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Parse, Don't Validate (2019)

(lexi-lambda.github.io)
389 points melse | 2 comments | 26 Jun 21 07:23 UTC | HN request time: 0.41s | source
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Attummm ◴[26 Jun 21 08:18 UTC] No.27640130[source]▶
That's how the validation tool for Python Maat works. By creating a completely new dictionary. https://github.com/Attumm/Maat
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mulmboy ◴[26 Jun 21 10:34 UTC] No.27640762[source]▶
How does Maat compare with pydantic? https://github.com/samuelcolvin/pydantic
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rmnclmnt ◴[26 Jun 21 11:03 UTC] No.27640874[source]▶
If only for conciseness, readability and speed, I'd take Pydantic over any day. Being able to express 80% of type checking using Python native type hints + dataclasses is just so intuitive!

And it's getting some wide adoption, for instance FastAPI which uses it for request validations.

replies(1): >>27641020 #
1. Attummm ◴[26 Jun 21 11:34 UTC] No.27641020[source]▶
Engineering is about tradeoffs, even though both projects do validation.

The points you made are all very valid points.

At my employer we use both projects. If the data is very nested, or really large Maat is used.

replies(1): >>27641056 #
2. rmnclmnt ◴[26 Jun 21 11:42 UTC] No.27641056[source]▶
Mmmh interesting requirement! Indeed, defining very nested structure with Pydantic is one of its weaknesses.

And of course I agree 100% about tradoffs in engineering. However I usually advise against using 2 dependencies doing mainly the same thing if possible within the same project.

Anyway, good catch, thanks for enlightening me!