This is great. Alexis King actually stated that, had she known how popular “Parse, Don’t Validate” had been, she would have written it in a language more widely used than Haskell.
With its crap type system Python might be even better, in a strange way.
Haskell's strong, static, non-reflective type system tends to make "parse, don't validate" produce code that also looks nicer. Which is great. So great that it steals a bit of the main message's valor.
In Python, though, it's really easy to just let your data be a dynamically typed list of dicts forever. So easy that parsing into something more strongly typed looks like a whole lot of extra effort. Upon looking at that sort of thing many a working Python programmer, myself included, hears the voice of GvR murmuring disparaging things about "academic" programmers down in the pit of their brain.
Which creates an opportunity to demonstrate all the ways the (arguably) more Pythonic way is actually a royal PITA when you try to make your code robust. Handling and reporting data validity errors gets scattered all over the code, which makes it annoying to maintain. Unit test suites get bloated because it's not obvious what inputs a function should be able to handle. Comments and docstrings to help keep track of this stuff begin to proliferate.
I'm the author of typedload. For json-type of data that is loaded in dictionaries you can do A LOT of validation at runtime automatically if you define the types.
jelder · · focus · HN ↗
esafak · · focus · HN ↗
bunderbunder · · focus · HN ↗
Haskell's strong, static, non-reflective type system tends to make "parse, don't validate" produce code that also looks nicer. Which is great. So great that it steals a bit of the main message's valor.
In Python, though, it's really easy to just let your data be a dynamically typed list of dicts forever. So easy that parsing into something more strongly typed looks like a whole lot of extra effort. Upon looking at that sort of thing many a working Python programmer, myself included, hears the voice of GvR murmuring disparaging things about "academic" programmers down in the pit of their brain.
Which creates an opportunity to demonstrate all the ways the (arguably) more Pythonic way is actually a royal PITA when you try to make your code robust. Handling and reporting data validity errors gets scattered all over the code, which makes it annoying to maintain. Unit test suites get bloated because it's not obvious what inputs a function should be able to handle. Comments and docstrings to help keep track of this stuff begin to proliferate.
LtWorf · · focus · HN ↗