Cerberus
pydantic
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Cerberus | pydantic | |
---|---|---|
3 | 166 | |
3,100 | 18,226 | |
0.6% | 4.2% | |
7.4 | 9.8 | |
5 months ago | 1 day ago | |
Python | Python | |
ISC License | 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.
Cerberus
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Show HN: Config-file-validator – CLI tool to validate all your config files
I was expecting this to validate the configuration files are also valid for their use cases, not just valid JSON, TOML, etc.
If you're looking for that and Python is your jam, the library cerberus[0] is very good at it.
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Do you think we need an open-source web scraping monitoring tool?
I wrote scrapy-test as a proof of concept for validating live pages for scrapy spiders if you're looking for some reference but if you're not using scrapy I'd recommend just adding validation tests using data validation tools like cerberus which is super underrated. I cover popular data validation techniques on this short blog I wrote if you want to learn more.
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Can you suggest something more to grow in scraping?
Other than that, have you looked into testing scrapers? Since scrapers are working with highly dynamic data writing good tests is quite a challange. For example, for parser monitoring using cerberus is a very cool tool which allows you to define loose requirements like "phone number should always be 9 numbers" etc.
pydantic
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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
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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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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.
- Pydantic 2.0
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[DISCUSSION] What's your favorite Python library, and how has it helped you in your projects?
As for the most utilized and still loved library, that would probably be pydantic, it helps declaring types so convenient - be it dto's, models or just complex arguments - and plays nice with bunch of other libraries from it's own ecosystem.
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popularity behind pydantic
I did read this ... Pydantic Docs.
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Guide to Serverless & Lambda Testing — Part 2 — Testing Pyramid
Schema validations logic — I use Pydantic for input validation and schema validation (boto responses, API responses, input validation, etc.) use cases. The Pydantic schema can contain type and value constraint checks or even more complicated logic with the custom validator code.
What are some alternatives?
jsonschema - An implementation of the JSON Schema specification for Python
nexe - 🎉 create a single executable out of your node.js apps
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
SQLAlchemy - The Database Toolkit for Python
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
schema - Schema validation just got Pythonic
mypy - Optional static typing for Python
pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]
phonenumbers - Python port of Google's libphonenumber
dacite - Simple creation of data classes from dictionaries.
Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
beanie - Asynchronous Python ODM for MongoDB