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Ask HN: Which library would you like to see ported on language X?

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Ask HN: Which library would you like to see ported on language X?

#1
As a practice exercise for every language, porting a library is a great way to have a better grasp of a language while filling a gap for its developers needs

It gives your learning project a real meaning and therefore helps with your motivation to learn.

I'm trying to build a list of libraries having this potential.

Which library made you think "I wish it was ported on language X" ?

Re: Ask HN: Which library would you like to see ported on language X?

#5
post #3

numpy/scipy to golang

Is it for performance/architecture improvements that could provide Go over Python or just for the sake of having a high level scientific library available in Go ? or both ?

The high performance parts of numpy and scipy aren't written in Python anyway so Go wouldn't be that much of an improvement. It's just that Go is a language better suited for professional software (imo).

Re: Ask HN: Which library would you like to see ported on language X?

#6
I would like to see a stream processing library ported to pure Python. For example, Java 8 Stream API, Scala Stream API, Spark RDD API, jOOL API. They're all similar.

That is, I would like to have an iterator in Python in which I could do:

    from statistics import mean
    from niceportedlib import Stream

    salaries = Stream([]) # Some data here
    mean_salary_by_department = salaries.group_by(lambda v: v['department']).map_values(statistics.mean)
Pandas does help, but is not pure Python (has native dependencies).

Re: Ask HN: Which library would you like to see ported on language X?

#7
post #6

I would like to see a stream processing library ported to pure Python. For example, Java 8 Stream API, Scala Stream API, Spark RDD API, jOOL API. They're all similar. That is, I would like to have an iterator in Python in which I could do: from statistics import mean from niceportedlib import Stream salaries = Stream([]) # Some data here mean_salary_by_department = salaries.group_by(lambda v: v['department']).map_val…

The streamz library (http://streamz.readthedocs.io/en/latest/) might be what you're looking for.