analytics 0.4.0

Requirements

analytics.create_analytic_backend

Creates an analytics object that allows to to store and retrieve metrics:

>>> from analytics import create_analytic_backend
>>>
>>> analytics = create_analytic_backend({
>>>     'backend': 'analytics.backends.redis.Redis',
>>>     'settings': {
>>>         'defaults': {
>>>             'host': 'localhost',
>>>             'port': 6379,
>>>             'db': 0,
>>>         },
>>>         'hosts': [{'db': 0}, {'db': 1}, {'host': 'redis.example.org'}]
>>>     },
>>> })

Internally, the Redis analytics backend uses nydus to distribute your metrics data over your cluster of redis instances.

There are two required arguements:

• backend: full path to the backend class, which should extend analytics.backends.base.BaseAnalyticsBackend

• settings: settings required to initialize the backend. For the Redis backend, this is a list of hosts in your redis cluster.

Example Usage

from analytics import create_analytic_backend
import datetime

analytics = create_analytic_backend({
    "backend": "analytics.backends.redis.Redis",
    "settings": {
        "hosts": [{"db": 5}]
    },
})

year_ago = datetime.date.today() - datetime.timedelta(days=265)

#create some analytics data
analytics.track_metric("user:1234", "comment", year_ago)
analytics.track_metric("user:1234", "comment", year_ago, inc_amt=3)
#we can even track multiple metrics at the same time for a particular user
analytics.track_metric("user:1234", ["comments", "likes"], year_ago)
#or track the same metric for multiple users (or a combination or both)
analytics.track_metric(["user:1234", "user:4567"], "comment", year_ago)

#retrieve analytics data:
analytics.get_metric_by_day("user:1234", "comment", year_ago, limit=20)
analytics.get_metric_by_week("user:1234", "comment", year_ago, limit=10)
analytics.get_metric_by_month("user:1234", "comment", year_ago, limit=6)

#create a counter
analytics.track_count("user:1245", "login")
analytics.track_count("user:1245", "login", inc_amt=3)

#retrieve multiple metrics at the same time
#group_by is one of ``month``, ``week`` or ``day``
analytics.get_metrics([("user:1234", "login",), ("user:4567", "login",)], year_ago, group_by="day")
>> [....]

#retrieve a count
analytics.get_count("user:1245", "login")

#retrieve counts
analytics.get_counts([("user:1245", "login",), ("user:1245", "logout",)])

TODO

• Add more backends (riak, …)?

• Add an API so it can be deployed as a stand alone service (http, protocolbuffers, …)