Making Python loggers output all messages to stdout in addition to log file

Making sense of log levels and handlers

Logging isn't just tracing breadcrumbs left by hidden bugs. It's an observational tool, used for monitoring your program's health and performance. That's where log levels like DEBUG, INFO, WARNING, ERROR, and CRITICAL pitch in. stdout and file logs with a consistent format brings clarity when analyzing logs.

Also, remember, the root logger affects all loggers in your application by default. If specificity is your thing, define different log levels or formats for stdout and file handlers.

Release resources after you're done using handlers. The logging module usually does that for you, but it's nice to do your own housekeeping.

Enhancing your logging game

If the basic setup's too vanilla for you, take the logging.config.dictConfig route. Trust me, it's an adventure:

• Tune your output by customizing formatters or using different handler subclasses.
• Use custom filter classes to roleplay as gatekeepers of your logs - only let through the important stuff!

It might seem like a lot, but the Python logging cookbook is the mentor we all need - always there, always helpful.

Going beyond mere simplicity

Sometimes, the basic configuration doesn’t cut it. This is when logging.config.dictConfig rides to the rescue! It's perfect for controlling complex configurations without breaking a sweat.

import logging.config
import yaml

# Serialize your logging configuration or load it from a YAML or JSON file 
logging_config = """
version: 1
formatters:
  simple:
    format: '%(asctime)s - %(levelname)s - %(message)s'
handlers:
  console:
    class: logging.StreamHandler
    level: DEBUG
    formatter: simple
    stream: ext://sys.stdout
  file:
    class: logging.FileHandler
    level: INFO
    formatter: simple
    filename: 'complex_logfile.log'
loggers:
  '':
    level: DEBUG
    handlers: [console, file]
"""

# Parsers assemble!
config = yaml.safe_load(logging_config)
logging.config.dictConfig(config)

# Keep on logging in the free world!
logging.debug('This is a debug message')


Sure, it's a bit more work compared to basicConfig, but look at that flexibility and control. It's like controlling the Matrix of logging.

Considering practical scenarios

In real-world scenarios, dealing with multiple loggers and broadcasting on different channels can be a bother. Setting up unique log levels for console and file handlers comes in handy in such cases.

Introducing error handling around file operations in your logging setup can save you hours of debugging. For wide application coverage, singleton instances or a shared logger could be handy.

Lastly, while the standard Python logging library is a force to reckon with, third-party libraries such as Loguru offer a simpler interface which could be well-suited in projects where ease of use trumps highly detailed configuration.