acrilog 1.1.3

acrilog is a Python library of providing multiprocessing idiom to us in multiprocessing environment

========
acrislog
========

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Multiprocessing logger
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.. contents:: Table of Contents
:depth: 2

Overview
========

**acrilog** is a python library encapsulating multiprocessing logging into practical use.

**acrilog** started as Acrisel's internal utility for programmers.

It included:
1. Time and size rotating handler.
#. Multiprocessing logging queue server

The library makes it easier to add logging in a multiprocessing environment where processes are split among multiple Python source codes.

We decided to contribute this library to Python community as a token of appreciation to
what this community enables us.

We hope that you will find this library useful and helpful as we find it.

If you have comments or insights, please don't hesitate to contact us at [e-mail]


TimedSizedRotatingHandler
=========================

Use TimedSizedRotatingHandler is combining TimedRotatingFileHandler with RotatingFileHandler.
Usage as handler with logging is as defined in Python's logging how-to

example
-------

.. code-block:: python

import logging

# create logger
logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)

# create console handler and set level to debug
ch = logging.TimedRotatingFileHandler()
ch.setLevel(logging.DEBUG)

# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# add formatter to ch
ch.setFormatter(formatter)

# add ch to logger
logger.addHandler(ch)

# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')

MpLogger and LevelBasedFormatter
================================

Multiprocessor logger using QueueListener and QueueHandler
It uses TimedSizedRotatingHandler as its logging handler

It also uses acris provided LevelBasedFormatter which facilitate message formats
based on record level. LevelBasedFormatter inherent from logging.Formatter and
can be used as such in customized logging handlers.

example
-------

Within main process
~~~~~~~~~~~~~~~~~~~

.. code-block:: python

import time
import random
import logging
from acris import MpLogger
import os
import multiprocessing as mp

def subproc(limit=1, logger_info=None):
logger=MpLogger.get_logger(logger_info, name="acrilog.subproc", )
for i in range(limit):
sleep_time=3/random.randint(1,10)
time.sleep(sleep_time)
logger.info("proc [%s]: %s/%s - sleep %4.4ssec" % (os.getpid(), i, limit, sleep_time))

level_formats={logging.DEBUG:"[ %(asctime)s ][ %(levelname)s ][ %(message)s ][ %(module)s.%(funcName)s(%(lineno)d) ]",
'default': "[ %(asctime)s ][ %(levelname)s ][ %(message)s ]",
}

mplogger=MpLogger(logging_level=logging.DEBUG, level_formats=level_formats, datefmt='%Y-%m-%d,%H:%M:%S.%f')
logger=mplogger.start(name='main_process')

logger.debug("starting sub processes")
procs=list()
for limit in [1, 1]:
proc=mp.Process(target=subproc, args=(limit, mplogger.logger_info(),))
procs.append(proc)
proc.start()

for proc in procs:
if proc:
proc.join()

logger.debug("sub processes completed")

mplogger.stop()


Example output
--------------

.. code-block:: python

[ 2016-12-19,11:39:44.953189 ][ DEBUG ][ starting sub processes ][ mplogger.<module>(45) ]
[ 2016-12-19,11:39:45.258794 ][ INFO ][ proc [932]: 0/1 - sleep 0.3sec ]
[ 2016-12-19,11:39:45.707914 ][ INFO ][ proc [931]: 0/1 - sleep 0.75sec ]
[ 2016-12-19,11:39:45.710487 ][ DEBUG ][ sub processes completed ][ mplogger.<module>(56) ]

Clarification of parameters
===========================

name
----

**name** identifies the base name for logger. Note the this parameter is available in both MpLogger init method and in its start method.

MpLogger init's **name** argument is used for consolidated logger when **consolidate** is set. It is also used for private logger of the main process, if one not provided when calling *start()* method.

proecess_key
------------

**process_key** defines one or more logger record field that would be part of the file name of the log. In case it is used, logger will have a file per records' process key. This will be in addition for a consolidated log, if **consolidate** is set.

By default, MpLogger uses **name** as the process key. If something else is provided, e.g., **processName**, it will be concatenated to **name** as postfix.

file_prefix and file_suffix
---------------------------

Allows to distinguish among sets of logs of different runs by setting one (or both) of **file_prefix** and **file_suffix**. Usually, the use of PID and granular datetime as prefix or suffix would create unique set of logs.

file_mode
---------

**file_mode** let program define how logs will be opened. In default, logs are open in append mode. Hense, history is collected and file a rolled overnight and by size.

consolidate
-----------

**consolidate**, when set, will create consolidated log from all processing logs.
If **consolidated** is set and *start()* is called without **name**, consolidation will be done into the main process.

kwargs
------

**kwargs** are named arguments that will passed to FileHandler. This include:
| file_mode='a', for RotatingFileHandler
| maxBytes=0, for RotatingFileHandler
| backupCount=0, for RotatingFileHandler and TimedRotatingFileHandler
| encoding='ascii', for RotatingFileHandler and TimedRotatingFileHandler
| delay=False, for TimedRotatingFileHandler
| when='h', for TimedRotatingFileHandler
| interval=1, TimedRotatingFileHandler
| utc=False, TimedRotatingFileHandler
| atTime=None, for TimedRotatingFileHandler


Change History
==============

0.9: added ability to pass logger_info to subprocess,
exposed encoding parameter,
1.0: replaced **force_global** with **consolidate** to genrerate consolidated log
add **name** argument to MpLogger.start(). This will return logger with that name for the main process.
MpLogger.__init__() **name** argument will be used for consolidated log.
1.1: add **file_prefix** and **file_suffix** as MpLogger parameters.

Next Steps
==========

1. Cluster support using TCP/IP
#. Logging monitor and alert