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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 time-series and RDBMS databases, publish to MQTT, output as JSON, or visualize in Grafana.
.. image:: https://github.com/earthobservations/luftdatenpumpe/workflows/Tests/badge.svg :target: https://github.com/earthobservations/luftdatenpumpe/actions?workflow=Tests :alt: CI outcome
.. image:: https://codecov.io/gh/earthobservations/luftdatenpumpe/branch/main/graph/badge.svg :target: https://codecov.io/gh/earthobservations/luftdatenpumpe :alt: Test suite code coverage
.. image:: https://pepy.tech/badge/luftdatenpumpe/month :target: https://pypi.org/project/luftdatenpumpe/ :alt: PyPI downloads per month
.. image:: https://img.shields.io/pypi/v/luftdatenpumpe.svg :target: https://pypi.org/project/luftdatenpumpe/ :alt: Package version on PyPI
.. image:: https://img.shields.io/pypi/status/luftdatenpumpe.svg :target: https://pypi.org/project/luftdatenpumpe/ :alt: Project status (alpha, beta, stable)
.. image:: https://img.shields.io/pypi/pyversions/luftdatenpumpe.svg :target: https://pypi.org/project/luftdatenpumpe/ :alt: Supported Python versions
.. image:: https://img.shields.io/pypi/l/luftdatenpumpe.svg :target: https://github.com/earthobservations/luftdatenpumpe/blob/main/LICENSE :alt: Project license
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############## Luftdatenpumpe ##############
.. image:: https://assets.okfn.org/images/ok_buttons/od_80x15_red_green.png :target: https://okfn.org/opendata/
.. image:: https://assets.okfn.org/images/ok_buttons/oc_80x15_blue.png :target: https://okfn.org/opendata/
.. image:: https://assets.okfn.org/images/ok_buttons/os_80x15_orange_grey.png :target: https://okfn.org/opendata/
About
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
Features
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.
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.
Then, each station's location information gets enhanced by
Information about stations can be
Luftdatenpumpe PostGIS tutorial <doc-postgis_>
_.Measurement readings can be
Synopsis
::
# 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
_.
Screenshots
Luftdaten-Viewer displays stations and measurements from luftdaten.info (LDI) in Grafana.
.. 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
.. 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
Installation
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
_.
Luftdaten-Viewer
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
_.
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
_License
This project is licensed under the terms of the GNU AGPL license.
Content attributions
The copyright of particular images and pictograms are held by their respective owners, unless otherwise noted.
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/
FAQs
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 time-series and RDBMS databases, publish to MQTT, output as JSON, or visualize in Grafana.
We found that luftdatenpumpe 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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