pixl-logger

Overview

This module provides a simple logging class, which appends to a text log file with bracket-delimited columns. You can define any number of columns you want, or use some of the built-in auto-populated columns. You can populate columns by name, or by using one of the shortcut methods described below.

Usage

Use npm to install the module:

	npm install pixl-logger

Then use require() to load it in your code:

	var Logger = require('pixl-logger');

To use the module, instantiate an object, and start logging:

	var columns = ['hires_epoch', 'date', 'hostname', 'component', 'category', 'code', 'msg', 'data'];
	var logger = new Logger( 'logs/debug.log', columns );
	logger.set('hostname', 'myserver.com');
	
	logger.print({
		category: 'debug',
		component: 'main',
		code: 1,
		msg: "Hello log!"
	});

This would append the following like to logs/debug.log:

	[1423462332.437][2015-02-08 22:12:12][myserver.com][main][debug][1][Hello log!][]

Some column names are special, and automatically populated (see below), but the rest are free-form. You can include any number of columns you like, and name them however you want.

All the log "columns" are basically just key/value pairs stored in an args property in the class, which don't have to be specified on every call to print(). Meaning, you can set some of them once, and only have to set them again when they change. Example:

	logger.set('component', 'main');
	logger.set('category', 'debug');
	
	logger.print({
		code: 1,
		msg: "Hello log!"
	});

You can also fetch arg values using get(). Pass in a key to fetch one arg, or omit to get the entire args object back.

Data Cleansing

In order to protect the log format and syntax, all column values are "cleansed" before being written. Specifically, any newlines are converted to single spaces, and the character sequence ][ is stripped (as it would corrupt the log column layout). All other characters are allowed. Example:

	logger.debug( 1, "This won't go well\n[Hi][There]\r\nGoodbye.\n" );

This would be logged as:

	[1423466726.159][2015-02-08 23:25:26][myserver.com][main][debug][1][This won't go well [HiThere]  Goodbye. ]

Shortcut Methods

The logger library provides the following three shortcut methods, which accept a list of common arguments instead of a hash:

debug

The debug() method is designed to assist with writing to a debug log. It automatically sets the category column to debug. It requires two arguments, which are values for the code (debug level) and msg columns, with the 3rd argument being an optional data object, if you want. Examples:

	logger.debug( 1, "Logged at debug level 1" );
	logger.debug( 2, "Logged at debug level 2", {some:"data"} );

An extra feature with the debug() call is that you can set a debugLevel arg on your class instance, and it'll only log entries if they have an equal or lower level (a.k.a. code). So imagine this setup:

	logger.set( 'debugLevel', 2 );
	
	logger.debug( 1, "Logged at debug level 1" );
	logger.debug( 2, "Logged at debug level 2" );
	logger.debug( 3, "This won't be logged at all!" );

In this case we set the debugLevel arg to 2, so only the first two calls will be logged. The third call, which is logged at a higher (more verbose) level than the debugLevel value, will be silently skipped.

error

The error() method is designed to assist with logging errors. It automatically sets the category column to error. It requires two arguments, which are values for the code and msg columns, with the 3rd argument being an optional data object, if you want. Example:

	logger.error( 1005, "An error of type 1005 occurred!" );

This would be equivalent to calling print() with the following:

	logger.print({
		category: 'error',
		code: 1005,
		msg: "An error of type 1005 occurred!"
	});

transaction

The transaction() method is designed to assist with logging transactions. A "transaction" is whatever action you define in your app as something you want logged, for audit or replay purposes. It automatically sets the category column to transaction. It requires two arguments, which are values for the code and msg columns, with the 3rd argument being an optional data object, if you want. Example:

	logger.transaction( "user_update", "User jhuckaby was updated", {username:"jhuckaby"} );

This would be equivalent to calling print() with the following:

	logger.print({
		category: 'transaction',
		code: "user_update",
		msg: "User jhuckaby was updated",
		data: {username:"jhuckaby"}
	});

Echo to Console

If you set the echo arg to any true value, the logger will echo all log entries to process.stdout, in addition to the log file. This is useful for running CLI scripts or your app in debug mode. Example:

	logger.set( 'echo', true );
	logger.debug( 1, "This will be logged and echoed to the console!" );

Last Line Logged

To grab the last line logged by the logger, pull the lastRow property off the class instance. It is the fully formatted line, including an EOL. Example:

	var line = logger.lastRow;

Special Column Names

Several column names are special, in that they are automatically populated, or have special behavior. Here they are:

epoch

Any column named epoch will automatically be populated with the current local server time, represented in integer Epoch seconds. Example:

	[1423433821]

hires_epoch

Any column named hires_epoch will automatically be populated with the current local server time, represented in high precision floating point Epoch seconds, with up to 3 digits after the decimal. Example:

	[1423433807.277]

date

Any column named date will automatically be populated with a human-friendly version of the current local server time, in YYYY-MM-DD HH:MI:SS format. Example:

	[2015-02-08 14:16:58]

pid

Any column named pid will automatically be populated with the current Process ID (PID), obtained by calling process.pid once at startup. Example:

	[13702]

data

The data column is special, in that if it contains an object, it will be serialized to JSON. Example:

	[{"code":0,"description":"Success"}]

category

The category column is only special in that the shortcut methods debug(), error() and transaction() automatically populate it to match their names.

Rotating Logs

To rotate a log file, call the rotate() method, passing in a destination filesystem path and a callback. This will atomically move the file to the destination directory/filename, attempting a rename, and falling back to a "copy to temp file + rename" strategy. Example:

	logger.rotate( '/logs/pickup/myapp.log', function(err) {
		if (err) throw err;
	} );

If you omit a filename on the destination path and leave a trailing slash, the source log filename will be appended to it.

You can actually rotate any log file you want by specifying three arguments, with the custom source log file path as the first argument. Example:

	logger.rotate( '/path/to/logfile.log', '/logs/pickup/otherapp.log', function(err) {
		if (err) throw err;
	} );

Archiving Logs

You can also "archive" logs using the archive() method. Archiving differs from rotation in that the log file is atomically copied to a custom location which may contain date/time directories (all auto-created as needed), and then the file is compressed using gzip. You can archive any number of logs at once by using filesystem glob syntax. Example:

	var src_spec = '/logs/myapp/*.log';
	var dest_path = '/archives/myapp/[yyyy]/[mm]/[dd]/[filename]-[hh].log.gz';
	var epoch = ((new Date()).getTime() / 1000) - 1800; // 30 minutes ago
	
	logger.archive( src_spec, dest_path, epoch, function(err) {
		if (err) throw err;
	} );

This example would find all the log files found in the /logs/myapp/ directory that end in .log, and archive them to destination directory /archives/myapp/[yyyy]/[mm]/[dd]/, with a destination filename pattern of [filename]-[hh].log.gz. All the bracket-delimited placeholders are expanded using the timestamp provided in the epoch variable. The special [filename] placeholder expands to the source log filename, sans extension. All directories are created as needed.

License

The MIT License

Copyright (c) 2015 Joseph Huckaby

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.