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Issue 1114 #1131

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CucumisSativus
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I have made things!

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  • I have double checked that there are no unrelated changes in this pull request (old patches, accidental config files, etc)
  • I have created at least one test case for the changes I have made
  • I have updated the documentation for the changes I have made
  • I have added my changes to the CHANGELOG.md

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Refs #1114

A simple implementation of filter for maybe. I am happy to implement something similar for Result, but I'm not entirely sure about the preferred approach.
In Scala it looks more or less like this

      if (p(value)) this else Failure(new NoSuchElementException("Predicate does not hold for " + value))

Not sure if something like this is ok for Python as well.

My second idea was to have a signature like

def filter(predicate, on_failure):
(...)

so user can specify exactly what happens in case of not matching predicate
馃檹 Please, if you or your company finds dry-python valuable, help us sustain the project by sponsoring it transparently on https://github.com/sponsors/dry-python. As a thank you, your profile/company logo will be added to our main README which receives hundreds of unique visitors per day.

@sobolevn
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We also need to make an interface type for filter. This way we will be able to use with HKT.
See interfaces/ folder.

@CucumisSativus
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@sobolevn I think i managed to add them, but lets say i'm not 100% sure about those. Looking forward for some feedback :)

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Thanks a lot! Just one question 馃檪

"""

@abstractmethod
def filter(
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Future note: we can also make an overload for TypeGuard case.
See python/typeshed#6140

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Could you elaborate a bit what can we do with type guard here? We are not filtering for example a list with different types. Filter executed on _FilterableType always returns _FilterableType. Did I miss something?

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Nevermind, this was a self note 馃檪
This is even not supported by mypy yet.

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It looks like mypy supports TypeGuard now 馃帀 :

returns/maybe.py Outdated
@@ -430,10 +436,10 @@ def failure(self):
raise UnwrapFailedError(self)

def filter(self, function):
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Is it possible to create a common filter_ function for all possible types? Result, IOResult, ...?

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filter is special in the sense that it 'empties' the container, which is possible in Maybe, but not in Result (i.e. what would the failure value of Success(4).filter(lambda x: False) be?)

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Ok, I see! Than, it looks like we can use MaybeLikeN to limit the input type of filter_?

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@sobolevn I used it, please tell me if its something you were looking for. I am not entirely sure if I did it right :)

@CucumisSativus
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@sobolevn when i'm running poetry run pytest typesafety -p no:cov -o addopts="" --mypy-ini-file=setup.cfg locally I get 830 passed, 1 warning. Any ideas why does it fail on github?

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I will take a look a bit later this week.

Thanks a lot for the PR!

self: _FilterableType,
predicate: Callable[[_FirstType], bool],
) -> Kind1[_FilterableType, _FirstType]:
"""Applies 'predicate' to the result fo a previous computation."""
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typo: fo->of

>>> from returns.maybe import Nothing, Some
>>> from returns.pointfree import filter_

>>> def example(argument: int) -> bool:
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what would you think of naming the example function? Naming the function is_even makes the example clearer in my mind

@CucumisSativus
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@sobolevn i think I found it

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codecov bot commented Dec 12, 2021

Codecov Report

Merging #1131 (cca6894) into master (b782c2e) will not change coverage.
The diff coverage is 100.00%.

Impacted file tree graph

@@            Coverage Diff            @@
##            master     #1131   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files           79        81    +2     
  Lines         2415      2450   +35     
  Branches       208       210    +2     
=========================================
+ Hits          2415      2450   +35     
Impacted Files Coverage 螖
returns/interfaces/filterable.py 100.00% <100.00%> (酶)
returns/maybe.py 100.00% <100.00%> (酶)
returns/pointfree/__init__.py 100.00% <100.00%> (酶)
returns/pointfree/filter.py 100.00% <100.00%> (酶)

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螖 = absolute <relative> (impact), 酶 = not affected, ? = missing data
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4 participants