Job

class geodesic.tesseract.job.Job(name=None, bbox=None, geometry=None, alias=None, description=None, bbox_epsg=4326, output_epsg=3857, output=None, job_id=None, **spec)

represents a Tesseract Job

The class can be initialized either with a dictionary (**spec) that represents the request for the particular type, or can be given an job ID. If a job ID is provided it will query for that job on the tesseract service and then update this class with the specifics of that job.

Parameters:

• **spec – A dictionary representing the job request.

• job_id (str) – The job ID string. If provided the job will be initialized with info by making a request to tesseract.

Attributes

alias	(str) - a human readable name for the dataset created by this job
bbox	(tuple, list, dict, str, bytes, BaseGeometry) - the rectangular extent of this job.
bbox_epsg	(int) - the EPSG code of the bounding box spatial reference.
dag
dataset
description	(str) - a longer description for the dataset created by this job
geometry	(str, dict, bytes, BaseGeometry) - A geometry to filter the job with only assets intersecting this will be processed.
hooks	(Webhook, dict) - NOT YET IMPLEMENTED.
item
name	(str) - a unique name for the dataset created by this job.
output	(Bucket, dict) - the output, other than default storage
output_epsg	(int) - the EPSG code of the output spatial reference.
project	the project that this job will be assigned to
state
steps	(Step, dict) - A list of steps to execute
workers	(int) - Number of workers to use for each step in the job.

Methods

add_create_assets_step(*, asset_name[, ...])	add a Data input to this Tesseract Job
add_data_input(*, asset_name[, name, ...])	add a Data input to this Tesseract Job
add_model_step(*, name, container, inputs, ...)	add a Model step to this Tesseract Job
add_multiscale_step(*, asset_name[, ...])	adds a multiscales step to the job
add_rechunk_step(*, asset_name, chunk_shape)	adds a rechunk step to the job
add_step(step)
clear()
copy()
delete([remove_data])	Deletes a job in the Tesseract service.
delete_and_wait([timeout_seconds])
fromkeys([value])	Create a new dictionary with keys from iterable and values set to value.
get(key[, default])	Return the value for key if key is in the dictionary, else default.
is_dag()
items()
keys()
load(job_id[, dry_run])	Loads job information for job_id if the job exists
ndarray(asset_name)	Returns a numpy.ndarray for specified asset name.
pop(k[,d])	If key is not found, default is returned if given, otherwise KeyError is raised
popitem()	Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])	Insert key with a value of default if key is not in the dictionary.
status([return_quark_geoms, ...])	Status queries the tesseract service for the jobs status.
submit([overwrite, dry_run, timeout_seconds])	Submits a job to be processed by tesseract
update(*mapping, **kwargs)
update_step_params(step_name[, input_index, ...])	updates the parameters for an existing step by looking up the step by name and then applying parameters
values()
watch()	Monitor the tesseract job with the SeerAI widget.
watch_terminal()
widget()
zarr([asset_name])	Returns the Zarr group for the corresponding asset name