schemaorg VS pydantic

export class AboutComponent { private renderer = inject(Renderer2) private rendererFactory = inject(RendererFactory2) ngOnInit(): void { this.renderer = this.rendererFactory.createRenderer(null, null); this.addStructuredData(); } addStructuredData() { const script = this.renderer.createElement('script'); script.type = 'application/ld+json'; script.text = ` { "@context": "http://schema.org", "@type": "Organization", "name": "Your Angular App", "url": "https://your-angular-app.com", "logo": "https://your-angular-app.com/logo.png", "description": "Learn more about us at Your Angular App." }`; this.renderer.appendChild(document.head, script); } }

{` { "@context": "https://schema.org", "@type": "Article", "headline": "${post.title}", "image": "${post.image}", "author": "${post.author}", "publisher": { "@type": "Organization", "name": "My Blog", "logo": { "@type": "ImageObject", "url": "https://my-site.com/logo.png" } }, "datePublished": "${post.datePublished}" } `} script>

jsonresume-component is a web component that generates your resume with microdata following the Schema.org vocabulary set. It's custom element is and it fetches a resume.json file following the JSON Resume schema to create your resume. HTML is created from using the jsonresume-theme-microdata theme, creating a resume documented with microdata following the Schema.org vocabulary set.

type="application/ld+json"> { "@context": "https://schema.org/", "@type": "Recipe", "name": "Chocolate Chip Cookies", "image": "https://example.com/chocolate-chip-cookies.jpg", "description": "A classic recipe for delicious chocolate chip cookies.", // ... more recipe details ... }

Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond. Schema.org website

itemscope itemtype="https://schema.org/Person"> itemprop="name">Scott Nath Work History itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company ABC itemprop="description">...company description... itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Software developer itemprop="description">...details about role... itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company Meow itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Sitting Volunteer History itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company 501c3 itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Software developer for free itemprop="description">...details about role...

I've been re-writing the HTML of my site and added structured data, in the form of microdata attributes, following the Schema.org vocabulary set. Structured data can be understood by search engines and other machines, giving your content structure and context.

Implementing Structured Data Markup annotation system, which can provide additional context about the content to search engines. Structured data markup such as Schema.org can be used to aid search engines to understand the content relevance and significance. This approach can help improve search results by improved ranking and visibility of the content.

export default async function Page({ params }) { const product = await getProduct(params.id); const jsonLd = { "@context": "https://schema.org", "@type": "Product", name: product.name, image: product.image, description: product.description, }; return ( {/* Add JSON-LD to your page */} {/* ... */} section> ); }

I'm really surprised ijl got angry that his mail was quoted, it looks innocent enough to me.

For reference it's been edited out here: https://github.com/pydantic/pydantic/issues/589

But github shows edits, so the edit is meaningless for privacy. Here's the original mail (yes, I'm blatantly ignoring his request to not publish this, I'm just this evil.)

    I've looked into replacing ujson in pydantic with orjson

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.

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

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

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.

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.

Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages

Not sure if it is exactly related, but there is an open issue on Github for that exact message.