[python-nextgen] optionally support float strict type

[wing328]

• optionally support float strict type via the option "floatStrictType" (default to true)
• add a test

To close #14499

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FYI @taxpon (2017/07) @frol (2017/07) @mbohlool (2017/07) @cbornet (2017/09) @kenjones-cisco (2017/11) @tomplus (2018/10) @arun-nalla (2019/11) @spacether (2019/11) @krjakbrjak (2023/02)

[tomplus]

LGTM

[spacether]

This code path is used for json schema number (float + int) and float only processing. Number should allow both in.

How about:

• not adding the strict info when it is number with no format
• adding it when it is float only
• adding tests of both of those cases (number vs float only) with and without strict on

[wing328]

It's an option so users can choose whether they want float in strict type or not.

[spacether]

Right but that option should only apply to floats right? The way it is now looks like you are applying float strict when the spec has type: number which should allow in float and int. Did I misunderstand something?

[wing328]

-    number: confloat(strict=True, le=543.2, ge=32.1) = ...
-   float: Optional[confloat(strict=True, le=987.6, ge=54.3)] = None
-    double: Optional[confloat(strict=True, le=123.4, ge=67.8)] = None
+    number: confloat(le=543.2, ge=32.1) = ...
+    float: Optional[confloat(le=987.6, ge=54.3)] = None
+    double: Optional[confloat(le=123.4, ge=67.8)] = None

As illustrated in the sample diff as part of this change, the option (when set to false) simply removes strict=True.

[spacether]

Why are you applying strict float to type number with no format? Won't it throw a validation error if an integer input is given to it? Integer input is valid for that definition per
https://json-schema.org/understanding-json-schema/reference/numeric.html#number

[wing328]

Why are you applying strict float to type number with no format?

It's a user decision - they can switch on or off strict mode via an option.

You can find more about why some users prefer strict mode in https://docs.pydantic.dev/blog/pydantic-v2/#strict-mode.

[aimxhaisse]

Thanks a lot for doing this :)