Logging in Python :

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November 30, 2024
Logging in Python
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Logging in Python lets you record important information about your program’s execution. You use the built-in logging module to capture logs, which provide insights into application flow, errors, and usage patterns. With Python logging, you can create and configure loggers, set log levels, and format log messages without installing additional packages. You can also generate log files to store records for later analysis.

Using a logging library instead of print() calls gives you better control over log management, formatting, and output destinations. The logging module also allows you to set severity levels, simplifying the management and filtering of log data.

By the end of this tutorial, you’ll understand that:

  • Logging in a computer involves recording program execution information for analysis.
  • You can use logging for debugging, performance analysis, and monitoring usage patterns.
  • No installation is needed for Python logging as the logging module is part of Python’s standard library.
  • Logging in Python works by configuring loggers and setting log levels.
  • Using a logging library provides structured logging and control over log output.
  • You should prefer logging over print() because it decreases the maintainance burden and allows you to manage log levels.
  • You can generate a log file in Python by setting filename and encoding through basicConfig().

You’ll do the coding for this tutorial in the Python standard REPL. If you prefer Python files, then you’ll find a full logging example as a script in the materials of this tutorial. You can download this script by clicking the link below:

Take the Quiz: Test your knowledge with our interactive “Logging in Python” quiz. You’ll receive a score upon completion to help you track your learning progress:

Logging in Python

Interactive Quiz

Logging in Python

In this quiz, you'll test your understanding of Python's logging module. With this knowledge, you'll be able to add logging to your applications, which can help you debug errors and analyze performance.

If you commonly use Python’s print() function to get information about the flow of your programs, then logging is the natural next step for you. This tutorial will guide you through creating your first logs and show you how to make logging grow with your projects.

Starting With Python’s Logging Module

The logging module in Python’s standard library is a ready-to-use, powerful module that’s designed to meet the needs of beginners as well as enterprise teams.

The main component of the logging module is something called the logger. You can think of the logger as a reporter in your code that decides what to record, at what level of detail, and where to store or send these records.

Exploring the Root Logger

To get a first impression of how the logging module and a logger work, open the Python standard REPL and enter the code below:

Python 
>>> import logging
>>> logging.warning("Remain calm!")
WARNING:root:Remain calm!

The output shows the severity level before each message along with root, which is the name the logging module gives to its default logger. This output shows the default format that can be configured to include things like a timestamp or other details.

In the example above, you’re sending a message on the root logger. The log level of the message is WARNING. Log levels are an important aspect of logging. By default, there are five standard levels indicating the severity of events. Each has a corresponding function that can be used to log events at that level of severity.

Here are the five default log levels, in order of increasing severity:

Log Level Function Description
DEBUG logging.debug() Provides detailed information that’s valuable to you as a developer.
INFO logging.info() Provides general information about what’s going on with your program.
WARNING logging.warning() Indicates that there’s something you should look into.
ERROR logging.error() Alerts you to an unexpected problem that’s occured in your program.
CRITICAL logging.critical() Tells you that a serious error has occurred and may have crashed your app.

The logging module provides you with a default logger that allows you to get started with logging without needing to do much configuration. However, the logging functions listed in the table above reveal a quirk that you may not expect:

Python 
>>> logging.debug("This is a debug message")

>>> logging.info("This is an info message")

>>> logging.warning("This is a warning message")
WARNING:root:This is a warning message

>>> logging.error("This is an error message")
ERROR:root:This is an error message

>>> logging.critical("This is a critical message")
CRITICAL:root:This is a critical message

Notice that the debug() and info() messages didn’t get logged. This is because, by default, the logging module logs the messages with a severity level of WARNING or above. You can change that by configuring the logging module to log events of all levels.

Adjusting the Log Level

To set up your basic logging configuration and adjust the log level, the logging module comes with a basicConfig() function. As a Python developer, this camel-cased function name may look unusual to you as it doesn’t follow the PEP 8 naming conventions:

Read the full article at https://realpython.com/python-logging/ »

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November 30, 2024 at 07:30PM
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