Read .smet file as pd.Dataframe. quick and dirty solution to read timeseries from a .smet file as pd.Dataframe. Assumes that a 'timestamp' field is present in the .smet file. The function has not been tested on many files. Use on your own responsibility.

read_smet.py

import configparser
from io import StringIO

import pandas as pd

def read_smet(file):
    """
    Read a .smet file as pd.Dataframe

    Parameters
    ----------
    file : str or pathlike

    Returns
    -------
    pd.Dataframe

    """
    with open(file, 'r') as f:
        filestr = f.read()

        headerstr = f"[HEADER]{(filestr.split('[HEADER]'))[1].split('[DATA]')[0]}"
        header = configparser.ConfigParser()
        header.read_string(headerstr)
        header = dict(header['HEADER'])

        datastr = filestr.split('[DATA]')[-1]

        data = pd.read_csv(
            StringIO(datastr),
            sep='\s+',
            names=[c for c in header['fields'].split(' ')],
            parse_dates=['timestamp'],
            na_values=float(header['nodata'])
        )

    return data