api-watch 0.1.5

Real-time API monitoring for Flask/FastAPI with async, zero-blocking logging

api-watch

Real-time API monitoring for Flask and FastAPI with zero-blocking async logging.

A lightweight, developer-focused tool that streams your API requests, responses, and metadata to a beautiful real-time dashboard. Perfect for debugging, development, and understanding your API traffic.

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Features

• Zero Performance Impact - Fire-and-forget async logging that never blocks your API
• Real-time Streaming - WebSocket-powered dashboard shows requests as they happen
• Auto-Start Dashboard - Just import and use, dashboard starts automatically
• Full Visibility - Method, path, status, timing, headers, request/response data
• Filter by Status - Quickly filter requests by status code
• Request Statistics - Visual metrics and charts
• Minimal UI - Clean, fast dashboard focused on what matters
• Multi-Framework - Works with Flask and FastAPI
• Production Ready - Standalone mode for Docker/Kubernetes
• Optimized Dependencies - Only install what you need

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Quick Start

Installation

For Flask:

pip install api-watch[flask]

For FastAPI:

pip install api-watch[fastapi]

For both:

pip install api-watch[all]

Flask Integration (Auto-Start)

from flask import Flask
from apiwatch import ApiWatcher
from apiwatch.middleware_flask import FlaskWatchMiddleware

app = Flask(__name__)

# Dashboard auto-starts
api_watcher = ApiWatcher(service_name='my-flask-app')
FlaskWatchMiddleware(app, api_watcher)

@app.route('/api/health', methods=['GET'])
def health():
    return jsonify({
        "status": "healthy",
        "service": "flask-service"
    })

if __name__ == '__main__':
    app.run(port=5000)

Terminal run:

python -m apiwatch

Docker run: easiest

docker pull theisaac/api-watch:latest
docker compose up -d

Open dashboard:

http://localhost:22222

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FastAPI Integration

from fastapi import FastAPI
from pydantic import BaseModel
from apiwatch import ApiWatcher
from apiwatch.middleware_fastapi import FastAPIWatchMiddleware

app = FastAPI()

api_watcher = ApiWatcher(
    service_name='fastapi-service',
    dashboard_host='localhost',
    auto_start_dashboard=False
)

app.add_middleware(FastAPIWatchMiddleware, watcher=api_watcher)

@app.get("/api/health")
async def health():
    return {
        "status": "healthy",
        "service": "fastapi-service"
    }

if __name__ == '__main__':
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

Run it:

uvicorn app:app --port 8000

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📊 Dashboard Features

Real-time Request Monitoring

• Live streaming of API requests
• Color-coded HTTP methods (GET, POST, PUT, DELETE)
• Status code highlighting (success/error)
• Response time tracking
• Service name badges (multi-service support)

Filters & Search

• Filter by status code (2xx, 3xx, 4xx, 5xx, All)
• Sort by newest, oldest, fastest, sloweset, status(high-low)
• Filter by HTTP method

Request Details

• Full request/response bodies
• Query parameters
• Headers (sensitive headers filtered)
• Timestamp and duration

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Configuration

Basic Options

api_watcher = ApiWatcher(
    service_name='my-app',           # Service identifier
    max_history=1000,                # Requests to keep in memory
    dashboard_host='localhost',      # Dashboard host
    dashboard_port=22222,            # Dashboard port
    auto_start_dashboard=True        # Auto-start if not running
)

Middleware Options

Flask:

FlaskWatchMiddleware(
    app,
    api_watcher,
    capture_request_body=True,   # Log request bodies
    capture_response_body=True   # Log response bodies
)

FastAPI:

app.add_middleware(
    FastAPIWatchMiddleware,
    watcher=api_watcher,
    capture_request_body=True,   # Log request bodies
    capture_response_body=True   # Log response bodies
)

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Production Deployment

Standalone Mode

For production, run the dashboard as a separate service:

Terminal 1: Start Dashboard

python -m apiwatch

Terminal 2: Start Your App

from apiwatch import ApiWatcher

api_watcher = ApiWatcher(
    service_name='my-app',
    auto_start_dashboard=False  # Don't auto-start in production
)

Docker Compose

services:
  apiwatch:
    image: theisaac/api-watch:latest
    container_name: apiwatch
    networks:
      - test-network
    ports:
      - "22222:22222"
    restart: unless-stopped
    environment:
      - PYTHONUNBUFFERED=1
      - WATCHDOG_USERNAME=admin
      - WATCHDOG_PASSWORD=admin
      - API_WATCH_DASHBOARD_HOST=0.0.0.
      - API_WATCH_DASHBOARD_PORT=22222
    command: python -m apiwatch

services:
  test_flask_app:
    image: theisaac/files-webapp:latest
    restart: always
    networks:
      - test-network
    environment:
      - API_WATCH_MAX_HISTORY=3000
      - API_WATCH_DASHBOARD_HOST=apiwatch
      - API_WATCH_DASHBOARD_PORT=22222
      - API_WATCH_AUTO_START=false
    ports:
      - 1515:1515

#### NOTE
In Dockerized applications, ensure that the **apiwatch** container and your **Flask/FastAPI** containers are on the same network.
Also, use the container name `apiwatch` as the host name in your Flask app.


**Service code:**
```python
import os
from apiwatch import ApiWatcher

api_watcher = ApiWatcher(
    service_name=os.getenv('SERVICE_NAME', 'api-service'),
    dashboard_host=os.getenv('WATCHDOG_HOST', 'localhost'),
    dashboard_port=int(os.getenv('WATCHDOG_PORT', 22222)),
    auto_start_dashboard=False
)

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How It Works

Flask/FastAPI Request
        ↓
   Middleware intercepts
        ↓
   Queue.put_nowait() (non-blocking, <0.1ms)
        ↓
   App continues normally
        ↓
Background Async Worker
        ↓
HTTP POST to Dashboard
        ↓
Dashboard broadcasts via WebSocket
        ↓
Browser UI updates in real-time

Zero blocking! Your API never waits for logging.

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Requirements

• Python 3.7+
• aiohttp 3.8+ (always required)
• Flask 2.0+ (optional - only for Flask integration)
• FastAPI 0.68+ & Starlette 0.14+ (optional - only for FastAPI integration)

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