Over the last couple of years, Coiled has made a cloud-SaaS application that runs Dask for folks smoothly and securely in the cloud. We thought you would like to hear a bit about the choices we made and why.

Along with the Cloud SaaS product, Coiled sells enterprise support for Dask. This article will be a more informal description of how we operate and why.

This blog post demonstrates how to output the contents of a Dask DataFrame to JSON files.

This post demonstrates how to speed up a pandas query to run 10 times faster with Dask using six performance optimizations.

This blog post explains how to read one or multiple CSV files into a Dask DataFrame with read_csv.

This post demonstrates how to merge Dask DataFrames and discusses important considerations when making large joins.

This post demonstrates how to read multiple Parquet files and write them into a single CSV file with just two lines of code.

With Dask’s map_partitions(), you can work on each partition of your Dask DataFrame, which is a pandas DataFrame, while leveraging parallelism for various custom workflows.