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import re
import pandas as pd
# Function to parse the log file
def parse_log_file(file_path):
with open(file_path, 'r') as file:
log_entries = file.readlines()
log_data = []
for entry in log_entries:
timestamp_match = re.match(r'(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})', entry)
if timestamp_match:
timestamp = timestamp_match.group(1)
log_level = re.search(r'- (\w+) -', entry)
url_match = re.search(r'HTTP Request: POST (.*?)"', entry)
status_code = re.search(r'"HTTP/1.1 (\d{3})', entry)
if log_level and url_match and status_code:
log_level = log_level.group(1)
url = url_match.group(1)
status_code = status_code.group(1)
if status_code == '429':
h1_tag = re.search(r'<h1>(\d+)</h1>', entry)
h1_error_code = h1_tag.group(1) if h1_tag else 'N/A'
log_data.append({
'Timestamp': timestamp,
'Log Level': log_level,
'URL': url,
'Status Code': status_code,
'H1 Error Code': h1_error_code
})
return pd.DataFrame(log_data)
# Parse the provided log file
file_path = 'paste.txt'
parsed_log_df = parse_log_file(file_path)
# Display the DataFrame
parsed_log_df
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