README.md

fs2-zip

Simple streaming wrappers for JDK's ZipInputStream and ZipOutputStream. The wrappers use Java stream converters from fs2-io.

Read Zip Archive

Reads a zip file and prints MD5 digests for each zip entry to STDOUT:

import cats.effect._
import fs2._
import satorg.fs2.zip._

def readZipFile[F[_]: ConcurrentEffect : ContextShift](
  filename: String,
  blocker: Blocker
)(implicit config: ZipConfig): F[Unit] =
  io.file.readAll(filename, blocker, config.chunkSize)
    .through(unzipPipe(blocker))
    .flatMap { (entry: ZipEntry[F]) =>
      entry.body
        .through(hash.md5) // simply calculate MD5 digest for each entry
        .foldMap(b => f"$b%02x")
        .map(_ + " " + entry.path)
    }
    .showLinesStdOutAsync(blocker)
    .compile.drain

Note that Stream[F, ZipEntry[F]] cannot be processed in an order other than how they come from the source. Furthermore, every ZipEntry#body stream must be completed (or drained) before pulling the next ZipEntry. This limitation comes from java.util.zip.ZipInputStream which is strictly sequential.

However, it is still possible to process the entries in parallel (e.g., using .parJoinUnbounded) – the entries will arrange each other in the order as they come from the source stream.

Write Zip Archive

Takes a stream of arbitrary entries, creates string representation for each entry and writes them into a zip file.

import cats.effect._
import cats.syntax.show._
import fs2._
import satorg.fs2.zip._

def writeZipFile[F[_]: Concurrent : ContextShift, A: Show](
  entries: Stream[F, A],
  filename: String,
  blocker: Blocker
)(implicit config: ZipConfig): F[Unit] =
  entries
    .zipWithIndex
    .map { case (entry, index) =>
      ZipEntry[F](
        path = s"$index.txt",
        body = Stream.emit(entry.show).covary[F].through(text.utf8Encode)
      )
    }
    .through(zipPipe(blocker))
    .through(io.file.writeAll(filename, blocker))
    .compile.drain

See ZipUnzipTest for more examples.