lax-nats-client 0.2.2

High-performance Python client for LAX NATS JetStream with smart routing

LAX NATS JetStream Python SDK

A high-performance Python client SDK for LAX NATS JetStream broker with intelligent routing between direct NATS (for ultra-low latency) and gRPC (for advanced features).

Perfect for FastAPI and other async Python applications.

Features

• 🚀 Smart Routing: Automatically routes to direct NATS (<1ms) or gRPC based on requirements
• 🔄 Async/Await: Built for modern async Python applications
• ⚡ FastAPI Ready: First-class FastAPI integration
• 🛡️ Circuit Breaker: Protects against cascading failures
• 📊 Prometheus Metrics: Built-in observability
• 🔁 Retry Logic: Configurable retry with exponential backoff
• 🏊 Connection Pooling: gRPC connection pool for high throughput
• 📨 Subscriptions: Stream processing with consumer groups and acknowledgments (v0.2.0+)
• 🎯 Load Balancing: Consumer groups for distributed message processing

Installation

pip install lax-nats-client

# For FastAPI integration
pip install lax-nats-client[fastapi]

Quick Start

import asyncio
from lax_client import LaxClient, PublishOptions, Tier

async def main():
    # Create client
    async with LaxClient() as client:
        # Publish to memory tier (uses direct NATS, <1ms latency)
        await client.publish(
            "events.user.login",
            {"user_id": "123", "ip": "192.168.1.1"}
        )
        
        # Publish to persistent tier (uses gRPC, guaranteed delivery)
        await client.publish(
            "orders.created",
            {"order_id": "456", "amount": 99.99},
            options=PublishOptions(
                tier=Tier.PERSISTENT,
                require_ack=True
            )
        )

asyncio.run(main())

FastAPI Integration

from fastapi import FastAPI, Depends
from contextlib import asynccontextmanager
from lax_client import LaxClient, ClientOptions

# Global client
lax_client = None

@asynccontextmanager
async def lifespan(app: FastAPI):
    global lax_client
    # Startup
    lax_client = LaxClient(ClientOptions(
        nats_urls=["nats://localhost:4222"],
        broker_addr="localhost:50051",
    ))
    await lax_client.connect()
    yield
    # Shutdown
    await lax_client.close()

app = FastAPI(lifespan=lifespan)

def get_client() -> LaxClient:
    return lax_client

@app.post("/events")
async def publish_event(
    data: dict,
    client: LaxClient = Depends(get_client)
):
    # Automatically uses direct NATS for memory tier
    message_id = await client.publish("events.api", data)
    return {"message_id": message_id}

@app.post("/orders")
async def create_order(
    order: dict,
    client: LaxClient = Depends(get_client)
):
    # Uses gRPC for persistent tier
    message_id = await client.publish(
        "orders.created",
        order,
        options=PublishOptions(tier=Tier.PERSISTENT, require_ack=True)
    )
    return {"order_id": order["id"], "message_id": message_id}

Configuration

from lax_client import ClientOptions

options = ClientOptions(
    # NATS settings
    nats_urls=["nats://nats1:4222", "nats://nats2:4222"],
    nats_connect_timeout=5.0,
    
    # gRPC settings
    broker_addr="broker:50051",
    connection_pool_size=20,
    
    # Performance tuning
    max_concurrent_publishes=1000,
    publish_timeout=5.0,
    retry_attempts=3,
    
    # Circuit breaker
    circuit_breaker_threshold=10,
    circuit_breaker_timeout=30.0,
    
    # Metrics
    enable_metrics=True,
    metrics_prefix="myapp_lax",
    
    # Logging
    log_level="INFO",
)

client = LaxClient(options)

Publishing Options

from lax_client import PublishOptions, Tier

# Memory tier (default) - Ultra fast, no persistence
await client.publish("topic", data)

# With specific tier
await client.publish(
    "topic", 
    data,
    options=PublishOptions(tier=Tier.PERSISTENT)
)

# Require acknowledgment (forces gRPC path)
await client.publish(
    "topic",
    data, 
    options=PublishOptions(require_ack=True)
)

# With headers and timeout
await client.publish(
    "topic",
    data,
    options=PublishOptions(
        tier=Tier.REPLICATED,
        headers={"trace-id": "abc123"},
        timeout=2.0
    )
)

# Batch publish for efficiency
messages = [
    {"subject": "events.click", "data": {"button": "submit"}},
    {"subject": "events.view", "data": {"page": "/home"}},
]
results = await client.batch_publish(messages)
print(f"Sent {results['success_count']} messages")

Subscriptions (v0.2.0+)

Basic Subscription

from lax_client import SubscribeOptions

# Iterator style
async for msg in client.subscribe("orders.*"):
    print(f"Received: {msg.get_data_as_json()}")
    await msg.ack()  # Acknowledge message

# Callback style
async def handler(msg):
    data = msg.get_data_as_json()
    print(f"Order: {data}")
    await msg.ack()

await client.subscribe("orders.*", callback=handler)

Consumer Groups

Create consumer groups for load-balanced message processing:

from lax_client import ConsumerGroupConfig

# Create/join a consumer group
group = await client.create_consumer_group(
    name="order-processors",
    stream="PERSISTENT_STREAM",
    subject_filter="orders.*",
    config=ConsumerGroupConfig(
        deliver_policy="new",  # Start with new messages
        max_deliver=3,         # Max redelivery attempts
        ack_wait_seconds=30    # ACK timeout
    )
)

# Subscribe as part of the group
async for msg in client.subscribe(
    "orders.*",
    consumer_group="order-processors",
    options=SubscribeOptions(
        max_inflight=10,      # Max unacked messages
        manual_ack=True,      # Require explicit ACK
        prefetch=5            # Prefetch for performance
    )
):
    try:
        # Process the message
        await process_order(msg.get_data_as_json())
        await msg.ack()
    except Exception as e:
        # Requeue for retry
        await msg.nack(delay=5.0)

Message Object

Received messages provide these methods:

msg.id              # Message ID
msg.subject         # Subject/topic
msg.data            # Raw bytes
msg.headers         # Headers dict
msg.sequence        # Stream sequence
msg.timestamp       # Message timestamp

# Helper methods
msg.get_data_as_string()  # Decode as string
msg.get_data_as_json()    # Parse as JSON
await msg.ack()           # Acknowledge
await msg.nack(delay=5)   # Requeue with delay

Smart Routing Logic

The SDK automatically chooses the optimal path:

Condition	Route	Latency	Use Case
tier=memory & require_ack=False	Direct NATS	<1ms	Events, metrics, logs
tier=persistent/replicated	gRPC to broker	10-50ms	Orders, payments
require_ack=True	gRPC to broker	10-50ms	Critical data

Performance

Based on benchmarks:

Method	Throughput	P99 Latency
Direct NATS (memory)	100k+ msg/sec	<5ms
gRPC (persistent)	5k msg/sec	50ms

Error Handling

from lax_client.exceptions import (
    PublishError,
    CircuitBreakerOpen,
    ConnectionError
)

try:
    await client.publish("topic", data)
except CircuitBreakerOpen:
    # Too many failures, circuit breaker is open
    logger.error("Circuit breaker open, service degraded")
except PublishError as e:
    # Publish failed after retries
    logger.error(f"Publish failed: {e}")
except ConnectionError as e:
    # Connection issues
    logger.error(f"Connection error: {e}")

Metrics

When enabled, Prometheus metrics are exposed:

# In your FastAPI app
from prometheus_client import generate_latest

@app.get("/metrics")
async def metrics():
    return Response(generate_latest(), media_type="text/plain")

Available metrics:

• lax_client_publish_total{tier,status}
• lax_client_publish_latency_seconds{tier,method}
• lax_client_direct_nats_total
• lax_client_grpc_total
• lax_client_circuit_breaker_state

Examples

See the examples directory for:

• Simple async usage
• FastAPI integration
• Performance testing

Development

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black lax_client/

# Type checking
mypy lax_client/

License

MIT License - see LICENSE file for details.