Parallel tasks using pipe streams
Author KlausC
8 Stars
Updated Last
1 Year Ago
Started In
November 2020


Build Status Coverage Status


    run( `ls`gzip() → "ls.gz")

The ChannelBuffers package integrates the concept of commandline pipelines into Julia. It is not only possible to execute external commands in parallel, but to mix them with internal Tasks and Threads.

If the user provides functions f, g, h, of the form f(input::IO, output::IO, args...), which read from in input stream and write their results to an output stream, they can execute the functions in parallel tasks.


Input/Output redirection is denoted by (\rightarrow), which indicates the direction of data flow. Besides that we support | to denote task pipelines. The symbols < and > known from commandline shells cannot be used, because they bear the semantics of comparison operators in Julia.


    tl = run("afile"closure(f, fargs...) → closure(g, gargs...) → "bfile")

Some standard closures are predefined, which make that possible:

    tl = run( curl("https::/myurltodownloadfrom.tgz") | gunzip() | tarx("targetdir") )


    a = my_object
    run( serializer(a) → "file") |> wait

    b = open("file") do cin
        run(cin → deserializer()) |> fetch

It is possible to open a pipe chain for read or write like for process pipes. And the can be run:

    tl = open("xxx.tar"tarxO())

    # or equivalently
    open("xxx.tar"tarxO()) do tl

    open(gzip() → "data.gz", "w") do tl
        write(tl, data)

    run(tarc(dir) → "dir.tar")

Predefined closures

    tarc(dir) # take files in input directory and create tar to output stream
    tarx(dir) # read input stream and extract files to empty target directory
    tarxO() # read input stream and concatenate all file contents to output stream
    gzip() # read input stream and write compressed data to output stream
    gunzip() # reverse of gzip
    transcoder(::Codec) # generalization for other kinds of TranscoderStreams
    curl(URL) # download file from URL and write to output stream
    serializer(obj) # write serialized form of input object to output stream
    deserializer() # read input stream and reconstruct serialized object


To create a user defined task, a function with the signature f(cin::IO, cout::IO, args...) is required. It can be transformed into a BClosure object

        fc = closure(f, args...) # ::BClosure

which can be run alone or combined with other closures and input/output specifiers. The following Base functions are redefined.

        Base: |, run, pipeline, wait, fetch

which are used as in

    tl = run(fc::BClosure) # ::TaskChain

    pl = in → fc → gc → hc → out
    pl = pipeline(fc, gc, hc, stdin=in stdout=out) # ::BClosureList

    tl = run(pl::BClosureList) # ::TaskChain

The assignments to pl are equivalent.

The pipelined tasks are considered finished, when the statically last task in the list terminates. The calling task can wait for this event with

    wait(tl::TaskChain) # ::Nothing

If the last task in the pipeline calculates a value, if can be waited for and obtained by

    fetch(tl::TaskChain) # ::Any

Both wait and fetch throw TaskFailedException if the last task in the list failed.


The internal pipes are implemented by ChannelIO <: IO which uses Channel objects to transport data between tasks. The tasks are spawned on different threads, if multithreading is available (JULIA_NUM_THREADS > 1). Communication endpoints of the pipeline can be arbitrary IO objects or AbstractStrings denoting file names. The files given as strings are appropriately opened and closed.

Element type of TaskChain is BTask, a tagging wrapper around Task. It delegates the most important methods, like wait, fetch, istask....

The full functionality of Base.pipeline is extended with the integration of Base.Cmd and BClosure.