pydantic-core
falcon
Our great sponsors
pydantic-core | falcon | |
---|---|---|
18 | 9 | |
1,270 | 9,384 | |
3.1% | 0.4% | |
9.6 | 6.7 | |
3 days ago | 8 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
pydantic-core
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Is there a pydantic.BaseSettings equivalent in rust?
Funny that you ask... https://github.com/pydantic/pydantic-core Unfortunately it seems that the functionality you ask for is not (yet) part of this ...
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Investigating Pydantic v2's Bold Performance Claims
I encourage you to checkout the official benchmarks for more realistic and detailed examples, and, as always, YMMV.
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Pydantic V2 leverages Rust's Superpowers [video]
> to also be constrained by a separate set of data types which are legal in rust.
This isn't really how writing rust/python iterop works. You tend to have opaque handles you call python methods on. Here's a decent example I found skimming the code.
https://github.com/pydantic/pydantic-core/blob/main/src/inpu...
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Pydantic vs Protobuf vs Namedtuples vs Dataclasses
Thanks for pointing out to that, I did not know about it. Also attaching repo in case someone would be interested as well - https://github.com/pydantic/pydantic-core
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Introducing CodSpeed: Continuous Performance Measurement
pydantic-core: The core validation logic for pydantic, a Python data parsing and validation library.
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Show HN: Python framework is faster than Golang Fiber
pydandic-core [0] will hopefully solve this issue (written in Rust)
[0] -- https://github.com/pydantic/pydantic-core
- Scala or Rust? which one will rule in future?
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Rust for Data Engineering—what's the hype about? 🦀
LinkedIn influencers are weird lol. Rust v Python is apples and oranges. Rust would be glued together by python just like it does with C/C++ and Java/Spark today. We’re already seeing some packages go this direction, like pydantic v2 is rewriting its core validation in rust.
- Python file structure with Rust extensions
- Pydantic 2 rewritten in Rust was merged
falcon
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Is something wrong with FastAPI?
Falcon FastAPI Sanic Starlite (disclosure: I do work here)
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A Look on Python Web Performance at the end of 2022
Sanic is very very popular with 16.6k stars, 1.5k forks, opencollective sponsors and a very active github. Falcon is more popular than japronto with 8.9k stars, 898 forks, opencollective sponsors and a very active github too. Despite Japronto been keeped as first place by TechEmPower, Falcon is a way better solution in general with performance similar to fastify an very fast node.js framework that hits 575k requests per second in this benchmark.
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Flask vs FastAPI?
I prefer Falcon for kicking up an API.
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Python for everyone : Mastering Python The Right Way
Falcon
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Pyjion – A Python JIT Compiler
And here's a project that's mostly Python, and optionally uses Cython https://github.com/falconry/falcon
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2 Questions to Ask Before Choosing a Python Framework
To help with the above two cases I would consider using a microframework, and the Python community provides many solutions. In my professional career I’ve had the opportunity to work with three very good alternatives to Django: Flask, Falcon, and Fast API. Flask is designed to be easy to use and extend. It follows the principles of minimalism and gives more control over the app. Choosing it, developers can use multiple types of databases, which is not easy to do in Django. We can also plug in our favorite ORM and use it without any risk of unpredictable app behavior. In contrast to Django, it’s easy to integrate NoSQL databases with Flask.
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Do you know any Python projects on Github that are examples of best practices and good architecture?
This may not be exactly what you asked for but I found contributing to open source projects really exposed me to different approaches I never would have considered and may not have fully grasped had I not had to actually dive into the code to solve an issue. Falcon is a great place to start and the guys are super friendly there.
- Falcon 3.0 released!
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Designing rest APIs as a data engineer
https://falcon.readthedocs.io/en/stable/ https://fastapi.tiangolo.com/
What are some alternatives?
aiohttp-apispec - Build and document REST APIs with aiohttp and apispec
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
hug - Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler.
pymartini - A Cython port of Martini for fast RTIN terrain mesh generation
Dependency Injector - Dependency injection framework for Python
koda-validate - Typesafe, Composable Validation
connexion - Connexion is a modern Python web framework that makes spec-first and api-first development easy.
modin - Modin: Scale your Pandas workflows by changing a single line of code
apistar - The Web API toolkit. 🛠
typedload - Python library to load dynamically typed data into statically typed data structures
restless - A lightweight REST miniframework for Python.