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risk_test.py
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# Copyright 2017 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.
from gcp_devrel.testing.flaky import flaky
import google.cloud.pubsub
import pytest
import risk
GCLOUD_PROJECT = 'nodejs-docs-samples'
TABLE_PROJECT = 'nodejs-docs-samples'
TOPIC_ID = 'dlp-test'
SUBSCRIPTION_ID = 'dlp-test-subscription'
DATASET_ID = 'integration_tests_dlp'
UNIQUE_FIELD = 'Name'
REPEATED_FIELD = 'Mystery'
NUMERIC_FIELD = 'Age'
STRING_BOOLEAN_FIELD = 'Gender'
# Create new custom topic/subscription
@pytest.fixture(scope='module')
def topic_id():
# Creates a pubsub topic, and tears it down.
publisher = google.cloud.pubsub.PublisherClient()
topic_path = publisher.topic_path(GCLOUD_PROJECT, TOPIC_ID)
try:
publisher.create_topic(topic_path)
except google.api_core.exceptions.AlreadyExists:
pass
yield TOPIC_ID
publisher.delete_topic(topic_path)
@pytest.fixture(scope='module')
def subscription_id(topic_id):
# Subscribes to a topic.
subscriber = google.cloud.pubsub.SubscriberClient()
topic_path = subscriber.topic_path(GCLOUD_PROJECT, topic_id)
subscription_path = subscriber.subscription_path(
GCLOUD_PROJECT, SUBSCRIPTION_ID)
try:
subscriber.create_subscription(subscription_path, topic_path)
except google.api_core.exceptions.AlreadyExists:
pass
yield SUBSCRIPTION_ID
subscriber.delete_subscription(subscription_path)
@flaky
def test_numerical_risk_analysis(topic_id, subscription_id, capsys):
risk.numerical_risk_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
NUMERIC_FIELD,
topic_id,
subscription_id)
out, _ = capsys.readouterr()
assert 'Value Range:' in out
@flaky
def test_categorical_risk_analysis_on_string_field(
topic_id, subscription_id, capsys):
risk.categorical_risk_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
UNIQUE_FIELD,
topic_id,
subscription_id, timeout=180)
out, _ = capsys.readouterr()
assert 'Most common value occurs' in out
@flaky
def test_categorical_risk_analysis_on_number_field(
topic_id, subscription_id, capsys):
risk.categorical_risk_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
NUMERIC_FIELD,
topic_id,
subscription_id)
out, _ = capsys.readouterr()
assert 'Most common value occurs' in out
@flaky
def test_k_anonymity_analysis_single_field(topic_id, subscription_id, capsys):
risk.k_anonymity_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
[NUMERIC_FIELD])
out, _ = capsys.readouterr()
assert 'Quasi-ID values:' in out
assert 'Class size:' in out
@flaky
def test_k_anonymity_analysis_multiple_fields(topic_id, subscription_id,
capsys):
risk.k_anonymity_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
[NUMERIC_FIELD, REPEATED_FIELD])
out, _ = capsys.readouterr()
assert 'Quasi-ID values:' in out
assert 'Class size:' in out
@flaky
def test_l_diversity_analysis_single_field(topic_id, subscription_id, capsys):
risk.l_diversity_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
UNIQUE_FIELD,
[NUMERIC_FIELD])
out, _ = capsys.readouterr()
assert 'Quasi-ID values:' in out
assert 'Class size:' in out
assert 'Sensitive value' in out
@flaky
def test_l_diversity_analysis_multiple_field(
topic_id, subscription_id, capsys):
risk.l_diversity_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
UNIQUE_FIELD,
[NUMERIC_FIELD, REPEATED_FIELD])
out, _ = capsys.readouterr()
assert 'Quasi-ID values:' in out
assert 'Class size:' in out
assert 'Sensitive value' in out
@flaky
def test_k_map_estimate_analysis_single_field(
topic_id, subscription_id, capsys):
risk.k_map_estimate_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
[NUMERIC_FIELD],
['AGE'])
out, _ = capsys.readouterr()
assert 'Anonymity range:' in out
assert 'Size:' in out
assert 'Values' in out
@flaky
def test_k_map_estimate_analysis_multiple_field(
topic_id, subscription_id, capsys):
risk.k_map_estimate_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
[NUMERIC_FIELD, STRING_BOOLEAN_FIELD],
['AGE', 'GENDER'])
out, _ = capsys.readouterr()
assert 'Anonymity range:' in out
assert 'Size:' in out
assert 'Values' in out
@flaky
def test_k_map_estimate_analysis_quasi_ids_info_types_equal(
topic_id, subscription_id):
with pytest.raises(ValueError):
risk.k_map_estimate_analysis(
GCLOUD_PROJECT,
TABLE_PROJECT,
DATASET_ID,
'harmful',
topic_id,
subscription_id,
[NUMERIC_FIELD, STRING_BOOLEAN_FIELD],
['AGE'])