lleaves
zod
lleaves | zod | |
---|---|---|
4 | 291 | |
300 | 30,630 | |
- | - | |
6.7 | 9.1 | |
about 1 month ago | 4 days ago | |
Python | TypeScript | |
MIT License | MIT License |
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lleaves
- LLeaves: A LLVM-based compiler for LightGBM decision trees
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Cold Showers
I built this decision tree (LightGBM) compiler last summer: https://github.com/siboehm/lleaves
It get's you ~10x speedups for batch predictions, more if your model is big. It's not complicated, it ended up being <1K lines of Python code. I heard a couple of stories like yours, where people had multi-node spark clusters running LightGBM, and it always amused me because by if you compiled the trees instead you could get rid of the whole cluster.
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Tree compiler that speeds up LightGBM model inference by ~30x
In a near-future version I'll expose some of the compilation parameters, I was somewhat afraid of having an API that's too complicated deterring people who just want a no-fuzz drop-in replacement for LightGBM. But as long as I keep sane defaults and have the parameters optional it should be fine. Relevant parameters are definitely block size (needs to adjust to L1i size and tree size) as well as the LLVM codemodel (a smaller adress space increases single-batch prediction speeds but doesn't work for large models). The thread-size specific compilation I'm still looking into, it makes the API more complicated and so might not be worth it.
zod
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Simplifying Form Validation with Zod and React Hook Form
[Zod Documentation](https://zod.dev/) [Zod Error Handling](https://zod.dev/ERROR_HANDLING?id=error-handling-in-zod) [React-Hook-Form Documentation](https://react-hook-form.com/get-started) [Hookform Resolvers](https://www.npmjs.com/package/@hookform/resolvers)
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Figma's Journey to TypeScript
This is a very fair comment, and you seem open to understanding why types are useful.
"problems that are due to typing" is a very difficult thing to unpack because types can mean _so_ many things.
Static types are absolutely useless (and, really, a net negative) if you're not using them well.
Types don't help if you don't spend the time modeling with the type system. You can use the type system to your advantage to prevent invalid states from being represented _at all_.
As an example, consider a music player that keeps track of the current song and the current position in the song.
If you model this naively you might do something like: https://gist.github.com/shepherdjerred/d0f57c99bfd69cf9eada4...
In the example above you _are_ using types. It might not be obvious that some of these issues can be solved with stronger types, that is, you might say that "You rarely see problems that are due to typing".
Here's an example where the type system can give you a lot more safety: https://gist.github.com/shepherdjerred/0976bc9d86f0a19a75757...
You'll notice that this kind of safety is pretty limited. If you're going to write a music app, you'll probably need API calls, local storage, URL routes, etc.
TypeScript's typechecking ends at the "boundaries" of the type system, e.g. it cannot automatically typecheck your fetch or localStorage calls return the correct types. If you're casting, you're bypassing the type systems and making it worthless. Runtime type checking libraries like Zod [0] can take care of this for you and are able to typecheck at the boundaries of your app so that the type system can work _extremely_ well.
[0]: https://zod.dev/ note: I mentioned Zod because I like it. There are _many_ similar libraries.
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From Flaky to Flawless: Angular API Response Management with Zod
Zod is an open-source schema declaration and validation library that emphasizes TypeScript. It can refer to any data type, from simple to complex. Zod eliminates duplicative type declarations by inferring static TypeScript types and allows easy composition of complex data structures from simpler ones. It has no dependencies, is compatible with Node.js and modern browsers, and has a concise, chainable interface. Zod is lightweight (8kb when zipped), immutable, with methods returning new instances. It encourages parsing over validation and is not limited to TypeScript but works well with JavaScript as well.
- TypeScript Essentials: Distinguishing Types with Branding
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You can’t run away from runtime errors using TypeScript
Zod is a TypeScript-first schema declaration and validation library. It helps create schemas for any data type and is very developer-friendly. Zod has the functional approach of "parse, don't validate." It supports coercion in all primitive types.
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Best Next.js Libraries and Tools in 2024
Link: https://zod.dev/
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Popular Libraries For Building Type-safe Web Application APIs
You can check out their documentation here.
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Epic Next JS 14 Tutorial Part 4: How To Handle Login And Authentication in Next.js
You can learn more about Zod on their website here.
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What even is a JSON number?
In JS, it's a good idea anyway to use some JSON parsing library instead of JSON.parse.
With Zod, you can use z.bigint() parser. If you take the "parse any JSON" snippet https://zod.dev/?id=json-type and change z.number() to z.bigint(), it should do what you are looking for.
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Error handling in our form component for the NextAuth CredentialsProvider
We will validate our input using client-side zod. Zod handles TypeScript-first schema validation with static type inference. This means that it will not only validate your fields, it will also set types on validated fields.
What are some alternatives?
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
class-validator - Decorator-based property validation for classes.
ngboost - Natural Gradient Boosting for Probabilistic Prediction
joi - The most powerful data validation library for JS [Moved to: https://github.com/sideway/joi]
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
typebox - Json Schema Type Builder with Static Type Resolution for TypeScript
miceforest - Multiple Imputation with LightGBM in Python
Yup - Dead simple Object schema validation
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
ajv - The fastest JSON schema Validator. Supports JSON Schema draft-04/06/07/2019-09/2020-12 and JSON Type Definition (RFC8927)
io-ts - Runtime type system for IO decoding/encoding
Superstruct - A simple and composable way to validate data in JavaScript (and TypeScript).