adapted-logger 1.0.4

adapted_logger is a lib based on Python logging module, permetting injection of new data on logsand redirection to different target

A helper log library based on default logging module permetting a custom format of logs to be redirected to Logstash - Elasticsearch - Kibana.

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Custom usage:

HOW TO INSTALL

• Install adapted_logger using easy_setup or pip:

  pip install adapted_logger

HOW TO USE:

from logger.adapted_logger import AdaptedLogger
logger = AdaptedLogger("project_name", "127.0.0.1") # specify project_name and ip address of current server
log = logger.get_logger()
log.info("This is an info message")
log.debug("This is a debug message")
log.warn("This is a warning message")
log.error("This is an error message")

RESULTS:

2015-10-27 17:06:50,176 project_name INFO 127.0.0.1 This is an info message
2015-10-27 17:06:55,552 project_name DEBUG 127.0.0.1 This is a debug message
2015-10-27 17:07:00,863 project_name WARNING 127.0.0.1 This is a warning message
2015-10-27 17:07:05,360 project_name ERROR 127.0.0.1 This is an error message

Redirect logs to console:

Instantiate AdaptedLogger object:

adapted_log = AdaptedLogger("retail_crm_server", "127.0.0.1")

Redirect logs to console (Default behavior):

adapted_log.redirect_to_console()

Get logger object:

logger = adapted_log.get_logger()
logger.debug("Testing Debug Message")
logger.info("Testing Info Message")
logger.warn("Testing Warn Message")
logger.error("Testing Error Message")

Redirect logs to file:

Instantiate AdaptedLogger object:

adapted_log = AdaptedLogger("retail_crm_server", "127.0.0.1")

Redirect logs to file:

adapted_log.redirect_to_file("/path/logfile.log")

Get logger object:

logger = adapted_log.get_logger()
logger.debug("Testing Debug Message")
logger.info("Testing Info Message")
logger.warn("Testing Warn Message")
logger.error("Testing Error Message")

Custom adapter

This adds the possibility to configure your logger within a config file like config.yml, inside /config folder you should specify your configuration in YAML format.

formatters:

simpleFormater:
    format: '%(asctime)s    %(name)s    %(levelname)s    %(message)s'
    datefmt: '%Y/%m/%d %H:%M:%S's

Here we specify time, package name, level name, and the message, right now there is no injection of the ip address

handlers

console:
    class: logging.StreamHandler
    formatter: simpleFormater
    level: DEBUG
    stream: ext://sys.stdout
file:
    class : logging.FileHandler
    formatter: simpleFormater
    level: WARNING
    filename: filename_or_path.log

Here we specify handlers, in this exemple we use 2 handlers : console and file.

loggers:

clogger:
    level: DEBUG
    handlers: [console]
flogger:
    level: WARNING
    handlers: [file]

And finally we create 2 loggers for console and file handlers.

To inject ip address into context, we have created CustomAdapter class that create an adapter and inject ip in the process.

Usage

logging_config = yaml.load(open('config/config.yml', 'r'))
dictConfig(logging_config)

logger_1 = logging.getLogger("project_name.application_name1")
logger_1 = CustomAdapter(logger_1, {'ip': ip})

logger_2 = logging.getLogger("project_name.application_name2")
logger_2 = CustomAdapter(logger_2, {'ip': ip})

Right now, we can call

logger_1.warning('This is a warning Message')
logger_2.error('This is an error message)