import mcp3008
m = mcp3008.read_pct(0)
print("Maisture level: {:>5}".format(m))
PREVIOUS_LINE="\x1b[1F"
RED_BACK="\x1b[41;37m"
GREEN_BACK="\x1b[42;30m"
YELLOW_BACK="\x1b[43;30m"
RESET="\x1b[0m"
readings = []
delta = datetime.timedelta(minutes=10)
next_time = datetime.datetime.now()+delta
next_water = datetime.datetime.now()
#the main sensor reading and plotting loop
while True:
dt = datetime.datetime.now()
while dt < next_time:
n = mcp3008.read_pct(5)
if n>15 and n<85:
if len(readings) >= 1000:
del readings[0];
readings.append(n)
dt = datetime.datetime.now();
else:
# Take the average from the readings list to smooth the graph a little
m = round(((sum(readings)/float(len(readings)))),1)
readings = []
# write the data to plotly
stream.write({'x': datetime.datetime.now(), 'y': m})
if m < 25:
background = RED_BACK
elif m < 65:
background = YELLOW_BACK
PREVIOUS_LINE="\x1b[1F"
RED_BACK="\x1b[41;37m"
GREEN_BACK="\x1b[42;30m"
YELLOW_BACK="\x1b[43;30m"
RESET="\x1b[0m"
readings = []
delta = datetime.timedelta(minutes=10)
next_time = datetime.datetime.now()+delta
next_water = datetime.datetime.now()
#the main sensor reading and plotting loop
while True:
dt = datetime.datetime.now()
while dt < next_time:
n = 100-mcp3008.read_pct(5)
if n>15 and n<85:
if len(readings) >= 1000:
del readings[0];
readings.append(n)
dt = datetime.datetime.now();
else:
# Take the average from the readings list to smooth the graph a little
m = round(1.5*((sum(readings)/float(len(readings)))),1)
readings = []
# write the data to plotly
stream.write({'x': datetime.datetime.now(), 'y': m})
if m < 25:
background = RED_BACK
elif m < 65:
background = YELLOW_BACK
