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.