Scala-IO Core: Output

The Output object is the primary trait for writing data to a resource. The basic usage is very simple but can get more complex when one wishes to serialize objects.

Lets start with the basic usage:

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import scalax.io._ import scalax.io.Resource   val out:Output = Resource.fromOutputStream(new java.io.FileOutputStream("daily-scala.out")) val in:Input = Resource.fromFile("daily-scala.out")   // Write some bytes to the output object // each write will typically overwrite //the previous data the processing API // can be used is you do not want this behaviour out write "data".getBytes() out write Array[Byte](1,2,3)   // print out file in REPL in.byteArray   // Writing strings need a Codec // for encoding the strings.  The default is UTF8 // but the default is easily overridden. out write "howdy"   // printout file in REPL in.string   out.write("howdy")(Codec.UTF8)   // printout file in REPL in.string   implicit val defaultCodec: Codec = Codec.UTF8   // The implicit code will be used instead of the // default codec out write "hi there"   // printout file in REPL in.string   // write all strings in a collection with default separator ("") out writeStrings Seq("it","was","a","dark","and","stormy","night")   // printout file in REPL in.string   // write all strings in sequence with a space as the separator out.writeStrings(Seq("it","was","a","dark","and","stormy","night"), " ")

A common need is to write several times to a single Output without overwriting the data. To do this one can use the processing API. A future post(s) will look at the processing API in more detail but for now a simple example:

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import scalax.io._   val output:Output = Resource.fromOutputStream(new java.io.FileOutputStream("daily-scala.out")) val in:Input = Resource.fromFile("daily-scala.out")   // Output processor are used when one // needs to perform batch writes on an // output object When a processor object // is used a "processing" pipeline is // created and the operations are performed // in batch form.   // The following example will write 2 lines // to the output object (a file in this case) // there are a few ways to use outputProcessors.    // This example is the pattern most developers will // likely be most comfortable with: for{   // create a processor (signalling the start of a batch process)   processor <- output.outputProcessor   // create an output object from it   out = processor.asOutput }{   // all writes to out will be on the same open output stream/channel   out.write("first write\n")   out.write("second write") }   // show data in REPL in.string   // As will be shown in the future, a processor is typically lazy // if created with map and flatmap calls. // The next example is another way to do the multiple writes.   // first create processor val processor = for{     // create the processor     out <- output.outputProcessor     // perform write calls     _ <- out.write("second time first write\n")     _ <- out.write("second time second write") } yield {} // at this point the writes have not occurred because // processor contains the processing pipeline   // show data in REPL in.string   processor.execute  // execute processor   // show data in REPL in.string