Start all the services

Test web server

In a shell/command window, move into the openrem folder:

  • Ubuntu linux: /usr/local/lib/python2.7/dist-packages/openrem/
  • Other linux: /usr/lib/python2.7/site-packages/openrem/
  • Linux virtualenv: lib/python2.7/site-packages/openrem/
  • Windows: C:\Python27\Lib\site-packages\openrem\
  • Windows virtualenv: Lib\site-packages\openrem\

Run the built in web server:

python manage.py runserver --insecure

Open the web addesss given, optionally appending /openrem (http://localhost:8000/openrem)

If you are using a headless server and need to be able to see the web interface from another machine, use python manage.py runserver x.x.x.x:8000 --insecure replacing the x with the IP address of the server and 8000 with the port you wish to use. Then on your client computer, go to http://x.x.x.x:8000/openrem, again replacing the x with the IP address of the server, and ammending the 8000 as appropriate.

Note

Why are we using the --insecure option? With DEBUG mode set to True the test web server would serve up the static files. In this release, DEBUG mode is set to False, which prevents the test web server serving those files. The --insecure option allows them to be served again.

Celery task queue

Celery will have been automatically installed with OpenREM, and along with RabbitMQ allows for asynchronous task processing for imports, exports and DICOM networking tasks.

Note

Celery needs to be able to write to the place where the Celery logs and pid file are to be stored, so make sure the folder permissions allow this for the user that starts Celery. In the examples below, the logs and pid files are written to the MEDIA_ROOT location, where Celery and the webserver also needs to be able to write exported files. For a Debian/Ubuntu server, the webserver user is usually www-data, so you might like to start Celery with the www-data user too.

You might instead wish to write the logs to a folder in /var/log/ on linux systems - wherever you define, the folder should already exist.

In a new shell/command window, move into the openrem folder:

  • Ubuntu linux: /usr/local/lib/python2.7/dist-packages/openrem/
  • Other linux: /usr/lib/python2.7/site-packages/openrem/
  • Linux virtualenv: lib/python2.7/site-packages/openrem/
  • Windows: C:\Python27\Lib\site-packages\openrem\
  • Windows virtualenv: Lib\site-packages\openrem\

Linux - \ is the line continuation character:

celery multi start default -A openremproject -c 4 -Q default \
--pidfile=/path/to/media/celery/%N.pid --logfile=/path/to/media/celery/%N.log

Windows - celery multi doesn’t work on Windows, and ^ is the continuation character:

celery worker -n default -A openremproject -c 4 -Q default ^
--pidfile=C:\path\to\media\celery\default.pid --logfile=C:\path\to\media\celery\default.log

For production use, see Daemonising Celery below

Set the number of workers (concurrency, -c) as you see fit. The more you have, the more processes (imports, exports, query-retrieve operations etc) can take place simultaneously. However, each extra worker uses extra memory and if you have too many they will be competing for CPU resources too.

To stop the celery queues in Linux:

celery multi stop stores default --pidfile=/path/to/media/celery/%N.pid

For Windows, just press Ctrl+c

You will need to do this twice if there are running tasks you wish to kill.

Celery periodic tasks: beat

Celery beat is a scheduler. If it is running, then every 60 seconds a task is run to check if any of the DICOM Store SCP nodes are set to keep_alive, and if they are, it tries to verify they are running with a DICOM echo. If this is not successful, then the Store SCP is started.

To run celery beat, open a new shell and move into the openrem folder:

  • Ubuntu linux: /usr/local/lib/python2.7/dist-packages/openrem/
  • Other linux: /usr/lib/python2.7/site-packages/openrem/
  • Linux virtualenv: lib/python2.7/site-packages/openrem/
  • Windows: C:\Python27\Lib\site-packages\openrem\
  • Windows virtualenv: Lib\site-packages\openrem\

Linux:

celery -A openremproject beat -s /path/to/media/celery/celerybeat-schedule \
-f /path/to/media/celery/celerybeat.log \
--pidfile=/path/to/media/celery/celerybeat.pid

Windows:

celery -A openremproject beat -s C:\path\to\media\celery\celerybeat-schedule ^
-f C:\path\to\media\celery\celerybeat.log ^
--pidfile=C:\path\to\media\celery\celerybeat.pid

For production use, see Daemonising Celery below

As with starting the Celery workers, the folder that the pid, log and for beat, schedule files are to be written must already exist and the user starting Celery beat must be able write to that folder.

To stop Celery beat, just press Ctrl+c

Configure the settings

  • Follow the link presented on the front page to get to the user and group administration.
Initial home page with no users in groups
Configuration menu
  • After the first users are configured, this link will no longer be presented and instead you can go to Config -> Manage users.

  • You will need the superuser username and password you created just after creating the database. The groups are

    • viewgroup can browse the data only
    • importsizegroup can use the csv import facility to add patient height and weight information
    • importqrgroup can use the DICOM query-retrieve facility to pull in studies, as long as they are pre-configured
    • exportgroup can view and export data to a spreadsheet
    • pidgroup can search using patient names and IDs depending on settings, and export with patient names and IDs if they are also a member of the exportgroup
    • admingroup can delete studies, configure DICOM Store/QR settings, configure DICOM keep or delete settings, configure patient ID settings, and abort and delete patient size import jobs. Members of the admingroup no longer inherit the other groups permissions.
Selecting groups in Django user admin
  • In addition to adding users to these groups, you may like to grant a second user superuser and staff status so that there are at least two people who can manage the users
  • Return to the OpenREM interface (click on View site at the top right)
Link from Django user admin back to OpenREM
  • Go to Config -> DICOM object delete settings and configure appropriately (see Delete objects configuration)
  • Go to Config -> Patient ID settings and configure appropriately (see Patient identifiable data)
  • If you want to use OpenREM as a DICOM store, or to use OpenREM to query remote systems, go to Config -> Dicom network configuration. For more information go to DICOM Store and QR (not yet up to date)
  • With data in the system, you will want to go to Config -> View and edit display names and customise the display names. An established system will have several entries for each device, from each time the software version, station name or other elements changes. See Viewing and editing individual x-ray system display names using the web interface for more information

Start using it!

Add some data!

openrem_rdsr.py rdsrfile.dcm

Further instructions

Daemonising Celery

In a production environment, Celery will need to start automatically and not depend on a particular user being logged in. Therefore, much like the webserver, it will need to be daemonised. For now, please refer to the instructions and links at http://celery.readthedocs.org/en/latest/tutorials/daemonizing.html.