Electric Power Meter Service written in Python with Adafruit.io logging

power-use-aggregrator.py

#!/usr/bin/env python3
## Download your adafruit.io json data and load it.
## UTC_HOURS_OFFSET - Set to match your local offset.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_json(ADAFRUITIO_JSON_DATAFILE)

# Change index to be usable by TimeGrouper().
df.set_index('created_at', inplace=True)

# Adjust for UTC Offset.
df.index = df.index - pd.DateOffset(hours=UTC_HOURS_OFFSET)

# Resample and interpolate data
df.resample('5T', closed='right').max().interpolate(method='linear').groupby(pd.TimeGrouper(freq='15Min'))['value'].agg({'value':{'use': lambda x: max(x) - min(x)}}).plot()

plt.show()

py-power.py

#!/usr/bin/env python3
## Requires:
# USB SDR dongle or equivalent.
# https://github.com/bemasher/rtlamr
# Adafruit.io account
# FILTERID = Your power meter's ID

import json

from subprocess import Popen, PIPE, CalledProcessError

from Adafruit_IO import *

aio = Client('ADAFRUITIO_KEY')

cmd=["rtlamr", "-format=json", "-quiet", "-filterid=FILTERID"]

with Popen(cmd, stdout=PIPE, bufsize=1, universal_newlines=True) as p:
    for line in p.stdout:
        data = json.loads(line)
        if isinstance(data, dict):
            if 'Message' in data:
                cur_kWh = data['Message']['Consumption']
                aio.send('ADAFRUITIO_FEEDID', cur_kWh * .01)

if p.returncode != 0:
    raise CalledProcessError(p.returncode, p.args)