We’ve been on a roll this year with Beelines, our integrations for quick, easy, and automagic instrumentation of your apps. You may have already seen our Node.js, Ruby, and Go beelines – today, we’re excited to announce the release of the Honeycomb Beeline for Python!
The Python Beeline automatically instruments HTTP requests and DB queries and sends the events to Honeycomb, so you can start asking questions like “Which endpoint has the worst P99 latency?” and “Which DB calls take up the most time?”
With support for Honeycomb Tracing included out of the box, you can also figure out where your app is spending the most time, visualize execution, and more!
- Python 2.7 or 3.x
- Flask, Django (>1.10), Bottle (support for more frameworks is on the way)
- Your Honeycomb API key, found on your Honeycomb Team Settings page.
First, install the package:
pip install honeycomb-beeline
If you’re running Flask, your HTTP requests will be instrumented, as will DB queries if you are using Flask’s SQLAlchemy extension.
Initialize the beeline module, then pass your app to HoneyMiddleware:
import beeline from beeline.middleware.flask import HoneyMiddleware beeline.init(writekey="yourApiKey", dataset="my-flask-app", service_name="my-app-name") app = Flask(__name__) # db_events defaults to True, set to False if not using our db middleware with Flask-SQLAlchemy HoneyMiddleware(app, db_events=True)
- If you’re running a Django version greater than 1.10, your HTTP requests will be automatically instrumented.
- If you’re running a Django version greater than 2.0, you’ll also get database instrumentation out of the box.
First, add the Beeline as middleware to your project’s settings.py. If you’d like HTTP instrumentation only, choose
HoneyMiddlewareHttp. If you’d like db instrumentation as well, choose
MIDDLEWARE = [ ... 'beeline.middleware.django.HoneyMiddleware', ... ]
Then, initialize the beeline module in your app’s apps.py:
from django.apps import AppConfig import beeline class MyAppConfig(AppConfig): def ready(self): beeline.init( writekey='yourApiKey', dataset='my-django-app', service_name='my-app-name' )
Don’t forget to set your app’s default config in your app’s __init__.py:
default_app_config = 'myapp.apps.MyAppConfig'
If you’re running Bottle, your HTTP requests will be instrumented via WSGI middleware.
Initialize the beeline module, and pass your app to HoneyWSGIMiddleware:
import beeline from beeline.middleware.bottle import HoneyWSGIMiddleware beeline.init( writekey='<MY HONEYCOMB API KEY>', dataset='my-app', service_name='my-app' ) app = bottle.app() myapp = HoneyWSGIMiddleware(app) bottle.run(app=myapp)
Events instrumented with the Python Beeline will automatically be traced, allowing you to gain insight into how your program executes.
Want to measure some other part of your program? Use the Beeline tracer to easily include parts of your code in the trace.
with beeline.tracer("external api call"): result = call_external_api() # do something with result
Adding more context
You know your app better than we do! You can easily add more data to your events at any point in your program. Want to log the user ID associated with a request? It’s simple:
with beeline.tracer("external api call"): result = call_external_api() beeline.add_context_field(‘status_code’, result.status_code) # do something with result
Check out the Beeline documentation for more information on what else is supported.
Want automagical instrumentation but haven’t tried Honeycomb before? Sign up for free!