Now that you’re set up, let’s get an overview of Dagster!
hello_pipeline example, you may find that there are some new concepts that you are not
familiar with, such as solids and pipelines. The pipeline can be visualized as above, in which
get_name returns a name of
'dagster' and passes that output to the solid
With these basic Dagster concepts, we'll give more concrete definitions of these terms:
Solid: a solid is a functional unit of computation with defined inputs and outputs.
Pipeline: in Dagster, pipelines are directed acyclic graphs (DAGs) of solids – that is, they are made up of a number of solids which have data dependencies on each other (but no circular dependencies).
Output: an output is how a solid’s compute function communicates the name and value of an output to Dagster.
Dependencies: solids are linked together into pipelines by defining the dependencies between their inputs and outputs. An important difference between Dagster and other workflow systems is that in Dagster, dependencies are expressed as data dependencies ("A requires a particular output from B"), not only ordering dependencies ("A runs after B").
You can learn more about Dagster concepts by reading Overviews section.