Proposal: "safe_pyimport" to delay "module not found" error
- Langage dominant
- Julia
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Description
I have a proposal for a simple feature that might be useful. It solves the problem that sometimes I want to import a Python package at the Julia module top-level, but I want the module still load-able if the Python package fails to load (the error instead can be delayed to when/if its actually attempted to be used).
```julia
module Foo
function __init__()
global pypkg = pyimport("DoesntExist")
end
foo() = pypkg.stuff(...)
end
using Foo # I want no error here
Foo.foo() # error only comes here when actually trying to use it
```
The reason for this is mostly convenience (to avoid having to write eg `pyimport("numpy")` a million times in each function and instead just have a single `np = pyimport("numpy")` in my module, and makes most sense for Python packages which aren't part of the "core" functionality of your Julia module.
A possible implementation is attached below and is only ~10 lines.
Just wanted to suggest this, let me know if there's any interest for a PR, but also feel totally free to close this without explanation (which I'll take as a very understandable, "not suited for PyCall itself")
```julia
struct FailedPyimport
err
end
getproperty(p::FailedPyimport, ::Symbol) = throw(getfield(p,:err))
@doc doc"""
safe_pyimport(s)
Like `pyimport`, but if `s` fails to import, instead of an error right away, the
error will be thrown the first time the user tries to access the contents of the
module.
"""
function safe_pyimport(s)
try
pyimport(s)
catch err
FailedPyimport(err)
end
end
```
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Piste de recherche
Commencez par lire le point d’entrée `pyimport` existant et l’implémentation proposée de `safe_pyimport` dans cette issue. Confirmez le comportement souhaité avec l’exemple `Foo` : l’importation du module Julia réussit lorsque le package Python n’est pas disponible, tandis que l’accès à l’importation échouée déclenche l’erreur enregistrée.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- julia, python
- Domaine
- tooling
- Type d'issue
- Fonctionnalité
- Difficulté
- 3/5
- Temps estimé
- 1-2 jours
- Activité
- À l'abandon
- Clarté
- Plutôt claire
- Accessibilité débutants
- 35/100