Advanced features of the REST API

This section of the Orthanc Book is a complement to the description of the REST API of Orthanc. It explains some advanced uses of the API.

Jobs

Since Orthanc 1.4.0, a jobs engine is embedded within Orthanc. Jobs are high-level tasks to be processed by Orthanc. Jobs can be started synchronously or asynchronously (see the section below). All Jobs, no matter how they were started, are first added to a queue of pending tasks, and Orthanc will simultaneously execute a fixed number of jobs (check out configuration option ConcurrentJobs). Once the jobs have been processed, they are tagged as successful or failed, and kept in a history (the size of this history is controlled by the JobsHistorySize option).

By default, Orthanc saves the jobs into its database (check out the SaveJobs option). Jobs are saved within 100ms after their creation, and then, the whole jobs list, with their updated status, is saved every 10 seconds and when Orthanc stops. If Orthanc is stopped then relaunched, the jobs whose processing was not finished are automatically put into the queue of pending tasks or resumed if they were being processed when Orthanc stopped, regardless of whether they were started synchronously or asynchronously (see the section below). The command-line option --no-jobs can also be used to prevent the loading of jobs from the database upon the launch of Orthanc.

Note that the queue of pending jobs has no size limit.

Synchronous vs. asynchronous calls

Some calls to the REST API of Orthanc need time to be executed, and thus result in adding a job to the processing queue. This notably includes the following URIs:

Such REST API calls can be configured to be executed in a synchronous or an asynchronous mode:

  • Synchronous calls wait for the end of the execution of their associated job. This is in general the default behavior.
  • Asynchronous calls end immediately and return a handle to their associated job. It is up to the caller to monitor the execution by calling the jobs API (e.g. to know whether the job has finished its execution).

The choice between synchronous and asynchronous modes is done by setting the Synchronous field (or indifferently the Asynchronous field) in the POST body of the call to the REST API. Note that the transfers accelerator only runs in asynchronous mode.

An integer number (possibly negative) can be specified in the Priority field of the POST body. Jobs with higher priority will be executed first. By default, the priority is set to zero.

Despite being more complex to handle, the asynchronous mode is highly recommended for jobs whose execution time can last over a dozen of seconds (typically, the creation of an archive if SynchronousZipStream configuration option is set to false, or a network transfer). Indeed, synchronous calls can be affected by timeouts in the HTTP protocol if they last too long.

When generating archives asynchronously, you should take care of the MediaArchiveSize configuration that defines the maximum number of ZIP/media archives that are maintained by Orthanc, as a response to the asynchronous creation of archive. As of Orthanc 1.12.1, this value is 1 by default.

Monitoring jobs

The list of all jobs can be retrieved as follows:

$ curl http://localhost:8042/jobs
[ "e0d12aac-47eb-454f-bb7f-9857931e2904" ]

Full details about each job can be retrieved:

$ curl http://localhost:8042/jobs/e0d12aac-47eb-454f-bb7f-9857931e2904
{
  "CompletionTime" : "20190306T095223.753851",
  "Content" : {
    "Description" : "REST API",
    "InstancesCount" : 1,
    "UncompressedSizeMB" : 0
  },
  "CreationTime" : "20190306T095223.750666",
  "EffectiveRuntime" : 0.001,
  "ErrorCode" : 0,
  "ErrorDescription" : "Success",
  "ID" : "e0d12aac-47eb-454f-bb7f-9857931e2904",
  "Priority" : 0,
  "Progress" : 100,
  "State" : "Success",
  "Timestamp" : "20190306T095408.556082",
  "Type" : "Archive"
}

Note that the /jobs?expand URI will retrieve this information in one single REST query. The Content field contains the parameters of the job, and is very specific to the Type of job.

The State field can be:

  • Pending: The job is waiting to be executed.
  • Running: The job is being executed. The Progress field will be continuously updated to reflect the progression of the execution.
  • Success: The job has finished with success.
  • Failure: The job has finished with failure. Check out the ErrorCode and ErrorDescription fields for more information.
  • Paused: The job has been paused.
  • Retry: The job has failed internally, and has been scheduled for re-submission after a delay. As of Orthanc 1.12.1, this feature is not used by any type of job.

In order to wait for the end of an asynchronous call, the caller will typically have to poll the /jobs/... URI (i.e. make periodic calls), waiting for the State field to become Success or Failure.

Note that the integration tests of Orthanc give an example about how to monitor a job in Python using the REST API (cf. function MonitorJob()).

Jobs priority

When executing jobs, Orthanc will pick the jobs with the highest Priority from the pending job list. An integer value is a valid Priority. You may also use negative number to lower the priority below the default one (0).

Pending jobs are not ordered in the API response but they are picked up in the right order.

Interacting with jobs

Given the ID of some job, one can:

  • Cancel the job by POST-ing to /jobs/.../cancel.
  • Pause the job by POST-ing to /jobs/.../pause.
  • Resume a job in Paused state by POST-ing to /jobs/.../resume.
  • Retry a job in Failed state by POST-ing to /jobs/.../resubmit.

The related state machine is depicted in the implementation notes.

Example: Asynchronous generation of an archive

Sucessful jobs are associated with a set of so-called “outputs” that can be attached to the job.

Here is a sample bash session to ask Orthanc to generate a ZIP archive, then to download it locally:

$ curl http://localhost:8042/studies/27f7126f-4f66fb14-03f4081b-f9341db2-53925988/archive -d '{"Asynchronous":true}'
{
  "ID" : "82cc02d1-03fe-41f9-be46-a308d16ea94a",
  "Path" : "/jobs/82cc02d1-03fe-41f9-be46-a308d16ea94a"
}
$ curl http://localhost:8042/jobs/82cc02d1-03fe-41f9-be46-a308d16ea94a
{
  "CompletionTime" : "20200817T144700.401777",
  "Content" : {
    "Description" : "REST API",
    "InstancesCount" : 232,
    "UncompressedSizeMB" : 64
  },
  "CreationTime" : "20200817T144658.011824",
  "EffectiveRuntime" : 2.3879999999999999,
  "ErrorCode" : 0,
  "ErrorDescription" : "Success",
  "ID" : "82cc02d1-03fe-41f9-be46-a308d16ea94a",
  "Priority" : 0,
  "Progress" : 100,
  "State" : "Success",
  "Timestamp" : "20200817T144705.770825",
  "Type" : "Archive"
}
$ curl http://localhost:8042/jobs/82cc02d1-03fe-41f9-be46-a308d16ea94a/archive > a.zip

Note how we retrieve the content of the archive by accessing the archive output of the job (check out the virtual method IJob::GetOutput() from the source code of Orthanc).

Here is the corresponding sequence of commands to generate a DICOMDIR media:

$ curl http://localhost:8042/studies/27f7126f-4f66fb14-03f4081b-f9341db2-53925988/media -d '{"Asynchronous":true}'
$ curl http://localhost:8042/jobs/6332be8a-0052-44fb-8cc2-ac959aeccad9/archive > a.zip

As of Orthanc 1.12.1, only the creation of a ZIP or a DICOMDIR archive produces such “outputs”.

Attaching PDF file as DICOM series

Among many different types of data, DICOM files can be used to store PDF files. The /tools/create-dicom URI can be used to upload a PDF file to Orthanc. The following scripts perform such a DICOM-ization; They convert the HelloWorld2.pdf file to base64, then perform a POST request with JSON data containing the converted payload.

Importantly, the Parent field of the POST body can be set to the Orthanc identifier of some study in order to attach the newly-created PDF series to the given parent study.

Using bash:

# create the json data, with the BASE64 data embedded in it
(echo -n '{"Parent": "b6e8436b-c5835b7b-cecc9576-0483e165-ab5c710b", "Tags" : {"Modality" : "CT"}, "Content" : "data:application/pdf;base64,'; base64 HelloWorld2.pdf; echo '"}') > /tmp/foo

# upload it to Orthanc
cat /tmp/foo | curl -H "Content-Type: application/json" -d @- http://localhost:8042/tools/create-dicom

Using powershell:

# create the BASE64 string data
$fileInBase64 = $([Convert]::ToBase64String((gc -Path "HelloWorld2.pdf" -Encoding Byte)))

# create the json data
$params = @{Tags = @{PatientName = "Benjamino";Modality = "CT"};Content= "data:application/pdf;base64,$fileInBase64"}

# disabling the progress bar makes the Invoke-RestMethod call MUCH faster
$ProgressPreference = 'SilentlyContinue'

# upload it to Orthanc
$reply = Invoke-RestMethod http://localhost:8042/tools/create-dicom -Method POST -Body ($params|ConvertTo-Json) -ContentType 'application/json'

# display the result
Write-Host "The instance can be retrieved in PDF at http://localhost:8042$($reply.Path)/pdf"

And here’s another sample using python.

Please note that the /tools/create-dicom API call will return the Orthanc instance ID of the newly created DICOM resource.

You can use the /instances/.../pdf URI to retrieve an embedded PDF file.

Creating DICOM instance with private tags

The /tools/create-dicom URI can be used to create DICOM instances containing private tags. Those private tags must first be defined in the Dictionary configuration option of Orthanc. Importantly, the xxxx,0010 tag must be defined to register the private creator, where xxxx is the private group of interest. Here is a sample:

{
  "Dictionary" : {
    "0405,0010" : [ "LO", "PrivateCreatorForMyCompany", 1, 1, "My Company" ],   // reserve 0405,10xx for "My Company"
    "0405,1001" : [ "ST", "MyPrivateXMLTag", 1, 1, "My Company" ]               // all tags from "My Company" must start with 0405,10xx
  }
}

Once Orthanc is started using this configuration file, it is possible to create a DICOM instance using the following POST body on /tools/create-dicom:

{
  "PrivateCreator" : "My Company",                             // private creator here
  "Tags" :
  {
    "PatientName" : "Love^Sarah",
    "PatientID" : "7",
    "PrivateCreatorForMyCompany" : "My Company",               // and here !
    "MyPrivateXMLTag" : "<xml><test>Testing</test></xml>"
  }
}

Which then gives this in Orthanc UI:

../_images/PrivateTagsInCreateDicom.png

Rob Oakes provides more a detailed explanation about how to use private tags with Orthanc on Oak-Tree’s homepage.

Instrumentation with Prometheus

Orthanc publishes its metrics according to the text-based format of Prometheus (check also the OpenMetrics project), onto the /tools/metrics-prometheus URI of the REST API. For instance:

$ curl http://localhost:8042/tools/metrics-prometheus
orthanc_count_instances 21741 1680083638028
orthanc_count_patients 86 1680083638028
orthanc_count_series 239 1680083638028
orthanc_count_studies 93 1680083638028
orthanc_dicom_cache_count 2 1680083630571
orthanc_dicom_cache_size 0.00191688538 1680083630571
orthanc_disk_size_mb 16855.9629 1680083638028
orthanc_jobs_completed 10 1680083638028
orthanc_jobs_failed 0 1680083638028
orthanc_jobs_pending 0 1680083638028
orthanc_jobs_running 0 1680083638028
orthanc_jobs_success 10 1680083638028
orthanc_last_change 81062 1680083638028
orthanc_rest_api_active_requests 1 1680083638027
orthanc_rest_api_duration_ms 77 1680083630549
orthanc_storage_create_duration_ms 2 1680083630565
orthanc_storage_read_duration_ms 2 1680083630557
orthanc_store_dicom_duration_ms 7 1680083630570
orthanc_uncompressed_size_mb 16855.9629 1680083638028
orthanc_up_time_s 64 1680083638028

Note that the collection of metrics can be statically disabled by setting the global configuration option MetricsEnabled to false, or dynamically disabled by PUT-ing 0 on /tools/metrics:

$ curl http://localhost:8042/tools/metrics
1
$ curl http://localhost:8042/tools/metrics -X PUT -d '0'
$ curl http://localhost:8042/tools/metrics
0

Here is a sample configuration for Prometheus (in the YAML format):

scrape_configs:
  - job_name: 'orthanc'
    scrape_interval: 10s
    metrics_path: /tools/metrics-prometheus
    basic_auth:
      username: orthanc
      password: orthanc
    static_configs:
      - targets: ['192.168.0.2:8042']

Obviously, make sure to adapt this sample with your actual IP address. Thanks to Docker, you can easily start a Prometheus server by writing this configuration to, say, /tmp/prometheus.yml, then type:

$ sudo run -p 9090:9090 -v /tmp/prometheus.yml:/etc/prometheus/prometheus.yml --rm prom/prometheus:v2.7.0