Clojurians Log v2

Data exploration with large files Hinted by Dragan's and practicalli's https://dragan.rocks/articles/20/Corona-1-Baby-steps-with-Covid-19-for-programmers https://github.com/practicalli/data-science-corvid-19 ... I wanted to explore this large file: https://open-covid-19.github.io/data/v2/latest/master.csv (Cf https://github.com/open-covid-19/data/blob/master/README.md#master) Alas, it's too big for my Java heap to slurp it in. Is there a library which allows to explore the data using e.g. map, reduce and core.async without ever loading the full file? I know there are ways, cf https://amp.reddit.com/r/Clojure/comments/5x2n47/counting_lines_60_faster_than_wc_with_clojure/ https://stackoverflow.com/questions/38340868/consuming-file-contents-with-clojures-core-async I just wanted to know if there is a set of ready to use functions for that, or at least a write up.

hmmm, this is not a large file, it's only 300kb

I can (slurp "<https://open-covid-19.github.io/data/v2/latest/master.csv>") without problems

@vlaaad imagine it was large. What would you do?

Depending on how large. If it's possible to fit into memory, maybe I'd have a look at tech.ml.dataset

If not, I'd used streaming processing (aka lazy seq + reduce)

So instead of slurp it would be something that reads csv line by line and processes individual items

@nick.romer for example:

(require '[<http://clojure.java.io|clojure.java.io> :as io]
         '[clojure.string :as str])
(with-open [reader (io/reader "<https://open-covid-19.github.io/data/v2/latest/master.csv>")]
  (let [[header &amp; rows] (line-seq reader)
        keys (map keyword (str/split header #","))]
    (-&gt;&gt; rows
         (map #(str/split % #","))
         (map #(zipmap keys %))
         (map :total_tested)
         (remove empty?)
         (map #(Integer/parseInt %))
         (reduce +))))

(there is clojure.data.csv for csv parsing, I just was too lazy to restart a repl)

Do we have a fix as to why the arc pie chart is not displaying/throwing an exception yet...

@nick.romer Have you tried processing it lazily?