Running a Generalized Compute Code Object using the Rhino SDK

This article explains how to use Rhino SDK to run a Generalized Compute Code object in Rhino FCP.

Note:  If you want to learn how to do this using the Rhino FCP UI, see Running a Generalized Compute Code Object.

Prerequisites

Before starting this process, you should have already:

1. Created a Project using the Rhino SDK or UI.
2. Created 1 or more Datasets using the Rhino SDK or UI.
3. Created a Code Object using the Rhino SDK or UI.

Import your Python Dependencies

import rhino_health as rh
from rhino_health.lib.endpoints.code.code_object_dataclass import (
    CodeObject,
    CodeObjectRunInput
)
import getpass

Note: Remember to change all lines with CHANGE_ME comments above them in all the blocks below!

Log into the Rhino SDK using your FCP Credentials

Your username will be the email address you log into the Rhino FCP platform with. 

print("Logging In")

# CHANGE_ME: MY_USERNAME
my_username = "MY_USERNAME"

session = rh.login(username=my_username, password=getpass.getpass())
print("Logged In")

Get Supporting FCP Information Needed to Run Your Code

At this point, you will need the name of your Project, any Dataset's name you would like to use as input, and your previously created Code Object's name. You can also retrieve each object's UUID by following the instructions here: How do I retrieve a Project's, Collaborator's, Data Schema's, Dataset's, Code's, or Code Run's' UUID?

# CHANGE_ME: YOUR_FCP_PROJECT_NAME
project = session.project.get_project_by_name('YOUR_FCP_PROJECT_NAME')

# CHANGE_ME: DATASET_NAME_1 & DATASET_NAME_2 & Possibly Version Number too
dataset1 = session.dataset.get_dataset_by_name("DATASET_NAME_1", project_uid=project.uid, version=1)
dataset2 = session.dataset.get_dataset_by_name("DATASET_NAME_2", project_uid=project.uid, version=1)
# Repeat the above for as many Datasets you would like to run as input to your Code

# CHANGE_ME: CODE_OBJECT_NAME & Possibly Version Number too
code_object = session.code.get_code_object_by_name("CODE_OBJECT_NAME:, project_uid=project.uid, version=1)

Run your Code

To run your Code you will need to supply the Code Object with the input Datasets you would like to run the Code over and an output Dataset names suffix.  The suffix will be appended to each input Dataset name so you can view the results of the Code Run once the output has been re-imported into the system as a Dataset.

code_object_params = CodeObjectRunInput(
  code_object_uid = code_object.uid,
  
  # CHANGE_ME: Add/Delete Dataset variables based on how many you want as input   
  input_cohort_uids = [dataset1.uid, dataset2.uid],        
  
  # CHANGE_ME: OUTPUT_SUFFIX    
  output_dataset_names_suffix = "OUTPUT_SUFFIX",
  
  run_params: {}, # Optional - The run params code you want to run on the Datasets
  timeout_seconds: 600, # Optional - The time before a timeout is declared for the run
  sync: False # Optional - If True wait for run to end if False let it run in the background
)
code_run = session.code.run_code_object(code_object_params)
run_result = code_run.wait_for_completion()

print("Finished running code")
print(f"Result status is '{run_result.status.value}', errors={run_result.result_info.get('errors') if run_result.result_info else None}")