marshmallow
pydantic
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marshmallow | pydantic | |
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11 | 167 | |
6,888 | 18,521 | |
0.8% | 3.8% | |
8.7 | 9.8 | |
7 days ago | 7 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
marshmallow
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Help making draggable items for Flask app.
Somehow get a serializer going for your database models. I used marshmallow and flask-marshmallow
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Faster time-to-market with API-first
Uses a robust data validation library: validating payloads is a complex business. Your data validation library must handle optional and required properties, string formats like ISO dates and UUIDs (both dates and UUIDs are string types in OpenAPI), and strict vs loose type validation (should a string pass as an integer if it can be casted?). Also, in the case of Python, you need to make sure 1 and 0 don’t pass for True and False when it comes to boolean properties. In my experience, the best data validation libraries in the Python ecosystem are pydantic and marshmallow. From the above-mentioned libraries, flasgger and flask-smorest work with marshmallow.
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What's best library for swagger + flask?
I also came across things like Marsmallow and Blueprints, but don't know what these are, still reading about this as I write.
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pydantic VS marshmallow - a user suggested alternative
2 projects | 21 Sep 2022
Pydantic is a data validation library, marshmallow is a data validation library. None of the other libraries in the list of pydantic alternatives is a data validation library.
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Yet another object serialization framework!
I have been working on a package that is very similar in concept to marshmallow (https://marshmallow.readthedocs.io), but which adds a versioning mechanism to track changes in object structure across time, allowing you to migrate objects between different versions.
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How to implement conditional model
Either using meta programming: https://github.com/marshmallow-code/marshmallow/issues/585
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Should I use SQLAlchemy for a side project?
You might be surprised how much I agree - I recently opened an issue there hoping to discuss something like this (still awaiting response). https://github.com/marshmallow-code/marshmallow/issues/2000
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The Pocket Guide To API Request Validation You Wish You Had Earlier
Marshmallow
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Project Althaia - looking for performance/accuracy feedback on my shallow fork of marshmallow
I created a shallow fork of everyone's favourite marshmallow, to work around some performance issues while dumping data. The performance gain I measured is around 45%, but since it's a bad idea to rely on one's own testing, I was hoping that there are some folks here who use marshmallow in their projects, and who would be willing to try it out. Doubly so if your project has some unit tests in it, to confirm that nothing is broken due to my patches.
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What's the fastest way to parse JSON to output?
I was looking at https://github.com/marshmallow-code/marshmallow That's a nice library to use to parsing?
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?
Fast JSON schema for Python - Fast JSON schema validator for Python.
Cerberus - Lightweight, extensible data validation library for Python
cattrs - Composable custom class converters for attrs.
nexe - 🎉 create a single executable out of your node.js apps
serpy - ridiculously fast object serialization
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
WTForms - A flexible forms validation and rendering library for Python.
SQLAlchemy - The Database Toolkit for Python
jsonschema - JSON Schema validation library
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
mypy - Optional static typing for Python