django-app-metrics is a reusable Django application for tracking and emailing application metrics.
Project description
Django App Metrics
django-app-metrics allows you to capture and report on various events in your applications. You simply define various named metrics and record when they happen. These might be certain events that may be immediatey useful, for example 'New User Signups', 'Downloads', etc.
Or they might not prove useful until some point in the future. But if you begin recording them now you'll have great data later on if you do need it.
For example 'Total Items Sold' isn't an exciting number when you're just launching when you only care about revenue, but being able to do a contest for the 1 millionth sold item in the future you'll be glad you were tracking it.
You then group these individual metrics into a MetricSet, where you define how often you want an email report being sent, and to which User(s) it should be sent.
Notes
This fork provides for changes specifically for Pivotal Energy Solutions
Documentation
Documentation can be found at ReadTheDocs
Requirements
Celery and django-celery
must be installed, however if you do not wish to actually use Celery you can
simply set CELERY_ALWAYS_EAGER = True
in your
settings and it will behave as if Celery was not configured.
Usage
from app_metrics.utils import create_metric, metric, timing, Timer, gauge
# Create a new metric to track
my_metric = create_metric(name='New User Metric', slug='new_user_signup')
# Create a MetricSet which ties a metric to an email schedule and sets
# who should receive it
my_metric_set = create_metric_set(name='My Set',
metrics=[my_metric],
email_recipients=[user1, user2])
# Increment the metric by one
metric('new_user_signup')
# Increment the metric by some other number
metric('new_user_signup', 4)
# Aggregate metric items into daily, weekly, monthly, and yearly totals
# It's fairly smart about it, so you're safe to run this as often as you
# like
manage.py metrics_aggregate
# Send email reports to users
manage.py metrics_send_mail
# Create a timer (only supported in statsd backend currently)
with timing('mytimer'):
for x in some_long_list:
call_time_consuming_function(x)
# Or if a context manager doesn't work for you you can use a Timer class
t = Timer()
t.start()
something_that_takes_forever()
t.stop()
t.store('mytimer')
# Gauges are current status type dials (think fuel gauge in a car)
# These simply store and retrieve a value
gauge('current_fuel', '30')
guage('load_load', '3.14')
Backends
app_metrics.backends.db
(Default) - This backend stores all metrics and
aggregations in your database. NOTE: Every call to metric()
generates a
database write, which may decrease your overall performance is you go nuts
with them or have a heavily traffic site.
app_metrics.backends.mixpanel
- This backend allows you to pipe all of
your calls to metric()
to Mixpanel. See the Mixpanel documentation
for more information on their API.
app_metrics.backends.statsd
- This backend allows you to pipe all of your
calls to metric()
to a statsd server. See statsd for more information
on their API.
app_metrics.backends.redis
- This backend allows you to use the metric() and
gauge() aspects, but not timer aspects of app_metrics.
app_metrics.backends.librato_backend
- This backend lets you send metrics to
Librato. See the Librato documentation for more information on their API.
This requires the Librato library. It uses use a librato Gauge by default,
although this can be overridden by supplying metric_type="counter"
as a
keyword arg to metric()
.
app_metrics.backends.composite
- This backend lets you compose multiple
backends to which metric-calls are handed. The backends to which the call is
sent can be configured with the APP_METRICS_COMPOSITE_BACKENDS
setting. This
can be overridden in each call by supplying a backends
keyword argument::
metric('signups', 42, backends=['app_metrics.backends.librato',
'app_metrics.backends.db'])
Settings
APP_METRICS_BACKEND
- Defaults to 'app_metrics.backends.db' if not defined.
APP_METRICS_SEND_ZERO_ACTIVITY
- Prevent e-mails being sent when there's been
no activity today (i.e. during testing). Defaults to True
.
APP_METRICS_DISABLED
- If True
, do not track metrics, useful for
debugging. Defaults to False
.
Mixpanel Settings
Set APP_METRICS_BACKEND
== 'app_metrics.backends.mixpanel'.
APP_METRICS_MIXPANEL_TOKEN
- Your Mixpanel.com API token
APP_METRICS_MIXPANEL_URL
- Allow overriding of the API URL end point
Statsd Settings
Set APP_METRICS_BACKEND
== 'app_metrics.backends.statsd'.
APP_METRICS_STATSD_HOST
- Hostname of statsd server, defaults to 'localhost'
APP_METRICS_STATSD_PORT
- statsd port, defaults to '8125'
APP_METRICS_STATSD_SAMPLE_RATE
- statsd sample rate, defaults to 1
Redis Settings
Set APP_METRICS_BACKEND
== 'app_metrics.backends.redis'.
APP_METRICS_REDIS_HOST
- Hostname of redis server, defaults to 'localhost'
APP_METRICS_REDIS_PORT
- redis port, defaults to '6379'
APP_METRICS_REDIS_DB
- redis database number to use, defaults to 0
Librato Settings
Set APP_METRICS_BACKEND
== 'app_metrics.backends.librato'.
APP_METRICS_LIBRATO_USER
- Librato username
APP_METRICS_LIBRATO_TOKEN
- Librato API token
APP_METRICS_LIBRATO_SOURCE
- Librato data source (e.g. 'staging', 'dev'...)
Composite Backend Settings
Set APP_METRICS_BACKEND
== 'app_metrics.backends.composite'.
APP_METRICS_COMPOSITE_BACKENDS
- List of backends that are used by default,
e.g.::
APP_METRICS_COMPOSITE_BACKENDS = ('librato', 'db', 'my_custom_backend',)
Running the tests
To run the tests you'll need some requirements installed, so run::
pip install -r requirements/test.txt
Then simply run::
django-admin.py test --settings=app_metrics.tests.settings
TODO
- Improve text and HTML templates to display trending data well
Build Process:
- Update the
__version_info__
inside of the application. Commit and push. - Tag the release with the version.
git tag <version> -m "Release"; git push --tags
- Build the release
rm -rf dist build *egg-info; python setup.py sdist bdist_wheel
- Upload the data
twine upload dist/*
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