🎯 Trackio

trackio is a lightweight alternative for wandb that uses Hugging Face Datasets for experiment logging and Gradio / Spaces for visualization.

Features

• API compatible with wandb.init, wandb.log, and wandb.finish (drop-in replacement: just use trackio instead of wandb)
• Persists logs in a private Hugging Face Dataset
• Visualize experiments with a Gradio dashboard locally or on Hugging Face Spaces
• Local-first design: dashboard runs locally by default. You can also host it on Spaces by specifying a space_id.
• Everything here, including hosting on Spaces, is free!

Trackio is designed to be lightweight (<1000 lines of Python code total), not fully-featured. It is designed in an extensible way and written entirely in Python so that developers can easily fork the repository and add functionality that they care about.

Installation

pip install trackio

or with uv:

uv pip install trackio

Usage

The usage of trackio is designed to be a drop-in replacement for wandb in most cases:

import trackio as wandb
import random
import time

runs = 3
epochs = 8

def simulate_multiple_runs():
    for run in range(runs):
        wandb.init(project="fake-training", config={
            "epochs": epochs,
            "learning_rate": 0.001,
            "batch_size": 64
        })
        
        for epoch in range(epochs):
            train_loss = random.uniform(0.2, 1.0)
            train_acc = random.uniform(0.6, 0.95)
    
            val_loss = train_loss - random.uniform(0.01, 0.1)
            val_acc = train_acc + random.uniform(0.01, 0.05)
    
            wandb.log({
                "epoch": epoch,
                "train_loss": train_loss,
                "train_accuracy": train_acc,
                "val_loss": val_loss,
                "val_accuracy": val_acc
            })
    
            time.sleep(0.2)

    wandb.finish()

simulate_multiple_runs()

Running the above will print to the terminal instructions on launching the dashboard.

Dashboard

You can launch the dashboard by running in your terminal:

$ trackio show

or, in Python:

trackio.show()

You can also provide an optional project name as the argument to load a specific project directly:

$ trackio show --project "my project"

or, in Python:

trackio.show(project="my project")

Deploying to Hugging Face Spaces

When calling trackio.init(), by default the service will run locally and collect data on the local machine.

If instead you pass a space_id to init, like:

trackio.init(space_id="org_name/space_name")

or

trackio.init(space_id="user_name/space_name")

it will use an existing or automatically deploy a new Hugging Face Space as needed. The current version of trackio is deployed to the specified space if it does not yet exist.

Embedding a Trackio Dashboard

One of the reasons we created trackio was to make it easy to embed live dashboards on websites, blog posts, or anywhere else you can embed a website.

If you are hosting your Trackio dashboard on Spaces, then you can embed the url of that Space as an IFrame. You can even use query parameters to only specific projects and/or metrics, e.g.

<iframe src="https://abidlabs-trackio-1234.hf.space/?project=fake-training&metrics=train_loss,train_accuracy" width=1600 height=500 frameBorder="0">

Supported query parameters:

• project: (string) Filter the dashboard to show only a specific project
• metrics: (comma-separated list) Filter the dashboard to show only specific metrics, e.g. train_loss,train_accuracy

License

MIT License