Package: analytics
Py-Analytics is a library designed to make it easy to provide analytics as part of any project.The project’s goal is to make it easy to store and retrieve analytics data. It does not provide
any means to visualize this data.Currently, onlyRedisis supported for storing data.InstallYou can install the latest official stable version using pypi:>>> pip install analyticsOr get the latest version directly from github:>>> pip install -e git+https://github.com/numan/py-analytics.git#egg=analyticsRequirementsRequiredRequirementsshouldbe handled by setuptools, but if they are not, you will need the following Python packages:nydusredisdateutilOptionalhiredisanalytics.create_analytic_backendCreates 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, theRedisanalytics backend usesnydusto 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.BaseAnalyticsBackendsettings: settings required to initialize the backend. For theRedisbackend, this is a list of hosts in your redis cluster.Example Usagefrom 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=365)

#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")
>> [....]

#set a metric count for a day
analytics.set_metric_by_day("user:1245", "login", year_ago, 100)

#sync metrics for week and month after setting day
analytics.sync_agg_metric("user:1245", "login", year_ago, datetime.date.today())

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

#retrieve a count between 2 dates
analytics.get_count("user:1245", "login", start_date=datetime.date(month=1, day=5, year=2011), end_date=datetime.date(month=5, day=15, year=2011))

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

#clear out everything we created
analytics.clear_all()BACKWARDS INCOMPATIBLE CHANGESV0.6.0This version introduces prefixes. Any old analytics data will be unaccessable.v0.5.2get_metric_by_day,get_metric_by_weekandget_metric_by_monthreturnseriesas a set of strings instead of a list of date/datetime objectsTODOAdd more backends possibly…?Add an API so it can be deployed as a stand alone service (http, protocolbuffers, …)