Adding JSON-Formatted Log Files

In addition to plain text log files, you can also log information in JSON format. JSON-formatted logs offer several advantages, including:

• Structured Data: JSON provides a structured format that is easier to parse and analyze using tools like Elasticsearch or Kibana.
• Machine Readability: JSON is machine-readable, making it suitable for automated processing and analysis.
• Flexibility: JSON can represent a wide range of data types and structures.

Creating a JSON Formatter

Import the JSON Formatter:

Python

import logging.json

Create a JSON Formatter:

Python

json_formatter = logging.json.JSONFormatter(
‘%(asctime)s %(name)s %(levelname)s %(message)s’,
ensure_ascii=False
)

This creates a JSON formatter that includes the timestamp, logger name, log level, and message in the JSON output. The ensure_ascii parameter ensures that non-ASCII characters are properly encoded.

Adding the JSON Formatter to a Handler

Create a File Handler:

Python

file_handler = logging.FileHandler(‘app.json’)

Set the Formatter:

Python

file_handler.setFormatter(json_formatter)

Add the Handler to the Logger:

Python

logger.addHandler(file_handler)

Logging JSON Objects

To log JSON objects directly, use the json.dumps function:

Python

import json

data = {"message": "This is a JSON object"}
logger.info(json.dumps(data))

Additional Considerations

• Logging Level: Adjust the logging level for the file handler to control which messages are written to the log file.
• Log Rotation: Consider using rotating file handlers to manage log file size.
• Log Analysis Tools: Use tools like Elasticsearch or Kibana to analyze JSON-formatted logs.