data_downloader.services.hyp3.Jobs

class data_downloader.services.hyp3.Jobs(jobs: list[Job])

A class to manage HyP3 jobs. It provides a pythonic interface to filter and select jobs using the numpy and pandas libraries. This class is designed to be used as the jobs attribute of the HyP3Service class.

__init__(jobs: list[Job]) → None

Initialize the Jobs class

Parameters:

jobs (list[sdk.Job]) – List of Job objects from HyP3 SDK. You can get the jobs from the hyp3_sdk.Batch.jobs attribute.

Methods

__init__(jobs)	Initialize the Jobs class
sel([name, job_type, status_code, request_time])	Select jobs based on job type and status code

Attributes

browse_images	the browse images of all jobs
credit_cost	the credit cost of all jobs
expiration_time	the expiration time of all jobs
failed	all failed jobs (not expired by default)
file_names	the file names of all jobs
file_sizes	the file sizes of all jobs
file_urls	the file urls of all jobs
files	the files of all jobs
frame	jobs in the form of a pandas DataFrame
job_id	the job ID of all jobs
job_parameters	the job parameters of all jobs
job_type	the job type of all jobs
logs	the logs of all jobs
name	the name of all jobs
pending	all pending jobs (not expired by default)
processing_times	the processing times of all jobs
request_time	the request time of all jobs
running	all running jobs (not expired by default)
status_code	the status code of all jobs
succeeded	all succeeded jobs (not expired by default)
thumbnail_images	the thumbnail images of all jobs
total_credit_cost	the total credit cost of all jobs
user_id	the user ID of all jobs

__init__(jobs: list[Job]) → None

Initialize the Jobs class

Parameters:

jobs (list[sdk.Job]) – List of Job objects from HyP3 SDK. You can get the jobs from the hyp3_sdk.Batch.jobs attribute.

property job_type: ndarray

the job type of all jobs

property job_id: ndarray

the job ID of all jobs

property request_time: ndarray

the request time of all jobs

property status_code: ndarray

the status code of all jobs

property user_id: ndarray

the user ID of all jobs

property name: ndarray

the name of all jobs

property job_parameters: ndarray

the job parameters of all jobs

property files: ndarray

the files of all jobs

property file_names: ndarray

the file names of all jobs

property file_urls: ndarray

the file urls of all jobs

property file_sizes: ndarray

the file sizes of all jobs

property logs: ndarray

the logs of all jobs

property browse_images: ndarray

the browse images of all jobs

property thumbnail_images: ndarray

the thumbnail images of all jobs

property expiration_time: ndarray

the expiration time of all jobs

property processing_times: ndarray

the processing times of all jobs

property credit_cost: ndarray

the credit cost of all jobs

property total_credit_cost: int

the total credit cost of all jobs

property frame: DataFrame

jobs in the form of a pandas DataFrame

sel(name: str | None = None, job_type: JobType | None = None, status_code: JobStatus | None = None, request_time: datetime | str | slice | None = None) → Jobs

Select jobs based on job type and status code

Parameters:

• name (str | None) – Name of the job to filter by

• job_type (JobType | None) – Job type to filter by

• status_code (JobStatus | None) – Status code to filter by

• request_time (datetime | str | slice | None) – Request time to filter by. Can be a datetime object, a string, or a slice object. If a slice object is used, the start must be a string or a datetime object, and the stop can be None, a string, or a datetime object. If a string is used, it must be in the format that can be converted to a datetime object using pd.to_datetime. by default None

property succeeded: Jobs

all succeeded jobs (not expired by default)

property failed: Jobs

all failed jobs (not expired by default)

property pending: Jobs

all pending jobs (not expired by default)

property running: Jobs

all running jobs (not expired by default)