Spark Logging Framework #

A lightweight, flexible logging system for Spark Social with multiple outputs and log levels.

Features #

• 6 log levels: verbose, debug, info, warning, error, fatal
• Console and file outputs
• Automatic stack traces
• Color-coded console logs
• File rotation

Basic Usage #

// Get a logger
final logger = GetIt.instance<LogService>().getLogger('MyFeature');

// Log at different levels
logger.v('Verbose message');
logger.d('Debug message');
logger.i('Info message');
logger.w('Warning message');
logger.e('Error message', error: exception, stackTrace: stackTrace);
logger.f('Fatal message');

Predefined Loggers #

final logService = GetIt.instance<LogService>();

// Use predefined loggers
logService.appLogger.i('Application message');
logService.networkLogger.d('Network operation');
logService.uiLogger.w('UI warning');

Configure Log Levels #

// Set minimum log level
LoggerFactory.setGlobalLogLevel(LogLevel.warning); // production
LoggerFactory.setGlobalLogLevel(LogLevel.debug);   // development

Log Levels #

• VERBOSE: Detailed debugging information
• DEBUG: Debugging information
• INFO: General application flow
• WARNING: Potential issues
• ERROR: Errors that impact functionality
• FATAL: Critical errors
• NOTHING: Special level to suppress logs