A client for Gecko SPA system using in.touch. It used the GeckoLib from gazoodle to connect to your SPA and publishes the most relevant information on a broker. From there your home automation system can retrieve the values again.
So far the heater, water care, filter, the pumps and lights status as well as the reminders are published. The lights can also be controlled.
The script has been written and tested only on a Linux machine. No idea, if it also works on a Windows host. For sure the service installation needs to be adapted.
You need to have Python 3.8 or later installed with the libraries geckolib and asyncio-paho.
sudo apt install python3-pip # if not already installed
sudo pip3 install geckolib==0.4.8
sudo pip3 install asyncio-pahoThe installation is quiet simple by coping the files to a dedicated folder and configuring the client to run as a service. If you update from an older version, please stop the service before coping the files.
cp src/*.py /opt/geckoclientconfig.py
cp src/config.py_template /opt/geckoclient/config.pyIn order to connect to your SPA and broker, you need to configure the connection parameters below. You can use the in.touch APP to retrieve the SPA_NAME and SPA_IDENTIFIER. The identifier should be the MAC address with SPA as prefix. If the spa is not detected you can add the IP address. That can help to fix the issue. See example below.
Please use the UUID generator to create an unique ID for your client. That is important for have a good communication. See also comments from the developer of the geckolib on this topic under https://github.com/gazoodle/geckolib
# SPA values
SPA_NAME = "My Spa"
SPA_IDENTIFIER = "SPAxx:xx:xx:xx:x:xx" # Please use lowercase characters
SPA_IP_ADDRESS = "DHCP" # either the IP address or DHCP in case of dynamic assignment
# Replace with your own UUID, see https://www.uuidgenerator.net/>
CLIENT_ID = "123"
# BROKER values
BROKER_ADDRESS = "192.168.1.100"
BROKER_PORT = 1883
BROKER_USERNAME = "username"
BROKER_PASSWORD = "password"
BROKER_ID = "geckoclient"
# Topic
TOPIC = "whirlpool"
# Log file
LOGFILE = "/var/log/geckoclient.log"
# Debug settings
# level # can be one of the following strings
# 'CRITICAL','FATAL', 'ERROR', 'WARN', 'INFO', 'DEBUG', 'NOTSET'
DEBUG_LEVEL = 'DEBUG'
GECKOLIB_DEBUG_LEVEL = 'WARN'
# number of log files to keep
BACKUP_COUNT=5cp service/gecko.service /etc/systemd/systemsudo systemctl enable gecko.serviceTo start the service use
sudo systemctl start gecko.serviceTo stop the service use
sudo systemctl stop gecko.serviceTo check the status of the service use
sudo systemctl status gecko.serviceSince version 0.6.x the SPA is controlled by only one control topic %prefix%/control. The message has been transferred into a JSON string. The different items can be controlled as following
| Item | JSON String | Comment |
|---|---|---|
| Lights | {"lights":"off|on"} | |
| Temperature | {"temp":TEMP} | TEMP is in steps of 0.5 |
| Pumps | {"pump":"off|low|high","number":PUMPNUMBER} | Not all SPA support 'low' value |
| Blower | {"blower":"off|high"} | |
| Watercare | {"watercare":"MODE"} | See below for possible MODE values |
| Refresh All | {"refresh":"all"} |
Watercare mode is one of the values below (you can use either the integer or the string value):
The control topic and messages have been changed from version 0.6.0. From this version only one command topic %prefix%\control is used to control the SPA. And the message has been switched to JSON.
Without manipulating the geckolib, receiving changed values might take up to 2 minutes. I was not able to figure out why.
If you need quicker, e.g because you want to measure runtime of pumps, etc. you need to change the file async_facade.py. To do so, first find the file (in a standard Debian 11 with python3.9 is might be under /usr/local/lib/python3.9/dist-packages/geckolib/automation). Then add after line 78 the block (take care to use tabs or spaces depending on what the exiting file already uses):
if self._ready:
active_mode = TrueIt should now look like:
76 for device in self.all_config_change_devices:
77 if device.is_on: # type: ignore
78 active_mode = True
79 if self._ready:
80 active_mode = True
81 set_config_mode(active_mode)Now changes are reported immediately. Still there is a 2 minuted gap after the startup of the service.
If you suffer from high CPU usage you can change the yield value for asyncio sleep time. That will dramatically reduce the CPU usage.
To do so, change the value _ASYNCIO_SLEEP_TIMEOUT_FORYIELD in geckolib const.py in geckolib main folder (see above) from 0.001 to 0.02. The latter value works well for me.
CONNECTION_STEP_PAUSE_IN_SECONDS = 0 # Time between connection steps
MAX_RF_ERRORS_BEFORE_HALT = 50
ASYNCIO_SLEEP_TIMEOUT_FOR_YIELD = 0.02 # Changed from 0.001Licensed under the EUPL-1.2-or-later.
https://joinup.ec.europa.eu/collection/eupl/eupl-text-eupl-12