esqueleto
FrameworkBenchmarks
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esqueleto | FrameworkBenchmarks | |
---|---|---|
5 | 366 | |
177 | 7,384 | |
0.0% | 1.2% | |
0.0 | 9.8 | |
over 7 years ago | 2 days ago | |
Haskell | Java | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
esqueleto
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Revisiting Haskell after 10 years
Writing Haskell programs that rely on third-party packages is still an issue when it’s a not actively maintained package. They get out of date with the base library (Haskell’s standard library), and you might see yourself in a situation where you need to downgrade to an older version. This is not exclusive to Haskell, but it happens more often than I’d like to assume. However, if you only rely on known well-maintained libraries/frameworks such as Aeson, Squeleto, Yesod, and Parsec, to name a few, it’s unlikely you will face troubles at all, you just need to be more mindful of what you add as a dependency. There’s stackage.org now, a repository that works with Stack, providing a set of packages that are proven to work well together and help us to have reproducible builds in a more manageable way—not the solution for all the cases but it’s good to have it as an option.
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How to use PostgreSQL with Haskell: persistent + esqueleto
However, we can use Esqueleto (”a bare bones, type-safe EDSL for SQL queries”) with Persistent's serialization to write type-safe SQL queries. It’s unlikely that you want to use Persistent by itself with SQL, so let’s use and review them together.
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What databases do you find the most productive to connect to Haskell?
Postgresql-simple is a great library, it makes a nice use of overloaded strings to do the job. Some other nice libraries to keep an eye on are opaleye (postgres specific, which is equally nice but could be a bit difficult to get why the types are so big) and a combination of persistent (not DB specific! can work on postgres, sqlite, but also noSQL DBs like mongo, it's still easy to learn but you lose some things, such as joins due to the power of being agnostic) + esqueleto for type safe joins (be sure to look up the experimental package, it's a more comfortable syntax that will soon become the default one).
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Notes on Luca Palmieri's Zero to Production in Rust
Using esqueleto in one of my haskell projects was a huge time sink and a major barrier to entry for colleagues.
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Go performance from version 1.2 to 1.18
In Haskell: https://hackage.haskell.org/package/esqueleto
Either it analyzes the given SQL to determine the in/out types of each SQL query, or it calls the database describe feature at compile-time.
FrameworkBenchmarks
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Why choose async/await over threads?
Neat. Thanks for sharing!
Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].
[1] https://www.techempower.com/benchmarks/
[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
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Ntex: Powerful, pragmatic, fast framework for composable networking services
ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.
ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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A decent VS Code and Ruby on Rails setup
Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.
It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.
If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.
*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources
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The Erlang Ecosystem [video]
Although that seems to have improved in recent years.
https://www.techempower.com/benchmarks/#hw=ph&test=json§...
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Ruby 3.3
RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.
On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.
https://www.techempower.com/benchmarks
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API: Go, .NET, Rust
Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.
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Rage: Fast web framework compatible with Rails
There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.
And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.
https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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Node.js – v20.8.1
oh what machine? with how many workers? doing what?
search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21
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Strong typing, a hill I'm willing to die on
JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...
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Rust vs Go: A Hands-On Comparison
In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21
Or, at least, they would be after applying optimizations to them.
In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.
What are some alternatives?
opaleye
zio-http - A next-generation Scala framework for building scalable, correct, and efficient HTTP clients and servers
yxdb-utils - Utilities for parsing Alteryx Database format
drogon - Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows [Moved to: https://github.com/drogonframework/drogon]
groundhog - This library maps datatypes to a relational model, in a way similar to what ORM libraries do in OOP. See the tutorial https://www.schoolofhaskell.com/user/lykahb/groundhog for introduction
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
hocilib - A lightweight Haskell binding to the OCILIB C API
LiteNetLib - Lite reliable UDP library for Mono and .NET
beam - A type-safe, non-TH Haskell SQL library and ORM
C++ REST SDK - The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
mysql-simple - A mid-level client library for the MySQL database, intended to be fast and easy to use.
SQLBoiler - Generate a Go ORM tailored to your database schema.