volnux

Introduction

Simplify complex process automation with a flexible, high-performance framework.

This library tackles the challenges of building reliable, scalable workflows by providing a clear separation between coordination and execution. It uses a declarative DSL, Pointy-Lang, to model your pipelines while managing the underlying complexity of concurrency, state, and task dependencies.

Build resilient automation that can handle anything from simple data processing to distributed, event-driven systems.

Features

• Define and manage events and pipelines in Python

• Support for conditional task execution

• Easy integration of custom event processing logic

• Supports remote task execution and distributed processing

• Seamless handling of task dependencies and event execution flow

Installation

To install the library, simply use pip:

pip install volnux

Requirements

• Python>=3.8

• ply==3.11

• treelib==1.7.0

• more-itertools<=10.6.0

• apscheduler<=3.11.0

• graphviz==0.20.3 (Optional)

Contents:

• Tutorials
  • Tutorials - Events
  • Tutorials - Pointy-lang
  • Tutorials - Pipeline
  • Tutorials - Batch Processing
• Pipeline
  • Defining Pipeline
  • Defining Input Data Field
  • Defining Pipeline Structure
  • Pointy Language Syntax
  • Executing Pipeline
  • Visualizing Pipeline
  • Batch Processing
• Events
  • Defining Events
  • Executor Configuration
  • Event Result Evaluation
  • Retry Policy
• Scheduling
  • Overview
  • CRON-based Scheduling
  • Interval-based Scheduling
  • One-time Scheduling
  • Advanced Configuration
  • Shutdown
• Signals
  • Overview
  • Default Signals
  • Connecting Signal Listeners
  • Best Practices
• Telemetry
  • Overview
  • Basic Usage
  • Network Telemetry
  • Metrics Publishing
  • Dashboard Templates
  • Installation
  • Custom Publishers
• Contributing
  • Getting Started
  • Development Setup
  • Running Tests
  • Code Style
  • Documentation
  • Making Changes
  • Pull Request Guidelines
  • Reporting Issues
  • License
• API Reference
  • API Reference - Events
  • API Reference - Pipeline
  • API Reference - Fields and Signals
  • API Reference - Scheduling
  • API Reference - Metrics
  • API Reference - Executors
  • API Reference - Managers
  • API Reference - Telemetry
  • API Reference - Results
  • API Reference - Backend
  • API Reference - Signals
  • API Reference - Mixins
  • API Reference - Parser
  • Core Components