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import logging
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
import tensorflow as tf
import numpy as np
import pandas as pd
import argusPython as aw
print(f"Dataset Testing Start")
if __name__ == '__main__':
# load Argus baseline for matching
aw.argusInit()
# aw.setArgusBaseline("baseline.2024.01.25.out")
# print(f"Baseline done")
aw.readArgusData("argus.2024.01.09.out")
print(f"Argus Datafile done")
# load data
data = pd.read_csv('argus.2024.01.09.csv')
# define categorical vs continuous variables
categoricalNames = ['StartTime','SrcAddr','DstAddr','Proto','Sport','Dport']
notCat = [f for f in filter(lambda x: x not in categoricalNames, data.columns)]
# rearrange categorical columns to be first
data = data[categoricalNames+notCat]
print(f"Dataset Size: {data.shape[0]}")
dataList = str(data.columns.values.tolist()).strip('[]')
dataList = dataList.replace(" ","");
dataList = dataList.replace("'","");
aw.setArgusSchema(dataList)
print("dataList ",dataList)
print(data)
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