kotlin4example
pydantic
kotlin4example | pydantic | |
---|---|---|
1 | 167 | |
15 | 18,733 | |
- | 2.7% | |
6.0 | 9.8 | |
about 2 months ago | 7 days ago | |
Kotlin | Python | |
MIT License | MIT License |
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kotlin4example
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Technical documentation that just works
This tool seems like it is a nice markdown based CMS but I don't see too many features related to the more difficult parts of doing technical documentation. Like having working code samples.
I attempted a Kotlin centric documentation framework a while ago to address this: https://github.com/jillesvangurp/kotlin4example
I mainly use it to generate the documentation for my Elasticsearch Kotlin Client (jillesvangurp/es-kotlin-client). The idea there is that all examples and source samples are correctly compiling Kotlin code that I can get the output of when they run (e.g. a println). Running the tests, actually generates the documentation markdown. Using a dsl and multiline strings, I can mix lambda code blocks, markdown, or markdown inside files. For the lambda blocks, it figures out the source and line numbers using reflection. But it can also grab source samples based on comment markers. For bigger blobs of markdown, it's easier to grab the content from markdown files. For smaller sections of markdown, I can use inline multi line strings or a Kotlin DSL.
The main benefit of this is that my examples update as I change and refactor the code base. Also, since it runs as part of my tests, I know when examples break.
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.
What are some alternatives?
ltex-ls - LTeX Language Server: LSP language server for LanguageTool :mag::heavy_check_mark: with support for LaTeX :mortar_board:, Markdown :pencil:, and others
Cerberus - Lightweight, extensible data validation library for Python
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
nexe - 🎉 create a single executable out of your node.js apps
mike - Manage multiple versions of your MkDocs-powered documentation via Git
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
mkdocs-material - Documentation that simply works
SQLAlchemy - The Database Toolkit for Python
mkdocstrings - :blue_book: Automatic documentation from sources, for MkDocs.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
crystal-book - Crystal reference with language specification, manuals and learning materials
mypy - Optional static typing for Python