pydantic
dacite
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pydantic | dacite | |
---|---|---|
167 | 4 | |
18,617 | 1,659 | |
4.3% | - | |
9.8 | 3.2 | |
2 days ago | 5 months ago | |
Python | Python | |
MIT License | MIT License |
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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.
dacite
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What's the difference between using and not using wrapper libraries for APIs?
This is a good approach, but FYI there are already very good libraries that can be used to create objects from JSON/dicts in a similar way to your example, like dacite or pydantic. A lot of boilerplate can be avoided with these.
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Project files for my own python GUI
You'll need to be able to serialize ProjectState objects into some file format that you can save to disk, like json. When working with dataclasses, dacite can also be very helpful to convert to/from dictionaries. (There's other options available, of course.)
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Master Dataclasses in Python Part 1 - Basic Structure and Validation
You also can't read any nested dataclassed from a dictionary. dacite! will help with this, but witihout it you can't just initialize it with NestedDataclass(**some_dict) or somethings like this. In the way it works for Plain dataclass.
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A look the new pattern matching in Python 3.10.0a6
There are also tools such as dacite and desert, which take a different approach to dealing with serialized data
What are some alternatives?
Cerberus - Lightweight, extensible data validation library for Python
dataclasses-json - Easily serialize Data Classes to and from JSON
nexe - 🎉 create a single executable out of your node.js apps
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
python-youtube - A simple Python wrapper for YouTube Data API :sparkles: :cake: :sparkles: .
SQLAlchemy - The Database Toolkit for Python
dataclassy - A fast and flexible reimplementation of data classes
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
jmespath.py - JMESPath is a query language for JSON.
mypy - Optional static typing for Python
pokebase - Python 3 wrapper for Pokéapi v2