On Fri, Jul 29, 2016 at 8:57 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
>
> Can you summarize once again in very simple terms what would be the big
> benefits?
>
Benefits for regular scikit-learn users
1. Reliable information on method signatures in a standarized way
("reliable" in the sense of "automatically verified")
2. Better integration with tools supporting PEP-484 (editors, documentation
tools). This is a small set now, but I expect it to grow (and it's also an
egg and chicken problem, support has to start somewhere)
Benefits for scikit-learn users also using mypy and/or PEP-484 (probably
not a large set, but I know a few people :) )
0. Same as the rest of the users
1. Early detection of errors in own code while writing code based on SKL
2. Making own code more readable/explicit by annotating functions that
receive/return SKL types (and verifying that annotations)
Benefits for scikit-learn developers
1. Some extra checks that changes keep internal consistency
2. (Future) possible simplification of typing information in docstrings,
which would make themselves redundant (this would require updating doc
generators)
Regarding the cost for contributing, an scenario where you get a CI error
due to mypy would be because:
* the change in the code somewhat changed the existing accepted/returned
types, which is a change in the API and should actually be verified
* the change in the code extended the signature of an existing function
(what Andreas mentioned); in this situation it's similar to a PR that adds
an argument and doesn't update the docstring (only that this is
automatically caught).
WRT to the second issue, the error here might be confusing when using the
"one line" syntax because arguments may "misalign" with their signatures.
The multiline version (or the python3-only form) is safer in that sense (in
fact, adding an argument there will not produce a CI problem because its
unannotated and assumed to be "any type").
Adding new modules/methods without no annotations wouldn't produce an
error, just an incompleteness in the annotations
A possible source of problems like the one you mention is that the
implementation of the annotated methods will be checked, and sometimes
you'll get a warning about a local variable if mypy can't infer its type
(it happens sometimes when assigning an empty list to a local, where mypy
knows that it's a list but doesn't know the element type). But in that case
I think the message you get is very obvious.
--
Daniel F. Moisset - UK Country Manager
www.machinalis.com
Skype: @dmoisset
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