Datadogpy is a collection of tools suitable for inclusion in existing Python projects or for development of standalone scripts. It provides an abstraction on top of Datadog's raw HTTP interface and the Agent's StatsD metrics aggregation server, to interact with Datadog and efficiently report events and metrics.
For usage of StatsD metrics, the Agent must be running and available.
- Library Documentation: http://datadogpy.readthedocs.org/en/latest/
- HTTP API Documentation: http://docs.datadoghq.com/api/
- DatadogHQ: http://datadoghq.com
See CHANGELOG.md for changes.
To install from pip:
pip install datadog
To install from source:
python setup.py install
# Configure the module according to your needs
from datadog import initialize
options = {
'api_key':'api_key',
'app_key':'app_key'
}
initialize(**options)
# Use Datadog REST API client
from datadog import api
title = "Something big happened!"
text = 'And let me tell you all about it here!'
tags = ['version:1', 'application:web']
api.Event.create(title=title, text=text, tags=tags)
# Use Statsd, a Python client for DogStatsd
from datadog import statsd
# Uncomment to set namespace or add tags to everything
# statsd.namespace = 'localdev'
# statsd.constant_tags = ['testing', 'dogstats']
statsd.increment('whatever')
statsd.gauge('foo', 42)
# Or ThreadStats, an alternative tool to collect and flush metrics, using Datadog REST API
from datadog import ThreadStats
stats = ThreadStats()
stats.start()
stats.increment('home.page.hits')DogStatsD and ThreadStats are thread-safe.