jrutil | opaleye | |
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2 | 9 | |
- | 605 | |
- | - | |
- | 8.3 | |
- | about 1 month ago | |
Haskell | ||
- | BSD 3-clause "New" or "Revised" License |
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jrutil
- Soustrast se všemi kdo jedou domů vlakem
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Against SQL
I've also tried to rewrite some of my challenging queries [0] in my hypothetical syntax and while I think your observation about pipeline length is correct, the result still came out much better than SQL. Frankly, even in F#, most of my pipelines are around 5 functions too. In my view, pipelines are just a convenient mental model. I'd love to see your sketches, here are my (very WIP) concepts: [1]
[0]: for example this monstrosity: https://gitlab.com/dvdkon/jrutil/-/blob/dbb971c18526e68dcc97...
opaleye
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What's your favorite Database EDSL/library in Haskell?
If you ever have any questions about Opaleye I'm happy to help. Feel free to open an issue to ask about anything any time.
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Persistent vs. beam for production database
Sounds like Opaleye isn't on your list of choices, but if it is then feel free to ask me any questions, any time by filing an issue (I'm the Opaleye maintainer).
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How to build a large-scale haskell backend for a photo sharing app (some questions)
Opaleye is Posgres-only, and Postgres does such a good job of optimizing queries that performance issues basically don't arise. I have a long-standing invitation to improve Opaleye's query generation as soon as anyone can produce a repeatable example of a poorly-performing query. In Opaleye's eight years, no one ever has. There's a thread where two reports have come close, but it's still not clear that that's simply due to using a six year old version of Postgres.
- What are things that the Haskell scene lacks the most?
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Out of memory when building product-profunctors
Nice! Well done. If you have any more questions about product-profunctors or Opaleye then please let me know. It's best to ask by [opening an issue](https://github.com/tomjaguarpaw/haskell-opaleye/issues/new).
- Embedded Pattern Matching
- How to simply do opaleye field type conversion
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Against SQL
The only way out that I can see is to design embedded domain specific languages (EDSLs) that inherit the expressiveness, composability and type safety from the host language. That's what Opaleye and Rel8 (Postgres EDSLs for Haskell do. Haskell is particularly good for this. The query language can be just a monad and therefore users can carry all of their knowledge of monadic programming to writing database queries.
This approach doesn't resolve all of the author's complaints but it does solve many.
Disclaimer: I'm the author of Opaleye. Rel8 is built on Opaleye. Other relational query EDSLs are available.
[1] https://github.com/tomjaguarpaw/haskell-opaleye/
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Combining Deep and Shallow Embedding of Domain-Specific Languages
For an example of how this plays out in practice observe Opaleye's MaybeFields (generously contributed by Shane and /u/ocharles at Circuithub). The definition is essentially identical to Optional from the paper. Instead of a specialised typeclass Inhabited we use the ProductProfunctor NullSpec (which happens to conjure up an SQL NULL, but it could be any other witness).
What are some alternatives?
Preql - An interpreted relational query language that compiles to SQL.
esqueleto - Bare bones, type-safe EDSL for SQL queries on persistent backends.
fquery - A graph query engine
mywatch
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
HDBC - Haskell Database Connectivity
rel8 - Hey! Hey! Can u rel8?
database-migrate - database-migrate haskell library to assist with migration for *-simple sql backends.
PostgreSQL - Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
HongoDB - A Simple Key Value Store
squeal-postgresql - Squeal, a deep embedding of SQL in Haskell