import pandas as pd

import configparser

from pathlib import Path

import os.path as op

from datetime import datetime, timedelta

import time

from uuid import uuid4

def process_codecarbon_file(filename, process_id, task_name, postal_code)-> pd.DataFrame:

"""

Read file and remove longitude and latitude from file.

"""

data = pd.read_csv(filename, sep=',', header=0)

data = data[['run_id', 'project_name','timestamp', 'duration', 'emissions',

'emissions_rate', 'cpu_power', 'gpu_power', 'ram_power', 'cpu_energy',

'gpu_energy', 'ram_energy', 'energy_consumed', 'country_name',

'country_iso_code', 'region', 'cloud_provider', 'cloud_region', 'os',

'python_version', 'codecarbon_version', 'cpu_count', 'cpu_model',

'gpu_count', 'gpu_model', 'ram_total_size',

'tracking_mode', 'on_cloud', 'longitude', 'latitude']]

data.columns = ['task_hash','task_name','start_time', 'duration', 'emissions',

'emissions_rate', 'cpu_power', 'gpu_power', 'ram_power', 'cpu_energy',

'gpu_energy', 'ram_energy', 'energy_consumed', 'country_name',

'country_iso_code', 'region', 'cloud_provider', 'cloud_region', 'os',

'python_version', 'codecarbon_version', 'cpu_count', 'cpu_model',

'gpu_count', 'gpu_model', 'ram_total_size',

'tracking_mode', 'on_cloud', 'longitude', 'latitude']

data['postal_code'] = postal_code

data['task_hash'] = process_id

data['task_name'] = task_name

return data