A Prometheus Python client library for asyncio-based applications
Project description
aioprometheus
aioprometheus is a Prometheus Python client library for asyncio-based applications. It provides metrics collection and serving capabilities, supports multiple data formats and pushing metrics to a gateway.
The project documentation can be found on ReadTheDocs.
Install
$ pip install aioprometheusExample
The example below shows a single Counter metric collector being created and exposed via a HTTP endpoint.
#!/usr/bin/env python
'''
This example demonstrates how a single Counter metric collector can be created
and exposed via a HTTP endpoint.
'''
import asyncio
import socket
from aioprometheus import Counter, Service
if __name__ == '__main__':
loop = asyncio.get_event_loop()
svr = Service()
events_counter = Counter(
"events",
"Number of events.",
const_labels={'host': socket.gethostname()})
svr.register(events_counter)
loop.run_until_complete(svr.start(addr="127.0.0.1"))
print(f'Serving prometheus metrics on: {svr.metrics_url}')
async def updater(m: Counter):
# Periodically update the metric to simulate some progress
# happening in a real application.
while True:
m.inc({'kind': 'timer_expiry'})
await asyncio.sleep(1.0)
try:
loop.run_until_complete(updater(events_counter))
except KeyboardInterrupt:
pass
finally:
loop.run_until_complete(svr.stop())
loop.close()In this simple example the counter metric is tracking the number of while loop iterations executed by the updater coroutine. In a realistic application a metric might track the number of requests, etc.
Following typical asyncio usage, an event loop is instantiated first then a metrics service is instantiated. The metrics service is responsible for managing metric collectors and responding to metrics requests.
The service accepts various arguments such as the interface and port to bind to. A collector registry is used within the service to hold metrics collectors that will be exposed by the service. The service will create a new collector registry if one is not passed in.
A counter metric is created and registered with the service. The service is started and then a coroutine is started to periodically update the metric to simulate progress.
The example script can be run using:
(venv) $ cd examples
(venv) $ python simple-example.py
Serving prometheus metrics on: http://127.0.0.1:50624/metricsIn another terminal fetch the metrics using the curl command line tool to verify they can be retrieved by Prometheus server.
By default metrics will be returned in plan text format.
$ curl http://127.0.0.1:50624/metrics
# HELP events Number of events.
# TYPE events counter
events{host="alpha",kind="timer_expiry"} 33Similarly, you can request metrics in binary format, though this will be hard to read on the command line.
$ curl http://127.0.0.1:50624/metrics -H "ACCEPT: application/vnd.google.protobuf; proto=io.prometheus.client.MetricFamily; encoding=delimited"The metrics service also responds to requests sent to its / route. The response is simple HTML. This route can be useful as a Kubernetes /healthz style health indicator as it does not incur any overhead within the service to serialize a full metrics response.
$ curl http://127.0.0.1:50624/
<html><body><a href='/metrics'>metrics</a></body></html>A number of convenience decorator functions are also available to assist with updating metrics.
There are more examples in the examples directory. The app-example.py file will likely be of interest as it provides a more representative application example.
License
aioprometheus is released under the MIT license.
aioprometheus originates from the (now deprecated) prometheus python package which was released under the MIT license. aioprometheus continues to use the MIT license and contains a copy of the orignal MIT license from the prometheus-python project as instructed by the original license.
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