    pub.publish({"user": "admin", "text": "Hello World"})
    pyzlc.info("Message published")
    pyzlc.sleep(1)

Subscriber:

import pyzlc

def on_chat_message(msg):
    # msg is automatically unpacked into a python dict
    pyzlc.info(f"Received from {msg['user']}: {msg['text']}")

if __name__ == "__main__":
    pyzlc.init("SubscriberNode", "127.0.0.1")
    
    # Register a callback for the topic
    pyzlc.register_subscriber_handler("chat_room", on_chat_message)
    
    # Keep the node running
    pyzlc.spin()

3. Service (RPC) Pattern Perform Request/Response communication between nodes.

Server (Service Provider):

import pyzlc

def add_two_ints(request):
    """Takes a dict, returns the sum."""
    result = request['a'] + request['b']
    pyzlc.info(f"Calculated: {result}")
    return {"sum": result}

if __name__ == "__main__":
    pyzlc.init("ServerNode", "127.0.0.1")
    
    # Register the service
    pyzlc.register_service_handler("add_ints", add_two_ints)
    
    pyzlc.spin()

Client (Caller):

import pyzlc

pyzlc.init("ClientNode", "127.0.0.1")

# Wait for service to be discovered on the network
pyzlc.wait_for_service("add_ints")

# Call the service synchronously
response = pyzlc.call("add_ints", {"a": 10, "b": 20})
print(f"Result: {response['sum']}") # Output: 30

🛠 Advanced Usage

Data Streaming For high-frequency data (e.g., sensor readings), use the Streamer class to publish at a fixed FPS.

from pyzlc.sockets.publisher import Streamer
import random

def get_sensor_data():
    return {"temp": 20 + random.random(), "timestamp": time.time()}

# Create a streamer that calls get_sensor_data() 30 times per second
streamer = Streamer("sensor_stream", get_sensor_data, fps=30, start_streaming=True)

pyzlc.spin()

Custom Message Structures Because pyzlc uses msgpack, you can use Python TypedDict to define schemas, but you don't need special compilation steps.

from typing import TypedDict, List

class RobotState(TypedDict):
    id: int
    joints: List[float]
    active: bool

# The library handles serialization automatically
msg: RobotState = {"id": 1, "joints": [0.1, 1.2, -0.5], "active": True}
publisher.publish(msg)

🧩 Architecture

pyzlc uses a hybrid architecture to ensure reliability and speed:

• UDP Multicast: Used for node presence (Heartbeats) and discovery.
• TCP (ZeroMQ): Used for actual data transport (PUB/SUB and REQ/REP) to ensure reliable delivery.
• Loop Manager: A dedicated thread pool handles the asyncio event loop, allowing you to run blocking code alongside async communication if needed.

📋 Requirements

Python 3.8+

pyzmq

msgpack

colorama

🧪 Testing

Install the local test dependencies:

pip install -e ".[test]"

Run the default unit suite:

python -m pytest

Run optional integration tests that may use localhost sockets:

python -m pytest -m "integration"

Run optional benchmarks:

pip install -e ".[test,benchmark]"
python -m pytest -m "benchmark" --benchmark-only

Report coverage without enforcing a threshold:

python -m pytest --cov=pyzlc --cov-report=term-missing

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.