def save_tasks():
# Creates a pickle file with the locations of every datacube observation specified in the yaml file
with open('stats_config.yaml') as fl:
config = yaml.load(fl)
print(yaml.dump(config, indent=4))
print('generating tasks')
dc = Datacube(app='api-example', config='cambodia.conf')
app = StatsApp(config, index = dc.index)
pickle_stream(app.generate_tasks(dc.index), 'task.pickle')
def prune_tasks(quartile):
# 'prunes' the output pickle file from save_tasks() with a list of dates to create a new pickle file
# Import netcdf with the list of dates
spei_q_dates = xr.open_dataset(f"spei_q{quartile}_dates.nc")
pruned = (transform_task(task, spei_q_dates, quartile)
for task in unpickle_stream('task.pickle'))
pruned = (task for task in pruned if task is not None)
pickle_stream(pruned, f'task_q{quartile}.pickle')
def save_tasks_to_file(self, filename, index):
_LOG.debug('Saving tasks to %s.', filename)
output_products = self.configure_outputs(index)
tasks = self.generate_tasks(index, output_products)
num_saved = pickle_stream(tasks, filename)
_LOG.debug('Successfully saved %s tasks to %s.', num_saved, filename)