Do you like Grafana but wish you could version your dashboard configuration? Do you find yourself repeating common patterns? If so, grafanalib is for you.

grafanalib lets you generate Grafana dashboards from simple Python scripts.

Take a look at the examples directory, e.g. this dashboard will configure a dashboard with a single row, with one QPS graph broken down by status code and another latency graph showing median and 99th percentile latency.

In the code is a fair bit of repetition here, but once you figure out what works for your needs, you can factor that out. See our Weave-specific customizations for inspiration.

You can read the entire grafanlib documentation on readthedocs.io.

grafanalib is just a Python package, so:

$ pip install grafanalib

Generate the JSON dashboard like so:

$ curl -o example.dashboard.py https://raw.githubusercontent.com/weaveworks/grafanalib/master/grafanalib/tests/examples/example.dashboard.py
$ generate-dashboard -o frontend.json example.dashboard.py

This library is in its very early stages. We'll probably make changes that break backwards compatibility, although we'll try hard not to.

grafanalib works with Python 3.6 through 3.9.

If you're working on the project, and need to build from source, it's done as follows:

$ virtualenv .env
$ . ./.env/bin/activate
$ pip install -e .

This repo used to contain a program gfdatasource for configuring Grafana data sources, but it has been retired since Grafana now has a built-in way to do it. See https://grafana.com/docs/administration/provisioning/#datasources

We'd like you to join the grafanalib community! Talk to us on Slack (see the links), or join us for one of our next meetings):

• Meetings take place monthly: third Friday of the month 15:00 UTC
• https://weaveworks.zoom.us/j/96824669060
• Meeting minutes and agenda (includes links to meeting recordings)

We follow the CNCF Code of Conduct.

If you have any questions about, feedback for or problems with grafanalib:

• Read the documentation at https://grafanalib.readthedocs.io
• Invite yourself to the Weave Users Slack.
• Ask a question on the #grafanalib slack channel.
• File an issue.

Your feedback is always welcome!