Logging module
Python’s standard-library module provides configurable facilities for creating, filtering, formatting, and routing application log records.
The Well-Grounded Python Developer: How the pros use Python and Flask
The logging module is Python's standard-library module for creating, filtering, formatting, and routing diagnostic log records.
- How it is used
- Replaces diagnostic print statements with configurable messages for monitoring application activity and investigating problems.
- How deep it goes
- Works through basic logger setup and application-level configuration, including severity filtering, formatting, and STDOUT routing.
- Examples
- Uses a logged exception, YAML configuration, and DEBUG messages from Flask routes.
- What you can do after
- Operate/configure it to retain diagnostic messages while filtering DEBUG output in production and restoring it for investigation.
Python How-To
The logging module is Python's standard-library module for recording application events through loggers, handlers, formatters, and severity levels.
- How it is used
- Records application events for immediate console feedback or later inspection in a file.
- How deep it goes
- Works through logger creation, file and stream handlers, severity filtering, and formatting; mentions other handler types without detailing them.
- Examples
- Uses a task-removal event, a saved log file, console warnings, level-filtered messages, and timestamped records.
- What you can do after
- Operate/configure it to route, filter, and format application records for console viewing and file storage.
The Art of Code
Python's logging module is a standard-library facility for creating, filtering, formatting, and routing log records.
- How it is used
- Supports production diagnostics by routing filtered, formatted records to destinations suited to persistence, aggregation, and monitoring.
- How deep it goes
- Explains destinations, formats, filtering, severity levels, and message quality, but does not detail Python configuration APIs.
- Examples
- Uses console printing, stack traces, vague messages, and contextual parsing errors to contrast weak and useful diagnostics.
- What you can do after
- Evaluate/understand when console output is insufficient and how contextual messages improve failure investigation.
ASP.NET Core in Action, 3e
A logging library provides APIs for recording and routing diagnostic and operational messages from an application.
- How it is used
- Supports ASP.NET Core monitoring and troubleshooting by recording events and routing diagnostic output.
- How deep it goes
- Explains the architecture, dependency-injection integration, ILogger records, verbosity, and logging providers.
- Examples
- Uses negative shopping-cart totals, exceptions, console output, files, and external services as logging examples.
- What you can do after
- Diagnose application errors by creating structured log messages and routing them to suitable destinations.
Read how ASP.NET Core in Action, 3e explains logging module →
Related concepts
- logging leveluses · A logging level is a severity or verbosity classification or setting that determines which log messages a logging system processes, emits, or retains.
- printalternative to · Print is a programming operation that writes a value or its textual representation to an output destination, often standard output.
- FileHandlerhas part · FileHandler is a Python logging handler class that writes log records to a file.
- standard librarypart of · A standard library is a collection of reusable modules, types, functions, APIs, and other facilities distributed with a programming language implementation or platform.
- Log4jincludes · Log4j is an Apache Java logging framework for recording, formatting, and routing application messages and events to configurable destinations and severity levels.
- Dockerused by · Docker is a platform and ecosystem for building, distributing, and running applications in containers.
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