API Analytics

A free and lightweight API analytics solution, complete with a dashboard.

Currently compatible with:

Python: FastAPI, Flask, Django and Tornado
Node.js: Express, Fastify and Koa
Go: Gin, Echo, Fiber and Chi
Rust: Actix, Axum and Rocket
Ruby: Rails and Sinatra
C#: ASP.NET Core

Getting Started

1. Generate an API key

Head to https://apianalytics.dev/generate to generate your unique API key with a single click. This key is used to monitor your API server and should be stored privately. It's also required in order to view your API analytics dashboard and data.

2. Add middleware to your API

Add our lightweight middleware to your API. Almost all processing is handled by our servers so there is minimal impact on the performance of your API.

FastAPI

pip install api-analytics[fastapi]

import uvicorn
from fastapi import FastAPI
from api_analytics.fastapi import Analytics

app = FastAPI()
app.add_middleware(Analytics, api_key=<API-KEY>)  # Add middleware

@app.get('/')
async def root():
    return {'message': 'Hello, World!'}

if __name__ == "__main__":
    uvicorn.run("app:app", reload=True)

Flask

pip install api-analytics[flask]

from flask import Flask
from api_analytics.flask import add_middleware

app = Flask(__name__)
add_middleware(app, <API-KEY>)  # Add middleware

@app.get('/')
def root():
    return {'message': 'Hello, World!'}

if __name__ == "__main__":
    app.run()

Django

pip install api-analytics[django]

Assign your API key to ANALYTICS_API_KEY in settings.py and add the Analytics middleware to the top of your middleware stack.

ANALYTICS_API_KEY = <API-KEY>

MIDDLEWARE = [
    'api_analytics.django.Analytics',  # Add middleware
    ...
]

Tornado

pip install api-analytics[tornado]

Modify your handler to inherit from Analytics. Create a __init__() method, passing along the application and response along with your unique API key.

import asyncio
from tornado.web import Application
from api_analytics.tornado import Analytics

# Inherit from the Analytics middleware class
class MainHandler(Analytics):
    def __init__(self, app, res):
        super().__init__(app, res, <API-KEY>)  # Provide api key
    
    def get(self):
        self.write({'message': 'Hello, World!'})

def make_app():
    return Application([
        (r"/", MainHandler),
    ])

if __name__ == "__main__":
    app = make_app()
    app.listen(8080)
    IOLoop.instance().start()

Express

npm install node-api-analytics

import express from 'express';
import { expressAnalytics } from 'node-api-analytics';

const app = express();

app.use(expressAnalytics(<API-KEY>)); // Add middleware

app.get('/', (req, res) => {
    res.send({ message: 'Hello, World!' });
});

app.listen(8080, () => {
    console.log('Server listening at http://localhost:8080');
})

Fastify

npm install node-api-analytics

import Fastify from 'fastify';
import { fastifyAnalytics } from 'node-api-analytics';

const fastify = Fastify();

fastify.addHook('onRequest', fastifyAnalytics(<API-KEY>)); // Add middleware

fastify.get('/', function (request, reply) {
  reply.send({ message: 'Hello, World!' });
})

fastify.listen({ port: 8080 }, function (err, address) {
  console.log('Server listening at http://localhost:8080');
  if (err) {
    fastify.log.error(err);
    process.exit(1);
  }
})

Koa

npm install node-api-analytics

import Koa from "koa";
import { koaAnalytics } from 'node-api-analytics';

const app = new Koa();

app.use(koaAnalytics(<API-KEY>)); // Add middleware

app.use((ctx) => {
  ctx.body = { message: 'Hello, World!' };
});

app.listen(8080, () =>
  console.log('Server listening at http://localhost:8080')
);

Gin

go get -u github.com/tom-draper/api-analytics/analytics/go/gin

package main

import (
    "net/http"
    "github.com/gin-gonic/gin"
    analytics "github.com/tom-draper/api-analytics/analytics/go/gin"
)

func root(c *gin.Context) {
    jsonData := []byte(`{"message": "Hello, World!"}`)
    c.Data(http.StatusOK, "application/json", jsonData)
}

func main() {
    router := gin.Default()
    
    router.Use(analytics.Analytics(<API-KEY>)) // Add middleware

    router.GET("/", root)
    router.Run(":8080")
}

Echo

go get -u github.com/tom-draper/api-analytics/analytics/go/echo

package main

import (
    "net/http"
    echo "github.com/labstack/echo/v4"
    analytics "github.com/tom-draper/api-analytics/analytics/go/echo"
)

func root(c echo.Context) error {
    jsonData := []byte(`{"message": "Hello, World!"}`)
    return c.JSON(http.StatusOK, jsonData)
}

func main() {
    apiKey := getAPIKey()

    router := echo.New()

    router.Use(analytics.Analytics(<API-KEY>)) // Add middleware

    router.GET("/", root)
    router.Start(":8080")
}

Fiber

go get -u github.com/tom-draper/api-analytics/analytics/go/fiber

package main

import (
    "github.com/gofiber/fiber/v2"
    analytics "github.com/tom-draper/api-analytics/analytics/go/fiber"
)

func root(c *fiber.Ctx) error {
    jsonData := []byte(`{"message": "Hello, World!"}`)
    return c.SendString(string(jsonData))
}

func main() {
    app := fiber.New()

    app.Use(analytics.Analytics(<API-KEY>)) // Add middleware

    app.Get("/", root)
    app.Listen(":8080")
}

Chi

go get -u github.com/tom-draper/api-analytics/analytics/go/chi

package main

import (
    "net/http"
    analytics "github.com/tom-draper/api-analytics/analytics/go/chi"
    chi "github.com/go-chi/chi/v5"
)

func root(w http.ResponseWriter, r *http.Request) {
    w.Header().Set("Content-Type", "application/json")
    w.WriteHeader(http.StatusOK)
    jsonData := []byte(`{"message": "Hello, World!"}`)
    w.Write(jsonData)
}

func main() {
    router := chi.NewRouter()

    router.Use(analytics.Analytics(<API-KEY>)) // Add middleware

    router.GET("/", root)
    router.Run(":8080")
}

Actix

cargo add actix-analytics

use actix_web::{get, web, App, HttpServer, Responder, Result};
use serde::Serialize;
use actix_analytics::Analytics;

#[derive(Serialize)]
struct JsonData {
    message: String,
}

#[get("/")]
async fn index() -> Result<impl Responder> {
    let data = JsonData {
        message: "Hello, World!".to_string(),
    };
    Ok(web::Json(data))
}

#[actix_web::main]
async fn main() -> std::io::Result<()> {
    HttpServer::new(|| {
        App::new()
            .wrap(Analytics::new(<API-KEY>))  // Add middleware
            .service(index)
    })
    .bind(("127.0.0.1", 8080))?
    .run()
    .await
}

Axum

cargo add axum-analytics

use axum::{routing::get, Json, Router};
use axum_analytics::Analytics;
use serde::Serialize;
use std::net::SocketAddr;

#[derive(Serialize)]
struct JsonData {
    message: String,
}

async fn root() -> Json<JsonData> {
    let json_data = JsonData {
        message: String::from("Hello World!"),
    };
    Json(json_data)
}

#[tokio::main]
async fn main() {
    let app = Router::new()
        .route("/", get(root))
        .layer(Analytics::new(<API-KEY>));

    let addr = SocketAddr::from(([127, 0, 0, 1], 8080));
    let listener = tokio::net::TcpListener::bind(addr).await.unwrap();
    println!("Server listening at: http://127.0.0.1:8080");
    axum::serve(listener, app).await.unwrap();
}

Rocket

cargo add rocket-analytics

#[macro_use]
extern crate rocket;
use rocket::serde::json::Json;
use serde::Serialize;
use rocket_analytics::Analytics;

#[derive(Serialize)]
pub struct JsonData {
    message: String,
}

#[get("/")]
fn root() -> Json<JsonData> {
    let data = JsonData {
        message: "Hello, World!".to_string(),
    };
    Json(data)
}

#[launch]
fn rocket() -> _ {
    rocket::build()
        .mount("/", routes![root])
        .attach(Analytics::new(<API-KEY>))
}

Rails

gem install api_analytics

Add the analytics middleware to your rails application in config/application.rb.

require 'rails'
require 'api_analytics'

Bundler.require(*Rails.groups)

module RailsMiddleware
  class Application < Rails::Application
    config.load_defaults 6.1
    config.api_only = true

    config.middleware.use ::Analytics::Rails, <API-KEY>  # Add middleware
  end
end

Sinatra

gem install api_analytics

require 'sinatra'
require 'api_analytics'

use Analytics::Sinatra, <API-KEY>  # Add middleware

before do
    content_type 'application/json'
end

get '/' do
    {message: 'Hello, World!'}.to_json
end

ASP.NET Core

NuGet Version

dotnet add package APIAnalytics.AspNetCore

using Analytics;
using Microsoft.AspNetCore.Mvc;

var builder = WebApplication.CreateBuilder(args);

var app = builder.Build();

app.UseAnalytics(<API-KEY>); // Add middleware

app.MapGet("/", () =>
{
    return Results.Ok(new OkObjectResult(new { message = "Hello, World!" }));
});

app.Run();

3. View your analytics

Your API will now log and store incoming request data on all valid routes. Your logged data can be viewed using two methods:

Through visualizations and statistics on the dashboard
Accessed directly via the data API

You can use the same API key across multiple APIs, but all of your data will appear in the same dashboard. We recommend generating a new API key for each additional API server you want analytics for.

Dashboard

Head to https://apianalytics.dev/dashboard and paste in your API key to access your dashboard.

Demo: https://apianalytics.dev/dashboard/demo

dashboard

Data API

Logged data for all requests can be accessed via our REST API. Simply send a GET request to https://apianalytics-server.com/api/data with your API key set as X-AUTH-TOKEN in the headers.

Python

import requests

headers = {
 "X-AUTH-TOKEN": <API-KEY>
}

response = requests.get("https://apianalytics-server.com/api/data", headers=headers)
print(response.json())

Node.js

fetch("https://apianalytics-server.com/api/data", {
  headers: { "X-AUTH-TOKEN": <API-KEY> },
})
  .then((response) => {
    return response.json();
  })
  .then((data) => {
    console.log(data);
  });

cURL

curl --header "X-AUTH-TOKEN: <API-KEY>" https://apianalytics-server.com/api/data

Parameters

You can filter your data by providing URL parameters in your request.

page - the page number, with a max page size of 50,000 (defaults to 1)
date - the exact day the requests occurred on (YYYY-MM-DD)
dateFrom - a lower bound of a date range the requests occurred in (YYYY-MM-DD)
dateTo - a upper bound of a date range the requests occurred in (YYYY-MM-DD)
hostname - the hostname of your service
ipAddress - the IP address of the client
status - the status code of the response
location - a two-character location code of the client
user_id - a custom user identifier (only relevant if a get_user_id mapper function has been set)

Example:

curl --header "X-AUTH-TOKEN: <API-KEY>" https://apianalytics-server.com/api/data?page=3&dateFrom=2022-01-01&hostname=apianalytics.dev&status=200&user_id=b56cbd92-1168-4d7b-8d94-0418da207908

Client ID and Privacy

By default, API Analytics logs and stores the client IP address of all incoming requests made to your API and infers a location (country) from the IP address if possible. This IP address is used as a form of client identification in the dashboard to estimate the number of users accessing your service.

This behaviour can be controlled through a privacy level defined in the configuration of the API middleware. There are three privacy levels to choose from 0 (default) to a maximum of 2. A privacy level of 1 will disable IP address storing, and a value of 2 will also disable location inference.

Privacy Levels:

0 - The client IP address is used to infer a location and then stored for user identification. (default)
1 - The client IP address is used to infer a location and then discarded.
2 - The client IP address is never accessed and location is never inferred.

from fastapi import FastAPI
from api_analytics.fastapi import Analytics, Config

config = Config()
config.privacy_level = 2  # Disable IP storing and location inference

app = FastAPI()
app.add_middleware(Analytics, api_key=<API-KEY>, config=config)  # Add middleware

With any of these privacy levels, there is the option to define a custom user ID as a function of a request by providing a mapper function in the API middleware configuration. For example, your service may require an API key sent in the X-AUTH-TOKEN header field that can be used to identify a user. In the dashboard, this custom user ID will identify the user in conjunction with the IP address or as an alternative.

from fastapi import FastAPI
from api_analytics.fastapi import Analytics, Config

config = Config()
config.get_user_id = lambda request: request.headers.get('X-AUTH-TOKEN', '')

app = FastAPI()
app.add_middleware(Analytics, api_key=<API-KEY>, config=config)  # Add middleware

Data and Security

All data is stored securely in compliance with The EU General Data Protection Regulation (GDPR).

For any given request to your API, data recorded is limited to:

Path requested by client
Client IP address (optional)
Client operating system
Client browser
Request method (GET, POST, PUT, etc.)
Time of request
Status code
Response time
API hostname
API framework (FastAPI, Flask, Express etc.)

Data collected is only ever used to populate your analytics dashboard. All stored data is pseudo-anonymous, with the API key the only link between you and your logged request data. Should you lose your API key, you will have no method to access your API analytics.

Data Deletion

At any time you can delete all stored data associated with your API key by going to https://apianalytics.dev/delete and entering your API key.

API keys and their associated logged request data are scheduled to be deleted after 6 months of inactivity.

Monitoring

Active API monitoring can be set up by heading to https://apianalytics.dev/monitoring to enter your API key. Our servers will regularly ping chosen API endpoints to monitor uptime and response time.

Monitoring

Contributions

Contributions, issues and feature requests are welcome.

Fork it (https://github.com/tom-draper/api-analytics)
Create your feature branch (git checkout -b my-new-feature)
Commit your changes (git commit -am 'Add some feature')
Push to the branch (git push origin my-new-feature)
Create a new Pull Request

If you find value in my work consider supporting me.

Buy Me a Coffee: https://www.buymeacoffee.com/tomdraper
PayPal: https://www.paypal.com/paypalme/tomdraper

api-analytics
api-analytics copied to clipboard

Metadata

API Analytics

Getting Started

1. Generate an API key

2. Add middleware to your API

FastAPI

Flask

Django

Tornado

Express

Fastify

Koa

Gin

Echo

Fiber

Chi

Actix

Axum

Rocket

Rails

Sinatra

ASP.NET Core

3. View your analytics

Dashboard

Data API

Python

Node.js

cURL

Parameters

Client ID and Privacy

Data and Security

Data Deletion

Monitoring

Contributions

← Metadata

Owner

Metadata

api-analytics api-analytics copied to clipboard

Metadata

API Analytics

Getting Started

1. Generate an API key

2. Add middleware to your API

FastAPI

Flask

Django

Tornado

Express

Fastify

Koa

Gin

Echo

Fiber

Chi

Actix

Axum

Rocket

Rails

Sinatra

ASP.NET Core

3. View your analytics

Dashboard

Data API

Python

Node.js

cURL

Parameters

Client ID and Privacy

Data and Security

Data Deletion

Monitoring

Contributions

← Metadata

Owner

Metadata

api-analytics
api-analytics copied to clipboard