Doc clarifications #604
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Doc clarifications #604
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| @@ -31,7 +31,7 @@ In practice, most programmers simply skip validation or implement it only partia | |||
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| ## Runtime checking | |||
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| Python 3 type annotations allow users to specify types for attributes and function returns, but these types are not normally checked at runtime, and so they do not have the same role of validating user input or programmer error as the type declarations in Params, Traits, Traitlets, pydantic, and attr. They also are limited to the type, so they cannot enforce constraints on range ('state' must be in the list ['Alabama', 'Alaska',...]). Thus even if type hinting is used, programmers still need to write code to actually validate the inputs to functions and methods, which is the role of packages like Param and Traitlets. Note that Pydantic focuses on [generating valid outputs at runtime](https://github.com/samuelcolvin/pydantic/issues/578focused) rather than detecting invalid inputs, so it may or may not be suitable for the same types of applications as the other libraries discussed here. | |||
| Python 3 type annotations allow users to specify types for attributes and function returns, but these types are not normally checked at runtime, and so they do not have the same role of validating user input or programmer error as the type declarations in Params, Traits, Traitlets, pydantic, and attr. They also are limited to the type, so they cannot enforce constraints on range ('state' must be in the list ['Alabama', 'Alaska',...]). Thus even if type hinting is used, programmers still need to write code to actually validate the inputs to functions and methods, which is the role of packages like Param and Traitlets. Note that Pydantic focuses on [generating valid outputs at runtime](https://github.com/samuelcolvin/pydantic/issues/578) rather than detecting invalid inputs, so it may or may not be suitable for the same types of applications as the other libraries discussed here. | |||
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Would it be an idea to add dataclasses to the list @jbednar ?
They are sort of the primitive that editors, IDEs, type checking tools will support and others like Param, Traitlets, Pydantic, attrs etc will have to conform to if they want to be aligned with the basics of Python parameters.
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Data classes are already listed on the page, but not discussed in detail. Contributions welcome!
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Minor fixes to docstrings, docs, and links, including not calling Parameter slots "parameters" and removing suggestions for installing dev releases that are likely to confuse most users.