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django-redis-metrics is a Django application for tracking application metrics backed by Redis.

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This app allows you do define various named metrics (such as ‘New Users’, ‘Downloads’, or ‘Purchases’) and record when they happen.

Eat metric can be assigned a Category or an optional Expiration time, and is stored at the second, minute, hourly, daily, weekly, monthly, and yearly level, so you can see the frequency of your data at different granularities.

Here’s a sneak peak at how it works:

>>> from redis_metrics.utils import metric
>>> metric("Downloads", category="User Metrics")

See the usage section for more examples.


This app was inspired by Frank Wiles django-app-metrics. It offers a similar feature set but:

  • It is only backed by Redis

  • Does not require Celery

  • Does not include any Timing


This app works with Python 2.7 and Django 1.4 - 1.6 and requires redis-py.

If you’d like to run the tests, install the packages listed in requirements/test.txt, which includes coverage and mock.


To install the current version, run pip install django-redis-metrics.

You can also install the development version with pip install -e git://

To use the built-in views, add redis_metrics to your INSTALLED_APPS, and include the following in your Root URLconf:

url(r'^metrics/', include('redis_metrics.urls')),

Then, to view your metrics, visit the /metrics/ url, (i.e. run the development server and go to

Upgrading to 0.8.0

If you used a prior version of this app, then installed 0.8.0, it’s likely that you’ll run into this error:

WRONGTYPE Operation against a key holding the wrong kind of value

To fix this, run the fix_redis_metrics_keys command, which should mitgrate data for metrics, gauges, and categories.


  • REDIS_METRICS_HOST - Hostname of redis server, defaults to ‘localhost’

  • REDIS_METRICS_PORT - redis port, defaults to ‘6379’

  • REDIS_METRICS_DB - redis database number to use, defaults to 0

  • REDIS_METRICS_PASSWORD - redis database password to use, defaults to None

  • REDIS_METRICS_SOCKET_TIMEOUT - redis database socket timeout, defaults to None

  • REDIS_METRICS_SOCKET_CONNECTION_POOL - redis database socket connection pool, defaults to None


Use the metric shortcut to start recording metrics.

from redis_metrics import metric

# Increment the metric by one

# Increment the metric by some other number
metric('new-user-signup', 4)

Metrics can also be categorized. To record a metric and add it to a category, specify a category keyword parameter

# Increment the metric, and add it to a category
metric('new-user-signup', category="User Metrics")

Metrics can also expire after a specified number of seconds

# The 'foo' metric will expire in 5 minutes
metric('foo', expire=300)

You can also reset a metric with the set_metric function. This will replace any existing values for the metric, rather than incrementing them. It’s api is similar to metric’s.

from redis_metrics import set_metric

# Reset the Download count.
set_metric("downloads", 0)

There are also gauge’s. A gauge is great for storing a cumulative value, and when you don’t care about keeping a history for the metric.

from redis_metrics import gauge

# Create a gauge
gauge('total-downloads', 0)

# Update the gauge
gauge('total-downloads', 9999)

There’s also an R class which is a lightweight wrapper around redis. You can use it directly to set metrics or gauges and to retrieve data.

>>> from redis_metrics.models import R
>>> r = R()
>>> r.metric('new-user-signup')
>>> r.get_metric('new-user-signup')
    'second': 0,
    'minute': 0,
    'hour': 1,
    'day': '29',
    'month': '29',
    'week': '29',
    'year': '29'

# list the slugs you've used to create metrics
>>> r.metric_slugs()
set(['new-user-signup', 'user-logins'])

# Get metrics for multiple slugs
>>> r.get_metrics(['new-user-signup', 'user-logins'])
    {'new-user-signup': {
        'second': '0', 'minute': '0', 'hour': '1',
        'day': '7', 'month': '7', 'week': '7', 'year': '7'}},
        'second': '0', 'minute': '0', 'hour': '1',
        'day': '7', 'month': '7', 'week': '7', 'year': '7'}},

# Delete a metric
>>> r.delete_metric("app-errors")


Feel free to submit bug reports or pull requests on the github repo.

If you do submit a pull request, please consider running the tests and (if applicable) adding test coverage for your changes. Thank You!


This code is distributed under the terms of the MIT license. See the LICENSE.txt file.

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