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Soft import #9561

Merged
merged 15 commits into from
Nov 20, 2024
Merged

Soft import #9561

merged 15 commits into from
Nov 20, 2024

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scott-huberty
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@scott-huberty scott-huberty commented Sep 30, 2024

I haven't replaced all individual instances of try: import optional_dep ... except: raise, but wanted to get this on the board earlier rather than later so folks have time to give feedback!

  • Added a function named soft_import to xarray.core.utils. It makes use of a function you already have named module_available.
  • Anytime I needed to use soft_import more than once or twice for the same optional dependency, I created a helper function for it that is just a thin wrapper around soft_import
  • Added a test

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This seems excellent!

(though others know this code better, so will wait for them to comment)

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Yeah this is a great contribution!

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Can we resolve merge conflicts and then merge?

resolved conflict stemming from pydata#9505 by accepting this branches changes (pydata#9505 was just a slight edit on the old try import .. except pattern)
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Can we resolve merge conflicts and then merge?

@max-sixty sorry about that! I just pushed a commit ( 3c5d35d ) to resolve the merge conflict, which stemmed from #9505. That PR had touched one of the try: import ... except lines in xarray.plot.utils

@scott-huberty scott-huberty marked this pull request as draft October 3, 2024 00:29
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Marking as draft until I can look into the failures. I think the proposed soft_import mechanism trips up the static type checking..

pinging @hoechenberger as the person driving the static type checking adoption in MNE-Python.. Do you recall whether MNE's _soft_import function ever caused problems with mypy (and if so, was there a work around?) 🙂

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@scott-huberty I don't remember details, but I do recall those soft imports to be an absolute nightmare to work with when using static type checkers, and I gave up trying to add those type hints at one point.

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I think it is basically impossible to have such imports work properly with static type checking. The imported modules will all be Any (ModuleType is effectively Any).

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Yes. It also means that you won't receive useful help from your IDE during development. I'd advise against this change, but that's just my very personal opinion without knowing any of the considerations that went into this work.

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Ah.. OK, thanks @hoechenberger ! Yes agreed if this proposal breaks Xarray functionality then maybe it's not a good idea after all.. I'll let the devs make the call on that.

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Agree it doesn't make sense if we really lose all type checking. but is it really not possible? Couldn't we even have a if TYPE_CHECKING vs if not TYPE_CHECKING as a hammer?

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In the strict=True case one could just check if available and raise a nice error if not and then import directly afterwards.

Something like

assert_xxx_installed()
import xxx

But this ofc doesn't protect against import errors.

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Couldn't we even have a if TYPE_CHECKING vs if not TYPE_CHECKING as a hammer?

I tried that and never got it to work. I think the language just doesn't allow for this.

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scott-huberty commented Oct 3, 2024

@headtr1ck I think I see what you are suggesting. So for example if we just start out with the optional dependencies that get imported a lot across the codebase (and thus could benefit from a dedicated function; e.g. cftime), this would look like:

def check_installed(name, purpose, strict=True):
    is_installed = module_available(name)
    if not is_installed and strict:
        raise ImportError(
            f"For {purpose}, {name} is required. Please install it via pip or conda."
        )
    return is_installed

def check_cftime_installed(strict=True):
    """Check if cftime is installed, otherwise raise an ImportError."""
    purpose = "working with dates with non-standard calendars"
    return check_installed("cftime", purpose, strict=strict)


def some_function_that_needs_cftime():
    check_cftime_intalled()
    import cftime
    ...

It's basically just a wrapper around the module_available function you added. Is this what you are thinking / does this still seem worth adding?

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It's basically just a wrapper around the module_available function you added. Is this what you are thinking / does this still seem worth adding?

You are right. Maybe it makes more sense to add the new functionality to module_available?

Maybe the TYPE_CHECKING idea is indeed better?

if TYPE_CHECKING:
    import xxx
else:
    xxx = check_xxx_installed()

But somehow all of this is adding a lot of boilerplate for just an improved error message, but I guess that's what the issue is for...

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One proposal, small change to the current version, retaining type checking and integration with module_available:

  • attempt_import(module, reason=None) -> Module
    • so don't have a strict flag, use module_available for those cases
    • possibly have a few common reasons which get looked up in the function so we don't need to pass "plotting" each time etc
  • surround with if TYPE_CHECKING as above

I agree it's a bit of boilerplate, but I do think the experience is much better for newer users. And if we do this across the library it'll be an easily recognizable pattern.

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Thanks both! I think the TYPE_CHECKING idea would work fine as long as you all agree that the informative error is worth the extra boilerplate 🙂 I tend to err on the side of being very explicit but others may disagree.

If folks don't want the boilerplate, one last idea is something like:

def import_matplotlib():
    """Raise an ImportError if matplotlib is not installed."""
    if module_available("matplotlib"):
        import matplotlib as mpl
        return mpl
    raise ImportError("For plotting, matplotlib is required. Please install it via pip or conda.")

Which would work fine with mypy since we are using a direct import. But the downside to that is that you would need to define one of these functions for every package / submodule that you want to install. So maybe it's not the most scalable.

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Which would work fine with mypy since we are using a direct import.

Unfortunately that doesn't work, because the return type is simply ModuleType. One cannot annotate specific modules (at least last time I have checked).

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Which would work fine with mypy since we are using a direct import.

Unfortunately that doesn't work, because the return type is simply ModuleType. One cannot annotate specific modules (at least last time I have checked).

Ah ok, you are right that annotating import_matplotlib_installed to return ModuleType, prevents a static type checker from accessing the modules attributes. FWIW When I tested the import_matplotlib example I gave, I didn't include a return type annotation - and in that case my static type checker (pylance) was able to access the attributes of the modules (and mypy wasn't throwing any errors locally..)

Screenshot 2024-10-05 at 8 51 29 AM

Anyways I am still new to mypy and so could be missing something. Happy to move forward with the proposed IF TYPE_CHECKING approach.

Per the proposal at pydata#9561 (comment)

This pairs any use of (a now simplified) `attempt_import` with a direct import of the same module, guarded by an `if TYPE_CHECKING` block.
I was able resolve the conflicts in the listed files below by accepting a combination of the changes from the main branch and this PR. Basically just stacked the changes that were recently merged to main with the changed in this PR. I did not modify the content of the changes from main at all.
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scott-huberty commented Oct 25, 2024

Hello, apologies for the delay here.

Per @max-sixty 's proposal, I've re-implemented (a now simplified) attempt_import function so that it is paired with a direct import of the module (guarded by an if TYPE_CHECKING clause). At least locally, it seems to be playing well with mypy now..

Feel free to provide feedback on the current pattern, and I'll mark as ready for review once the CI's are green!

EDIT:


Here is a MWE of the new behavior, assuming you only have the base dependencies installed:

import xarray as xr

ds = xr.tutorial.scatter_example_dataset(seed=42)
ds["A"].plot()
ImportError: The matplotlib package is required for plotting but could not be imported. Please install it with your package manager (e.g. conda or pip).

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Super!

Any objections? Otherwise let's merge...

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@max-sixty max-sixty added the plan to merge Final call for comments label Oct 26, 2024
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Looks good thanks.
Only a couple of minor remarks.

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@headtr1ck headtr1ck marked this pull request as ready for review October 26, 2024 07:53
Co-authored-by: Michael Niklas  <mick.niklas@gmail.com>
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Thanks for the review and for your patience @max-sixty and @headtr1ck ! I haven't forgotten about this, I just unfortunately had to focus on a grant deadline. I should be able to return to this in the next few days.

@headtr1ck headtr1ck removed the plan to merge Final call for comments label Nov 16, 2024
Manually fixed a conflict in xarray/backends/common.py, specifically LOC touched/added  by pydata#9727 and pydata#9787

In one case I just needed to incorporate the xarray.core.types imports from pydata#9787
In the other case, a flake was fixed in one of the attempted imports that will utilize the attempt_import function in this PR. I just incorporated that flake fix from pydata#9727  into this PR
- Also change raise ImportError to raise RuntimeError, since we are catching both ImportError and ModuleNotFoundError
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Looks great! Will hit the button.

@max-sixty max-sixty enabled auto-merge (squash) November 20, 2024 21:15
@max-sixty max-sixty merged commit 339ed93 into pydata:main Nov 20, 2024
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@scott-huberty scott-huberty deleted the soft_import branch November 20, 2024 21:52
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Looks great! Will hit the button.

Thanks for the patience! 🙏

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ENH: Throw informative error if missing optional dependency
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