Getting Started with grafanalib
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.
How it works
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/main/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 3.10.
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 .
Configuring Grafana Datasources
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 currently don't follow a roadmap for
grafanalib and both maintainers
<https://github.com/weaveworks/grafanalib/blob/main/MAINTAINERS> have recently
become somewhat occupied otherwise.
We'd like you to join the
grafanalib community! If you would like to
help out maintaining
grafanalib that would be great. It's a fairly laid-back
and straight-forward project. Please talk to us on Slack (see the links below).
We follow the CNCF Code of Conduct.
If you have any questions about, feedback for or problems with
- 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!