marshmallow
cattrs
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marshmallow | cattrs | |
---|---|---|
11 | 7 | |
6,865 | 750 | |
0.9% | 2.9% | |
8.8 | 8.9 | |
2 days ago | 11 days ago | |
Python | Python | |
MIT License | MIT License |
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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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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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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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Strict YAML deserialization in Python with marshmallow
I found a recommendation to use marshmallow to parse dict generated from JSON object. I decided that these cases are the same as mine only uses JSON instead of YAML. And so I tried to use class_schema generator for dataclass schema:
cattrs
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Writing Python like it’s Rust
I'd suggest you look at my cattrs (https://catt.rs) library as a good serde lookalike in Python (sum type support present and getting better), and to use attrs instead of dataclasses in general.
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Starlite updates March '22 | 2.0 is coming
Pydantic is by far not the only library of its kind, with prominent members of the same class being attrs, cattrs or even plain dataclasses for some use cases.
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apischema v0.17 - I've developed the fastest typed JSON (de)serialization library, and you can also build your GraphQL schema with it
This month, I've released version 0.17, and it's now blazing fast; there is in fact no more comparison with Pydantic, which more than 5x slower (up to 30x in serialization). It's also faster than alternatives like mashumaro or cattrs. (See the quick benchmark result in documentation, and the code)
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I use attrs instead of pydantic
```
Cattrs has some problems with generics [1] [2]. Dacite and marshmallow-dataclasses don't support generics well either, with some issues around Union types.
They do work well for simple python types but what I'd like to see is guarantee that the serialisation operation is completely reversible and if not raise warning/exception.
What are some alternatives?
Fast JSON schema for Python - Fast JSON schema validator for Python.
serpy - ridiculously fast object serialization
WTForms - A flexible forms validation and rendering library for Python.
jsonschema - JSON Schema validation library
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
pydantic - Data validation using Python type hints
Trafaret - Ultimate transformation library that supports validation, contexts and aiohttp.
jsons - 🐍 A Python lib for (de)serializing Python objects to/from JSON
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)
mashumaro - Fast and well tested serialization library