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Post Processing Agent

New version of the post-processing agent for automated reduction and cataloging.

For the old version of the post-processing agent, see https://github.com/mantidproject/autoreduce

codecov

Configuration

A configuration must be placed in /etc/autoreduce/post_processing.conf.

The configuration/post_process_consumer.conf.development file will make a good starting point for configuration. Here are the entries to pay attention to:

{
    "brokers": [("localhost", 61613)],
    "amq_user": "",
    "amq_pwd": "",
    "sw_dir": "/opt/postprocessing",
    "python_dir": "/opt/postprocessing/postprocessing",
    "start_script": "python",
    "task_script": "PostProcessAdmin.py",
    "task_script_queue_arg": "-q",
    "task_script_data_arg": "-d",
    "log_file": "/opt/postprocessing/log/postprocessing.log",

    "communication_only": 1,
    "jobs_per_instrument": 2
}

ActiveMQ settings

  • The ActiveMQ server settings must be set by replacing localhost above by the proper address and the "amq_user" and "amq_pwd" must be filled out.

  • If "jobs_per_instrument" is set to an integer greater than zero, no more than that number of jobs will run on a given node for a given instrument. Set "jobs_per_instrument" to zero to turn this feature off.

    If this feature is used, you must add the following to activemq.xml:

       <broker xmlns="http://activemq.apache.org/schema/core" brokerName="localhost" ... schedulerSupport="true">

   ...

   <plugins>
     <redeliveryPlugin fallbackToDeadLetter="true" sendToDlqIfMaxRetriesExceeded="true">
       <redeliveryPolicyMap>
         <redeliveryPolicyMap>
           <defaultEntry>
             <redeliveryPolicy maximumRedeliveries="4" initialRedeliveryDelay="5000" redeliveryDelay="10000" />
           </defaultEntry>
         </redeliveryPolicyMap>
       </redeliveryPolicyMap>
     </redeliveryPlugin>
   </plugins>

Installation settings

Mantid settings

  • Don't forget to set your Mantid user's properties to send output logs to stdout:
logging.channels.consoleChannel.class=StdoutChannel

Runtime settings

ONCat processing

The post processing agent handles cataloging raw and reduced data files in ONCat https://oncat.ornl.gov/ by calling scripts hosted on the analysis cluster.

Installation

Create the configuration files and edit according to your installation.

cd configuration
cp post_process_consumer.conf.developement /etc/autoreduce/post_processing.conf

To run, simply call

python [installation path]/queueProcessor.py

Development environment

The conda environment for running queueProcessor.py and tests locally is defined in environment.yml. Create and activate the conda environment for development.

conda env create  # or: mamba env create
conda activate post_processing_agent

Running the tests

The tests for this project are all written using pytest.

python -m pytest tests/

This is one of the ways pytest allows for selecting tests. Specifying a directory or file will run all tests within that directory (recursively) or file. Specifying a regular expression using -k will select all tests that match the regular expression independent of where they are defined

Integration tests

The integration tests requires activemq and the queueprocessor to be running, they will be automatically skipped if activemq is not running. This can be achieved using the docker-compose file provided,

docker compose -f tests/integration/docker-compose.yml up -d --build

then run

python -m pytest tests/integration

after which you can stop docker with

docker compose -f tests/integration/docker-compose.yml down

Running manual tests for mantidpython.py

Manual tests can be executed as

$ python scripts/mantidpython.py /SNS/HYP/shared/auto_reduction/reduce_HYS.py [HYS nexus file] [Output Dir]

or

$ python scripts/mantidpython.py tests/reduce_CONDA.py [Data file]  [Output dir]

as an example for how to activate a specific conda environment for reduction.

Running with docker

docker build --tag postprocessing .
docker run --network host postprocessing

Creating a new release

  1. Update the version number in SPECS/postprocessing.spec and pyproject.toml and commit the change to main.
  2. Create a new tag and create a release from the tag (see the three dots menu for the tag at https://github.com/neutrons/post_processing_agent/tags).
  3. Build the RPM using rpmbuild.sh and upload the .rpm and .srpm files as release assets to the GitHub release page.