Transforming annotated csv (influxdb) to normal csv file using python script

I have a CSV file that was downloaded from InfluxDB UI. I want to extract useful data from the downloaded file. A snippet of the downloaded file is as follows:

#group	FALSE	FALSE	TRUE	TRUE	FALSE	FALSE	TRUE	TRUE	TRUE	TRUE	TRUE
#datatype	string	long	dateTime:RFC3339	dateTime:RFC3339	dateTime:RFC3339	double	string	string	string	string	string
#default	mean										
	result	table	_start	_stop	_time	_value	_field	_measurement	smart_module	serial	type
		0	2023-03-31T08:12:40.697076925Z	2023-03-31T09:12:40.697076925Z	2023-03-31T08:20:00Z	0	sm_alarm	system_test	8	2.14301E+11	sm_extended
		0	2023-03-31T08:12:40.697076925Z	2023-03-31T09:12:40.697076925Z	2023-03-31T08:40:00Z	0	sm_alarm	system_test	8	2.14301E+11	sm_extended
		0	2023-03-31T08:12:40.697076925Z	2023-03-31T09:12:40.697076925Z	2023-03-31T09:00:00Z	0	sm_alarm	system_test	8	2.14301E+11	sm_extended
		0	2023-03-31T08:12:40.697076925Z	2023-03-31T09:12:40.697076925Z	2023-03-31T09:12:40.697076925Z	0	sm_alarm	system_test	8	2.14301E+11	sm_extended

I'd like to have the output CSV as follows:

_time                   sm_alarm  next_column next_column ....... ...........
2023-03-29T08:41:15Z    0

Please note that sm_alarm is only one field among 9 others (that are under _filed).

I tried to do with the following script, but could not solve my problem.

import csv

# Specify the input and output file names
input_file = 'influx.csv'
output_file = 'output.csv'

try:
    # Open the input file for reading
    with open(input_file, 'r') as csv_file:
        # Create a CSV reader object
        csv_reader = csv.reader(csv_file)

        # Skip the first row (header)
        next(csv_reader)

        # Open the output file for writing
        with open(output_file, 'w', newline='') as output_csv:
            # Create a CSV writer object
            csv_writer = csv.writer(output_csv)

            # Write the header row
            csv_writer.writerow(['_time', '_field', '_value'])

            # Iterate over the input file and write the rows to the output file
            for row in csv_reader:
                # Check if the row is not empty
                if row:
                    # Split the fields
                    fields = row[0].split(',')

                    # Write the row to the output file
                    csv_writer.writerow(fields)

    print(f'{input_file} converted to {output_file} successfully!')

except FileNotFoundError:
    print(f'Error: File {input_file} not found.')

except Exception as e:
    print(f'Error: {e}')

Thank you.

The format of your expected output is ambiguous and not fully clear.
But as a starting point, you can straighten your file with read_csv from [tag:pandas] this way :

import pandas as pd
​
with open("influx.csv", "r") as csv_file:
    headers = csv_file.readlines()[3].strip().split()[1:]
    
df = pd.read_csv("influx.csv", header=None, skiprows=4, sep="\s+",
                 engine="python", names=headers).iloc[:, 1:]

#df.to_csv("output.csv", index=False, sep=",") # <- uncomment this line to make a real csv

Output :

print(df)

                           _start                           _stop                           _time  _value    _field _measurement  smart_module        serial         type
0  2023-03-31T08:12:40.697076925Z  2023-03-31T09:12:40.697076925Z            2023-03-31T08:20:00Z       0  sm_alarm  system_test             8  2.143010e+11  sm_extended
1  2023-03-31T08:12:40.697076925Z  2023-03-31T09:12:40.697076925Z            2023-03-31T08:40:00Z       0  sm_alarm  system_test             8  2.143010e+11  sm_extended
2  2023-03-31T08:12:40.697076925Z  2023-03-31T09:12:40.697076925Z            2023-03-31T09:00:00Z       0  sm_alarm  system_test             8  2.143010e+11  sm_extended
3  2023-03-31T08:12:40.697076925Z  2023-03-31T09:12:40.697076925Z  2023-03-31T09:12:40.697076925Z       0  sm_alarm  system_test             8  2.143010e+11  sm_extended

If you share a clear expected ouptut, I'll update my answer accordingly.