An introduction to Kerf (scottlocklin.wordpress.com)

Great description from the reference manual (https://github.com/kevinlawler/kerf/blob/master/manual/refma...):

"Kerf is a programming language built on pragmatism, borrowing ideas from many popular tools. The syntax of Kerf will be familiar enough to anyone who has programmed in C, Python or VBA. Data is described using syntax from JSON (JavaScript Object Notation), a text-based data interchange format. Queries to search, sort and aggregate data can be performed using SQL syntax. Kerf’s built-in commands have aliases which allow programmers to use names and terms they are already used to."

Kerf homepage: http://www.kerfsoftware.com/

Kerf github: https://github.com/kevinlawler/kerf

Why do these products always have to be closed source... especially when the market's already fairly saturated, this seems to make little sense...

Nice name. Pity about the 8th bit, though.

Ha! I've asked the question about existence of something like Kerf quite a while ago[1]. Good to finally have an answer other than "it is not really needed".

[1] https://news.ycombinator.com/item?id=7890931

Slightly unrelated question - where would I find an interpreter for K so I can start playing around with the language?

Good intro Scott. I just start playing with Kerf and it seems to me a pretty well written piece of software with potential. I like the json style assignment. Will keep an eye on this.

I don't think the authors claim that "The only thing comparable to it from an engineering standpoint are the other APL based databases such as KDB and Jd" is correct, at least not based on this blog post. Numpy+pandas also seems pretty similar, as is breeze, and Julia has similar features also.

Let me emphasize that while I'm about to implement most of his blog post in numpy/pandas, I don't mean to come off as critical or dismiss building a new one. Kerf looks pretty cool. I just don't think this post gives much reason to believe there is nothing comparable to it.

Idiomatic numpy:

    def wavg(x,y):
        return sum(x*y) / sum(x)

Less idiomatic, but analogous to kerf or J:

    def wavg(x,y):
        return add.reduce(x*y) / add.reduce(x)

arange(1,6) is equivalent to his range(5), and full((5,), 1) is equivalent to repeat(5,1).

The SQL-ish engine looks fairly similar to pandas:

    df = pandas.DataFrame({'a' : arange(5), 'b' : ['a', 'b', 'c', 'd', 'e']})
    #Result is:
       a  b
    0  0  a
    1  1  b
    2  2  c
    3  3  d
    4  4  e

    df[df.a > 2]
    #Result is
       a  b
    3  3  d
    4  4  e

Pandas similarly has joins, averages and other aggregates, etc. E.g.:

    pandas.merge(df1, df2, how='inner', left_on='a', right_on='b')

is equivalent to:

    SELECT * FROM df1 INNER JOIN df2 ON df1.a = df2.b;

Syntactically it's a bit different (embedded SQL is pretty cool) but from this blog post I don't see any major semantic differences.

However, if there are important differences under the hood, I'd love to hear about them. Again, I'm really not trying to criticize Locklin for rolling his own, I'm just disputing a minor point.

Any word on what the license will look like?

Gonna grab the current binary to play around with, I love learning new styles of programming and kerf seems rather approachable compared to the others in it's family.