Cross posting to grumpy-users

On Thursday, 5 January 2017 00:42:31 UTC-8, Justin Israel wrote:
>
> I just gave this a play since I was really curious what it could do. But 
> it seems like of your python module has imports for other python modules, 
> they get transpiled into Go import statements that look at the grumpy 
> stdlib location. Does anyone have any information on the extend of the 
> support, besides the documented caveats? 
>
>
Basically the build and import systems are pretty immature right now and so 
the only way to import Python libraries is by stuffing them into the same 
directory as the standard library. There's been a couple discussions about 
how to best support third party libs:

https://github.com/google/grumpy/issues/43
https://groups.google.com/forum/#!topic/grumpy-users/JJFFube8qkM
 

> From what I gather, it seems to target the use case of single file 
> executable scripts, in pure python, with only dependencies on the python 
> stdlib or the Go stdlib, and use multithreading as a focus (in order for it 
> to realize the performance benefits). Does that seem correct? If so, can 
> anyone explain a real or hypothetical example of where grumpy is most 
> useful? I can't say I have anything that fits this use case. But I suppose 
> google/YouTube team have a bunch of these concurrent data crunching 
> scripts. 
>
>
Pure Python, yes. C extensions are not supported. However, the long term 
goal is to support any third party pure Python library. The originating use 
case is the YouTube frontend which is a very large application with many 
external dependencies.
 

> Justin 
>
>
> On Thu, Jan 5, 2017, 10:54 AM andrey mirtchovski <mirtc...@gmail.com 
> <javascript:>> wrote:
>
>> > It’s also about 2x slower than the original Python. All of this 
>> indirection is necessary to preserve the dynamic semantics of Python. 
>> Basically it’s taking the calls into the runtime that a Python interpreter 
>> would make, and writing them out one after another.
>>
>> this single-thread slowdown does appear on the performance graph
>> published in the article. python historically has had significant
>> effort thrown behind single-thread/process performance.
>>
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