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Commit 936e77f

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beccasaurusbeccasaurus
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Merge branch 'master' into patch-15
2 parents 2e1afda + 3619a77 commit 936e77f
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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
4+
5+
# Copy local code to the container image.
6+
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

Copy file name to clipboardExpand all lines: appengine/flexible/tasks/README.md
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@@ -101,24 +101,3 @@ endpoint, with a payload specified:
101101
```
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python create_app_engine_queue_task.py --project=$PROJECT_ID --queue=$QUEUE_ID --location=$LOCATION_ID --payload=hello
103103
```
104-
105-
### Using HTTP Push Queues
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Set an environment variable for the endpoint to your task handler. This is an
108-
example url to send requests to the App Engine task handler:
109-
```
110-
export URL=https://<project_id>.appspot.com/example_task_handler
111-
```
112-
113-
Running the sample will create a task and send the task to the specific URL
114-
endpoint, with a payload specified:
115-
116-
```
117-
python create_http_task.py --project=$PROJECT_ID --queue=$QUEUE_ID --location=$LOCATION_ID --url=$URL --payload=hello
118-
```
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120-
Now view that the payload was received and verify the payload:
121-
122-
```
123-
gcloud app logs read
124-
```

‎appengine/flexible/tasks/requirements.txt

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@@ -1,3 +1,3 @@
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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

Copy file name to clipboardExpand all lines: bigtable/hello/main.py
+16-16Lines changed: 16 additions & 16 deletions
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@@ -25,24 +25,24 @@
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"""
2626

2727
import argparse
28-
# [START dependencies]
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# [START bigtable_hw_imports]
2929
import datetime
3030

3131
from google.cloud import bigtable
3232
from google.cloud.bigtable import column_family
3333
from google.cloud.bigtable import row_filters
34-
# [END dependencies]
34+
# [END bigtable_hw_imports]
3535

3636

3737
def main(project_id, instance_id, table_id):
38-
# [START connecting_to_bigtable]
38+
# [START bigtable_hw_connect]
3939
# The client must be created with admin=True because it will create a
4040
# table.
4141
client = bigtable.Client(project=project_id, admin=True)
4242
instance = client.instance(instance_id)
43-
# [END connecting_to_bigtable]
43+
# [END bigtable_hw_connect]
4444

45-
# [START creating_a_table]
45+
# [START bigtable_hw_create_table]
4646
print('Creating the {} table.'.format(table_id))
4747
table = instance.table(table_id)
4848

@@ -56,9 +56,9 @@ def main(project_id, instance_id, table_id):
5656
table.create(column_families=column_families)
5757
else:
5858
print("Table {} already exists.".format(table_id))
59-
# [END creating_a_table]
59+
# [END bigtable_hw_create_table]
6060

61-
# [START writing_rows]
61+
# [START bigtable_hw_write_rows]
6262
print('Writing some greetings to the table.')
6363
greetings = ['Hello World!', 'Hello Cloud Bigtable!', 'Hello Python!']
6464
rows = []
@@ -82,36 +82,36 @@ def main(project_id, instance_id, table_id):
8282
timestamp=datetime.datetime.utcnow())
8383
rows.append(row)
8484
table.mutate_rows(rows)
85-
# [END writing_rows]
85+
# [END bigtable_hw_write_rows]
8686

87-
# [START creating_a_filter]
87+
# [START bigtable_hw_create_filter]
8888
# Create a filter to only retrieve the most recent version of the cell
8989
# for each column accross entire row.
9090
row_filter = row_filters.CellsColumnLimitFilter(1)
91-
# [END creating_a_filter]
91+
# [END bigtable_hw_create_filter]
9292

93-
# [START getting_a_row]
93+
# [START bigtable_hw_get_with_filter]
9494
print('Getting a single greeting by row key.')
9595
key = 'greeting0'.encode()
9696

9797
row = table.read_row(key, row_filter)
9898
cell = row.cells[column_family_id][column][0]
9999
print(cell.value.decode('utf-8'))
100-
# [END getting_a_row]
100+
# [END bigtable_hw_get_with_filter]
101101

102-
# [START scanning_all_rows]
102+
# [START bigtable_hw_scan_with_filter]
103103
print('Scanning for all greetings:')
104104
partial_rows = table.read_rows(filter_=row_filter)
105105

106106
for row in partial_rows:
107107
cell = row.cells[column_family_id][column][0]
108108
print(cell.value.decode('utf-8'))
109-
# [END scanning_all_rows]
109+
# [END bigtable_hw_scan_with_filter]
110110

111-
# [START deleting_a_table]
111+
# [START bigtable_hw_delete_table]
112112
print('Deleting the {} table.'.format(table_id))
113113
table.delete()
114-
# [END deleting_a_table]
114+
# [END bigtable_hw_delete_table]
115115

116116

117117
if __name__ == '__main__':

‎bigtable/hello_happybase/main.py

Copy file name to clipboardExpand all lines: bigtable/hello_happybase/main.py
+14-13Lines changed: 14 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -25,32 +25,33 @@
2525
"""
2626

2727
import argparse
28-
28+
# [START bigtable_hw_imports_happybase]
2929
from google.cloud import bigtable
3030
from google.cloud import happybase
31+
# [END bigtable_hw_imports_happybase]
3132

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.
3738
client = bigtable.Client(project=project_id, admin=True)
3839
instance = client.instance(instance_id)
3940
connection = happybase.Connection(instance=instance)
40-
# [END connecting_to_bigtable]
41+
# [END bigtable_hw_connect_happybase]
4142

4243
try:
43-
# [START creating_a_table]
44+
# [START bigtable_hw_create_table_happybase]
4445
print('Creating the {} table.'.format(table_name))
4546
column_family_name = 'cf1'
4647
connection.create_table(
4748
table_name,
4849
{
4950
column_family_name: dict() # Use default options.
5051
})
51-
# [END creating_a_table]
52+
# [END bigtable_hw_create_table_happybase]
5253

53-
# [START writing_rows]
54+
# [START bigtable_hw_write_rows_happybase]
5455
print('Writing some greetings to the table.')
5556
table = connection.table(table_name)
5657
column_name = '{fam}:greeting'.format(fam=column_family_name)
@@ -75,26 +76,26 @@ def main(project_id, instance_id, table_name):
7576
table.put(
7677
row_key, {column_name.encode('utf-8'): value.encode('utf-8')}
7778
)
78-
# [END writing_rows]
79+
# [END bigtable_hw_write_rows_happybase]
7980

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:')
8990

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]
9394

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]
9899

99100
finally:
100101
connection.close()

‎opencensus/README.md

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1+
<img src="https://avatars2.githubusercontent.com/u/38480854?v=3&s=96" alt="OpenCensus logo" title="OpenCensus" align="right" height="96" width="96"/>
2+
3+
# OpenCensus Stackdriver Metrics Sample
4+
5+
[OpenCensus](https://opencensus.io) is a toolkit for collecting application
6+
performance and behavior data. OpenCensus includes utilities for distributed
7+
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/)
12+
backend.
13+
14+
## Prerequisites
15+
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).
24+
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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+76Lines changed: 76 additions & 0 deletions
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1+
#!/usr/bin/env python
2+
3+
# Copyright 2019 Google Inc. All Rights Reserved.
4+
#
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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