Hawklog December [953 Logs].zip 🎯 Trusted

# Main if __name__ == "__main__": zipfilename = 'HAWKLOG DECEMBER [953 LOGS].zip' log_data = read_log_file(zipfilename) visualize_log_levels(log_data) The feature developed around the "HAWKLOG DECEMBER [953 LOGS].zip" file would involve unzipping, parsing, analyzing, and visualizing the log data. The specifics would depend on the log file format and the requirements of the analysis. This example provides a basic framework to start with.

# Simple visualization example def visualize_log_levels(data): counts = data['log_level'].value_counts() plt.figure(figsize=(10, 6)) plt.bar(counts.index, counts.values) plt.title('Log Levels Distribution') plt.xlabel('Log Level') plt.ylabel('Count') plt.show() HAWKLOG DECEMBER [953 LOGS].zip

return data

# Unzip and read the log file def read_log_file(zipfilename): with zipfile.ZipFile(zipfilename, 'r') as z: z.extractall() # Main if __name__ == "__main__": zipfilename =

# Assuming the log file is named 'hawklog.txt' and is in a standard format logfile = 'hawklog.txt' data = pd.read_csv(logfile, sep='\t') # Adjust based on actual log format HAWKLOG DECEMBER [953 LOGS].zip

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