Python, to its credit, has the nice inclusive property of extensible
interpreters of being friendly to "hang things" onto just like ornaments on
trees. By linking with C/C++-libraries and adding glue/shim code, anything
can be used from Python. This facility and interpretive execution (as Eric
Johnson observed above) makes it a natural for discovery and trying of
things.

These virtues may seem less so in eventual deployments, at scale, and in
other cases.

On Mon, Jan 27, 2020 at 8:48 AM 'Eric Johnson' via golang-nuts <
golang-nuts@googlegroups.com> wrote:

>
> On Sunday, January 26, 2020 at 10:27:35 PM UTC-8, pentel...@gmail.com
> wrote:
>>
>>
>> IMHO, golang didn't make a dent on key areas to become a language of
>> choice like big data (analytics, complex event processing, etc.) and
>> consequently, hot topics like artificial intelligence. Exactly areas where
>> python excels today.
>
>
> At least when it comes to analytics, ML, AI, there are various languages
> at play in this space. Python isn't replacing "R" either. I don't think we
> should expect that it would either. One of Python's intended strengths for
> AI / ML / analytics involves REPL, which is specifically not a targeted
> feature of Go. On the other hand, when it comes to situations like the
> execution of AI / ML models in performance critical environments, I have
> heard / read of anecdotal evidence of teams opting for Go.
>
> The question isn't whether Go making an impact for a specific area, it is
> whether it is making an impact where it is appropriate. For that, from what
> I see, the answer is overwhelmingly *yes*.
>
> Eric.
>
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>


-- 

*Michael T. jonesmichael.jo...@gmail.com <michael.jo...@gmail.com>*

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