NAME

       weaver - workflow engine for executing distributed workflows

SYNOPSIS

       weaver [options] <weaverfile>

DESCRIPTION

       Weaver  is  a  high level interface to makeflow. A weaver input file is written in python,
       with the definition of functions to be applied on sets of files.  weaver  interprets  this
       input  file  and generates a workflow specification that can be executed by makeflow. This
       allows an straightforward implementation of different workflow execution patterns, such as
       MapReduce, and AllPairs.

                                         /--------                        +-+ Python |
                                       | ---+----/
               +---------------------------------+ |     | Generate DAG
               |          Weaver          +-+     v
               +---------------------------------+   /-------|        Makeflow         +---+  DAG  |
               +--------+-----------+-----+------+   -------/
               | Condor | WorkQueue | SGE | Unix +-+     | Dispatch Jobs
               +--------+-----------+-----+------+ |     v
                                       | /-------                    +-+ Jobs  |
                                         -------/

OPTIONS

       By  default,  running  weaver  on  a  <weaverfile>  generates  an input file for makeflow,
       <Makeflow>, and a directory, <_Stash>, in which intermediate files are stored.

       General options:

        -h    Give help information.

        -W    Stop on warnings.

        -g    Include debugging symbols in DAG.

        -I    Do not automatically import built-ins.

        -N    Do not normalize paths.

        -b <options>
              Set batch job options (cpu, memory, disk, batch, local, collect).

        -d <subsystem>
              Enable debugging for subsystem.

        -o <log_path>
              Set log path (default: stderr).

        -O <directory>
              Set stash output directory (default <_Stash>).

              Optimization Options:

        -a    Automatically nest abstractions.

        -t <group_size>
              Inline tasks based on group size.

              Engine Options:

        -x    Execute DAG using workflow engine after compiling.

        -e <arguments>
              Set arguments to workflow engine when executing.

        -wwrapper <>
              Set workflow engine wrapper.

EXIT STATUS

       On success, returns zero.  On failure, returns non-zero.

EXAMPLES

       Weaver expresses common workflow patterns succinctly. For example, with only the following
       three  lines  of code we can express a map pattern, in which we convert some images to the
       jpeg format:

               convert = ParseFunction('convert {IN} {OUT}')
               dataset = Glob('/usr/share/pixmaps/*.xpm')
               jpgs    = Map(convert, dataset, '{basename_woext}.jpg')

       Please refer to cctools/doc/weaver_examples for further information.

       The Cooperative Computing Tools are Copyright (C) 2005-2019 The University of Notre  Dame.
       This  software  is distributed under the GNU General Public License.  See the file COPYING
       for details.