prism
pydantic
Our great sponsors
prism | pydantic | |
---|---|---|
25 | 167 | |
4,006 | 18,521 | |
2.4% | 3.8% | |
8.5 | 9.8 | |
4 days ago | 6 days ago | |
TypeScript | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
prism
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How to Automatically Consume RESTful APIs in Your Frontend
Since the OpenAPI can effectively describe our resources, we can reuse it to generate a dummy server that can be later used for development and testing purposes without bootstrapping any actual services. There some tools available that can help us with this task, such as Prism, OpenAPI Mock, OpenAPI Backend and the MSW library we have already seen.
- The most effective Schema-Driven Development using OpenAPI for Logistic Engineer
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Show HN: Generate JSON mock data for testing/initial app development
I use https://stoplight.io/open-source/prism with x-faker properties in my OpenAPI specs to mock APIs with dynamic content.
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Please recommend a good API Mocking tool
Haven't tried it yet, but discovered https://microcks.io/ yesterday. Otherwise https://stoplight.io/open-source/prism is pretty good
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Prism: a useful developer tool for OpenAPI specs
Prism does more than mocking; You can also use it to inspect any discrepancies between your API implementation and the API spec. You can find out more on their GitHub page:https://github.com/stoplightio/prism
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How do people deal with mocking CRUD operations for the purposes of testing?
use a mock API server that can read openapi spec (e.g. Prism)
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Faster time-to-market with API-first
prism
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install db locally or go with docker image for development?
What about skipping the DB all together and using OpenAPI w/ a Mock Server for local development https://openapi.tools/#mock personally like https://stoplight.io/open-source/prism
- Resurse utile pentru crearea unui REST API?
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Mock REST APIs with just OpenAPI YAML/JSON
Pretty simple to run [prism](https://github.com/stoplightio/prism) locally for free.
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?
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.
Cerberus - Lightweight, extensible data validation library for Python
msw - Seamless REST/GraphQL API mocking library for browser and Node.js.
nexe - 🎉 create a single executable out of your node.js apps
dredd - Language-agnostic HTTP API Testing Tool
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
backstage - Backstage is an open platform for building developer portals
SQLAlchemy - The Database Toolkit for Python
cli - Mockoon's official CLI. Deploy your mock APIs anywhere.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
sst - Build modern full-stack applications on AWS
mypy - Optional static typing for Python