# Copyright 2020 Google LLC

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

import os

import time

import backoff

from google.api_core.client_options import ClientOptions

from google.api_core.exceptions import DeadlineExceeded

from google.api_core.exceptions import FailedPrecondition

from google.cloud import datalabeling_v1beta1 as datalabeling

import create_annotation_spec_set as annotation_spec_set_sample

import create_instruction as instruction_sample

import import_data as import_sample

import manage_dataset as dataset_sample

RETRY_DEADLINE = 60

def create_client():

# If provided, use a provided test endpoint - this will prevent tests on

# this snippet from triggering any action by a real human

if 'DATALABELING_ENDPOINT' in os.environ:

opts = ClientOptions(api_endpoint=os.getenv('DATALABELING_ENDPOINT'))

client = datalabeling.DataLabelingServiceClient(client_options=opts)

else:

client = datalabeling.DataLabelingServiceClient()

return client

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def create_dataset(project_id):

return dataset_sample.create_dataset(project_id)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def delete_dataset(name):

return dataset_sample.delete_dataset(name)

def delete_old_datasets(project_id):

client = create_client()

formatted_project_name = client.project_path(project_id)

response = client.list_datasets(formatted_project_name)

# It will delete datasets created more than 2 hours ago

cutoff_time = time.time() - 7200

for element in response:

if element.create_time.seconds < cutoff_time:

print("Deleting {}".format(element.name))

try:

dataset_sample.delete_dataset(element.name)

except FailedPrecondition as e:

# We're always getting FailedPrecondition with 400

# resource conflict. I don't know why.

print("Deleting {} failed.".format(element.name))

print("Detail: {}".format(e))

# To avoid quota error

time.sleep(1)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def create_annotation_spec_set(project_id):

return annotation_spec_set_sample.create_annotation_spec_set(project_id)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def delete_annotation_spec_set(name):

client = create_client()

client.delete_annotation_spec_set(name)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def create_instruction(project_id, data_type, gcs_uri):

return instruction_sample.create_instruction(project_id, data_type, gcs_uri)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def delete_instruction(name):

client = create_client()

client.delete_instruction(name)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def cancel_operation(name):

client = create_client()

client.transport._operations_client.cancel_operation(name)

@backoff.on_exception(backoff.expo, DeadlineExceeded, max_time=RETRY_DEADLINE)

def import_data(dataset_name, data_type, gcs_uri):

import_sample.import_data(dataset_name, data_type, gcs_uri)