Python

How to get project id and token

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Usage

Install Footprint SDK

Footprint analytics SDK requires python 3.6 above and lower than python 4.

pip install footprint-analytics

Simple Demo

import time
import logging
from fga import FGA, User, Event, Account, Config


logger=logging.getLogger('fga')
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
ch.setLevel(logging.INFO)
logger.addHandler(ch)


client = FGA(
  token='xxxxxxxx',
  project_id=2,
  configuration=Config(logger=logger)
)

user = User(
    user_id='sdk_user_id_2',
    user_name='sdk_user_name_2',
    sign_up_at=int(time.time())
)

event = Event(
    event_type='login',
    event_name='login',
    user_id='sdk_user_id_2',
    event_id='sdk_event_id_2',
)
account = Account(
    user_id='sdk_user_id_2',
    wallet_address='0x1234567890'
)

if __name__ == '__main__':
    client.track(event)
    client.user_set(user)
    client.account_set(account)

Initialize SDK

You must initialize the SDK before any events are instrumented. The token for your Footprint project is required. You can also pass a config object in this call. You can use the SDK client instance across requests after it's initialized.

from fga import FGA

client = FGA(
  token=FOOTPRINT_PROJECT_TOKEN,
  project_id=1
)

Configuration

from fga import FGA
from fga.config import Config 

def callback_func(event, code, message=None):
  # callback function that takes three input parameters
  # event: the event that triggered this callback
  # code: status code of request response
  # message: a optional string message for more detailed information

config = Config(
  flush_queue_size=10,
  fulush_interval_millis=1,
  flush_max_retries=1,
  callback=callback_func,
  opt_out=True
)

client = FGA(
  token=FOOTPRINT_PROJECT_TOKEN,
  project_id=1,
  configuration=config
)

Set User Properties

User properties help you understand your users at the time they performed some action within your app such as their device details, their preferences, or language.

Set user properties

The user object provides controls over setting user properties. An user object must first be instantiated, then user_set methods can be called on it, and finally the client makes a call with the user object.

from fga import FGA, User


client = FGA(
  token=FOOTPRINT_PROJECT_TOKEN,
  project_id=1
)

user = User(
    user_id="USER_ID",
    user_name="USER_NAME",
    sign_up_at=int(time.time())
)

client.user_set(user)

Track User Event

Events represent how users interact with your application. For example, login may be an action you want to note.

Event Properties

from fga import FGA, Event


client = FGA(
  token=FOOTPRINT_PROJECT_TOKEN,
  project_id=1
)

# Track events with optional properties
client.track(
    Event(
        event_id="sdk_event_id_1",
        event_type="login",
        user_id="sdk_user_id_1",
        event_name="login"
    )
)

Set Account Mapping

Account mapping represent need to combine web3 data to analyze certain user behaviors, need a mapping relationship between wallet_address and user_id.

User Properties

from fga import FGA, Account


client = FGA(
  token=FOOTPRINT_PROJECT_TOKEN,
  project_id=1
)

account = Account(
    user_id='sdk_user_id_2',
    wallet_address='0x1234567890'
)

client.account_set(account)

View Data From SDK

Generally, after successful uploading, you will see the corresponding data within 1min.

User Dashboard

You can login Footprint Growth Analytics page, and click Users -> Users Acquistion, the Number of Users of this dashboard can show the changes if you set user. See screenshot as follow:

Event Dashboard

Click the User Engagement menu. The DAU metric of this dashboard can show the changes if you track event. See screenshot as follow:

Custom Analysis

Entering Custom Analysis page, directly use the user and user_event table to do some custom analytics. And these standard tables have a field extra_data that stored the event_properties and user_properties from SDK.

SDK Event Analytics Demo

User Growth Analysis Scenario

This scenario involves analyzing the increase in the number of users of a service or application over different periods.

Event Analysis Scenario

This scenario involves analyzing user interactions with a service or application by tracking various events.

Traffic Analysis Scenario

This scenario involves analyzing the volume of visits to a particular service or application over different periods.

User Retention Scenarios

This scenario involves analyzing the percentage of users who return to a service or application after their initial visit over various time periods.