open-analytics 0.1.0

Open sournce application analytics tracking library

Open-Analytics

An open-source analytical data capturing pacakge.

Open-Analytics lib enables you to capture and track analyitical data of your application at real-time into your own data-source. You can use your own or open-source tools to visualize the capture data.

Installation

Install the dependencies and devDependencies and start the server.

pip install open-analytics

Initalize

from openanalytics.client import Client

client = Client(connector=connector, sync_mode=False, debug=True)

Connecting to data-source

As of now the open-analytics library provide Connector Plugins for three types of databases.

MongoDBConnector

from openanalytics.connectors.MongoDBConnector import MongoDBConnector
connector = MongoDBConnector(host="mongodb://localhost:27017/", dbname="demobucket")

InfluxDBConnector

from openanalytics.connectors.InfluxDBConnector import InfluxDBConnector
connector = InfluxDBConnector(
    token="5wttcrwYX3COT8OQaorbOKUYAmPPNE-7oC_2itF60bBqIfC33L9g4k3APNjcCkCAuBuwWurOVEBo6gNYP0cAuA==",
    org="demoorg",
    url="http://localhost:8086",
    bucket="demobucket",
)

SQLiteConnector

from openanalytics.connectors.SQLiteConnector import SQLiteConnector
connector = SQLiteConnector(db="handshake.sqlite3")

Features

Identify

The Identify method lets you tie a user to their actions and record traits about them. It includes a unique User ID and any optional traits you know about them.

from openanalytics.models.Identify import Identify

client.idetify(
    Identify(
        userID="UserName / UserEmail", 
        event="Custom Event", 
        metadata={"data": "query data", "location": "query location"},
        timestamp=datetime.now(timezone.utc),
    )
)

Token

Useful in Generative AI token processing. The Token method lets you record token utlization for you events, along with optional extra information about the token processing.

from openanalytics.models.Token import Token

client.token(
    Token(
        event="LLM Query Event",
        action="Similarity Search",
        count=134,
        metadata={
            "query": "llm prompt",
            "location": {"context": "context of the prompt", "rag": "enabled"},
        },
    )
)

Track

Track lets you record the actions your users perform. Every action triggers what Segment calls an “event”, which can also have associated properties.

from openanalytics.models.Track import Track

client.track(
    Track(
        endpoint="http:localhost:8080/search",
        event="Profile Search",
        properties={"params": "q=username"},
        timestamp=datetime.now(timezone.utc),
    )
)

Page

The Page method lets you record page views on your website, along with optional extra information about the page being viewed.

from openanalytics.models.Page import Page

client.page(
    Page(
        name="Dashboard", 
        category="AdminGroup", 
        properties={"status": True}
    )
)

Logger

The Log method lets you record log events of your actions, along with optional extra information about the log event.

from openanalytics.models.Logger import Logger

client.logger(
    Log(
        summary="Log Message",
        level="Debug",
        event="Process Login Function",
        metadata={"user": "username"},
    )
)

License

Apache License v2.0