69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
import requests
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import time
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import paho.mqtt.client as mqtt
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from db_connect import database_connect
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mqtt_broker = "localhost"
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mqtt_port = 1883
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publish_interval = 300 # Secondes om een aanvraag te doen
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api_endpoints = [
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{"url": "https://garden.inajar.nl/api/devices/", "topic": "goodgarden/devices"},
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{"url": "https://garden.inajar.nl/api/relative_humidity_events/", "topic": "goodgarden/relative_humidity"},
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{"url": "https://garden.inajar.nl/api/battery_voltage_events/", "topic": "goodgarden/battery_voltage"},
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{"url": "https://garden.inajar.nl/api/soil_electric_conductivity_events/", "topic": "goodgarden/soil_electric_conductivity"},
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{"url": "https://garden.inajar.nl/api/soil_relative_permittivity_events/", "topic": "goodgarden/soil_electric_permittivity"},
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{"url": "https://garden.inajar.nl/api/soil_temperature_events/", "topic": "goodgarden/soil_temperature"},
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{"url": "https://garden.inajar.nl/api/par_events/", "topic": "goodgarden/par_events"}
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]
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client = mqtt.Client()
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client.connect(mqtt_broker, mqtt_port, 60)
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client.loop_start()
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def publish_to_mqtt(topic, data):
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"""
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Publiceer de opgehaalde data naar een MQTT-topic.
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"""
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client.publish(topic, str(data))
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print(f"Data published to MQTT topic {topic}.")
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def fetch_and_publish_data():
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"""
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Haal data op van alle endpoints en publiceer naar MQTT.
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"""
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for endpoint in api_endpoints:
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url = endpoint["url"]
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mqtt_topic = endpoint["topic"]
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access_token = "33bb3b42452306c58ecedc3c86cfae28ba22329c"
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try:
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headers = {
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"Authorization": f"Token {access_token}"
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}
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response = requests.get(url, headers=headers)
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response.raise_for_status()
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data = response.json()
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print(f"Data from {url}:")
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print(data)
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# Publiceer naar MQTT voordat de data wordt geladen in de database
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publish_to_mqtt(mqtt_topic, data)
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# Hier kan je de data laden naar je database
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load_data(data)
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except requests.exceptions.RequestException as e:
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print(f"Error fetching data from {url}: {e}")
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def load_data(data):
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"""
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Implementeer de database logica hier.
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Deze functie moet mogelijk worden aangepast om te werken met verschillende datastructuren van verschillende endpoints.
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"""
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print("Data processing and loading logic goes here.")
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if __name__ == "__main__":
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while True:
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fetch_and_publish_data()
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print("Waiting for the next retrieval action...")
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time.sleep(publish_interval)
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client.loop_stop()
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