Using strict data structures is usually the simplest way to regain predictability:
data QueryExpr
= RelVar !Text
| Restrict !ScalarExpr !QueryExpr
| Select !(HashMap Text ScalarExpr) !QueryExpr
| SummarizeBy !(Vector Text) !(HashMap Text ScalarExpr) !QueryExpr
Excessive strictness can cost you performance if you end up evaluating things you didn’t have to, but ASTs should probably be strict. Using Criterion for benchmarking helps find the sweet spot.
I have found Haskell’s library ecosystem quite good—any time I’ve needed a library, there has been a suitable one. In the rare case that changes are necessary, maintainers tend to be responsive and helpful. We probably just work on different kinds of software.
Comments
Using strict data structures is usually the simplest way to regain predictability:
Excessive strictness can cost you performance if you end up evaluating things you didn’t have to, but ASTs should probably be strict. Using Criterion for benchmarking helps find the sweet spot.I have found Haskell’s library ecosystem quite good—any time I’ve needed a library, there has been a suitable one. In the rare case that changes are necessary, maintainers tend to be responsive and helpful. We probably just work on different kinds of software.