luftdatenpumpe

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############## Luftdatenpumpe ##############

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About

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Process live and historical data from luftdaten.info, irceline and OpenAQ_. Filter by station-id, sensor-id and sensor-type, apply reverse geocoding, store into TSDB_ and RDBMS_ databases (InfluxDB_ and PostGIS_), publish to MQTT_ or just output as JSON.

.. figure:: https://cdn.jsdelivr.net/gh/earthobservations/luftdatenpumpe@main/doc/logo.svg :target: https://github.com/earthobservations/luftdatenpumpe :height: 200px :width: 200px

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Features

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1. Luftdatenpumpe_ acquires the measurement readings either from the livedata API of luftdaten.info_ or from its archived CSV files published to archive.luftdaten.info. To minimize impact on the upstream servers, all data gets reasonably cached.

2. While iterating the readings, it optionally filters on station-id, sensor-id or sensor-type and restrains information processing to the corresponding stations and sensors.

3. Then, each station's location information gets enhanced by

   • attaching its geospatial position as a Geohash_.
   • attaching a synthetic real-world address resolved using the reverse geocoding service Nominatim_ by OpenStreetMap_.

4. Information about stations can be

   • displayed on STDOUT or STDERR in JSON format.
   • filtered and transformed interactively through jq_, the swiss army knife of JSON manipulation.
   • stored into RDBMS_ databases like PostgreSQL_ using the fine dataset_ package. Being built on top of SQLAlchemy_, this supports all major databases.
   • queried using advanced geospatial features when running PostGIS_, please follow up reading the Luftdatenpumpe PostGIS tutorial <doc-postgis_>_.

5. Measurement readings can be

   • displayed on STDOUT or STDERR in JSON format, which allows for piping into jq_ again.
   • forwarded to MQTT_.
   • stored to InfluxDB_ and then
   • displayed in Grafana_.

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Synopsis

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::

# List networks
luftdatenpumpe networks

# List LDI stations
luftdatenpumpe stations --network=ldi --station=49,1033 --reverse-geocode

# Store list of LDI stations and metadata into RDBMS database (PostgreSQL), also display on STDERR
luftdatenpumpe stations --network=ldi --station=49,1033 --reverse-geocode --target=postgresql://luftdatenpumpe@localhost/weatherbase

# Store LDI readings into InfluxDB
luftdatenpumpe readings --network=ldi --station=49,1033 --target=influxdb://luftdatenpumpe@localhost/luftdaten_info

# Forward LDI readings to MQTT
luftdatenpumpe readings --network=ldi --station=49,1033 --target=mqtt://mqtt.example.org/luftdaten.info

For a full overview about all program options including meaningful examples, you might just want to run luftdatenpumpe --help on your command line or visit luftdatenpumpe --help_.

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Screenshots

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Luftdaten-Viewer displays stations and measurements from luftdaten.info (LDI) in Grafana.

Map display and filtering

• Filter by different synthesized address components and sensor type.
• Display measurements from filtered stations on Grafana Worldmap Panel.
• Display filtered list of stations with corresponding information in tabular form.
• Measurement values are held against configured thresholds so points are colored appropriately.

.. image:: https://community.hiveeyes.org/uploads/default/original/2X/f/f455d3afcd20bfa316fefbe69e43ca2fe159e62d.png :target: https://weather.hiveeyes.org/grafana/d/9d9rnePmk/amo-ldi-stations-5-map-by-sensor-type

Map popup labels

• Humanized label computed from synthesized OpenStreetMap address.
• Numeric station identifier.
• Measurement value, unit and field name.

.. image:: https://community.hiveeyes.org/uploads/default/original/2X/4/48eeda1a1d418eaf698b241a65080666abcf2497.png :target: https://weather.hiveeyes.org/grafana/d/9d9rnePmk/amo-ldi-stations-5-map-by-sensor-type

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Installation

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If you are running Python 3 already, installing the program should be as easy as::

pip install luftdatenpumpe

At this point, you should be able to conduct simple tests like luftdatenpumpe stations as seen in the synopsis section above. At least, you should verify the installation succeeded by running::

luftdatenpumpe --version

However, you might have to resolve some prerequisites so you want to follow the detailed installation instructions at install Luftdatenpumpe_.

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Luftdaten-Viewer

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About

Using Luftdatenpumpe, you can build user-friendly interactive GIS systems on top of PostGIS, InfluxDB and Grafana. We are calling this "Luftdaten-Viewer".

Without further ado, you might enjoy reading about existing "Luftdaten-Viewer" installations at Testimonials for Luftdatenpumpe_.

Instructions

These installation instructions outline how to setup the whole system to build similar interactive data visualization compositions of map-, graph- and other panel-widgets like outlined in the "Testimonials" section.

• Luftdaten-Viewer Applications_
• Luftdaten-Viewer Databases_
• Luftdaten-Viewer Grafana_

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License

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This project is licensed under the terms of the GNU AGPL license.

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Content attributions

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The copyright of particular images and pictograms are held by their respective owners, unless otherwise noted.

Icons and pictograms

• Water Pump Free Icon <https://www.onlinewebfonts.com/icon/97990>_ from Icon Fonts <http://www.onlinewebfonts.com/icon>_ is licensed by CC BY 3.0.

.. _doc-virtualenv: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/virtualenv.rst .. _doc-postgis: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/postgis.rst

.. _luftdaten.info: https://luftdaten.info/ .. _irceline: http://www.irceline.be/en/documentation/open-data .. _OpenAQ: https://openaq.org/

.. _Luftdatenpumpe: https://github.com/earthobservations/luftdatenpumpe

.. _Testimonials for Luftdatenpumpe: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/testimonials.rst .. _luftdatenpumpe --help: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/usage.rst .. _install Luftdatenpumpe: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/setup/luftdatenpumpe.rst .. _Luftdaten-Viewer Applications: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/setup/ldview-applications.rst .. _Luftdaten-Viewer Databases: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/setup/ldview-databases.rst .. _Luftdaten-Viewer Grafana: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/setup/ldview-grafana.rst .. _Luftdaten-Viewer Cron Job: https://github.com/earthobservations/luftdatenpumpe/blob/main/doc/setup/ldview-cronjob.rst

.. _Erneuerung der Luftdatenpumpe: https://community.hiveeyes.org/t/erneuerung-der-luftdatenpumpe/1199

.. _The Hiveeyes Project: https://hiveeyes.org/

.. _OpenStreetMap: https://en.wikipedia.org/wiki/OpenStreetMap .. _Nominatim: https://wiki.openstreetmap.org/wiki/Nominatim .. _Geohash: https://en.wikipedia.org/wiki/Geohash .. _dataset: https://dataset.readthedocs.io/ .. _SQLAlchemy: https://www.sqlalchemy.org/ .. _TSDB: https://en.wikipedia.org/wiki/Time_series_database .. _RDBMS: https://en.wikipedia.org/wiki/Relational_database_management_system .. _MQTT: http://mqtt.org/

.. _PostgreSQL: https://www.postgresql.org/ .. _PostGIS: https://postgis.net/ .. _InfluxDB: https://github.com/influxdata/influxdb .. _Grafana: https://github.com/grafana/grafana

.. _jq: https://stedolan.github.io/jq/