Job API

The Job API is your execution context when running a job on the platform. A job being defined as a model training process, or the process of creating a test report.

It provides a python interface to the website, and keeps track of the resources you have available there, and parsing of input in the form of settings to your code.

From the platform, a job (model or test report) is an input configuration with a storage space attached. The storage space freely available to use by the job, but following a few conventions, allows the platform to parse specific content for display on the model page.

##Job object A Job in the python code is collected into a single object containing its state and settings at runtime. you can use the Job object directly, or subclass it to add your own functionality. Settings may be added to a job by subclassing the Job object, and changing the settings parameter type to a settings object to a new JobSettings object.

from brevettiai import Job, JobSettings
class MyJobSettings(JobSettings):
    my_custom_int_setting: int
    
class MyJob(Job):
    settings: MyJobSettings
    
    def run(self):
        print(f"My setting is {self.my_custom_setting}")
        return None

job = MyJob.init(job_id='UUID', api_key='key')
job.start()

Settings may themselves subclass JobSettings, pydantic BaseModel, pydantic dataclasses or python dataclasses. resulting in a tree of settings. Like the job_id and apikey the settings may be set from argv using a dot notation (--setting_name.sub_setting 42). for the job above, this may be set as --my_custom_int_setting 37. To add information about the field, use the pydantic Field class as default value.

Job lifecycle

Initialize

To begin executing a job you first need do get an execution context. retrieving settings datasets, access rights, etc. to do this you call the init function on a brevetti Job object.

from brevettiai import Job
job = Job.init()

The init function can use either arguments on the function or command line arguments --job_id and --api_key to find the job on the brevetti ai platform

Start

The Job is started by running the start the start function. By default this will upload a job output json file to the job, call the run function, and then complete the job. Overwrite the Job.run() function to perform the job you would like, returning a path to where the output model file is at the end. See example in the Job object section above.