Yes, that would help.
On Thursday, February 25, 2016 at 11:48:44 AM UTC-5, Josh Langsfeld wrote:
>
> Maybe a solution to this kind of design problem would be to allow multiple
> top-level modules per package, with syntax to let you load the particular
> one you want/need.
>
> On Thursday, February 25, 2016 at 1:10:28 AM UTC-5, John Myles White wrote:
>>
>> I don't think Julia is really amenable to this kind of organization
>> because Julia's modules have no logical relationship to filesystem layouts,
>> whereas Python's system is all about filesystem layout and has nothing to
>> do with textual inclusion.
>>
>> On Wednesday, February 24, 2016 at 1:28:08 PM UTC-8, Cedric St-Jean wrote:
>>>
>>>
>>>
>>> On Wednesday, February 24, 2016 at 4:15:49 PM UTC-5, Jeffrey Sarnoff
>>> wrote:
>>>>
>>>> This should not be a problem. What is your concern?
>>>>
>>>
>>> Loading time/RAM usage. I'm trying to wrap/port scikit-learn, and their
>>> module arrangement makes a lot of sense. In Python, I don't get to load
>>> code for support vector machines unless I actually need them.
>>>
>>> import sklearn.svm
>>>
>>> I could define separate modules like "sklearn_svm", "sklearn_cluster",
>>> but it's awfully ugly.
>>>
>>>
>>>> On Wednesday, February 24, 2016 at 3:45:50 PM UTC-5, Cedric St-Jean
>>>> wrote:
>>>>>
>>>>> In Python, loading a module (i.e. importing a file) does not load
>>>>> sub-modules, eg.:
>>>>>
>>>>> import sklearn
>>>>> import sklearn.linear_model
>>>>>
>>>>> Is there any way to achieve the same thing in Julia?
>>>>>
>>>>> module A
>>>>> println("loaded A")
>>>>>
>>>>> module B
>>>>> println("loaded B")
>>>>> end
>>>>>
>>>>> end
>>>>>
>>>>> Can I have "loaded A" without "loaded B"?
>>>>>
>>>>
