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chore: move samples from python-docs-sample to here (#29)
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* Data Labeling Beta samples [(#2096)](#2096)

* add files

* upate create_annotation_spec_set and test

* add requirements.txt

* update create_instruction and test

* update import data and test

* add label image and test

* add label_text test

* add label_video_test

* add manage dataset and tests

* flake

* fix

* add README

* Adds updates including compute [(#2436)](#2436)

* Adds updates including compute

* Python 2 compat pytest

* Fixing weird \r\n issue from GH merge

* Put asset tests back in

* Re-add pod operator test

* Hack parameter for k8s pod operator

* Update datalabeling samples to hit test endpoint. [(#2641)](#2641)

* Auto-update dependencies. [(#2005)](#2005)

* Auto-update dependencies.

* Revert update of appengine/flexible/datastore.

* revert update of appengine/flexible/scipy

* revert update of bigquery/bqml

* revert update of bigquery/cloud-client

* revert update of bigquery/datalab-migration

* revert update of bigtable/quickstart

* revert update of compute/api

* revert update of container_registry/container_analysis

* revert update of dataflow/run_template

* revert update of datastore/cloud-ndb

* revert update of dialogflow/cloud-client

* revert update of dlp

* revert update of functions/imagemagick

* revert update of functions/ocr/app

* revert update of healthcare/api-client/fhir

* revert update of iam/api-client

* revert update of iot/api-client/gcs_file_to_device

* revert update of iot/api-client/mqtt_example

* revert update of language/automl

* revert update of run/image-processing

* revert update of vision/automl

* revert update testing/requirements.txt

* revert update of vision/cloud-client/detect

* revert update of vision/cloud-client/product_search

* revert update of jobs/v2/api_client

* revert update of jobs/v3/api_client

* revert update of opencensus

* revert update of translate/cloud-client

* revert update to speech/cloud-client

Co-authored-by: Kurtis Van Gent <31518063+kurtisvg@users.noreply.github.com>
Co-authored-by: Doug Mahugh <dmahugh@gmail.com>

* Update datalabeling to match lint. [(#2642)](#2642)

* datalabeling: ensure all tests use test endpoint [(#2918)](#2918)

* datalabeling: ensure all tests use test endpoint

* requires an input csv for text input, slight print statement cleanup

Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>

* chore(deps): update dependency google-cloud-datalabeling to v0.4.0 [(#3081)](#3081)

This PR contains the following updates:

| Package | Update | Change |
|---|---|---|
| [google-cloud-datalabeling](https://github.com/googleapis/python-datalabeling) | minor | `==0.3.0` -> `==0.4.0` |

---

### Release Notes

<details>
<summary>googleapis/python-datalabeling</summary>

### [`v0.4.0`](https://github.com/googleapis/python-datalabeling/blob/master/CHANGELOG.md#&#8203;040-httpswwwgithubcomgoogleapispython-datalabelingcomparev030v040-2020-01-31)

[Compare Source](https://github.com/googleapis/python-datalabeling/compare/v0.3.0...v0.4.0)

##### Features

-   **datalabeling:** undeprecate resource name helper methods (via synth) ([#&#8203;10039](https://www.github.com/googleapis/python-datalabeling/issues/10039)) ([88f8090](https://www.github.com/googleapis/python-datalabeling/commit/88f809008ee6a709c02c78b1d93af779fab19adb))

##### Bug Fixes

-   **datalabeling:** deprecate resource name helper methods (via synth) ([#&#8203;9832](https://www.github.com/googleapis/python-datalabeling/issues/9832)) ([e5f9021](https://www.github.com/googleapis/python-datalabeling/commit/e5f902154ebe7fcb139aa405babfe9993fd51319))

</details>

---

### Renovate configuration

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:vertical_traffic_light: **Automerge**: Disabled by config. Please merge this manually once you are satisfied.

:recycle: **Rebasing**: Never, or you tick the rebase/retry checkbox.

:no_bell: **Ignore**: Close this PR and you won't be reminded about this update again.

---

 - [ ] <!-- rebase-check -->If you want to rebase/retry this PR, check this box

---

This PR has been generated by [WhiteSource Renovate](https://renovate.whitesourcesoftware.com). View repository job log [here](https://app.renovatebot.com/dashboard#GoogleCloudPlatform/python-docs-samples).

* Simplify noxfile setup. [(#2806)](#2806)

* chore(deps): update dependency requests to v2.23.0

* Simplify noxfile and add version control.

* Configure appengine/standard to only test Python 2.7.

* Update Kokokro configs to match noxfile.

* Add requirements-test to each folder.

* Remove Py2 versions from everything execept appengine/standard.

* Remove conftest.py.

* Remove appengine/standard/conftest.py

* Remove 'no-sucess-flaky-report' from pytest.ini.

* Add GAE SDK back to appengine/standard tests.

* Fix typo.

* Roll pytest to python 2 version.

* Add a bunch of testing requirements.

* Remove typo.

* Add appengine lib directory back in.

* Add some additional requirements.

* Fix issue with flake8 args.

* Even more requirements.

* Readd appengine conftest.py.

* Add a few more requirements.

* Even more Appengine requirements.

* Add webtest for appengine/standard/mailgun.

* Add some additional requirements.

* Add workaround for issue with mailjet-rest.

* Add responses for appengine/standard/mailjet.

Co-authored-by: Renovate Bot <bot@renovateapp.com>

* testing: mark some tests as flaky [(#3288)](#3288)

fixes #3138

* [datalabeling] testing: wrap rpcs with backoff [(#3443)](#3443)

* wrap all the rpcs with backoff
* add a shared testing lib
* remove flaky

* [datalabeling] fix: clean up old datasets before the test [(#3707)](#3707)

fixes #3710 
fixes #3711

* [datalabeling] testing: retry upon ServerError [(#3762)](#3762)

fixes #3760

* Replace GCLOUD_PROJECT with GOOGLE_CLOUD_PROJECT. [(#4022)](#4022)

* chore(deps): update dependency pytest to v5.4.3 [(#4279)](#4279)

* chore(deps): update dependency pytest to v5.4.3

* specify pytest for python 2 in appengine

Co-authored-by: Leah Cole <coleleah@google.com>

* Update dependency pytest to v6 [(#4390)](#4390)

* chore: update templates

* chore: fix docs error

* chore: skip unavailable samples

* chore: use staging endpoint for labeling tests

Co-authored-by: Rebecca Taylor <remilytaylor@gmail.com>
Co-authored-by: Gus Class <gguuss@gmail.com>
Co-authored-by: Kurtis Van Gent <31518063+kurtisvg@users.noreply.github.com>
Co-authored-by: DPEBot <dpebot@google.com>
Co-authored-by: Doug Mahugh <dmahugh@gmail.com>
Co-authored-by: Noah Negrey <nnegrey@users.noreply.github.com>
Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>
Co-authored-by: WhiteSource Renovate <bot@renovateapp.com>
Co-authored-by: Takashi Matsuo <tmatsuo@google.com>
Co-authored-by: Leah Cole <coleleah@google.com>
Co-authored-by: Bu Sun Kim <busunkim@google.com>
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1 change: 1 addition & 0 deletions datalabeling/AUTHORING_GUIDE.md
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See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/AUTHORING_GUIDE.md
1 change: 1 addition & 0 deletions datalabeling/CONTRIBUTING.md
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See https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/CONTRIBUTING.md
78 changes: 78 additions & 0 deletions datalabeling/snippets/README.rst
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.. This file is automatically generated. Do not edit this file directly.
Google Cloud Data Labeling Service Python Samples
===============================================================================

.. image:: https://gstatic.com/cloudssh/images/open-btn.png
:target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=datalabeling/README.rst


This directory contains samples for Google Cloud Data Labeling Service. `Google Cloud Data Labeling Service`_ allows developers to request having human labelers label a collection of data that you plan to use to train a custom machine learning model.




.. _Google Cloud Data Labeling Service: https://cloud.google.com/data-labeling/docs/

Setup
-------------------------------------------------------------------------------


Authentication
++++++++++++++

This sample requires you to have authentication setup. Refer to the
`Authentication Getting Started Guide`_ for instructions on setting up
credentials for applications.

.. _Authentication Getting Started Guide:
https://cloud.google.com/docs/authentication/getting-started

Install Dependencies
++++++++++++++++++++

#. Clone python-docs-samples and change directory to the sample directory you want to use.

.. code-block:: bash
$ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
#. Install `pip`_ and `virtualenv`_ if you do not already have them. You may want to refer to the `Python Development Environment Setup Guide`_ for Google Cloud Platform for instructions.

.. _Python Development Environment Setup Guide:
https://cloud.google.com/python/setup

#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

.. code-block:: bash
$ virtualenv env
$ source env/bin/activate
#. Install the dependencies needed to run the samples.

.. code-block:: bash
$ pip install -r requirements.txt
.. _pip: https://pip.pypa.io/
.. _virtualenv: https://virtualenv.pypa.io/



The client library
-------------------------------------------------------------------------------

This sample uses the `Google Cloud Client Library for Python`_.
You can read the documentation for more details on API usage and use GitHub
to `browse the source`_ and `report issues`_.

.. _Google Cloud Client Library for Python:
https://googlecloudplatform.github.io/google-cloud-python/
.. _browse the source:
https://github.com/GoogleCloudPlatform/google-cloud-python
.. _report issues:
https://github.com/GoogleCloudPlatform/google-cloud-python/issues


.. _Google Cloud SDK: https://cloud.google.com/sdk/
18 changes: 18 additions & 0 deletions datalabeling/snippets/README.rst.in
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# This file is used to generate README.rst

product:
name: Google Cloud Data Labeling Service
short_name: Cloud Data Labeling
url: https://cloud.google.com/data-labeling/docs/
description: >
`Google Cloud Data Labeling Service`_ allows developers to request having
human labelers label a collection of data that you plan to use to train a
custom machine learning model.

setup:
- auth
- install_deps

cloud_client_library: true

folder: datalabeling
87 changes: 87 additions & 0 deletions datalabeling/snippets/create_annotation_spec_set.py
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#!/usr/bin/env python

# Copyright 2019 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 argparse
import os

from google.api_core.client_options import ClientOptions


# [START datalabeling_create_annotation_spec_set_beta]
def create_annotation_spec_set(project_id):
"""Creates a data labeling annotation spec set for the given
Google Cloud project.
"""
from google.cloud import datalabeling_v1beta1 as datalabeling
client = datalabeling.DataLabelingServiceClient()
# [END datalabeling_create_annotation_spec_set_beta]
# 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)
# [START datalabeling_create_annotation_spec_set_beta]

project_path = client.project_path(project_id)

annotation_spec_1 = datalabeling.types.AnnotationSpec(
display_name='label_1',
description='label_description_1'
)

annotation_spec_2 = datalabeling.types.AnnotationSpec(
display_name='label_2',
description='label_description_2'
)

annotation_spec_set = datalabeling.types.AnnotationSpecSet(
display_name='YOUR_ANNOTATION_SPEC_SET_DISPLAY_NAME',
description='YOUR_DESCRIPTION',
annotation_specs=[annotation_spec_1, annotation_spec_2]
)

response = client.create_annotation_spec_set(
project_path, annotation_spec_set)

# The format of the resource name:
# project_id/{project_id}/annotationSpecSets/{annotationSpecSets_id}
print('The annotation_spec_set resource name: {}'.format(response.name))
print('Display name: {}'.format(response.display_name))
print('Description: {}'.format(response.description))
print('Annotation specs:')
for annotation_spec in response.annotation_specs:
print('\tDisplay name: {}'.format(annotation_spec.display_name))
print('\tDescription: {}\n'.format(annotation_spec.description))

return response
# [END datalabeling_create_annotation_spec_set_beta]


if __name__ == '__main__':
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter
)

parser.add_argument(
'--project-id',
help='Project ID. Required.',
required=True
)

args = parser.parse_args()

create_annotation_spec_set(args.project_id)
53 changes: 53 additions & 0 deletions datalabeling/snippets/create_annotation_spec_set_test.py
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#!/usr/bin/env python

# Copyright 2019 Google, Inc
#
# 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 backoff
from google.api_core.exceptions import ServerError
import pytest

import create_annotation_spec_set
import testing_lib


PROJECT_ID = os.getenv('GOOGLE_CLOUD_PROJECT')


@pytest.fixture(scope='module')
def cleaner():
resource_names = []

yield resource_names

for resource_name in resource_names:
testing_lib.delete_annotation_spec_set(resource_name)


def test_create_annotation_spec_set(cleaner, capsys):

@backoff.on_exception(
backoff.expo, ServerError, max_time=testing_lib.RETRY_DEADLINE)
def run_sample():
return create_annotation_spec_set.create_annotation_spec_set(PROJECT_ID)

response = run_sample()

# For cleanup
cleaner.append(response.name)

out, _ = capsys.readouterr()
assert 'The annotation_spec_set resource name:' in out
103 changes: 103 additions & 0 deletions datalabeling/snippets/create_instruction.py
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#!/usr/bin/env python

# Copyright 2019 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 argparse
import os

from google.api_core.client_options import ClientOptions


# [START datalabeling_create_instruction_beta]
def create_instruction(project_id, data_type, instruction_gcs_uri):
""" Creates a data labeling PDF instruction for the given Google Cloud
project. The PDF file should be uploaded to the project in
Google Cloud Storage.
"""
from google.cloud import datalabeling_v1beta1 as datalabeling
client = datalabeling.DataLabelingServiceClient()
# [END datalabeling_create_instruction_beta]
# 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)
# [START datalabeling_create_instruction_beta]

project_path = client.project_path(project_id)

pdf_instruction = datalabeling.types.PdfInstruction(
gcs_file_uri=instruction_gcs_uri)

instruction = datalabeling.types.Instruction(
display_name='YOUR_INSTRUCTION_DISPLAY_NAME',
description='YOUR_DESCRIPTION',
data_type=data_type,
pdf_instruction=pdf_instruction
)

operation = client.create_instruction(project_path, instruction)

result = operation.result()

# The format of the resource name:
# project_id/{project_id}/instruction/{instruction_id}
print('The instruction resource name: {}'.format(result.name))
print('Display name: {}'.format(result.display_name))
print('Description: {}'.format(result.description))
print('Create time:')
print('\tseconds: {}'.format(result.create_time.seconds))
print('\tnanos: {}'.format(result.create_time.nanos))
print('Data type: {}'.format(
datalabeling.enums.DataType(result.data_type).name))
print('Pdf instruction:')
print('\tGcs file uri: {}\n'.format(
result.pdf_instruction.gcs_file_uri))

return result
# [END datalabeling_create_instruction_beta]


if __name__ == '__main__':
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter
)

parser.add_argument(
'--project-id',
help='Project ID. Required.',
required=True
)

parser.add_argument(
'--data-type',
help='Data type. Only support IMAGE, VIDEO, TEXT and AUDIO. Required.',
required=True
)

parser.add_argument(
'--instruction-gcs-uri',
help='The URI of Google Cloud Storage of the instruction. Required.',
required=True
)

args = parser.parse_args()

create_instruction(
args.project_id,
args.data_type,
args.instruction_gcs_uri
)
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