chore: Add flake8 static check (#449)

* remove trailing whitespace

* add flake8 static check to check_format.sh and Dockerfile

* fix flake8 issues tools/slo-generator

* fix flake8 issues tools/quota-manager

* ignore line length

* remove trailing whitespace

* fix tools

* fix examples

* remove max line length as it's later ignored

cloudbuild/Dockerfile

@@ -10,6 +10,7 @@ RUN apt-get update && apt-get install -y build-essential
 # install yapf
 RUN pip install yapf
 RUN pip3 install yapf
+RUN pip3 install flake8
 
 # install golang (+gofmt)
 RUN apt-get install -y golang

examples/alert-absence-dedup/policy_doc.md

@@ -18,6 +18,6 @@ sources are monitored by this alert.
 data ingestion.
 
 ### Case 2: At least 1 time-series absent
-1. The time series that has gone absent should be able to be identified with 
+1. The time series that has gone absent should be able to be identified with
 by the chart for metric: ${metric.display_name}.
 2. Investigate the specific data sources. The resource type is: ${resource.type}

examples/bigquery-audit-log/README.md

@@ -23,14 +23,14 @@ A short description relevant to our use case is presented below -
 1. In the GCP Cloud Console select the project you want to export the logs to. Go to Stackdriver --> Logging --> Exports.
 2. Click on Create Export. Select the following in the drop down menu: "BigQuery", "All logs", "Any log level", "No limit" and "Jump to now" respectively.
 3. In the configuration windows on the right side of the screen, enter a Sink Name of your choice. Select BigQuery as Sink Service. Select the "BigQuery Audit" (refer to Prerequisites) dataset as the Sink Destination.
-4. Click on Create Sink. 
+4. Click on Create Sink.
 5. A message box pops up to notify you of successful creation. Click on Close.
 6. Click on the Play button located on the top bar to start the export.
 
 ### 2. Scheduling a BigQuery job
-Use the SQL script in the file bigquery_audit_log.sql (located in this GitHub folder) to create a scheduled query in BigQuery. Click [here](https://cloud.google.com/bigquery/docs/scheduling-queries) for instructions on how to create scheduled queries. 
+Use the SQL script in the file bigquery_audit_log.sql (located in this GitHub folder) to create a scheduled query in BigQuery. Click [here](https://cloud.google.com/bigquery/docs/scheduling-queries) for instructions on how to create scheduled queries.
 
-Create a materialized table that stores data from the scheduled query. 
+Create a materialized table that stores data from the scheduled query.
 You can give it a custom name, we will be referring to it as **bigquery_audit_log**.
 
 ### 3. Copying the data source in Data Studio

examples/bigquery-audit-log/bigquery_audit_log.sql

@@ -42,7 +42,7 @@ WITH BQAudit AS (
       protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.startTime, SECOND)) / 60) AS INT64)
       AS executionMinuteBuckets,
     IF(COALESCE(protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.totalProcessedBytes,
-      protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.totalSlotMs, 
+      protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.totalSlotMs,
       protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatus.error.code) IS NULL, TRUE, FALSE
     ) AS isCached,
     protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.totalSlotMs,
@@ -60,8 +60,8 @@ WITH BQAudit AS (
   WHERE
     protopayload_auditlog.serviceName = 'bigquery.googleapis.com'
     AND protopayload_auditlog.methodName = 'jobservice.jobcompleted'
-    AND protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.eventName IN 
-    ( 
+    AND protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.eventName IN
+    (
       'table_copy_job_completed',
       'query_job_completed',
       'extract_job_completed',

examples/bigquery-audit-log/docs/query_jobs.md

@@ -10,7 +10,7 @@ The Selection Bar allows the user to filter the data in the report to a specific
 ![Selection Bar](../images/query_jobs/Image1.png)
 
 ### No. of Queries (this week vs. last week) - per day of the week
-The graph displays the total number of queries run per day of the week for the current week, also displaying a contrast with the same data for the previous week. 
+The graph displays the total number of queries run per day of the week for the current week, also displaying a contrast with the same data for the previous week.
 
 ![No. of Queries (this week vs. last week) - per day of the week](../images/query_jobs/Image2.png)
 

examples/bigquery-billing-dashboard/bigquery_billing_export.sql

@@ -4,11 +4,11 @@
  * Description:
  * This SQL script transforms the billing export table to anonymize user data
  * and included a linear projection for daily running cost. The output table
- * powers the Cloud Billing Dashboard 
+ * powers the Cloud Billing Dashboard
  * (https://cloud.google.com/billing/docs/how-to/visualize-data).
  */
 
-WITH 
+WITH
 -- Generate dates in the current month.
 current_month_dates AS (
   SELECT gen_date
@@ -17,8 +17,8 @@ current_month_dates AS (
       GENERATE_DATE_ARRAY(
         DATE_TRUNC(CURRENT_DATE(), MONTH),
         DATE_SUB(DATE_TRUNC(
-          DATE_ADD(CURRENT_DATE(), INTERVAL 1 MONTH), MONTH), 
-        INTERVAL 1 DAY), 
+          DATE_ADD(CURRENT_DATE(), INTERVAL 1 MONTH), MONTH),
+        INTERVAL 1 DAY),
       INTERVAL 1 DAY)
     ) AS gen_date),
 
@@ -41,11 +41,11 @@ avg_daily_cost AS (
 
 -- Calculate projected_running_cost
 projected_cost AS (
-SELECT 
+SELECT
   daily_cost.gen_date AS date,
   daily_cost.cost AS daily_cost,
   avg_daily_cost.cost AS avg_daily_cost,
-  (DATE_DIFF(daily_cost.gen_date, DATE_TRUNC(CURRENT_DATE, MONTH), DAY) + 1) * 
+  (DATE_DIFF(daily_cost.gen_date, DATE_TRUNC(CURRENT_DATE, MONTH), DAY) + 1) *
     avg_daily_cost.cost AS projected_running_cost
 FROM daily_cost
 CROSS JOIN avg_daily_cost)

examples/bigquery-cross-project-slot-monitoring/tests/main_test.py

@@ -124,7 +124,7 @@ def testCopyMetrics_NotCalledByCloudTasks(self):
 
   def testCopyMetrics_MissingParameters(self):
     self.app.get(
-      '/CopyMetrics', 
+      '/CopyMetrics',
       headers={'X-AppEngine-QueueName': 'SomeQueue'},
       status=400)
 

examples/bigquery-row-access-groups/auth_util.py

@@ -29,8 +29,8 @@
 
 def get_credentials(admin_email, scopes):
   request = google.auth.transport.requests.Request()
-  #  This retrieves the default credentials from the environment - in this 
-  #  case, for the Service Account attached to the VM. The unused _ variable 
+  #  This retrieves the default credentials from the environment - in this
+  #  case, for the Service Account attached to the VM. The unused _ variable
   #  is just the GCP project ID - we're dropping it because we don't care.
   default_credentials, _ = google.auth.default()
   #  The credentials object won't include the service account e-mail address

examples/bigtable-change-key/README.md

@@ -1,10 +1,10 @@
 ## Dataflow pipeline to change the key of a Bigtable
 
 For an optimal performance of our requests to a Bigtable instance, [it is crucial to choose
-a good key for our records](https://cloud.google.com/bigtable/docs/schema-design), 
-so that both read and writes are evenly distributed across the keys space. Although we have tools 
-such as [Key Visualizer](https://cloud.google.com/bigtable/docs/keyvis-overview), to diagnose how 
-our key is performing, it is not obvious how to change or update a key for all the records in a table.  
+a good key for our records](https://cloud.google.com/bigtable/docs/schema-design),
+so that both read and writes are evenly distributed across the keys space. Although we have tools
+such as [Key Visualizer](https://cloud.google.com/bigtable/docs/keyvis-overview), to diagnose how
+our key is performing, it is not obvious how to change or update a key for all the records in a table.
 
 This example contains a Dataflow pipeline to read data from a table in a
 Bigtable instance, and to write the same records to another table with the same
@@ -20,7 +20,7 @@ The build process is managed using Maven. To compile, just run
 
 To create a package for the pipeline, run
 
-`mvn package` 
+`mvn package`
 
 ### Setup `cbt`
 
@@ -144,7 +144,7 @@ You should see a job with a simple graph, similar to this one:
 
 You can now check that the destination table has the same records as the input
 table, and that the key has changed.  You can use `cbt count` and `cbt read` for
-that purpose, by comparing with the results of the original table. 
+that purpose, by comparing with the results of the original table.
 
 ### Change the update key function
 
@@ -176,11 +176,11 @@ It is only provided as an example so it is easier to write your own function.
 ```
 
 The function has two input parameters:
- 
+
 * `key`: the current key of the record
 * `record`: the full record, with all the column families, columns,
    values/cells, versions of cells, etc.
- 
+
 The `record` is of type
 [com.google.bigtable.v2.Row](http://googleapis.github.io/googleapis/java/all/latest/apidocs/com/google/bigtable/v2/Row.html).
 You can traverse the record to recover all the elements. See [an example of how

examples/bigtable-change-key/scripts/copy_schema_to_new_table.sh

@@ -13,7 +13,7 @@
 # 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.
- 
+
 usage() {
   echo "Usage $0 INPUT_TABLE_NAME OUTPUT_TABLE_NAME"
   echo
@@ -25,7 +25,7 @@ then
   usage
   exit 0
 fi
-   
+
 
 if [ $# -lt 2 ]
 then