Have you also considered changes to the modules under test that might make
it easier for both implementations to exist and be tested side-by-side (so
with fewer hacks on the testing side)?

—Chris

On Wed, May 6, 2020 at 2:33 PM Paul Ganssle <p...@ganssle.io> wrote:

> Thanks for the suggestion.
>
> I think I tried something similar for tests that involved an environment
> variable and found that it doesn't play nicely with coverage.py *at all*.
>
> Also, I will have to solve this problem at some point anyway because the
> property tests for the module (not currently included in the PR) include
> tests that have the C and pure Python version running side-by-side, which
> would be hard to achieve with subinterpreters.
>
> On 5/6/20 4:51 PM, Nathaniel Smith wrote:
>
> On Wed, May 6, 2020 at 7:52 AM Paul Ganssle <p...@ganssle.io> 
> <p...@ganssle.io> wrote:
>
> As part of PEP 399, an idiom for testing both C and pure Python versions of a 
> library is suggested making use if import_fresh_module.
>
> Unfortunately, I'm finding that this is not amazingly robust. We have this 
> issue: https://bugs.python.org/issue40058, where the tester for datetime 
> needs to do some funky manipulations to the state of sys.modules for reasons 
> that are now somewhat unclear, and still sys.modules is apparently left in a 
> bad state.
>
> When implementing PEP 615, I ran into similar issues and found it very 
> difficult to get two independent instances of the same module – one with the 
> C extension blocked and one with it intact. I ended up manually importing the 
> C and Python extensions and grafting them onto two "fresh" imports with 
> nothing blocked.
>
> When I've had to deal with similar issues in the past, I've given up
> on messing with sys.modules and just had one test spawn a subprocess
> to do the import+run the actual tests. It's a big hammer, but the nice
> thing about big hammers is that there's no subtle issues, either they
> smash the thing or they don't.
>
> But, I don't know how awkward that would be to fit into Python's
> unittest system, if you have lots of tests you need to run this way.
>
> -n
>
>
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