Fetch predicted renewable energy generation for Germany and find time of day where appliances would theoretically run with lowest environmental impact

energy.py

import datetime
import urllib.request
import json

weeknr = datetime.date.today().strftime("%V")
year = datetime.date.today().strftime("%Y")

url = "https://energy-charts.info/charts/power/data/de/week_"+year+"_"+weeknr+".json"
data = urllib.request.urlopen(url).read()
data = json.loads(data)
odata = []
max = [0,0]
for section in data:
    if 'xAxisValues' in section:
        for xv in section['xAxisValues']:
            odata.append([datetime.datetime.fromtimestamp(xv/1000)])
    if 'name' in section and 'data' in section and len(section['name']) > 0 and 'en' in section['name'][0] and section['name'][0]['en'] == 'Renewable Share forecast':
        i = 0
        for xv in section['data']:
            if xv is not None:
                odata[i].append(xv)
                if xv > max[1]:
                    max = [odata[i][0], xv]
            i = i + 1
            
print("Prefered load time: " + max[0].strftime("%Y-%m-%d_%H:%M") + " with " + str(max[1]) + "% Renewables")

This does not take in account load profiles (aka: is there any surplus or not) or CO² (aka: nuclear power)