Introduction
workflow.py
is a minimalist file based workflow engine. It runs as a background process and can automate certain tasks such as deleting old files, emailing you when new files are created or run a script to process new files.
License
3-clause BSD License
Copyright (c) 2012, Massimo Di Pierro All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
- Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
- Neither the name of the nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Configuring and Starting the workflow
- create a file
workflow.config
using the syntax below - run
workflow.py
in that folder
Workflow options
-f <path>
the folder to monitor and process-s <seconds>
the time interval between checks for new files-n <name>
the current filename, defaults to$0
-x <path>
the config file to use (workflow.config)-y <path>
the cache file to use (workflow.cache.db)-l <path>
the output logfile (else console output)-d
daemonizes the workflow process-c <rulename>
does not start the workflow but clears a rule (see below)
workflow.config
syntax
workflow.config
consists of a series of rules with the following syntax
rulename: pattern [dt]: command
where
rulename
is the name of the rule (cannot contain spaces).pattern
is a glob pattern for files to monitor. Avoid using*.*
!dt
is a time interval (default is 1 second). Only files modified more thandt
seconds ago will be considered.command
is the command to execute for each file matchingpattern
created more thandt
seconds ago and not processed already. If the command ends in&
, it is executed in background, else it blocks the workflow until completion. The name of the matching file can be referred to into the command with$0
. Multiline commands can be continued with\
.
Lines starting with #
are interpreted as comments and ignored.
Examples of rules
*.log
files older than one day
Delete all delete_old_logs: *.log [1d]: rm $0
*.txt
files older than one hour to other folder
Move all move_old_txt: *.txt [1h]: mv $0 otherfolder/$0
*.doc
file is created
Email me when a new email_me_on_new_doc: *.doc: mail -s 'new file: $0' [email protected] < /dev/null
*.dat
files using a Python script
Process new process_dat: *.dat: python process.py $0
*.src
file
Create a finite state machine for each rule1: *.src [1s]: echo > $0.state.1
rule2: *.state.1 [1s]: mv $0 `expr "$0" : '\(.*\).1'`.2
rule3: *.state.2 [1s]: mv $0 `expr "$0" : '\(.*\).2'`.3
rule4: *.state.3 [1s]: rm $0
Details
When a file matches a pattern, a new process is created to execute the corresponding command. The pid of the process is saved in <filename>.<rulename>.pid
. This file is deleted when the process is completed. If the process fails the output log and error is saved in <filename>.<rulename>.err
. If the process does not fail the output is stored in <filename>.<rulename>.out
.
If a file has already been processed according to a certain rule, this info is stored in a file workflow.cache
and it is not processed again unless:
- the mtime of the file changes (for example you edit or touch the file)
- the rule is cleaned up.
You can cleanup a rule with
python workflow.py -c rulename
This has the effect of creating a file .workflow.rulename.clear
which the running workflow.py picks up and uses to clear the entry identified by rulename
in workflow.cache
, after which the rule will run again.
You can also delete the workflow.cache
file. In this case all rules will run again when you restart workflow.py
.
If the main workflow.py
process is killed or crashes while some commands are being executed, those commands also are killed. You can find which files and rules where being processed by looking for <filename>.<rulename>.pid
files. If you restart workflow.py
those pid files are deleted.
If a rule results in an error and a <filename>.<rulename>.err
is created, the file is not processed again according to the rule, unless the error file is deleted.
If a file is edited or touched and the rule runs again, the <filename>.<rulename>.out
will be overwritten.
Unless otherwise specified each file is processed 1s after it is last modified. It is possible that a different process is still writing the file but it is pausing more than 1s between writes (for example the file is being downloaded via a slow connection). In this case it is best to download the file with a different name than the name used for the pattern and rename the file to its proper name after the write of the file is completed. This must be handled outside of workflow. Workflow has no way of knowing when a file is completed or not.
If the workflow.config
file is edited or changed, it is reloaded without the need to re-start workflow.py
.