falcon
pydantic
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falcon | pydantic | |
---|---|---|
9 | 167 | |
9,388 | 18,617 | |
0.4% | 4.3% | |
7.1 | 9.8 | |
11 days ago | 5 days ago | |
Python | 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.
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/
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?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Cerberus - Lightweight, extensible data validation library for Python
hug - Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler.
nexe - 🎉 create a single executable out of your node.js apps
Dependency Injector - Dependency injection framework for Python
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
connexion - Connexion is a modern Python web framework that makes spec-first and api-first development easy.
SQLAlchemy - The Database Toolkit for Python
apistar - The Web API toolkit. 🛠
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
restless - A lightweight REST miniframework for Python.
mypy - Optional static typing for Python