TransformationJob¶
A single asynchronous execution of a transformation image over a set of input files.
Properties¶
| Name | Type | Description | Notes |
|---|---|---|---|
| archived | bool | Whether the job has finished and been moved to long-term storage. Archived jobs can no longer be cancelled, but their final status and logs remain available. | [optional] |
| configuration_reference | TransformationConfigurationReference | [optional] | |
| create_time | datetime | Timestamp at which the job was created. | |
| dry_run | bool | If true, the job validates and simulates execution without producing or persisting output. | [optional] [default to False] |
| end_time | datetime | Timestamp at which the job reached a terminal state. Absent while the job is still in progress. | [optional] |
| id | int | Unique numeric identifier of the transformation job. | |
| image_reference | TransformationImageReference | ||
| input_accessions | List[str] | Accessions of the input files the job processes. | |
| memory_size | str | Amount of memory granted to the job. Accepts a size with a unit suffix, e.g. 512Mi or 2Gi; a plain number with no unit is interpreted as bytes. When omitted, the image's default memory size is used. | [optional] |
| status | TransformationStatus | ||
| volume_size | str | Working-volume size granted to the job. Accepts a size with a unit suffix, e.g. 30Gi; a plain number with no unit is interpreted as bytes. When omitted, the image's default volume size is used. | [optional] |
Example¶
from odm_api.models.transformation_job import TransformationJob
# TODO update the JSON string below
json = "{}"
# create an instance of TransformationJob from a JSON string
transformation_job_instance = TransformationJob.from_json(json)
# print the JSON string representation of the object
print(TransformationJob.to_json())
# convert the object into a dict
transformation_job_dict = transformation_job_instance.to_dict()
# create an instance of TransformationJob from a dict
transformation_job_from_dict = TransformationJob.from_dict(transformation_job_dict)