Readme
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Kotori
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*Telemetry data acquisition and sensor networks for humans.*
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Status:
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Usage:
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Compatibility:
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About
Kotori is a multi-channel, multi-protocol, telemetry data acquisition and
graphing toolkit for time-series_ data processing. Free, open, simple.
It supports scientific environmental monitoring projects,
distributed sensor networks, and likewise scenarios.
Kotori is a data historian_ based on Grafana_, Mosquitto_, and InfluxDB_,
and is written in Python_ with Twisted_.
The best way to find out what you can do with Kotori, is by looking at
some outlined scenarios_ and by reading how others are using it at the
example gallery <gallery_>. To learn more about the technical details, have
a look at the used technologies.
Installation
Kotori can be installed in different ways. You may prefer using a Debian
package, install it from the Python Package Index (PyPI), or run it within
a development sandbox_ directly from the Git repository.
Corresponding installation instructions are bundled at https://getkotori.org/docs/setup/.
Synopsis
A compact example how to submit measurement data on a specific channel, using MQTT and HTTP, and export it again.
First, let's define a data acquisition channel::
CHANNEL=amazonas/ecuador/cuyabeno/1
and some example measurement data::
DATA='{"temperature": 42.84, "humidity": 83.1}'
Submit with MQTT::
MQTT_BROKER=daq.example.org
echo "$DATA" | mosquitto_pub -h $MQTT_BROKER -t $CHANNEL/data.json -l
Submit with HTTP::
HTTP_URI=https://daq.example.org/api/
echo "$DATA" | curl --request POST --header 'Content-Type: application/json' --data @- $HTTP_URI/$CHANNEL/data
Measurement data can be exported in a variety of formats.
This is a straight-forward example for CSV data export::
http $HTTP_URI/$CHANNEL/data.csv
Acknowledgements
Thanks a stack to all the contributors_ who helped to co-create and conceive
Kotori in one way or another. You know who you are.
Project information
Every kind of contribution, feedback, or patch, is much welcome. Create an issue_ or submit a patch if you think we should include a new feature, or to
report or fix a bug.
In order to setup a development environment on your workstation, please head over
to the development sandbox_ documentation. When you see the software tests succeed,
you should be ready to start hacking.
Source code <https://github.com/daq-tools/kotori>_Documentation <https://getkotori.org/>_Python Package Index (PyPI) <https://pypi.org/project/kotori/>_The project is licensed under the terms of the GNU AGPL license, see LICENSE_.
.. _Autobahn: https://crossbar.io/autobahn/ .. _contributors: https://getkotori.org/docs/project/contributors.html .. _Create an issue: https://github.com/daq-tools/kotori/issues/new .. _data historian: https://en.wikipedia.org/wiki/Operational_historian .. _development sandbox: https://getkotori.org/docs/setup/sandbox.html .. _gallery: https://getkotori.org/docs/gallery/ .. _Grafana: https://en.wikipedia.org/wiki/Grafana .. _InfluxDB: https://en.wikipedia.org/wiki/InfluxDB .. _LICENSE: https://github.com/daq-tools/kotori/blob/main/LICENSE .. _MongoDB: https://en.wikipedia.org/wiki/MongoDB .. _Mosquitto: https://github.com/eclipse/mosquitto .. _MQTT: https://en.wikipedia.org/wiki/MQTT .. _Python: https://www.python.org/ .. _scenarios: https://getkotori.org/docs/about/scenarios.html .. _technologies: https://getkotori.org/docs/about/technologies.html .. _time-series: https://en.wikipedia.org/wiki/Time_series .. _Twisted: https://en.wikipedia.org/wiki/Twisted_(software)
FAQs
Kotori is a data acquisition, processing and graphing toolkit for humans
We found that kotori demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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