readme.rst

Apis mellifera flowering example

This is a demo program which generates flowering events for phenology species suitable as fruits for bees (Apis mellifera) as Grafana annotations.

Image: Flowering events for some species around Müncheberg, Brandenburg, Germany.

Setup

pip install grafana-pandas-datasource phenodata>=0.10.0 cachetools

Acquire example files

export EXAMPLES_BASEURL=https://raw.githubusercontent.com/panodata/grafana-pandas-datasource/0.1.0/examples

wget ${EXAMPLES_BASEURL}/phenodata-mellifera/demo.py \
    --output-document=phenodata-mellifera-demo.py

wget ${EXAMPLES_BASEURL}/phenodata-mellifera/datasource.json \
    --output-document=phenodata-mellifera-datasource.json

wget ${EXAMPLES_BASEURL}/phenodata-mellifera/dashboard.json \
    --output-document=phenodata-mellifera-dashboard.json

Invoke

# Run Grafana.
docker run --rm -it \
    --publish=3000:3000 --volume="$(pwd)/var/lib/grafana":/var/lib/grafana \
    --env='GF_SECURITY_ADMIN_PASSWORD=admin' --env='GF_INSTALL_PLUGINS=grafana-simple-json-datasource' \
    grafana/grafana:7.3.6

# Run Grafana pandas Datasource demo.
python phenodata-mellifera-demo.py

Configure

Note

The host where the datasource service is running can be accessed from the Grafana Docker container using the hostname host.docker.internal.

You can have a quickstart by putting examples/phenodata-mellifera/datasource.json and examples/phenodata-mellifera/dashboard.json into Grafana:

# Login to Grafana.
export GRAFANA_URL=http://localhost:3000
http --session=grafana ${GRAFANA_URL} --auth=admin:admin

# Create datasource.
cat phenodata-mellifera-datasource.json | \
    http --session=grafana POST ${GRAFANA_URL}/api/datasources

# Create dashboard.
cat phenodata-mellifera-dashboard.json | \
    http --session=grafana POST ${GRAFANA_URL}/api/dashboards/db

open ${GRAFANA_URL}