WebMock VS pydantic

If you want to check out an alternative to VCR, have a look at webmock.

Well, that's why your test says: "When the API responds like this I do that". People hate on ruby but webmock makes it very nice to mock/stub that, or for python there's responses. For the database you can use a local database with factories to easily create the data you need for each test and clear it between tests.

Man if you think python has great mocking/testing support, you check out some ruby tests! Honestly some of the best testing libraries that pioneered approaches that are becoming more common elsewhere, such as the expectations syntax. And now that I'm coding more in python I find myself missing libaries like webmock, letting you stub web reqests in a way that's agnostic of the HTTP/web libary, chef's kiss.

In order to keep our test suite faster and consistent, we need to mock our http requests. A simple and good way to achieve this is using the Webmock gem which allow easily mock the http responses for your requests.

We can avoid managing HTTP communication with our dependency. Instead, we'll stub out how we expect it to respond. In this case, we'll use webmock to stub out a response at the HTTP layer.

The other option is to mock the web requests to Hetzner - this: https://github.com/bblimke/webmock or similar may help.

There are fine istructions in WebMock README. I want to share it here for reference:

You can find the setup instructions and examples on how to use WebMock, in their github documentation. WebMock will prevent any external HTTP requests from your application so make sure you add this gem under the test group of your Gemfile.

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.

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.