This repository contains the module aranet_cloud.py, which allows recovering
data of the Aranet4 CO₂ sensors from the Aranet
Cloud.
After loading the module with
import aranet_clouda configuration object is needed to call the module functions. This configuration object will store the credentials to the Aranet Cloud as well as some other parameters.
The configuration object is a
ConfigParser object
which may be created from a configuration file with the read_aranet_conf
function, e.g.:
aranet_conf = aranet_cloud.read_aranet_conf("aranet_cloud.conf")A template for this configuration file is included in this repository in the
file aranet_cloud.conf.template (see the following section for a description of the available settings)
The configuration file admits the following settings in the DEFAULT section:
endpoint: endpoint of the Aranet Cloud, default value: https://aranet.cloud/.apilogin_cache_file: File to store the login information for reuse. If not provided each data request will need to do first a login request.password: Aranet Cloud password for the user.username: Aranet Cloud username.space_name: The organization name set in the Aranet Cloud.
Get information about a sensor. Usage:
get_sensors_info(
aranet_conf, fields=['metrics', 'telemetry', 'name'],
**kwargs) -> Dict[str, Any]:where fields is a list of str with the field names of the data to
request. The fields available in the Aranet Cloud are:
alarms: Alarms raised by the sensor.devices: List of base stations to which the sensor is paired.files: Number of files stored in the sensor.integrations: ?metrics: Latest data captured by the sensor, e.g., CO2, temperature, humidity, pressure.name: Name of the sensor.position: Localization of the sensor.rules: Alarm rules for the sensor.skills: ?tagids: Tags identifiers for the tags of the sensor.telemetry: Telemetry data, e.g., battery, RSSI.txint: ?virtual: ?
The function will return a dictionary object with the representation of the JSON data returned by the Aranet Cloud. An example output for two sensors with names "1.01", and "1.02" is the following:
{'params': {'lastModified': '2022-02-07T11:01:33.391'},
'data': {'lang': 'en',
'currentItemCount': 2,
'items': [{'id': '4196648',
'metrics': [{'id': '1',
't': 1644231619,
'v': 21.2,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '2',
't': 1644231619,
'v': 46,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '3',
't': 1644231619,
'v': 1059,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '4',
't': 1644231619,
'v': 1030,
'novelty': {'id': '1', 'name': 'New'}}],
'name': '1.01',
'telemetry': [{'id': '61',
't': 1644231619,
'v': -98,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '62',
't': 1644231619,
'v': 56,
'v%': 56,
'novelty': {'id': '1', 'name': 'New'}}],
'type': {'id': 'S4V2'}},
{'id': '4196666',
'metrics': [{'id': '1',
't': 1644231655,
'v': 19.6,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '2',
't': 1644231655,
'v': 50,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '3',
't': 1644231655,
'v': 1066,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '4',
't': 1644231655,
'v': 1030,
'novelty': {'id': '1', 'name': 'New'}}],
'name': '1.02',
'telemetry': [{'id': '61',
't': 1644231655,
'v': -93,
'novelty': {'id': '1', 'name': 'New'}},
{'id': '62',
't': 1644231655,
'v': 50,
'v%': 50,
'novelty': {'id': '1', 'name': 'New'}}],
'type': {'id': 'S4V2'}}]}}For each object in the metrics and the telemetry arrays, the measured value
will be returned in the v field, and the id field will indicate the metric
(e.g., CO₂, temperature, etc). The possible values of id for the metrics
and telemetry data can be queried with the get_metrics function.
Query the recorded data of an Aranet4 sensor during a certain time interval. Usage:
get_sensor_data(
aranet_conf, sensor_id, from_time, to_time, timezone="0000",
metrics=list(DEFAULT_METRICS_DICT.keys()), **kwargs) -> pandas.DataFrame:where
sensor_idis the sensor ID as astror anint.from_timeis the earliest time of the sensor data, as astrin the ISO 8601 format, for example2022-01-31T12:00:00Z. Note: currently it seems that the Aranet Cloud only allows times in UTC, specified with the timezoneZspecification or without any timezone information. A different timezone specification will make the request fail.to_timeis the latest time of the sensor data, as astrwith the same format asfrom_time.timezoneis the timezone string of the datetime field of the retrieved data, with format hhmm, being hh the hours and mm the minutes.metricsis a list of the metrics identifiers to query. The default islist(DEFAULT_METRICS_DICT.keys()), which is["1", "2", "3", "4"].
For example,
df = aranet_cloud.get_sensor_data(
aranet_conf, 4196648, '2022-02-01T12:00:00Z', '2022-02-01T12:20:00Z')
print(df.to_string())may return the following data
datetime(UTC) temperature(C) humidity(%) co2(ppm) atmosphericpressure(hPa)
0 2022.02.01 12:00:01 21.0 41.0 743 1033
1 2022.02.01 12:01:03 21.1 41.0 769 1033
2 2022.02.01 12:02:01 21.1 41.0 775 1033
3 2022.02.01 12:03:01 21.1 41.0 772 1033
4 2022.02.01 12:04:03 21.1 41.0 770 1033
5 2022.02.01 12:05:03 21.0 41.0 769 1033
6 2022.02.01 12:06:02 21.1 41.0 760 1033
7 2022.02.01 12:07:05 21.1 41.0 765 1033
8 2022.02.01 12:08:06 21.1 41.0 742 1033
9 2022.02.01 12:09:06 21.0 41.0 741 1033
10 2022.02.01 12:10:07 21.0 41.0 736 1033
11 2022.02.01 12:11:07 21.0 41.0 726 1033
12 2022.02.01 12:12:05 21.0 41.0 710 1032
13 2022.02.01 12:13:05 21.0 41.0 707 1032
14 2022.02.01 12:14:06 21.0 41.0 712 1032
15 2022.02.01 12:15:06 21.0 41.0 697 1032
16 2022.02.01 12:16:05 21.0 41.0 688 1032
17 2022.02.01 12:17:05 21.0 41.0 681 1032
18 2022.02.01 12:18:05 21.0 41.0 675 1032
19 2022.02.01 12:19:06 21.0 41.0 668 1032
Get available metrics in the Aranet Cloud. Usage:
get_metrics(aranet_conf, **kwargs) -> Dict[str, Any]:The output may be the following:
{'data': {'lang': 'en',
'currentItemCount': 6,
'items': [{'id': '1',
'name': 'Temperature',
'units': [{'id': '1',
'name': '°C',
'precision': 1,
'selected': True,
'default': True,
'overrides': [{'type': 2, 'variant': 10, 'precision': 2}]},
{'id': '102',
'name': 'K',
'precision': 1,
'overrides': [{'type': 2, 'variant': 10, 'precision': 2}]},
{'id': '101',
'name': '°F',
'precision': 1,
'overrides': [{'type': 2, 'variant': 10, 'precision': 2}]}]},
{'id': '2',
'name': 'Humidity',
'units': [{'id': '2',
'name': '%',
'precision': 1,
'selected': True,
'default': True}]},
{'id': '3',
'name': 'CO₂',
'units': [{'id': '3',
'name': 'ppm',
'precision': 0,
'selected': True,
'default': True}]},
{'id': '4',
'name': 'Atmospheric Pressure',
'units': [{'id': '104',
'name': 'hPa',
'precision': 0,
'selected': True,
'default': True},
{'id': '114', 'name': 'inHg', 'precision': 2},
{'id': '103', 'name': 'mmHg', 'precision': 1},
{'id': '105', 'name': 'bar', 'precision': 3},
{'id': '106', 'name': 'psi', 'precision': 2},
{'id': '117', 'name': 'atm', 'precision': 3},
{'id': '4', 'name': 'Pa', 'precision': 0}]},
{'id': '61',
'name': 'RSSI',
'units': [{'id': '11',
'name': 'dBm',
'precision': 0,
'selected': True,
'default': True}]},
{'id': '62',
'name': 'Battery voltage',
'units': [{'id': '132',
'name': '%',
'precision': 0,
'selected': True,
'default': True},
{'id': '16', 'name': 'V', 'precision': 2}]}]}}Get rules defined in the Aranet Cloud. Usage:
get_rules(aranet_conf, **kwargs) -> Dict[str, Any]:In the Aranet Cloud there is a low battery built-in rule, thus if no other rules are defines, the output of the function will be similar to the following:
{'data': {'lang': 'en',
'currentItemCount': 1,
'items': [{'id': '289',
'title': 'Low battery',
'selection': {'type': {'id': 'all', 'name': 'All sensors'}, 'sensors': 57},
'metric': {'id': '62'},
'state': {'id': '1', 'name': 'Enabled'},
'lastAction': '2022-03-03T11:47:53Z',
'notes': 'This is a built-in rule that controls sensor battery levels. Battery level thresholds depends on the sensor type. This rule cannot be deleted or copied.'}]}}Get gateways (base stations) registered into the Aranet Cloud. Usage:
get_gateways(aranet_conf, **kwargs) -> Dict[str, Any]:For example, with two gateways in the Aranet Cloud the output may be the following:
{'devices': [{'id': '123',
'device': 'Aranet-AAAAAA',
'serial': '111111111111',
'regdate': '2020-01-01T08:00:00Z',
'files': 0},
{'id': '456',
'device': 'Aranet-BBBBBB',
'serial': '222222222222',
'regdate': '2021-01-01T08:00:00Z',
'files': 0}]}This repository includes several exemplary scripts in the examples folder.
These are described below.
Queries the Aranet Cloud for the most recent data of the Aranet4 sensors and returns them in a JSON format. The script may be called in the following way:
$ PYTHONPATH="." python3 aranet.py | jqthen, considering two sensors with names "1.01", and "1.02", the output of the command may be the following:
{
"num_sensors": 2,
"1.01_time": 1644228737,
"1.01_temperature": 21.3,
"1.01_humidity": 45,
"1.01_CO2": 1289,
"1.01_pressure": 1030,
"1.01_RSSI": -96,
"1.01_battery": 56,
"1.02_time": 1644228711,
"1.02_temperature": 19.2,
"1.02_humidity": 50,
"1.02_CO2": 1136,
"1.02_pressure": 1030,
"1.02_RSSI": -89,
"1.02_battery": 50
}Queries the Aranet Cloud and returns the list of sensor IDs and names in CSV format. The script may be called in the following way:
$ PYTHONPATH="." python3 aranet_get_sensor_list.pyand the output may be the following:
id,name
4196648,1.01
4196666,1.02
Queries the Aranet Cloud and returns a list with the data of each sensor and the gateway to which each one is paired. Moreover, old pairings are also shown. The script may be called in the following way:
$ PYTHONPATH="." python3 aranet_get_gw_pairing.pythen, considering two sensors with names "1.01", and "1.02" and two base stations, the output of the command may be the following:
Found 2 paired sensors
name id pair_date gw_id gw_name gw_serial
0 1.01 4196648 2020-01-01T10:00:00Z 123 Aranet-AAAAAA 111111111111
1 1.02 4196666 2021-01-01T10:00:00Z 456 Aranet-BBBBBB 222222222222
Found 0 removed pairings
Creates Home Assistant configuration files to integrate the Aranet sensors by querying the Aranet Cloud.
This script creates the following files:
ha_aranet_cloud_main.yaml: Main configuration file. Creates anaranetsensor entity which stores all the sensor data as attributesha_aranet_cloud_templates.yaml: Templates configuration file. Creates a sensor entity for each Aranet sensor retrieving the corresponding attribute from thearanetentity.
Also, an additional configuration file of statistics sensors may be created with the --stats option.
Creates Home Assistant configuration files to integrate the Aranet sensors from the MQTT messages sent by the Aranet base stations.
This script by default creates the files ha_aranet_mqtt_main.yaml. Also, an additional configuration file of statistics sensors may be created with the --stats option.
This code is available as open source under the terms of the MIT License.
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