tixxit / delimited

Scala library for working with {tab,colon,semicolon,comma,pipe,etc}-separated files.

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A fast, easy-to-use CSV parser for Scala.

Set Up

Delimited is published for both Scala 2.10 and 2.11. To get started with SBT, use the following in your SBT build file:

libraryDependencies += "net.tixxit" %% "delimited-core" % "0.8.0"

If you are using Delimited's iteratee library then you will also want to include:

libraryDependencies += "net.tixxit" %% "delimited-iteratee" % "0.8.0"

If you're using gradle add this to your build.gradle file (and similarly for delimited-iteratee):

compile 'net.tixxit:delimited-core_2.11:0.8.0'

API Docs (Scaladoc)

The latest version of the API docs are available here: http://tixxit.github.io/delimited/latest/api/


Delimited is a library for parsing CSV and CSV-like data in Scala. The parsing portion of the library revolves around DelimitedParser.

import java.io.{ BufferedReader, File, FileReader }
import net.tixxit.delimited._

// Create a parser for CSVs.
val parser: DelimitedParser =

// Parse a CSV string into a Vector
val rows: Vector[Either[DelimitedError, Row]] =

// Parse a File into a Vector
val rows: Vector[Either[DelimitedError, Row]] =
  parser.parseFile(new File("some-data.csv"))

// Parse a Reader into an Iterator
val reader: Reader = new BufferedReader(new FileReader("some-data.csv", "utf-8"))
val rows: Iterator[Either[DelimitedError, Row]] =

Fully Configurable Formats

Delimited is fairly open in how a format has been "delimited". You can specify the following parameters for parsing/rendering:

  • separators
  • quote characters
  • quote escaping
  • row delimiters
  • are row delimiters allowed in quotes?
  • etc

For example, we may want to delimit our rows with pipes, instead of newlines.

val MyCSV: DelimitedFormat = DelimitedFormat.CSV.withRowDelim("|")
val rows: Vector[Either[DelimitedError, Row]] =
assert(rows == Vector(Right(Row("a", "b", "c")), Right(Row("d", "e", "f"))))

The actual choices for all the delimiters/options doesn't really matter though. We could get really fancy, for example:

val myFormat: DelimitedFormat = DelimitedFormat(
  separator = "  ", // 2-spaces
  quote = "''", // Use 2 single quotes for quote characters
  quoteEscape = "%", // Escape quotes inside quotes with this character
  rowDelim = RowDelim("\u0000"), // Separate rows with a null character
  allowRowDelimInQuotes = true // Allow row delimiters inside quotes
val rows: Vector[Either[DelimitedError, Row]] =
  DelimitedParser(myFormat).parseString("a  b c  d\u0000''e \u0000 ''  ''%''''  f")
assert(rows == Vector(Right(Row("a", "b c", "d")), Right(Row("e \u0000 ", "''", "f"))))

Format Inference

Delimited can infer any unspecified parameters in your DelimitedFormat. Only pick what you know, even if that is nothing! This is handy when playing with data for the first time, or when you need to parse delimited files from unknown sources.

The easy way to get started is just to use DelimitedFormat.Guess, which is a DelimitedFormatStrategy for basic inference of the various DelimitedFormat parameters.

val parser: DelimitedParser = DelimitedParser(DelimitedFormat.Guess)
val rows: Vector[Either[DelimitedError, Row]] =
assert(rows == Vector(
  Right(Row("a", "b", "c")),
  Right(Row("d", "e", "f")),
  Right(Row("g", "h\ti", "j"))))

You can also fix certain parameters if you know them ahead of time:

val TSVish = DelimitedFormat.Guess
  .withSeparator("\t") // tab-delimited values
  .withRowDelim("\n")  // newline delimited rows
val parser: DelimitedParser = DelimitedParser(TSVish)
val rows: Vector[Either[DelimitedError, Row]] =
assert(rows == Vector(
  Right(Row("a,b,c", "d,e,f")),
  Right(Row("g,h,i", "j,k,l"))))

Streaming Parser

Delimited supports streaming parsing. You feed in chunks of data and it'll give you the rows as they are able to be parsed. For simple data import jobs, this means you can parse a huge CSV in a constant amount of memory. Don't know the format ahead of time? No problem! Format inference works just fine with streaming parsing.

While things like parseReader use the streaming parser behind the scenes, it is useful to know why this is useful outside of this context. The important point is that DelimitedParsers are actually immutable. To parse a stream of data, you create new DelimitedParsers successively by feeding chunks of character data into the parseChunk method. This method returns any rows that were able to be parsed,as well as a new DelimitedParser that can be used to parse the next chunk. This makes it easier to integrate Delimited into functional stream processing frameworks.

val parser0: DelimitedParser = DelimitedParser(DelimitedFormat.CSV)
val (parser1, rows1) = parser0.parseChunk(Some("a,b,c\nd"))
val (parser2, rows2) = parser1.parseChunk(Some(",e,"))
val (parser3, rows3) = parser2.parseChunk(Some("f\ng,h,i\nj,k,l"))
val (parser4, rows4) = parser3.parseChunk(None)

// Only the first row is available after the first chunk has been parsed.
assert(rows1 == Vector(Right(Row("a", "b", "c"))))
// The 2nd chunk doesn't have a row delimiter, so no rows can be returned.
assert(rows2 == Vector())
// The last chunk contains the end of the 2nd row, as well as the 3rd row.
assert(rows3 == Vector(
  Right(Row("d", "e", "f")),
  Right(Row("g", "h", "i"))))
// We use None to indicate EOF, so the parser is able to return the last row.
assert(rows1 == Vector(Right(Row("a", "b", "c"))))

Iteratee Support (Cats)

Delimited also has support for Travis Brown's Iteratee library for cats in the delimited-iteratee library. You can review the scaladoc for some more details.

This provides an Enumeratee that parses chunks of character data into rows. It supports the same format inference as the methods on DelimitedParser.

import io.iteratee._
import net.tixxit.delimited.iteratee.Delimited

// An Iteratee that renders a sequence of Rows using the specified format.
val formatAsTSV: Iteratee[Lazy, Row, String] =
// An Enumeratee that parses delimited files (guesses format).
val parseAny: Enumeratee[Lazy, String, Row] =
// An iteratee that converts a delimited file in an inferred format to a TSV.
val convert: Iteratee[Lazy, String, String] =