pydantic
TypeScript
pydantic | TypeScript | |
---|---|---|
167 | 1,305 | |
18,617 | 98,060 | |
2.1% | 0.5% | |
9.8 | 9.9 | |
7 days ago | about 7 hours ago | |
Python | TypeScript | |
MIT License | Apache License 2.0 |
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.
pydantic
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Advanced RAG with guided generation
First, note the method prefix_allowed_tokens_fn. This method applies a Pydantic model to constrain/guide how the LLM generates tokens. Next, see how that constrain can be applied to txtai's LLM pipeline.
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utype VS pydantic - a user suggested alternative
2 projects | 15 Feb 2024
utype is a concise alternative of pydantic with simplified parameters and usages, supporting both sync/async functions and generators parsing, and capable of using native logic operators to define logical types like AND/OR/NOT, also provides custom type parsing by register mechanism that supports libraries like pydantic, attrs and dataclasses
- Pydantic v2 ruined the elegance of Pydantic v1
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Ask HN: Pydantic has too much deprecation. Why is it popular?
I like some of the changes from v1 to v2. But then you have something like this [0] removed from the library without proper documentation or replacement, resulting in ugly workarounds in the link that wont' work properly.
[0]: https://github.com/pydantic/pydantic/discussions/6337
- OpenAI uses Pydantic for their ChatCompletions API
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🍹GinAI - Cocktails mixed with generative AI
The easiest implementation I found was to use a PyDantic class for my target schema — and use that as a parameter for the method call to “ChatCompletion.create()”. Here’s a fragment of the GinAI Python classes used.
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FastStream: Python's framework for Efficient Message Queue Handling
Also, FastStream uses Pydantic to parse input JSON-encoded data into Python objects, making it easy to work with structured data in your applications, so you can serialize your input messages just using type annotations.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages
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Cannot get Langchain to work
Not sure if it is exactly related, but there is an open issue on Github for that exact message.
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FastAPI 0.100.0:Release Notes
Well the performance increase is so huge because pydantic1 is really really slow. And for using rust, I'd have expected more tbh…
I've been benchmarking pydantic v2 against typedload (which I write) and despite the rust, it still manages to be slower than pure python in some benchmarks.
The ones on the website are still about comparing to v1 because v2 was not out yet at the time of the last release.
pydantic's author will refuse to benchmark any library that is faster (https://github.com/pydantic/pydantic/pull/3264 https://github.com/pydantic/pydantic/pull/1525 https://github.com/pydantic/pydantic/pull/1810) and keep boasting about amazing performances.
On pypy, v2 beta was really really really slow.
TypeScript
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JSR Is Not Another Package Manager
Regular expressions are part of the language, so it's not so unreasonable that TypeScript should parse them and take their semantics into account. Indeed, TypeScript 5.5 will include [new support for syntax checking of regular expressions](https://github.com/microsoft/TypeScript/pull/55600), and presumably they'll eventually be able to solve the problem the GP highlighted on top of those foundations.
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TypeScript Essentials: Distinguishing Types with Branding
Dedicated syntax for creating unique subsets of a type that denote a particular refinement is a longstanding ask[2] - and very useful, we've experimented with implementations.[3]
I don't think it has any relation to runtime type checking at all. It's refinement types, [4] or newtypes[5] depending on the details and how you shape it.
[1] https://github.com/microsoft/TypeScript/blob/main/src/compil...
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What is an Abstract Syntax Tree in Programming?
GitHub | Website
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Smart Contract Programming Languages: sCrypt vs. Solidity
Learning Curve and Developer Tooling sCrypt is an embedded Domain Specific Language (eDSL) based on TypeScript. It is strictly a subset of TypeScript, so all sCrypt code is valid TypeScript. TypeScript is chosen as the host language because it provides an easy, familiar language (JavaScript), but with type safety. There’s an abundance of learning materials available for TypeScript and thus sCrypt, including online tutorials, courses, documentation, and community support. This makes it relatively easy for beginners to start learning. It also has a vast ecosystem with numerous libraries and frameworks (e.g., React, Angular, Vue) that can simplify development and integration with Web2 applications.
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Understanding the Difference Between Type and Interface in TypeScript
As a JavaScript or TypeScript developer, you might have come across the terms type and interface when working with complex data structures or defining custom types. While both serve similar purposes, they have distinct characteristics that influence when to use them. In this blog post, we'll delve into the differences between types and interfaces in TypeScript, providing examples to aid your understanding.
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Type-Safe Fetch with Next.js, Strapi, and OpenAPI
TypeScript helps you in many ways in the context of a JavaScript app. It makes it easier to consume interfaces of any type.
- Proposal: Types as Configuration
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How to scrape Amazon products
In this guide, we'll be extracting information from Amazon product pages using the power of TypeScript in combination with the Cheerio and Crawlee libraries. We'll explore how to retrieve and extract detailed product data such as titles, prices, image URLs, and more from Amazon's vast marketplace. We'll also discuss handling potential blocking issues that may arise during the scraping process.
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Shared Tailwind Setup For Micro Frontend Application with Nx Workspace
TypeScript
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Building a Dynamic Job Board with Issues Github, Next.js, Tailwind CSS and MobX-State-Tree
Familiarity with TypeScript, React and Next.js
What are some alternatives?
Cerberus - Lightweight, extensible data validation library for Python
zod - TypeScript-first schema validation with static type inference
nexe - 🎉 create a single executable out of your node.js apps
Flutter - Flutter makes it easy and fast to build beautiful apps for mobile and beyond
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
Tailwind CSS - A utility-first CSS framework for rapid UI development.
SQLAlchemy - The Database Toolkit for Python
zx - A tool for writing better scripts
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
esbuild - An extremely fast bundler for the web
mypy - Optional static typing for Python
gray-matter - Smarter YAML front matter parser, used by metalsmith, Gatsby, Netlify, Assemble, mapbox-gl, phenomic, vuejs vitepress, TinaCMS, Shopify Polaris, Ant Design, Astro, hashicorp, garden, slidev, saber, sourcegraph, and many others. Simple to use, and battle tested. Parses YAML by default but can also parse JSON Front Matter, Coffee Front Matter, TOML Front Matter, and has support for custom parsers. Please follow gray-matter's author: https://github.com/jonschlinkert