Grafana Pandas Datasource Save

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######################### Grafana pandas datasource #########################

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 pure Python application can be used to directly supply data to Grafana, both 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.

Screenshots

.. figure:: https://user-images.githubusercontent.com/453543/103137119-78dab480-46c6-11eb-829f-6aa957239804.png

Image: Sinewave data and midnights annotations, both generated using NumPy_,
see `Sinewave/Midnights example`_.

Setup

Grafana pandas datasource setup_ outlines how to install all software prerequisites needed to run this project. Please read this section carefully.

::

pip install grafana-pandas-datasource

Synopsis

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.

Then, configure the Grafana entities. You will need a datasource object and a dashboard object.

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.

Custom implementations

In order to conceive your own pandas-based data source, please use the Sinewave/Midnights demo.py as a blueprint. If you think it would be a valuable contribution to the community, we will be happy to add it to the repository.

Credits

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

Other projects

Oz Tiram conceived a similar piece of software with Python. He uses the Bottle web framework.

• https://gitlab.com/oz123/grafana-python-datasource
• https://oz123.github.io/writings/2019-06-16-Visualize-almost-anything-with-Grafana-and-Python/index.html

.. _different demo programs: https://github.com/panodata/grafana-pandas-datasource/tree/main/examples .. _Flask: https://github.com/pallets/flask .. _Grafana: https://github.com/grafana/grafana .. _Grafana pandas datasource setup: https://github.com/panodata/grafana-pandas-datasource/blob/main/docs/setup.rst .. _Grafana Simple JSON Datasource: https://grafana.com/grafana/plugins/grafana-simple-json-datasource/ .. _NumPy: https://numpy.org/ .. _pandas: https://github.com/pandas-dev/pandas .. _Sinewave/Midnights demo.py: https://github.com/panodata/grafana-pandas-datasource/blob/main/examples/sinewave-midnights/demo.py .. _Sinewave/Midnights example: https://github.com/panodata/grafana-pandas-datasource/tree/main/examples/sinewave-midnights