CPU Temperature on Pi

At first I wanted to do a two branch split for both Mac M1 and RaspberryPI ARM -- Quad core Cortex-A72 (ARM v8). However, it turns out that getting the CPU temp through CLI on a mac is extremely difficult and it was not worth the time and trouble.

I found plenty of free programs that do the same thing, and better. You can find the list here: apps.

What you can do is use powermetrics.

Mac

Install powermetrics

brew install powermetrics

Run powermetrics

sudo powermetrics -s cpu_power,gpu_power

Run powermetrics MacOS X

 sudo powermetrics --samplers smc |grep -i "CPU die temperature"

RaspberryPI

I was not surprised by the ease of how you can write a few lines of python code and have a working script capable of logging CPU temperature. We basically need only 1 command from shell, this means we can easily write the same script as bash:.sh. This command is: vcgencmd -- vc stands for VideoCore. gen stands for general. cmd for command.

🐍Get CPU temperature script:

import os
from datetime import datetime 
import time
 
def temperature_of_raspberry_pi():
    cpu_temp = os.popen("vcgencmd measure_temp").readline()
    return cpu_temp.replace("temp=", "")

now = datetime.now().strftime('%d-%m-%Y_%H:%M:%S')


def main():
	while True:
	    
	    print(datetime.now().strftime('%d/%m/%Y,%H:%M:%S'),",",temperature_of_raspberry_pi())
	    file = open('temp_'+now+'.log','a')
	    line = datetime.now().strftime('%d/%m/%Y,%H:%M:%S') + "," + temperature_of_raspberry_pi().replace("'C","")
	    file.write(line)
	    time.sleep(1)
    
if __name__=="__main__":
	main()

Ok, remember to: chmod 755 the python script before running it for a few minutes.

Output .log

12/09/2023,17:10:31,78.4
12/09/2023,17:10:32,78.8
12/09/2023,17:10:33,76.4
12/09/2023,17:10:34,77.4
12/09/2023,17:10:35,76.9
12/09/2023,17:10:36,75.9
12/09/2023,17:10:37,76.4
12/09/2023,17:10:38,75.4

Now we have the data, we only need to process it and to plot using pandas and matplotlib

🐍Plot temperature data script:

import os
import pandas as pd
import matplotlib.pyplot as plt

# Step 1: Identify the most recent log file in the directory
log_files = [f for f in os.listdir() if f.endswith('.log')]
log_files.sort()
latest_log_file = log_files[-1]  # The last file when sorted alphabetically

# Step 2: Read the data from the latest log file into a Pandas DataFrame
df = pd.read_csv(latest_log_file, header=None, names=['Date', 'Time', 'Temperature'])
df['Datetime'] = pd.to_datetime(df['Date'] + ' ' + df['Time'], format='%d/%m/%Y %H:%M:%S')
df.set_index('Datetime', inplace=True)

# Step 3: Plot the data using Pyplot
plt.figure(figsize=(10, 6))
plt.plot(df.index, df['Temperature'], label='Temperature')
plt.xlabel('Datetime')
plt.ylabel('Temperature (°C)')
plt.title('Temperature Over Time')
plt.legend()
plt.show()

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