pynenc-redis 0.1.4

Redis plugging for pynenc, a distributed task queue for Python.

Pynenc Redis Plugin

Redis backend implementation for Pynenc distributed task management

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Main Documentation: https://docs.pynenc.org

Source Code: https://github.com/pynenc/pynenc-redis

Pynenc Core: https://github.com/pynenc/pynenc

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The pynenc-redis plugin provides Redis-based implementations for Pynenc's core components, enabling distributed task orchestration with Redis as the backend. This plugin offers production-ready implementations for orchestration, message brokering, state management, argument caching, and trigger systems.

Overview

This plugin extends Pynenc with Redis-backed implementations for:

• RedisOrchestrator: Distributed task orchestration and coordination
• RedisBroker: Message queue and task distribution
• RedisStateBackend: Persistent state and result storage
• RedisArgCache: Efficient argument caching for large payloads
• RedisTrigger: Event-driven and scheduled task execution

Installation

Install the plugin using pip:

pip install pynenc-redis

The plugin automatically registers itself with Pynenc when installed.

Quick Start

Using PynencBuilder (Recommended)

The easiest way to configure Redis components is using the PynencBuilder:

from pynenc import PynencBuilder

# Basic Redis configuration
app = (
    PynencBuilder()
    .redis(url="redis://localhost:6379")
    .process_runner()
    .build()
)

@app.task
def add(x: int, y: int) -> int:
    return x + y

Configuration Options

Full Redis Stack

Configure all Redis components with a single call:

app = (
    PynencBuilder()
    .redis(url="redis://localhost:6379/0")  # With database number
    .multi_thread_runner()
    .build()
)

Or using individual parameters:

app = (
    PynencBuilder()
    .redis(db=1)  # Uses default host/port with specific database
    .process_runner()
    .build()
)

Redis Argument Cache

Configure Redis-based argument caching for large payloads:

app = (
    PynencBuilder()
    .redis(url="redis://localhost:6379")
    .redis_arg_cache(
        min_size_to_cache=1024,    # Cache arguments > 1KB
        local_cache_size=1000       # Keep 1000 entries in local cache
    )
    .build()
)

Redis Trigger System

Enable Redis-based triggers for scheduled and event-driven tasks:

app = (
    PynencBuilder()
    .redis(url="redis://localhost:6379")
    .redis_trigger(
        scheduler_interval_seconds=60,  # Check every minute
        enable_scheduler=True
    )
    .build()
)

Using pyproject.toml

Alternatively, configure Redis components in your pyproject.toml:

[tool.pynenc]
app_id = "my_app"
orchestrator_cls = "RedisOrchestrator"
broker_cls = "RedisBroker"
state_backend_cls = "RedisStateBackend"
arg_cache_cls = "RedisArgCache"
trigger_cls = "RedisTrigger"
runner_cls = "ProcessRunner"

[tool.pynenc.redis]
redis_url = "redis://localhost:6379/0"
# Or use individual parameters:
# redis_host = "localhost"
# redis_port = 6379
# redis_db = 0

Plugin Components

RedisOrchestrator

Manages task dependencies and execution flow using Redis:

• Atomic operations for task state transitions
• Efficient dependency tracking
• Batch processing for high-throughput scenarios
• Connection pooling and automatic reconnection

RedisBroker

Distributes tasks across workers:

• FIFO task queue with blocking pop operations
• Efficient batch routing
• Configurable timeouts and retry mechanisms
• Support for task priorities

RedisStateBackend

Persists task state and results:

• Invocation history and status tracking
• Result storage with TTL support
• Workflow data persistence
• App discovery and registration

RedisArgCache

Optimizes handling of large arguments:

• Automatic caching based on size thresholds
• LRU eviction for memory management
• Shared cache across processes
• Fingerprint-based deduplication

RedisTrigger

Enables event-driven task execution:

• Cron-based scheduling
• Task status change triggers
• Result-based triggers
• Custom event handling

Connection Configuration

The plugin supports multiple ways to configure Redis connections:

URL-based (Recommended)

.redis(url="redis://localhost:6379/0")
.redis(url="redis://:password@localhost:6379/0")
.redis(url="rediss://localhost:6380/0")  # SSL/TLS

Parameter-based

.redis(db=1)  # Uses REDIS_HOST and REDIS_PORT from config/env

Environment Variables

PYNENC__REDIS__REDIS_URL="redis://localhost:6379/0"
# Or individual parameters:
PYNENC__REDIS__REDIS_HOST="localhost"
PYNENC__REDIS__REDIS_PORT=6379
PYNENC__REDIS__REDIS_DB=0

Advanced Features

Connection Resilience

The plugin includes robust connection handling:

• Automatic reconnection with exponential backoff
• Configurable retry mechanisms
• Socket timeouts and health checks
• Connection pooling

Performance Optimization

• Batch processing for parallel task creation
• Pipeline operations for reduced network overhead
• Local caching to minimize Redis queries
• Efficient serialization strategies

Monitoring Integration

Works seamlessly with Pynenc's monitoring interface:

pynenc --app your_app monitor

Development and Testing

The plugin supports both development and production modes:

Development Mode

# Synchronous execution for testing
app = (
    PynencBuilder()
    .redis(url="redis://localhost:6379")
    .dev_mode(force_sync_tasks=True)
    .build()
)

Integration Testing

Integration tests use testcontainers to automatically manage Redis instances. Docker must be installed and running for integration tests to execute.

Run tests with:

poetry run pytest tests/integration/

Requirements

• Python >= 3.11.6
• Pynenc >= 0.0.24
• Redis >= 4.6.0
• A running Redis server

Documentation

For comprehensive documentation on Pynenc and its features, visit:

• Main Documentation: https://docs.pynenc.org
• API Reference: https://docs.pynenc.org/apidocs/
• Usage Examples: https://github.com/pynenc/samples

Contributing

Contributions are welcome! Please see the Contributing Guide for details.

License

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

Support

• Issues: https://github.com/pynenc/pynenc-redis/issues
• Discussions: https://github.com/pynenc/pynenc/discussions
• Main Project: https://github.com/pynenc/pynenc