CSV files are the de-facto standard in many cases of data transfer, particularly when dealing with enterprise application or disparate database systems.
While there are a number of csv libraries in Haskell, at the time of this project's start, there wasn't one that provided all of the following:
Over time, people created other plausible CSV packages like cassava. The major benefit from this library remains to be:
csv-conduit is a conduit-based CSV parsing library that is easy to use, flexible and fast. It leverages the conduit infrastructure to provide constant-space operation, which is quite critical in many real world use cases.
For example, you can use http-conduit to download a CSV file from the internet and plug its Source into intoCSV to stream-convert the download into the Row data type and do something with it as the data streams, that is without having to download the entire file to disk first.
type MapRow t = Map t t
type Row t = [t]
While fast operation is of concern, I have so far cared more about correct operation and a flexible API. Please let me know if you notice any performance regressions or optimization opportunities.
{-# LANGUAGE OverloadedStrings #-}
import Data.Conduit
import Data.Conduit.Binary
import Data.Conduit.List as CL
import Data.CSV.Conduit
import Data.Text (Text)
-- Just reverse te columns
myProcessor :: Monad m => Conduit (Row Text) m (Row Text)
myProcessor = CL.map reverse
test :: IO ()
test = runResourceT $
transformCSV defCSVSettings
(sourceFile "input.csv")
myProcessor
(sinkFile "output.csv")
{-# LANGUAGE OverloadedStrings #-}
import Data.Conduit
import Data.Conduit.Binary
import Data.CSV.Conduit
import Data.Text (Text)
myProcessor :: Monad m => Conduit (Row Text) m (Row Text)
myProcessor = awaitForever $ yield
-- Let's simply stream from a file, parse the CSV, reserialize it
-- and push back into another file.
test :: IO ()
test = runResourceT $
sourceFile "test/BigFile.csv" $=
intoCSV defCSVSettings $=
myProcessor $=
fromCSV defCSVSettings $$
sinkFile "test/BigFileOut.csv"