
Scala is the new golden child - altstar
http://techcrunch.com/2016/06/14/scala-is-the-new-golden-child/
======
ctvo
I dread reading techcrunch technical articles. This wasn't an exception.

The author, a data scientist, interviews at start-ups and is asked to solve
algorithm / data structure questions. Some of these were challenging in Python
due to the lack of available data structures in the standard library (he used
an example of a heap). He swapped to Scala and got better results.

Scala is also great with Spark. Scala is the new golden child.

~~~
hayd
heapq is in python's standard library...

~~~
ratbeard
why is it called heapq?

~~~
yareally
heap queue

------
gizzlon
Not to discount Scala, I don't know it well enough to have an opinion, but
this article is shit >(

So the authors anecdotal experiences and subjective feelings after a few
interviews is suppose to tell us what the "next big thing is" ? That's really
hard to predict even for those _who do some actual research_. Most of the
people he talked to did not even know the language FFS!

~~~
angryasian
My opinion although I know others will feel differently.

Scala is a good language and serves its purpose very well when working with
Spark. I think the environment surrounding it is still shit. I think Play is
not good, and other related frameworks are still not where they need to be.
Even the ORM solutions I think are more complicated compared to every other
major language. Yes you can use Java with it, but then the benefits of using
scala and switching between your Java and scala become burdensome. I think
Scala has many more features almost to a fault. Its a large complex language,
unless you have a dedicated team with a defined coding style it'll be hard to
maintain. With that being said, I do like the language but I prefer
opinionated languages like Java and Go

------
kafkaesq
_This is a classic heap problem. However, Python doesn’t have a proper
collections library, so to solve it I would try to import a specialized module
like heapq, which usually wasn’t included in the interview environments._

This is an odd thing to say - heapq has been part of the standard library
since 2.3. The fact that it isn't part of collections... just doesn't mean
very much.

 _With a few exceptions, Python was clearly frowned upon. Of course, no one
ever explicitly told me I couldn’t use Python to solve a problem. The coding
environments always had a Python interpreter, but the interviewers would
usually suggest that I use “a compiled language” (read: Java)_

Well, actually they _were_ explicitly telling him, right there. But if their
interviewing teams would let a candidate go on and code in the "wrong"
language (obviously a huge waste of both the candidate's time and theirs)...
then they have much worse problems than any of us are likely to be able to
help them with.

~~~
asphyxiac
There's probably an entirely different discussion that can be had about
interviewing techniques for data science positions.

------
kmonsen
I have done a lot of interviews, and also been interviewed a few times.

I think:

\- Interviews are significantly easier in a higher level language. You will
get more done in less time in Python than C in general. Also less tripwires I
think.

\- Even more important, choose a language you know really well. If you can
pick the language I will assume you pick one you know well, so if you don't
know something basic that is a major red flag.

So I think learning a new language for interviews is a bad idea. Use it on
some hobby projects first at least.

