Here is how I would do it:

https://play.golang.org/p/-aSfOYst6w

-s

sent from my droid

On Dec 6, 2017 8:03 PM, "Jonathan Yu" <jonathan.i...@gmail.com> wrote:

>
>
> 2017-12-06 10:38 GMT-08:00 Christian LeMoussel <cnh...@gmail.com>:
>
>> I have to write a Python program that uses numpy in GO.
>> I have this Python code :
>>   prefix = "de98671db1ce0e5c9ba89ab7ccdca6c427460295b8dd3642e9b2bb96172
>> 3307c57629b1ad37909a863a56965"
>>   prefix_np = np.fromstring(prefix[0:64], dtype=np.uint32, count=16)
>>   print("prefix_np: {}".format(prefix_np))
>>
>> Output :
>>
>> prefix_np: [ 943285604 1680946998 1700999522 1664443696  945906233  
>> 929194297 1667523427  878917217  909391666  892940848 1684289634  842282547 
>> 845298021  909730402  858928945 1664561203]
>>
>>
>> Some idea how can I do this efficiently in GO ?
>>
>
> I guess this would depend on whether this is  a well-defined format; you
> might have to port numpy's fromstring to Go? But it should be possible...
> If you control the Python side, it might be easier to dump the data as JSON
> and import into Go that way.
>
> Is there a library equivalent to numpy in GO?
>>
>
> I'm not knowledgeable enough to say, but Go has gonum which has similar
> goals to numpy and other data science toolkits: https://github.com/
> gonum/gonum
>
>>
>>
>>
>> Thank you for your help
>> G
>> M
>> T
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> --
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> Twitter <https://twitter.com/jawnsy>, GitHub <https://github.com/jawnsy>,
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> *“Ever tried. Ever failed. No matter. Try again. Fail again. Fail better.”* —
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>
> “In an adaptive environment, winning comes from adapting to change by
> continuously experimenting and identifying new options more quickly and
> economically than others. The classical strategist's mantra of sustainable
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> <https://hbr.org/2015/06/navigating-the-dozens-of-different-strategy-options>
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