A generic framework for on-demand, incrementalized computation.
Very much a WORK IN PROGRESS at this point. Ready for experimental use but expect frequent breaking changes.
This system is heavily inspired by adapton, glimmer, and rustc's query system. So credit goes to Eduard-Mihai Burtescu, Matthew Hammer, Yehuda Katz, and Michael Woerister.
The key idea of salsa is that you define your program as a set
of queries. Queries come in two basic varieties:
- Inputs: the base inputs to your system. You can change these whenever you like.
- Functions: pure functions (no side effects) that transform your inputs into other values. The results of queries is memoized to avoid recomputing them a lot. When you make changes to the inputs, we'll figure out (fairly intelligently) when we can re-use these memoized values and when we have to recompute them.
Using salsa is as easy as 1, 2, 3...
- Define one or more query context traits that contain the inputs and queries you will need. We'll start with one such trait, but later on you can use more than one to break up your system into components (or spread your code across crates).
- Implement the queries using the
query_definition!macro. - Implement the query context trait for your query context struct, which contains a full listing of all the inputs/queries you will be using. The query struct will contain the storage for all of the inputs/queries and may also contain anything else that your code needs (e.g., configuration data).
To see an example of this in action, check out the hello_world
example, which has a number of comments
explaining how things work. The hello_world
README has a more detailed writeup.