Data Transformation
with Python at Scale

Coiled manages Dask for you in the cloud.

Run Python at Scale in your cloud

Get more work done with Coiled.

How it works

What's it like to use Dask and Coiled?

$ pip install coiled
$ coiled setup  # connect coiled to your cloud 
$ ipython
>>> import coiled, dask
>>> cluster = coiled.Cluster(n_workers=200)

>>> import dask.dataframe as dd    
>>> df = dd.read_parquet(
...     "s3://bucket/mydata.parquet",
... )

>>> df = df[df.balance < 0]
>>> df.to_parquet("s3://...")

>>> from optuna.integration.dask import DaskStorage
>>> def objective(...):
...     ...
>>> study = optuna.create_study(storage=DaskStorage())
>>> study.optimize(objective, ...)

>>> study.best_params
{"n_layers": ..., "optimizer": ...,  ...}
>>> futures = []
>>> for fn in filenames:
...     future = client.submit(process, fn)
...     futures.append(future)

>>> results = client.gather(futures)

Trusted by the best

Coiled Customers

Companies Using Dask

Python Users Switching from Spark to Dask

Companies Using Dask

Python Users Switching from Spark to Dask

Hear from Dask and
Coiled Users


"The speed is nice, sure, but the real benefit is taking a multi-day effort and finishing it in an afternoon. Coiled changed the character of our work."

Matt Plough

Software Engineer, KoBold Metals

"Coiled is a super simple way to launch a cluster with a simple API that's hard to break."

Eric Jeske

Head of Data Science, Telemetry

"Quite literally ‘burst to the cloud from your laptop’, everything I've been dreaming of since grad school."

Eric Ma

Principal Data Scientist, Moderna

Learn More

Familiar tools. Easy Setup. Rock-solid infrastructure. Check out the next steps to get started with Coiled.

$ pip install coiled
$ coiled setup
$ ipython
>>> import coiled
>>> cluster = coiled.Cluster(n_workers=500)