sl4p 1.4.0

Simple logger for python. Easy configuration and Multiprocess supported.

SL4P : simplest logging for your python

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sl4p is a logging library that makes it easy to introduce more production-focused logging into your python applications.
sl4p users need not know anything about the slightly complex built-in python logging, although sl4p uses built-in Python's logging internally.
Quite simply, you can start logging right in any code with the three lines below.

from sl4p import *

log = sl4p.getLogger(__file__)
log.info("Hello Sl4p logger !")

Then, a log file with the contents below will be created in the folder ./sl4p_logs in the same location as your code.

INFO   | 2023.03.22-17:19:13 - embedding.py (  86) :: OPERATING TIMEZONE: +9:00
INFO   | 2023.03.22-17:19:13 - embedding.py (  87) :: Program  @c8abb11e  started.  <<ex1.py>>
DEBUG  | 2023.03.22-17:19:13 - embedding.py (  88) ::          @@-- argv[0] = C:\path\to\your\python\app.py
INFO   | 2023.03.22-17:19:13 - ex1.py   (   4) :: Hello Sl4p logger !
INFO   | 2023.03.22-17:19:13 - embedding.py ( 105) :: Program  c8abb11e  finished  <<ex1.py>>  -----  Elapsed    0.0010 s

Don't waste your time learning logging. Just enjoy this!

Main Features

Here are the main features that are very easy to use:

Basic

• Logging that can be used right away with little to no setup required (by default config)
• ConfigFile: Single/multi-application logger settings by JSON files and python dictionary
• Auto purging: log files can be divided and recorded by specified time period or filesize, and old ones can be automatically deleted.
• Snippet log: Logging to separate files for specific modules or subset of your Python program package
• Logging in multi-threaded/multi-process (internally, without IPC, with recording to a same file)
• Log of program context info: Timezone info, program execution path, total program run time, etc.

Utils & Advanced

• SimpleTimer: a stopwatch logging utility that supports start and multiple checks
• @sl4p_time() records the time taken for function execution (optional user tag)
• @sl4p_try, @sl4p_try_exit automatically log traceback using Try~Except statements
• Profiling: record CPU and memory usage as a separate CSV file during program life
• ExceptionHook: Register your function to execute in the event of an abnormal program termination

Installation

The 'sl4p' package can be easily installed using pip.

$ pip install sl4p

Or download the appropriate .whl file for your Python version from the 'dist' folder on GitHub.

$ pip install sl4p-{pkg_ver}-{py_ver}-none-any.whl

Configuration (Single App)

Sl4p has key concepts of 'configuration' and 'logging'.
Configuration decides sl4p logger's behavior including logging level, message format, logfile savedir and so on.
You can use Python dictionary or .cfg Yaml file to configuring as you want.

The following table describes the available keys and their corresponding values (default values indicated with an asterisk):

# Configured example
{
    "__configver__": "C4",  # For .cfg Yaml file, you must specify __configver__ 

    "LOG": {
        "use_console_print": true,
        "console_level": "WARNING",
        
        "logging_level": "DEBUG",
        "logging_format": "basic",

        "logfile_savedir": "logs",
        "logfile_name": "EXAMPLE_1",
    }
}

Key	Description	Available value (*default)
use_console_print	Whether to print log messages to the console.	Bool (*) True, False
console_level	The minimum level of logs to be printed in console. Logs below this level will not be printed.	(*) "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"
console_format	The level of detail to include in the log message in console.	"simple", (*) "basic", "detail", "adap"
logging_level	The minimum level of logs to be recorded. Logs below this level will not be recorded.	(*) "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"
logging_format	The level of detail to include in the log message in file.	"simple", (*) "basic", "detail", "adap"
logfile_savedir	The absolute path to the directory where log files will be saved. The path should be in either Windows or Linux format.	String : The OS-specific folder path windows ex) "E:\\Workspace\\sl4p_logs\\app-abc" linux ex) "/opt/my_appvar/data/sl4p_logs/app_abc"
logfile_name	The prefix of the log file name for your application. Sl4p will use this prefix to identify and purge old log files.	String : OS-supported filename. ex) "LOG.your_app_name"
There are many other options, see examples on Github.

Make logging

1. Load your configuration

It is important to load your configuration before using your application. I recommend placing this loading config phase at the beginning of your application's main function. Please note that this loading phase only needs to be executed once for the entire application package.

When loading your configuration, you can pass your config (dict or Yaml file's path) as second parameter of getLogger(). Additionally, you can use the optional parameter debugprt=True to display sl4p's initialization info.

Here are three ways to load your configuration:

A. 'get-logger' style loading

log = sl4p.getLogger(__file__, cfg="./applog.cfg", debugprt=True)  #debugprt param is optional!
log.info("hello sl4p!")

B. 'with-block' style loading

with sl4p(__file__, cfg=logcfg_dict) as log:
    log.info("hello sl4p!")
    log.error("Error occured! #%d" % (400))
    # log.error("Error occured! ", 400)  --> Not support this 'print()' style, Please formatting.

C. How to load logger in Jupyter
__file__, the first argument of getLogger, is used as an identifier in Snippet logging.
Instead, enter any string in Jupyter.

log = sl4p.getLogger('jupyter', cfg=logcfg_dict) as log:
log.info('Hello sl4p in jupyter!')

2. Write a log message

After loading your configuration, you can log messages anywhere in your application, even in another file, without passing the second parameter into getLogger.
Here are two ways to use logging:

A. 'get-logger' style logging

log = sl4p.getLogger(__file__)
log.debug("Just pass only __file__")

B. 'with-block' style logging

with sl4p(__file__) as log:
    log.warning("warn msg! : you should not pass 2nd parameter to sl4p() after configuration completed")

That's it! Enjoy logging your application :)
Remember to load your configuration only once and log your messages everywhere.

Utils & Advanced

The 'with-block' logging feature can measure elapsed time as DEBUG log and can also include a custom tag using ##TAG_NAME##.
Here is an example:

import time
with sl4p(__file__, tag='myTag') as log:
    time.sleep(1.0)
    log.info('with-block time measuring and tagging feature!')

This is the output log:

DEBUG  | 2019.11.14-22:03:43 - example2.py #myTag @adfd08e4 started
INFO   | 2019.11.14-22:03:44 - with-block time measuring and tagging feature!
DEBUG  | 2019.11.14-22:03:44 - example2.py #myTag @adfd08e4 finished  ----  Elapsed    1.0001 s

Decorator - @sl4p_time(tag={TAG_NAME})
You can also use the @l4p_time(tag={TAG_NAME}) decorator to measure the execution time of a function and log it with DEBUG level:

@sl4p_time()  # Although you do not use tagging, l4p_time decorator must be written with () brackets.
def my_function1():
    time.sleep(1.5)
    log.error('not yet...')

This is the output log:

DEBUG  | 2019.11.14-22:12:43 - example3.py f`my_function1() @19f19de9 started
ERROR  | 2019.11.14-22:12:44 - not yet...
DEBUG  | 2019.11.14-22:12:44 - example3.py f`my_function1 @19f19de9 finished  ----  Elapsed    1.5038 s

Decorator - @sl4p_try, @sl4p_try_exit
you can use the @sl4p_try and @sl4p_try_exit decorator to try-except your function and log the traceback of the exception.

@sl4p_try
def take_exception():
    a = 'ABCD' + None

This is the output log:

ERROR  | 2019.11.14-22:12:44 - can only concatenate str (not "NoneType") to str
Traceback (most recent call last):
  File "D:\Devel_Workspace\py27_9\devel_logger\sl4p\decorators.py", line 21, in wrapped
    return func(*args, **kwargs)
  File "D:/Devel_Workspace/py27_9/devel_logger/example3.py", line 15, in take_exception
    a = 'ABCD' + None
TypeError: can only concatenate str (not "NoneType") to str

Rememter @sl4p_try will continue the program when excepted. But @sl4p_try_exit will terminate it.

About

Dependencies

• json
• psutil
• pywin32 (only in windows)

License

BSD 3

Getting Help / Discussion / Contributing

Right here, please be active in this GitHub repository.
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.

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Release Note

(*) ver 1.4.0 :: Layered apps-config, Support console level&format, IndLogger, Enhance stability
ver 1.3.3linux :: excluding 'psutil' in requires for linux
ver 1.3.3 :: override_dict bugfix (support python 3.9+)
ver 1.3.2 :: Add log_level for SimpleTimer: logger.create_simpleTimer(), config bugfix
ver 1.3.1 :: Add log_level for @sl4p_time decorator
ver 1.2.0 :: Add stopwatch(SimpleTimer), Profiling stats(CPU & MEM), Recording TimeZone
ver 1.0.1 :: Supports multi-byte msg, update config and constants / Patch debugprt, start_ts
ver 1.0.0 :: First deployed release version