Hey there,
This would be an idiomatic Nim translation of your program (and the result is
more similar to the Python one).
import os, strutils, times, math, parsecsv, streams
const CsvPath = "./build/EUR_USD_Week1.csv"
# Row: lTid,cDealable,CurrencyPair,RateDateTime,RateBid,RateAsk
proc main() =
var ctime = getTime()
echo("time: ", ctime)
var cpustart = cpuTime()
var csv: CsvParser
let stream = newFileStream(CsvPath, mode = fmRead)
csv.open( stream, CsvPath,
separator = ',',
quote = '\"',
skipInitialSpace = true
)
defer: csv.close
var
psum = 0.0
pcount = -1
pips = 0.0
psumsum = 0.0
# Preallocating the seq.
# Plain arrays are allocated on the stack and
# stack size is very limited (a couple MB)
# Use seq or ref arrays instead
farray = newSeq[float](337588)
discard csv.readRow # Skip header row
while csv.readRow():
let price = csv.row[5].parseFloat
pcount += 1
farray[pcount] = ((price * price) * ((pcount+1) / farray.len))
pips += price
psum = farray.sum()
psumsum += psum
echo("pcount: ", $pcount, " pips: ", $pips, " farray[^1]: ",
farray[^1], " psum: ", $psum, " psumsum: ", $psumsum)
echo("clock: " & $(getTime()-ctime) & " cpuTime: " &
$(cpuTime()-cpustart))
main()
Run
Now this idiomatic Nim is still 2.3x slower than Python but I'll have a look at
the performance issue later.
Also for your csv processing (and tabular data in general) I suggest you use
Python [Pandas](https://pandas.pydata.org) and
[NimData](https://github.com/bluenote10/NimData) they are made for this.
