pyyaml
marshmallow
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pyyaml | marshmallow | |
---|---|---|
16 | 11 | |
2,425 | 6,888 | |
1.3% | 0.8% | |
3.9 | 8.7 | |
7 days ago | 2 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.
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.
pyyaml
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Cython 3.0 Released
PyYAML knew about the breakage since january 2022[0], and nothing really happened. After a year and a half with lots of alphas and betas, I don't think there is much cython could do, short of fixing PyYAML themselves.
- Cython v3 release breaking PyYAML install well used in Python ecosystem
- Cython and pyyaml is breaking many builds
- I'm needing a hand, I do not understand some (seemingly) simple Python stuff.
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is there any difference between using string.format() or an fstring?
They did finally change the default, in PyYAML 6, after many many bugs pointing out that their previous approach is broken (including one by yours truly), so the default is now safe.
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Using Rust to not have to touch Yaml in k8s land
Note some parsers, most notably pyyaml are still at yaml 1.1, because 13 years is just not enough time to update it.
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JSON is not a YAML subset
That part of the YAML 1.2 spec is in conflict with reality, though. The base of YAML 1.1 documents is large enough that a backwards-incompatible change to default behavior is for practical purposes impossible.
YAML 1.1 was released in 2005, and 1.2 in 2009 -- only four years later. But here we are, in 2022, and YAML 1.1 is still the default (in many cases, only) version supported. That's why the "Norway problem" persists -- it's not possible for the parser to know whether an un-versioned YAML document containing "a: no" should parse the same as {"a": false} or {"a": "no"}.
Python (PyYAML) doesn't support 1.2 yet: https://github.com/yaml/pyyaml/issues/116
Ruby (Psych) ditto -- I can't even find a tracking issue to enable it.
Go (go-yaml) is a mixture of YAML 1.1 and 1.2, depending on the author's preferences.
Also, as a rough guideline, you can't have a backwards-incompatible revision of a versioned spec declare that it's the new default version, because that breaks all existing users.
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I accidentally used YAML.parse instead of JSON.parse, and it worked?
Many parsers either default to YAML pre-1.2 or do not even expose a YAML 1.2 option. PyYAML has no 1.2 option, for example. So unless Ansible is using something other than PyYAML...
Relevant (open) PR: https://github.com/yaml/pyyaml/pull/555
- AttributeError: '_io.TextIOWrapper' object has no attribute 'items'
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Why doesn't yaml allow safe_dump for decimals?
Are you perhaps talking about decimal.Decimal? https://github.com/yaml/pyyaml/issues/255
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?
What are some alternatives?
confuse - painless YAML config files for Python
Fast JSON schema for Python - Fast JSON schema validator for Python.
strictyaml - Type-safe YAML parser and validator.
cattrs - Composable custom class converters for attrs.
yamllint - A linter for YAML files.
serpy - ridiculously fast object serialization
jsonnet - Jsonnet - The data templating language
WTForms - A flexible forms validation and rendering library for Python.
python-strict-yaml-parsing - Examples of strict yaml parsing in python
jsonschema - JSON Schema validation library
python-frontmatter - Parse and manage posts with YAML (or other) frontmatter
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings