If you're new to Dagster, we recommend working through this tutorial to become familiar with Dagster's feature set and tooling, using small examples that are intended to be illustrative of real data problems.


The tutorial is divided into several sections:

Advanced Tutorials

These sections will introduce some advanced features and give you deeper insight into Dagster. It's worth reading if you have needs including things like:

What Are We Building?

We'll build examples around a simple but scary CSV dataset, cereal.csv, which contains nutritional facts about 80 breakfast cereals. You can find this dataset on Github. Or, if you've cloned the dagster git repository, you'll find this dataset at dagster/examples/dagster_examples/intro_tutorial/cereal.csv

To get the flavor of this dataset, let's look at the header and the first five rows:

100% Bran,N,C,70,4,1,130,10,5,6,280,25,3,1,0.33,68.402973
100% Natural Bran,Q,C,120,3,5,15,2,8,8,135,0,3,1,1,33.983679
All-Bran with Extra Fiber,K,C,50,4,0,140,14,8,0,330,25,3,1,0.5,93.704912
Almond Delight,R,C,110,2,2,200,1,14,8,-1,25,3,1,0.75,34.384843

You can find all of the tutorial code checked into the dagster repository.