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‎appengine/flexible/tasks/Dockerfile

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# Use the official Python image.
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# https://hub.docker.com/_/python
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FROM python:3.7
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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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COPY . .
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# Install production dependencies.
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RUN pip install Flask gunicorn
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# Run the web service on container startup. Here we use the gunicorn
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# webserver, with one worker process and 8 threads.
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# For environments with multiple CPU cores, increase the number of workers
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# to be equal to the cores available.
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CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 main:app

‎appengine/flexible/tasks/README.md

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@@ -101,24 +101,3 @@ endpoint, with a payload specified:
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```
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python create_app_engine_queue_task.py --project=$PROJECT_ID --queue=$QUEUE_ID --location=$LOCATION_ID --payload=hello
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```
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### Using HTTP Push Queues
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Set an environment variable for the endpoint to your task handler. This is an
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example url to send requests to the App Engine task handler:
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```
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export URL=https://<project_id>.appspot.com/example_task_handler
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```
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Running the sample will create a task and send the task to the specific URL
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endpoint, with a payload specified:
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```
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python create_http_task.py --project=$PROJECT_ID --queue=$QUEUE_ID --location=$LOCATION_ID --url=$URL --payload=hello
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```
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Now view that the payload was received and verify the payload:
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```
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gcloud app logs read
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```

‎appengine/flexible/tasks/requirements.txt

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Flask==1.0.2
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gunicorn==19.9.0
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google-cloud-tasks==0.6.0
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google-cloud-tasks==0.7.0

‎bigtable/hello/main.py

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@@ -25,24 +25,24 @@
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"""
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import argparse
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# [START dependencies]
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# [START bigtable_hw_imports]
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import datetime
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from google.cloud import bigtable
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from google.cloud.bigtable import column_family
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from google.cloud.bigtable import row_filters
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# [END dependencies]
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# [END bigtable_hw_imports]
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def main(project_id, instance_id, table_id):
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# [START connecting_to_bigtable]
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# [START bigtable_hw_connect]
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# The client must be created with admin=True because it will create a
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# table.
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client = bigtable.Client(project=project_id, admin=True)
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instance = client.instance(instance_id)
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# [END connecting_to_bigtable]
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# [END bigtable_hw_connect]
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# [START creating_a_table]
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# [START bigtable_hw_create_table]
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print('Creating the {} table.'.format(table_id))
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table = instance.table(table_id)
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@@ -56,9 +56,9 @@ def main(project_id, instance_id, table_id):
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table.create(column_families=column_families)
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else:
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print("Table {} already exists.".format(table_id))
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# [END creating_a_table]
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# [END bigtable_hw_create_table]
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# [START writing_rows]
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# [START bigtable_hw_write_rows]
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print('Writing some greetings to the table.')
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greetings = ['Hello World!', 'Hello Cloud Bigtable!', 'Hello Python!']
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rows = []
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timestamp=datetime.datetime.utcnow())
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rows.append(row)
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table.mutate_rows(rows)
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# [END writing_rows]
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# [END bigtable_hw_write_rows]
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# [START creating_a_filter]
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# [START bigtable_hw_create_filter]
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# Create a filter to only retrieve the most recent version of the cell
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# for each column accross entire row.
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row_filter = row_filters.CellsColumnLimitFilter(1)
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# [END creating_a_filter]
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# [END bigtable_hw_create_filter]
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# [START getting_a_row]
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# [START bigtable_hw_get_with_filter]
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print('Getting a single greeting by row key.')
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key = 'greeting0'.encode()
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9797
row = table.read_row(key, row_filter)
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cell = row.cells[column_family_id][column][0]
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print(cell.value.decode('utf-8'))
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# [END getting_a_row]
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# [END bigtable_hw_get_with_filter]
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102-
# [START scanning_all_rows]
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# [START bigtable_hw_scan_with_filter]
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print('Scanning for all greetings:')
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partial_rows = table.read_rows(filter_=row_filter)
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106106
for row in partial_rows:
107107
cell = row.cells[column_family_id][column][0]
108108
print(cell.value.decode('utf-8'))
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# [END scanning_all_rows]
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# [END bigtable_hw_scan_with_filter]
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# [START deleting_a_table]
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# [START bigtable_hw_delete_table]
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print('Deleting the {} table.'.format(table_id))
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table.delete()
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# [END deleting_a_table]
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# [END bigtable_hw_delete_table]
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if __name__ == '__main__':

‎bigtable/hello_happybase/main.py

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"""
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2727
import argparse
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28+
# [START bigtable_hw_imports_happybase]
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from google.cloud import bigtable
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from google.cloud import happybase
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# [END bigtable_hw_imports_happybase]
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3233

3334
def main(project_id, instance_id, table_name):
34-
# [START connecting_to_bigtable]
35+
# [START bigtable_hw_connect_happybase]
3536
# The client must be created with admin=True because it will create a
3637
# table.
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client = bigtable.Client(project=project_id, admin=True)
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instance = client.instance(instance_id)
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connection = happybase.Connection(instance=instance)
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# [END connecting_to_bigtable]
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# [END bigtable_hw_connect_happybase]
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4243
try:
43-
# [START creating_a_table]
44+
# [START bigtable_hw_create_table_happybase]
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print('Creating the {} table.'.format(table_name))
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column_family_name = 'cf1'
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connection.create_table(
4748
table_name,
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{
4950
column_family_name: dict() # Use default options.
5051
})
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# [END creating_a_table]
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# [END bigtable_hw_create_table_happybase]
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# [START writing_rows]
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# [START bigtable_hw_write_rows_happybase]
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print('Writing some greetings to the table.')
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table = connection.table(table_name)
5657
column_name = '{fam}:greeting'.format(fam=column_family_name)
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table.put(
7677
row_key, {column_name.encode('utf-8'): value.encode('utf-8')}
7778
)
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# [END writing_rows]
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# [END bigtable_hw_write_rows_happybase]
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80-
# [START getting_a_row]
81+
# [START bigtable_hw_get_by_key_happybase]
8182
print('Getting a single greeting by row key.')
8283
key = 'greeting0'.encode('utf-8')
8384
row = table.row(key)
8485
print('\t{}: {}'.format(key, row[column_name.encode('utf-8')]))
85-
# [END getting_a_row]
86+
# [END bigtable_hw_get_by_key_happybase]
8687

87-
# [START scanning_all_rows]
88+
# [START bigtable_hw_scan_all_happybase]
8889
print('Scanning for all greetings:')
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9091
for key, row in table.scan():
9192
print('\t{}: {}'.format(key, row[column_name.encode('utf-8')]))
92-
# [END scanning_all_rows]
93+
# [END bigtable_hw_scan_all_happybase]
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94-
# [START deleting_a_table]
95+
# [START bigtable_hw_delete_table_happybase]
9596
print('Deleting the {} table.'.format(table_name))
9697
connection.delete_table(table_name)
97-
# [END deleting_a_table]
98+
# [END bigtable_hw_delete_table_happybase]
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99100
finally:
100101
connection.close()

‎opencensus/README.md

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<img src="https://avatars2.githubusercontent.com/u/38480854?v=3&s=96" alt="OpenCensus logo" title="OpenCensus" align="right" height="96" width="96"/>
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3+
# OpenCensus Stackdriver Metrics Sample
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5+
[OpenCensus](https://opencensus.io) is a toolkit for collecting application
6+
performance and behavior data. OpenCensus includes utilities for distributed
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tracing, metrics collection, and context propagation within and between
8+
services.
9+
10+
This example demonstrates using the OpenCensus client to send metrics data to
11+
the [Stackdriver Monitoring](https://cloud.google.com/monitoring/docs/)
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backend.
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14+
## Prerequisites
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16+
Install the OpenCensus core and Stackdriver exporter libraries:
17+
18+
```sh
19+
pip install -r opencensus/requirements.txt
20+
```
21+
22+
Make sure that your environment is configured to [authenticate with
23+
GCP](https://cloud.google.com/docs/authentication/getting-started).
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25+
## Running the example
26+
27+
```sh
28+
python opencensus/metrics_quickstart.py
29+
```
30+
31+
The example generates a histogram of simulated latencies, which is exported to
32+
Stackdriver after 60 seconds. After it's exported, the histogram will be
33+
visible on the [Stackdriver Metrics
34+
Explorer](https://app.google.stackdriver.com/metrics-explorer) page as
35+
`OpenCensus/task_latency_view`.

‎opencensus/metrics_quickstart.py

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#!/usr/bin/env python
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3+
# Copyright 2019 Google Inc. All Rights Reserved.
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#
5+
# Licensed under the Apache License, Version 2.0 (the "License");
6+
# you may not use this file except in compliance with the License.
7+
# You may obtain a copy of the License at
8+
#
9+
# http://www.apache.org/licenses/LICENSE-2.0
10+
#
11+
# Unless required by applicable law or agreed to in writing, software
12+
# distributed under the License is distributed on an "AS IS" BASIS,
13+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14+
# See the License for the specific language governing permissions and
15+
# limitations under the License.
16+
17+
# [START monitoring_opencensus_metrics_quickstart]
18+
19+
from random import random
20+
import time
21+
22+
from opencensus.ext.stackdriver import stats_exporter
23+
from opencensus.stats import aggregation
24+
from opencensus.stats import measure
25+
from opencensus.stats import stats
26+
from opencensus.stats import view
27+
28+
29+
# A measure that represents task latency in ms.
30+
LATENCY_MS = measure.MeasureFloat(
31+
"task_latency",
32+
"The task latency in milliseconds",
33+
"ms")
34+
35+
# A view of the task latency measure that aggregates measurements according to
36+
# a histogram with predefined bucket boundaries. This aggregate is periodically
37+
# exported to Stackdriver Monitoring.
38+
LATENCY_VIEW = view.View(
39+
"task_latency_distribution",
40+
"The distribution of the task latencies",
41+
[],
42+
LATENCY_MS,
43+
# Latency in buckets: [>=0ms, >=100ms, >=200ms, >=400ms, >=1s, >=2s, >=4s]
44+
aggregation.DistributionAggregation(
45+
[100.0, 200.0, 400.0, 1000.0, 2000.0, 4000.0]))
46+
47+
48+
def main():
49+
# Register the view. Measurements are only aggregated and exported if
50+
# they're associated with a registered view.
51+
stats.stats.view_manager.register_view(LATENCY_VIEW)
52+
53+
# Create the Stackdriver stats exporter and start exporting metrics in the
54+
# background, once every 60 seconds by default.
55+
exporter = stats_exporter.new_stats_exporter()
56+
print('Exporting stats to project "{}"'
57+
.format(exporter.options.project_id))
58+
59+
# Record 100 fake latency values between 0 and 5 seconds.
60+
for num in range(100):
61+
ms = random() * 5 * 1000
62+
print("Latency {}: {}".format(num, ms))
63+
64+
mmap = stats.stats.stats_recorder.new_measurement_map()
65+
mmap.measure_float_put(LATENCY_MS, ms)
66+
mmap.record()
67+
68+
# Keep the thread alive long enough for the exporter to export at least
69+
# once.
70+
time.sleep(65)
71+
72+
73+
if __name__ == '__main__':
74+
main()
75+
76+
# [END monitoring_opencensus_metrics_quickstart]

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