Fire: Simple CLIs done right

Fire: Simple CLIs done right

Fire: Simple CLIs done right. Creating CLIs can help improve accessibility and reuse of your ML pipelines, but they can be a pain to set up. Enter Fire.

What is Fire?

A few months ago, I had an enthusiastic outburst in which I expressed my appreciation for a little package called TQDM for creating progress bars. This post is in the same vein but this time for Fire: a great package that can make getting a Command Line Interfaces (CLI) up and running in (literally) a couple of seconds a breeze.

So, why write a CLI? Practically, a simple CLI can make configuring a script as simple as changing a couple of command line arguments. Let’s say you’ve got a script set up on an orchestration service (maybe something like Jenkins) that regularly retrains your latest and greatest Tweet sentiment classifier. Let’s say it’s a Scikit-Learn Random Forest. You might run the job as something like:

python tweet-classifier/train.py

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