fluxly 0.2.1

A framework for building portable, self-contained DAG workflows decoupled from orchestration.

Fluxly — Lightweight framework for portable, self-contained DAG workflows, decoupled from orchestration.

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🚀 Introduction

Fluxly is a lightweight framework for building and running directed acyclic graph (DAG)-based workflows.

The entire workflow acts as a self-contained execution endpoint:

• Run them locally or via CLI commands, API calls, or environment triggers.
• Package them in containers for portability.
• Integrate seamlessly with higher-level orchestrators (Argo, Airflow, Prefect, CI/CD) without extra glue code.

With Fluxly, pipelines are highly structured, enabling safer execution, easier debugging, and better modularity.
Workflows can run standalone or as part of a larger system, making Fluxly both lightweight and flexible.

❓ Why Fluxly (the problem it solves)

• Unstructured container pipelines tend to become spaghetti: ad‑hoc scripts across containers, inconsistent inputs/outputs, and scattered retries/timeouts/logging with no shared wrapper.
• Heavyweight orchestrators like Airflow add operational burden (schedulers, DBs, webservers, DAG deployment) when all you need is a simple, portable workflow image.
• Orchestrator‑coupled SDKs (e.g., Prefect) optimize for remote control planes and persistent backends, introducing communication channels and runtime coupling that don’t fit autonomous, fire‑and‑forget jobs.
• Fluxly keeps logic structured and isolated inside a single codebase and container: typed I/O models, explicit DAG, uniform entrypoints (CLI/API/env), and clear node boundaries. Any scheduler can trigger it, but your workflow remains clean and portable.
• Best when each Docker stays simple and self‑sufficient, and you want clarity, low overhead, and no hidden glue.
• In monorepos—or by wrapping Fluxly—you can centralize shared services, typed inputs, validations, outputs, and metadata to fit your org standards. This thin wrapper standardizes containers and removes boilerplate across pipelines.

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🔌 Generated Entrypoints (CLI and API)

The package automatically exposes a CLI command and API endpoints for each registered workflow.

Auto-generated CLI commands per workflow.

Auto-generated API endpoints per workflow in Swagger UI.

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📚 Documentation

Comprehensive documentation for Fluxly is available online:

• View the docs: GitHub Pages

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✨ Key Features

• Flexible entrypoints – workflows can be triggered via CLI, API calls, or environment variables.
• DAG-based workflows – define arbitrary connections between nodes and their dependencies.
• Highly structured workflows – strict validation ensures safer pipelines, easier debugging, and predictable behavior.
• Self-orchestrated nodes – each node manages its own execution, retries, and dependencies.
• Lightweight building blocks – workflows are self-contained units that can run independently in any environment.
• Extensible by design – wrap workflows with custom classes to add logging, metrics, or integrations.
• Local-first development – debug and run workflows standalone, then scale seamlessly to CI/CD or external orchestrators.

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🛠️ Technology Stack

• Pydantic: Strict data validation and schema for inputs/outputs.
• Typer: Easy wrapper for building great CLIs.
• FastAPI: Modern, high-performance web framework for building APIs.
• Uvicorn: Lightning-fast ASGI server for running FastAPI apps.
• Loguru: Simple, efficient logging for Python.
• Diagrams: Auto-generate DAG diagrams as code.
• Pixi: Cross-platform package and environment management.
• Ruff: Lightning-fast linting.
• Mypy: Static type checking for Python, enforcing type safety and correctness.
• Coverage.py: Measures code coverage of tests for quality assurance.
• Pytest: Testing framework.
• MkDocs: Documentation generator for Markdown-based docs.
• Material for MkDocs: Modern, responsive theme for MkDocs.
• GitHub CI/CD: Continuous integration and deployment.

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📦 Installation

Install with pip:

pip install fluxly