grafana-pandas-datasource 0.2.0

About

A HTTP API based on Flask for serving pandas data frames to Grafana, generated by NumPy. The Grafana Simple JSON Datasource is used to interface Grafana with the HTTP API.

This way, a native Python application can be used to directly supply data to Grafana easily and powerfully.

The framework supports feeding both timeseries data as well as annotations through corresponding /query and /annotations endpoints and also provides /search and /panels endpoints.

Sandbox environment

In order to work efficiently with the resources provided by this repository, we recommend to install some programs upfront. This will optimally work on Linux and macOS. Windows users might use the WSL subsystem.

Install prerequisites:

# Debian Linux
apt install git python3 python3-pip httpie docker.io
pip install poetry

# macOS / Homebrew
brew install git python3 poetry httpie docker

Acquire sources and bootstrap sandbox environment:

git clone https://github.com/panodata/grafana-pandas-datasource
cd grafana-pandas-datasource
poetry install
poetry shell

Test drive:

# Run Grafana pandas datasource demo.
python examples/sinewave-midnights/demo.py

# Submit a timeseries data request.
echo '{"targets": [{"target": "sine_wave:24"}], "range": {"from": "2022-02-22T15", "to": "2022-02-22T20"}}' | http http://127.0.0.1:3003/query

# Submit an annotation data request.
echo '{"annotation": {"query": "midnights:xx"}, "range": {"from": "2022-02-20", "to": "2022-02-22"}}' | http http://127.0.0.1:3003/annotations

When the environment has been properly configured, both requests above will yield appropriate responses.

Examples

There are different demo programs accompanied with Grafana datasource and dashboard definition files.

After confirming the sandbox environment has been installed successfully, please head over to the Sinewave/Midnights example page in order to learn how to provision Grafana with corresponding resources.

Setup

When aiming to run a dedicated service, without needing to invoke the examples, you can add the package grafana-pandas-datasource to the list of your project requirements.

pip install grafana-pandas-datasource

Credits

Kudos to Linar, who conceived the initial version of this software the other day at https://gist.github.com/linar-jether/95ff412f9d19fdf5e51293eb0c09b850.