Backend of the Data Quality Monitoring. Web based display and analysis tools for Data Quality Assessment
A redis instance is needed, for that you can install docker and then run
docker pull redis
docker run -p 6379:6379 -d redis
The web display has only been tested on recent python versions so it is recommended to set up a DUNEDAQ working area with a recent nightly and run the web server from there.
Temporarily, copy the Web repository from a working location in np04 since it
contains one of the dependencies with a bugfix that it is not in the main
repository
To install for the first time run:
./make_env
./prepare_dqm
When using the prepare_dqm script, it is possible to change the port by changing by changing the last line to:
./manage.py runserver --nostatic 0.0.0.0:PORT
After it has been installed for the first time it's not necessary to run make_env and prepare_dqm again.
This application consists of two components: the web display and consumer.py. Both must be running for it to function.
One should remember to set up the workarea if the web display has been installed from one. The first step is to activate the virtual environment that was set up when running the previous two scripts. Run:
source env/bin/activate
There are two parts running, the first one is the script that receives the data from kafka, saves it and is used to trigger the updates in the web display. Run:
python dqm/manage.py shell < scripts/consumer.py
and leave the terminal open (for example using a tmux session). The second part is the web display itself. Run:
python dqm/manage.py runserver 0.0.0.0:PORT
where PORT can be changed. The address can be ommitted and it will run on 127.0.0.1:8050 by default