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How to Configure Levels and Outputs of Logging Module in Python

Proper logging is the backbone of monitoring and debugging Python applications. Unlike print() statements, the built-in logging module allows you to categorize messages by severity (Levels) and route them to different destinations (Outputs), such as the console, files, or external monitoring services.

This guide explains how to control verbosity using logging levels and how to configure handlers to direct logs to specific outputs.

Understanding Logging Levels​

The Python logging system uses a hierarchy of levels. When you set a logging level, you are telling the application to record events of that severity and higher.

LevelNumeric ValueDescription
DEBUG10Detailed info, mostly for diagnosing problems.
INFO20Confirmation that things are working as expected.
WARNING30(Default) Something unexpected happened, but the software is still working.
ERROR40A more serious problem; the software couldn't perform a function.
CRITICAL50A serious error indicating the program itself may be unable to continue.

Method 1: Basic Configuration (Console Output)​

By default, Python logs to the console (stderr). However, the default level is WARNING, meaning DEBUG and INFO messages are ignored unless configured otherwise.

Setting the Threshold​

Use logging.basicConfig() to set the minimum reporting level.

import logging

# ⛔️ Default Behavior: INFO messages are hidden
# logging.info("This will not print by default")

# ✅ Correct: Configure the level to capture INFO and above
logging.basicConfig(level=logging.INFO)

logging.debug("This is a debug message (Hidden, because DEBUG < INFO)")
logging.info("System startup complete.")
logging.warning("Disk space low.")
logging.error("Database connection failed.")

Output:

INFO:root:System startup complete.
WARNING:root:Disk space low.
ERROR:root:Database connection failed.
warning

logging.basicConfig() creates a default configuration. It must be called before any other logging commands. If you call logging.info(...) before basicConfig, the function will be ignored because a default handler has already been created.

Method 2: Writing Logs to a File​

To persist logs for later analysis, you can redirect output to a file using the filename parameter.

import logging

# ✅ Correct: Directs all logs to 'app.log'
# 'filemode="w"' overwrites the file each run. Use "a" (default) to append.
logging.basicConfig(
    filename='app.log', 
    filemode='w', 
    level=logging.DEBUG
)

logging.info("This message is written to the file, not the console.")
logging.error("An error occurred.")

Content of app.log:

INFO:root:This message is written to the file, not the console.
ERROR:root:An error occurred.

Method 3: Using Multiple Outputs (Handlers)​

In production applications, you often want INFO logs to go to the console and ERROR logs (or everything) to be saved to a file. To achieve this, you must attach specific Handlers to the logger.

Configuring Console and File Simultaneously​

You can define a list of handlers inside basicConfig.

import logging
import sys

# 1. Create Handlers
# FileHandler writes to a file
file_handler = logging.FileHandler('server.log')

# StreamHandler writes to the console (stdout)
console_handler = logging.StreamHandler(sys.stdout)

# 2. Configure Logging with both handlers
logging.basicConfig(
    level=logging.DEBUG, # Global minimum level
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[file_handler, console_handler]
)

# ✅ Correct: This prints to BOTH the console and 'server.log'
logging.info("Server started on port 8080")
logging.warning("High memory usage detected")

Output (Console):

2023-10-27 10:00:01,123 - INFO - Server started on port 8080
2023-10-27 10:00:01,124 - WARNING - High memory usage detected
note

You can even set different levels for different handlers (e.g., console_handler.setLevel(logging.WARNING) and file_handler.setLevel(logging.DEBUG)), allowing you to see only important errors on screen while saving detailed debugging info to disk.

Conclusion​

To manage logs effectively in Python:

  1. Use logging.basicConfig(level=...) to control verbosity.
  2. Use filename='...' to save logs for historical analysis.
  3. Use Handlers (FileHandler, StreamHandler) when you need to send logs to multiple destinations simultaneously or apply different formatting rules.

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