dstack is an open-source platform to build and share data and ML applications within hours

Installation

Installing and running

dstack

pip install dstack
dstack server start

If you run it for the first time, it may take a while. Once it's done, you'll see the following output:

To access the application, open this URL in the browser: http://localhost:8080/auth/verify?user=dstack&code=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx&next=/

The default profile in "~/.dstack/config.yaml" is already configured. You are welcome to push your applications using Python package.

To access

dstack

dstack

If you open the URL, you'll see the following interface:

You'll be logged as the

dstack

Applications

ML Models

Settings

Documentation

Chat

Minimal Application

Here's an elementary example of using

dstack

import dstack.controls as ctrl
import dstack as ds
import plotly.express as px


@ds.cache()
def get_data():
    return px.data.stocks()
def output_handler(self, ticker):
    self.data = px.line(get_data(), x='date', y=ticker.value())
app = ds.app(controls=[(ctrl.ComboBox(items=get_data().columns[1:].tolist()))],
             outputs=[(ctrl.Output(handler=output_handler))])
result = ds.push("minimal_app", app)
print(result.url)

If you run it and click the provided URL, you'll see the application:

To learn about how this application works and to see other examples, please check out the Tutorials documentation page.

To learn in more detail about what applications consist of and how to use all their features, check out the Concepts documentation page.

ML Models

dstack

ML registry

dstack

ML Registry

Tensorflow

PyTorch

Scikit-Learn

Here's a very simple example of how to push a model to

dstack

from sklearn import datasets
from sklearn import svm
import dstack as ds

digits = datasets.load_digits()
clf = svm.SVC(gamma=0.001, C=100.)
clf.fit(digits.data[:-1], digits.target[:-1])
url = ds.push("clf_app", clf)
print(url)

Now, if you click the URL, it will open the following page:

Here you can see the snippet of how to pull the model from an application or from anywhere else:

import dstack as ds

model = ds.pull('/dstack/clf_app')

To learn how to build an application that uses a simple ML model, check out the corresponding tutorial.

Feedback

Do you have any feedback either minor or critical? Please, file an issue in our GitHub repo or write to us on our Discord Channel.

Have you tried

dstack

Documentation

For more details on the API and code samples, check out the docs.

Contribution

The instructions on how to build dstack from sources can be found here.

License

dstack