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---
author: "Roland Thomas Jr"
title: "Falyx"
date: "2025-04-15"
description: ""
tags: ["post", "falyx", "cli"]
ShowToc: false
ShowBreadCrumbs: true
---
## 🛡️ Introducing Falyx: A Resilient CLI Framework for Modern Workflows
In the ever-evolving landscape of software development, tools that offer resilience, clarity, and introspection are invaluable.
Enter **Falyx**—a robust, asynchronous command-line interface (CLI) framework designed to streamline and fortify your workflows.
### ⚙️ What is Falyx?
Falyx is a Python-based CLI framework that empowers developers to build **modular**, **fault-tolerant** command-line applications. Inspired by the discipline and strength of a phalanx, Falyx ensures that each component of your workflow stands firm — even in the face of failure.
### 🚀 Key Features
- **Modular Action Chaining** Compose complex workflows by chaining together discrete actions, each with its own context and lifecycle.
- **Built-in Retry Mechanism** Handle flaky or transient failures with configurable retry policies, including exponential backoff.
- **Lifecycle Hooks** Inject logic at every stage: `before`, `after`, `on_success`, `on_error`, and `on_teardown`.
- **Execution Tracing** Built-in logging, result tracking, and timing for complete visibility.
- **Async-First Design** Built on `asyncio`, with optional multiprocessing via `ProcessAction`.
- **Extensible CLI Menus** Create interactive or headless menus using `prompt_toolkit` and `rich`, with support for history, tags, toggle states, and more.
### 🧪 Getting Started
Here's a simple example to illustrate how Falyx can be used to build a resilient CLI application:
```python
import asyncio
import random
from falyx import Falyx, Action, ChainedAction
# Define a flaky asynchronous step
async def flaky_step():
await asyncio.sleep(0.2)
if random.random() < 0.5:
raise RuntimeError("Random failure!")
return "ok"
# Create actions with retry enabled
step1 = Action(name="step_1", action=flaky_step, retry=True)
step2 = Action(name="step_2", action=flaky_step, retry=True)
# Chain the actions together
chain = ChainedAction(name="my_pipeline", actions=[step1, step2])
# Set up the CLI menu
falyx = Falyx("🚀 Falyx Demo")
falyx.add_command(
key="R",
description="Run My Pipeline",
action=chain,
logging_hooks=True,
preview_before_confirm=True,
confirm=True,
)
# Entry point
if __name__ == "__main__":
asyncio.run(falyx.run())
```
When run, this script presents an interactive CLI menu with built-in preview, confirmation, and retry handling.
```bash
python simple.py
🚀 Falyx Demo
[R] Run My Pipeline
[Y] History [Q] Exit
>
```
Or run headlessly using intuitive CLI arguments:
```bash
python simple.py run R
Command: 'R' — Run My Pipeline
└── ⛓ ChainedAction 'my_pipeline'
├── ⚙ Action 'step_1'
│ ↻ Retries: 3x, delay 1.0s, backoff 2.0x
└── ⚙ Action 'step_2'
↻ Retries: 3x, delay 1.0s, backoff 2.0x
Confirm execution of R — Run My Pipeline (calls `my_pipeline`) [Y/n] y
[2025-04-15 22:03:57] WARNING ⚠️ Retry attempt 1/3 failed due to 'Random failure!'.
✅ Result: ['ok', 'ok']
```
### 📈 Real-World Applications
Falyx is particularly well-suited for:
- **Automation Script**: Build resilient tools that self-heal from transient errors.
- **Data Pipelines**: Orchestrate complex data flows with retry logic and full observability.
- **Deployment Tooling**: Create safe deploys with preview, rollback, and confirmation baked in.
### 📚 Learn More
- 📖 [Source Code on GitHub](https://github.com/rolandtjr/falyx)
---
Falyx was designed for developers who dont just want CLI tools to **run** — they want them to **recover**, **report**, and **adapt**.
If that sounds like you, give it a spin and start building resilient command flows today.
> _"Like a phalanx: organized, resilient, and reliable."_ ⚔️
---