With the Partek Flow REST API, you can create custom solutions to query or drive your server. Below are some use cases for the REST API:
A complete list of all the commands available for the API can be found on the REST API Command List
The public key and Python libraries can be downloaded here.
Generate an authentication token
An access token can be generated from the System information section of the settings page.
Alternatively, GetToken.py will generate a token:
>python GetToken.py --server localhost:8080 --user admin
Example output:
TOKEN: cUOWY0VvkSFagrDUANVtM7A8SPal8Gx0cf0ee24bfa9fe68e2b5564dab2b6a27e1fb525e5...
This token can be specified as the --password parameter for the Python API. If the token is not supplied, then the Python API will prompt for the password and encrypt it.
When accessing the API directly, the encrypt parameter must be specified with the RSA value to use the token:
curl --form username=admin --form encrypt=RSA --form password=cUOWY0VvkSFagr... http://localhost:8080/flow/api/v1/users/list
Upload and analyze a group of samples
Get the name of a pipeline from the GUI or from the API
http://localhost:8080/flow/api/v1/pipelines/list
Get the list of required inputs for the pipeline from the API
http://localhost:8080/flow/api/v1/pipelines/inputs?project=iDEA&pipeline=AlignAndQuantify
Get the IDs for the library files that match the required inputs
http://localhost:8080/flow/api/v1/library_files/list?assembly=hg19
Use UploadSamples.py to upload the samples and launch the pipeline:
> python UploadSamples.py -v --server http://localhost:8080 --user admin --password [access token] --files ~/sample1.fastq.gz ~/sample2.fastq.gz --project ProjectName --pipeline AlignAndQuantify --inputs 28061,145855
Add a collaborator to a project
To add a collaborator to a project:
curl -X PUT "http://localhost:8080/flow/api/v1/projects?project=ProjectName&collaborator=user1&role=Collaborator&username=admin&encrypt=RSA&password=[url encoded token]"
Monitor a folder and upload files as they are created
#!/bin/bash
inotifywait -m $PATH_TO_MONITOR -e create -e moved_to |
while read path action file; do
if [[ $file == *.fastq.gz ]]; then
echo "Uploading $file"
python UploadSamples.py -v --server $SERVER --user $USER --password $TOKEN --files $path/$file --project "$PROJECT"
fi
done
Monitor the queue and send a notification if there are too many waiting tasks:
#!/bin/bash
while true; do
result=`python QueueStatistics.py --server $SERVER --user $USER --password $TOKEN --max_waiting $MAX_WAITING`
if [ $? -eq 1 ]; then
/usr/bin/notify-send $result
exit 1
fi
sleep $INTERVAL
done
Additional Assistance
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