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
Head to apianalytics.dev/generate to generate your unique API key with a single click. This key is used to monitor your specific API and should be stored privately. It's also required in order to access your API analytics dashboard and data.
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.
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)
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()
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
...
]
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()
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');
})
npm install node-api-analytics
import fastify from 'Fastify';
import { useFastifyAnalytics } from 'node-api-analytics';
const fastify = Fastify();
useFastifyAnalytics(fastify, apiKey);
fastify.get('/', function (request, reply) {
reply.send({ message: 'Hello World!' });
})
fastify.listen({ port: 8080 }, function (err, address) {
console.log('Server listening at https://localhost:8080');
if (err) {
fastify.log.error(err);
process.exit(1);
}
})
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')
);
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")
}
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")
}
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")
}
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")
}
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
}
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();
}
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>))
}
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
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
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();
Your API will now log and store incoming request data on all 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.
Head to apianalytics.dev/dashboard and paste in your API key to access your dashboard.
Demo: apianalytics.dev/dashboard/demo
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.
import requests
headers = {
"X-AUTH-TOKEN": <API-KEY>
}
response = requests.get("https://apianalytics-server.com/api/data", headers=headers)
print(response.json())
fetch("https://apianalytics-server.com/api/data", {
headers: { "X-AUTH-TOKEN": <API-KEY> },
})
.then((response) => {
return response.json();
})
.then((data) => {
console.log(data);
});
curl --header "X-AUTH-TOKEN: <API-KEY>" https://apianalytics-server.com/api/data
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 serviceipAddress
- the IP address of the clientstatus
- the status code of the responselocation
- a two-character location code of the clientuser_id
- a custom user identifier (only relevant if aget_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
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 each IP address if possible. The 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
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.
At any time you can delete all stored data associated with your API key by going to 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.
Active API monitoring can be set up by heading to apianalytics.dev/monitoring to enter your API key. Our servers will regularly ping chosen API endpoints to monitor uptime and response time.
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