json-parser-in-typescript-very-bad-idea-please-dont-use
pydantic
json-parser-in-typescript-very-bad-idea-please-dont-use | pydantic | |
---|---|---|
4 | 167 | |
431 | 18,854 | |
- | 3.3% | |
0.0 | 9.8 | |
over 3 years ago | 7 days ago | |
TypeScript | Python | |
- | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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json-parser-in-typescript-very-bad-idea-please-dont-use
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Python Type Hints Are Turing Complete
[1]: https://github.com/jamiebuilds/json-parser-in-typescript-ver...
- TypeScript Tricks I wish I knew when I learned TypeScript
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Type-safe regular expression matching with named capture groups
Also, shoutout to this guy who implemented a json parser in typescript types. This is what gave me the idea.
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I need to learn about TypeScript Template Literal Types
The next examples get progressively more bonkers, so I'm not going to write down all my thinking about them - you should check them out though and see if you can see how they work. The JSON parser is probably the best mix of complex and readable.
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?
xlcalculator - xlcalculator converts MS Excel formulas to Python and evaluates them.
Cerberus - Lightweight, extensible data validation library for Python
python-typing-machines - Python type hints are Turing complete.
nexe - 🎉 create a single executable out of your node.js apps
awesome-template-literal-types - Curated list of awesome Template Literal Types examples
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
typanion - Static and runtime type assertion library with no dependencies
SQLAlchemy - The Database Toolkit for Python
typing-euler - Typing Euler because values are code smells
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
json-parser-in-typescript-ver
mypy - Optional static typing for Python