Source code for gsf.task

The GSF task object provides task information and can submit a job to the GSF server with input.
from __future__ import absolute_import
from abc import abstractmethod, abstractproperty
from string import Template
from pprint import PrettyPrinter
from .gsfmeta import GSFMeta
from .utils import with_metaclass

[docs]class Task(with_metaclass(GSFMeta, object)): """ The GSF Task object connects to a GSF Task and its parameters. :Example: Import the modules for the example. >>> from gsf import Server >>> from pprint import pprint Connect to the GSF server, and then retrieve the SpectralIndex task. >>> server = Server('localhost','9191') >>> service = server.service('ENVI') >>> task = service.task('SpectralIndex') >>> print(type(task)) <class 'gsf.ese.task.Task'> Investigate task information. >>> print(task.uri, type(task.uri)) ('http://localhost:9191/ese/services/ENVI/SpectralIndex', <type 'str'>) >>> print(task.description, type(task.description)) ('This task creates a spectral index raster from one pre-defined spectral index. Spectral indices are combinations of surface reflectance at two or more wavelengths that indicate relative abundance of features of interest.', <type 'str'>) >>> print(task.display_name, type(task.display_name)) ('Spectral Index', <type 'str'>) >>> task_parameters = task.parameters >>> pprint(task_parameters) Submit a job to the GSF Server. See GSF Job for details on waiting for job to complete. >>> input_raster = dict(url='http://localhost:9191/ese/data/qb_boulder_msi', factory='URLRaster') >>> parameters = dict(INPUT_RASTER=input_raster, INDEX='Normalized Difference Vegetation Index') >>> job = task.submit(parameters) >>> print(type(job)) <class 'gsf.ese.job.Job'> """ def __str__(self): pretty_print = PrettyPrinter(indent=2) props = dict(, uri=self.uri, display_name=self.display_name, description=self.description, parameters=pretty_print.pformat(self.parameters)) return Template(''' name: ${name} uri: ${uri} display_name: ${display_name} description: ${description} parameters: ${parameters} ''').substitute(props) def __repr__(self): return self.__str__() def __unicode__(self): return self.__str__() @abstractmethod def __init__(self, uri=None): """ Returns a GSF Task object based on the uri. :param uri: A String representing the unique id of the task. :return: None """ self._uri = uri @abstractproperty def uri(self): """ The unique identifier of this task :return: a string """ pass @abstractproperty def name(self): """ The name of the task :return: a string """ pass @abstractproperty def display_name(self): """ The display name of the task :return: a string """ pass @abstractproperty def description(self): """ The task description :return: a string """ pass @abstractproperty def parameters(self): """ A list of the task parameter definitions. Each task parameter is a dictionary containing, but not limited to, the following keys: ================= ========== ================= ========================================================== Key Data Type Type Description ================= ========== ================= ========================================================== name string Required The name of the parameter display_name string Required The display name of the parameter type string Required The parameter data type direction string Required Can be *input* or *output* description string Required The parameter description required bool Required Indicates if the parameter is required on input when submitting a job dimensions string Optional Indicates if the parameter is an array if set. Dimesions is of the format *[dim1,dim2,...]* choice_list list Optional A list of available choices for the parameter input min type Optional The minimum value allowed for the parameter max type Optional The maximum value allowed for the parameter ================= ========== ================= ========================================================== :return: a list of parameter dictionaries """ pass @abstractmethod
[docs] def submit(self, parameters): """ Submits a task to the server asynchronously :param parameters: A dictionary of key-value pairs of parameter names and values. The dictionary serves as input to the job. :return: GSF Job object """ pass