eventbrite / pymetrics

Versatile Metrics Collection for Python

PyMetrics - Versatile Metrics Collection for Python

PyMetrics is versatile metrics collection library for Python that encapsulates the collection of counters, gauges, histograms, and timers into a generic interface with pluggable publishers so that you can helpfully instrument your applications without suffering vendor lock.

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Publishing metrics is a straightforward process involving two steps. First, configure your metrics and publisher(s):

METRICS_CONFIG = {
    'version': 2,
    'error_logger_name': 'pymetrics',
    'publishers': [
        {
            'path': 'pymetrics.publishers.datadog.DogStatsdPublisher',
            'kwargs': {
                'host': 'localhost',
                'port': 8135,
            },
        },
    ],
}

Then, use a pymetrics.recorders.base.MetricsRecorder in your application to collect and publish:

from pymetrics.recorders.default import DefaultMetricsRecorder

metrics = DefaultMetricsRecorder(config=settings.METRICS_CONFIG)

metrics.counter('counter.name').increment()

metrics.gauge('gauge.name', tag_name1='tag_value1', tag_name2='tag_value2').set(12)

metrics.histogram('histogram.name').set(1730)

with metrics.timer('timer.name'):
    do_something()

cumulative_timer = metrics.timer('cumulative_timer.name')
for item in items:
    do_something_without_timing()
    with cumulative_timer:
        do_something_with_timing()

metrics.publish_all()

Provided publisher plugins include Statsd, Datadog, Python Logging, SQLite, and a null publisher. Writing your own is simple and we encourage you to share your work with the community by submitting a pull request.

License

PyMetrics is licensed under the Apache License, version 2.0.

Installation

PyMetrics is available in PyPi and can be installing directly via Pip or listed in setup.py, requirements.txt, or Pipfile:

pip install 'pymetrics~=1.0'

install_requires=[
    ...
    'pymetrics~=1.0',
    ...
]

pymetrics~=1.0

pymetrics = {version="~=1.0"}

Documentation

The complete PyMetrics documentation is available on Read the Docs!

pymetrics's Issues

Fix circular import error when Conformity is involved in the import

When PyMetrics tries to import Django to look for settings, it already has protections against circular imports. However, those projections break down when one of the imports happens in Conformity validation code, which turns the ImportError into a ValidationError.