Dragon2fly / logger_tt

Logging makes simple. Log even the exception that you forgot to catch. Log messages from your print(msg). Support multiprocessing logging too.

Logger_tt

Make configuring logging simpler and log even exceptions that you forgot to catch.
Even multiprocessing logging becomes a breeze.

Table of contents

• Install

• Overview

• Usage

  • Overwrite the default log path
  • Provide your config file
  • Capture stdout
  • Exception logging
  • try-except exception logging
  • Silent unwanted loggers
  • Logging in multiprocessing
  • Temporary disable logging
  • Limit traceback line length
  • Analyze raise exception line
  • StreamHandler with buffer
  • TelegramHandler

• Sample config

  • YAML format
  • JSON format

• Changelog

Install

• From PYPI: pip install logger_tt
• From Github: clone or download this repo then python setup.py install

Overview:

In the most simple case, add the following code into your main python script of your project:

from logger_tt import setup_logging    

setup_logging(full_context=1)

Then from any of your modules, you just need to get a logger and start logging. There are two ways that you could obtain a logger.

• Conventional way: as you have always done it that way

  from logging import getLogger
  
  logger = getLogger(__name__)

• Convenient way: use a pre-made logger named logger_tt from this package.

  from logger_tt import logger

After that, you start logging as usual:

logger.debug('Module is initialized')
logger.info('Making connection ...')

# output
[2020-07-21 11:24:19] [__main__:5 DEBUG] Module is initialized
[2020-07-21 11:24:19] [__main__:6 INFO] Making connection ...

Both ways give you the same output except the line number, obviously.
The pre-made logger also has an advantage that it will automatically inject threadName and processName to the output in case of multithreading or multiprocessing.

Both ways will provide your project with the following default log behaviors:

• log file: Assume that your working directory is project_root, log.txt is stored at your project_root/logs/ folder.
  If the log path doesn't exist, it will be created.
  The log file is time rotated at midnight. A maximum of 15 dates of logs will be kept. This log file's level is DEBUG.
  The log format is [%(asctime)s] [%(name)s:%(lineno)d %(levelname)s] %(message)s,
  where the time format is %Y-%m-%d %H:%M:%S.
  Example: [2020-05-09 00:31:33] [myproject.mymodule:26 DEBUG] Module is initialized

• console: log records with level INFO and above will be printed to stdout of the console.
  The format for console log is simpler: [%(asctime)s] %(levelname)s: %(message)s.
  Example: [2020-05-09 00:31:34] INFO: Making connection ...

• urllib3 logger: this ready-made logger is to silent unwanted messages from requests library.

• suppressed logger: exchangelib. This sets logging level of exchangelib logger to WARNING.
  This is another way to silent unwanted messages from other module, read below for details.

• root logger: if there is no logger initialized in your module, this logger will be used with the above behaviors. This logger is also used to log uncaught exception in your project. Example:

  raise RecursionError

  # log.txt
  [2020-05-31 19:16:01] [root ERROR] Uncaught exception
  Traceback (most recent call last):
    File "D:/MyProject/Echelon/eyes.py", line 13, in <module>
      raise RecursionError
      => var_in = Customer(name='John', member_id=123456)
      => arg = (456, 789)
      => kwargs = {'my_kw': 'hello', 'another_kw': 'world'}
  RecursionError

• context logging: When an exception occur, variables used in the line of error are also logged.
  To log full local variables of current function scope, pass full_context=1 to setup_logging.
  If you need the outer scope too, set full_context to 2, 3 and so on...

Usage:

All configs are done through setup_logging function:

setup_logging(config_path="", log_path="", 
              capture_print=False, strict=False, guess_level=False,
              full_context=False,
              suppress_level_below=logging.WARNING,
              use_multiprocessing=False,
              limit_line_length=1000, 
              analyze_raise_statement=False,
              host="",
              port=0,
              )

This function also return a LogConfig object. Except config_path, log_path, use_multiprocessing, host and port, other parameters are attributes of this object and can be changed on the fly.

Except config_path, log_path, all other parameters can be defined in logger_tt section in the config file (see Sample config chapter below). Parameter with the same name passed in setup_logging function will override the one in the config file.

1. Overwrite the default log path:

Instead of ./logs/logs.txt, you can overwrite with your own as follows

setup_logging(log_path='new/path/to/your_log.txt')

If you have multiple handlers and want each of them log to different destinations, you can pass in a dict of "handler_name": "log_path". The handler names must match what is defined in the config file.

setup_logging(log_path={'error_file_handler': 'log/error.txt',
                        'info_file_handler': 'log/info_and_above.txt',
                        }
              )

2. Provide your config file:

You can config your own logger and handler by providing either yaml or json config file as follows:

setup_logging(config_path='path/to/.yaml_or_.json')

Without providing a config file, the default config file with the above default log behavior is used. You could copy log_conf.yaml or log_conf.json shipped with this package to start making your version.

Warning: To process .yaml config file, you either need pyyaml or ruamel.yaml package installed.

3. Capture stdout:

If you have an old code base with a lot of print(msg) or sys.stdout.write(msg) and don't have access or time to refactor them into something like logger.info(msg), you can capture these msg and log them to file, too.

To capture only msg that is printed out by print(msg), simply do as follows:

setup_logging(capture_print=True)

Example:

print('To be or not to be')
sys.stdout.write('That is the question')

# log.txt
[2020-05-09 11:42:08] [PrintCapture INFO] To be or not to be

---

Yes, That is the question is not captured. Some libraries may directly use sys.stdout.write to draw on the screen (eg. progress bar) or do something quirk. This kind of information is usually not useful for users. But when you do need it, you can capture it as follows:

setup_logging(capture_print=True, strict=True)

Example:

sys.stdout.write('The plane VJ-723 has been delayed')
sys.stdout.write('New departure time has not been scheduled')

# log.txt
[2020-05-09 11:42:08] [PrintCapture INFO] The plane VJ-723 has been delayed
[2020-05-09 11:42:08] [PrintCapture INFO] New departure time has not been scheduled

---

As you have seen, the log level of the captured message is INFO . What if the code base prints something like An error has occurred. Abort operation. and you want to log it as Error? Just add guess_level=True to setup_logging().

setup_logging(capture_print=True, guess_level=True)

Example:

print('An error has occurred. Abort operation.')
print('A critical error has occurred during making request to database')

# log.txt
[2020-05-09 11:42:08] [PrintCapture ERROR] An error has occurred. Abort operation.
[2020-05-09 11:42:08] [PrintCapture CRITICAL] A critical error has occurred during making request to database

Note: Capturing stdout ignores messages of blank line. That means messages like \n\n or (spaces) will not appear in the log. But messages that contain blank line(s) and other characters will be fully logged. For example, \nTo day is a beautiful day\n will be logged as is.

4. Exception logging:

Consider the following error code snippet:

API_KEY = "asdjhfbhbsdf82340hsdf09u3ionf98230234ilsfd"
TIMEOUT = 60

class MyProfile:
    def __init__(self, name):
        self.my_boss = None
        self.name = name

def my_faulty_func(my_var, *args, **kwargs):
    new_var = 'local scope variable'
    me = MyProfile('John Wick')
    boss = MyProfile('Winston')
    me.my_boss = boss
    print(f'Information: {var} and {me.my_boss.name}' 
           ' at {me.my_boss.location} with {API_KEY}')

if __name__ == '__main__':
    cpu_no = 4
    max_concurrent_processes = 3
    my_faulty_func(max_concurrent_processes, 'ryzen 7', freq=3.4)

In our hypothetical code above,print function will raise an exception. This exception, by default, will not only be logged but also analyzed with objects that appeared in the line:

[2020-06-06 09:36:01] ERROR: Uncaught exception:
Traceback (most recent call last):
  File "D:/MyProject/AutoBanking/main.py", line 31, in <module>
    my_faulty_func(max_concurrent_processes, 'ryzen 7', freq=3.4)
     |-> my_faulty_func = <function my_faulty_func at 0x0000023770C6A288>
     |-> max_concurrent_processes = 3

  File "D:/MyProject/AutoBanking/main.py", line 25, in my_faulty_func
    print(f'Information: {var} and {me.my_boss.name}'
           ' at {me.my_boss.location} with {API_KEY}')
     |-> me.my_boss.name = 'Winston'
     |-> me.my_boss.location = '!!! Not Exists'
     |-> (outer) API_KEY = 'asdjhfbhbsdf82340hsdf09u3ionf98230234ilsfd'
NameError: name 'var' is not defined

Note: look at the print(f'Information... line, logger-tt print this error line different from normal python traceback! With normal traceback, multi-line python statement has its only first line printed out. With logger-tt, a full statement is grabbed for you.

For each level in the stack, any object that appears in the error line is shown with its readable representation. This representation may not necessarily be __repr__. The choice between __str__ and __repr__ are as follows:

• __str__ : __str__ is present, and the object class's __repr__ is default with <class name at Address>.
• __repr__: __str__ is present, but the object class's __repr__ is anything else, such as ClassName(var=value).
  Also, when __str__ is missing, even if __repr__ is <class name at Address>, it is used.

Currently, if an object doesn't exist and is directly accessed, as var in this case, it will not be shown up. But if it is attribute accessed with dot ., as location in me.my_boss.location, then its value is an explicit string '!!! Not Exists'.

As you may have noticed, a variable API_KEY has its name prefixed with outer.
This tells you that the variable is defined in the outer scope, not local.

More often than not, only objects in the error line are not sufficient to diagnose what has happened. You want to know what the inputs of the function were. You want to know what the intermediate calculated results were. You want to know other objects that appeared during runtime, not only local but also outer scope. In other words, you want to know the full context of what has happened. logger-tt is here with you:

setup_logging(full_context=2)

With the above hypothetical code snippet, the error log becomes the following:

[2020-06-06 10:35:21] ERROR: Uncaught exception:
Traceback (most recent call last):
  File "D:/MyProject/AutoBanking/main.py", line 31, in <module>
    my_faulty_func(max_concurrent_processes, 'ryzen 7', freq=3.4)
     |-> my_faulty_func = <function my_faulty_func at 0x0000019E3599A288>
     |-> max_concurrent_processes = 3
     => __name__ = '__main__'
     => __doc__ = None
     => __package__ = None
     => __loader__ = <_frozen_importlib_external.SourceFileLoader object at 0x0000019E35840E48>
     => __spec__ = None
     => __annotations__ = {}
     => __builtins__ = <module 'builtins' (built-in)>
     => __file__ = 'D:/MyProject/AutoBanking/main.py'
     => __cached__ = None
     => setup_logging = <function setup_logging at 0x0000019E35D111F8>
     => getLogger = <function getLogger at 0x0000019E35BC7C18>
     => logger = <Logger __main__ (DEBUG)>
     => API_KEY = 'asdjhfbhbsdf82340hsdf09u3ionf98230234ilsfd'
     => TIMEOUT = 60
     => MyProfile = <class '__main__.MyProfile'>
     => cpu_no = 4

  File "D:/MyProject/AutoBanking/main.py", line 25, in my_faulty_func
    print(f'Information: {var} and {me.my_boss.name} at {me.my_boss.location} with {API_KEY}')
     |-> me.my_boss.name = 'Winston'
     |-> me.my_boss.location = '!!! Not Exists'
     |-> (outer) API_KEY = 'asdjhfbhbsdf82340hsdf09u3ionf98230234ilsfd'
     => my_var = 3
     => args = ('ryzen 7',)
     => kwargs = {'freq': 3.4}
     => new_var = 'local scope variable'
     => me = <__main__.MyProfile object at 0x0000019E35D3BA48>
     => boss = <__main__.MyProfile object at 0x0000019E35D3B9C8>
NameError: name 'var' is not defined

Additional objects that not appear in the error line are prefixed with =>.

Note: from version 1.6, uncaught exception happened in child thread of a multithreading program will also be caught by logger-tt and logged normally. If you are using python 3.8+, the new threading.excepthook won't be called as the uncaught exception has been handled by logger-tt.

5. try-except exception logging:

exception context logging also applies for try-except block. This means that if you call logger.exception() inside except block, you would have all variables' value at the line of exception. For example,

def my_faulty_func():
    a = 10
    b = 0
    c = a/b
    return c

def my_main():
    try:
        my_faulty_func()
    except Exception as e:
        logger.exception('some error has occured')
        print('Clean up resource')

my_main()

Then the log will show up as follows:

[2020-06-12 21:37:00] ERROR: some error has occured
Traceback (most recent call last):
  File "D:/MyProject/exception_log.py", line 19, in my_main
    my_faulty_func()
     |-> my_faulty_func = <function my_faulty_func at 0x000001875DD4B168>

  File "D:/MyProject/exception_log.py", line 13, in my_faulty_func
    c = a / b
     |-> a = 10
     |-> b = 0
ZeroDivisionError: division by zero
Clean up resource

Note: As in python's logging document, logger.exception() should only be called from an exception handler, eg. inside except block.

You don't need to pass exception object to logger.exception(). It already knows how to get a traceback internally. This enable you to pass any string in as a hint or a short description of what may have happened.
Otherwise, passing exception object, as logger.exception(e), will cause the first line of error report to be the message of exception. In the case of the above example, it would be come [2020-06-12 21:37:00] ERROR: division by zero.

6. Silent unwanted loggers:

Third party modules also have loggers, and their messages are usually not related to your code. A bunch of unwanted messages may hide the one that come from your own module. To prevent that and also reduce log file size, we need to silent unwanted loggers.

By config file, there are two ways to silent a logger:

• Create a new logger: in logger section of the config file, add a new logger whose name is the same with the one you want to silent. Set it level to WARNING or above. If you add handlers, you should also set propagate to no or False. Otherwise, the same message may be logged multiple times. Ex:

  urllib3:
    level: WARNING
    handlers: [console, error_file_handler]
    propagate: no
  

  Above setting only allow messages with level WARNING and above to be processed. Usually that is enough to silent most of unwanted messages. If you need to silent more messages, try ERROR or CRITICAL.

• Add logger's name to suppress list: Then a new logger with level default to WARNING will be automatically created for you. Ex:

  suppress: [exchangelib, urllib3]
  

  If you need to suppress at even higher level, use suppress_level_below in setup_logging. For example suppress any message below ERROR level that comes from loggers in suppress list:

  setup_logging(suppress_level_below=logging.ERROR)
  

You could also suppress loggers directly by setup_logging:

from logger_tt import setup_logging    

setup_logging(suppress=['urllib3', 'exchangelib'])

7. Logging in multiprocessing:

This is archived by using multiprocessing queues or a socket server.

For linux, copy-on-write while forking carries over logger's information. So multiprocess.Queue is enough in this case.

For Windows, it is important that setup_logging() must be call out side of if __name__ == '__main__': guard block. Because child processes run from scratch and re-import __main__, by re-executing setup_logging(), logger SocketHandler can be setup automatically.

This also means that the same config can work with both multiprocessing.Process and multiprocessing.Pool magically without user doing anything special.

Below is a minimal example:

import time
from random import randint
from multiprocessing import Process

from logger_tt import setup_logging, logger


setup_logging(use_multiprocessing=True)        # for Windows, this line must be outside of guard block


def worker(arg):
    logger.info(f'child process {arg}: started')
    time.sleep(randint(1,10))                  # imitate time consuming process
    logger.info(f'child process {arg}: stopped')


if __name__ == '__main__':
    all_processes = []
    logger.info('Parent process is ready to spawn child')
    for i in range(3):
        p = Process(target=worker, args=(i,))
        all_processes.append(p)
        p.daemon = True
        p.start()

    for p in all_processes:
        p.join()

The content of log.txt should be similar to below:

[2020-10-28 20:39:14] [root:129 DEBUG] _________________New log started__________________
[2020-10-28 20:39:17] [root:130 DEBUG] Log config file: D:\my_project\log_config.json
[2020-10-28 20:39:17] [root:131 DEBUG] Logging server started!
[2020-10-28 20:39:22] [__main__:28 INFO] Parent process is ready to spawn child
[2020-10-28 20:39:22] [__mp_main__:16 INFO] Process-3 child process 2: started
[2020-10-28 20:39:22] [__mp_main__:16 INFO] Process-2 child process 1: started
[2020-10-28 20:39:22] [__mp_main__:16 INFO] Process-1 child process 0: started
[2020-10-28 20:39:23] [__mp_main__:18 INFO] Process-2 child process 1: stopped
[2020-10-28 20:39:23] [__mp_main__:18 INFO] Process-3 child process 2: stopped
[2020-10-28 20:39:24] [__mp_main__:18 INFO] Process-1 child process 0: stopped

Note: Under linux, to use queueHandler, you must pass use_multiprocessing="fork" to setup_logging.
Other options True, spawn, forkserver will use socketHandler by default.
This is to prevent you set_start_method as spawn under linux and thus queueHandler won't work.

Socket Address:

• v1.7.3 and before: socketHandler will use tcp localhost and port 9020 by default. In the rare cases where you run multiple multiprocessing applications with logger_tt, the Address already in use error will be raised. In such cases, you have to set the address manually.
• v1.7.4 and after: socketHandler will use tcp localhost and a random available port by default.

setup_logging(host='localhost', port=6789)

You can omit the host if you use "localhost". You can also set this in the log config file for each application.

8. Temporary disable logging:

Some block of code contain critical information, such as password processing, that should not be logged. You can disable logging for that block with a logging_disabled context:

from logger_tt import logging_disabled, getLogger

logger = getLogger(__name__) 


logger.debug('Begin a secret process')
with logging_disabled():
    logger.info('This will not appear in any log')

logger.debug('Finish')

9. Limit traceback line's length:

Sometimes the variable on the exception line can hold enormous amount of data, such as content of some huge json file or html. In this case, printing out the whole content of the variable is quite point less and hinders debugging process as it hides away exception line.

So we should limit the character to be printed out in each line of the traceback. And we can do it as simple as follow:

setup_logging(limit_line_length=1000)

The default limit is 1000 characters. All left characters will be replaced with .... limit_line_length=0 means no limit at all, prints the content of variable as is.

Note: if you input a float, it will be round down to nearest int. A negative input is treated as inputting 0.

For demonstration purpose, the example below will limit to 100 characters:

from logger_tt import setup_logging

setup_logging(limit_line_length=100)

def will_fail():
 loren_ipsum = "On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and " \
               "demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot " \
               "foresee the pain and trouble that are bound to ensue; and equal blame belongs to those who fail in " \
               "their duty through weakness of will, which is the same as saying through shrinking from toil and " \
               "pain. These cases are perfectly simple and easy to distinguish. In a free hour, when our power of " \
               "choice is untrammelled and when nothing prevents our being able to do what we like best, " \
               "every pleasure is to be welcomed and every pain avoided. But in certain circumstances and owing to " \
               "the claims of duty or the obligations of business it will frequently occur that pleasures have to " \
               "be repudiated and annoyances accepted. The wise man therefore always holds in these matters to " \
               "this principle of selection: he rejects pleasures to secure other greater pleasures, or else he " \
               "endures pains to avoid worse pains. "

 print(f'Below is the {random} text used as a standard to test font: \n{loren_ipsum}')

if __name__ == '__main__':
 will_fail()

It will output the follow traceback. Pay attention to the loren_ipsum variable.

[2021-06-19 17:40:39] ERROR: Uncaught exception:
Traceback (most recent call last):
  File "D:\my_project\long_line.py", line 21, in <module>
    will_fail()

  File "D:\my_project\long_line.py", line 18, in will_fail
    print(f'Below is the {random} text used as a standard to test font: \n{loren_ipsum}')
     |-> loren_ipsum = 'On the other hand, we denounce with righteous indignation and dislike men wh... (922 characters more)
NameError: name 'random' is not defined

10. Analyze raise exception line:

If the code explicitly raise an exception, in most cases, the variables on the line are substituted and printed out at the end of traceback. With logger-tt analyzing the raise statement, these variables are printed again too.

[2021-06-19 18:15:01] ERROR: Uncaught exception:
Traceback (most recent call last):
  File "D:\my_project\module.py", line 9, in <module>
    raise RuntimeError(f'Too much laughing with a={a} and b={b}')
     |-> a = 'haha'
     |-> b = 'hihi'
RuntimeError: Too much laughing with a=haha and b=hihi

The duplication is unnecessary, so from version 1.6.1, raise exception line will not be analyzed as default. This resulted in a much cleaner log:

[2021-06-19 18:15:30] ERROR: Uncaught exception:
Traceback (most recent call last):
  File "D:\my_project\module.py", line 9, in <module>
    raise RuntimeError(f'Too much laughing with a={a} and b={b}')
RuntimeError: Too much laughing with a=haha and b=hihi

If the raise exception line in turn, raise another exception, and you want to analyze it, you could turn it back on as below:

setup_logging(analyze_raise_statement=True)

11. StreamHandler with buffer:

This handler is mainly to solve the problem of outputting a tremendous amount of logs to GUI applications in real-time.

GUI applications use threading to display content while listening for user input (button click, key pressing, mouse scroll). But since cpython actually running only one thread at a time due to the GIL (global interpreter lock), processing to display a tremendous amount of logs to the GUI widget will lock a thread for quite a long time. During this time, no user input will be handled and the app seems unresponsive.

The answer to this problem is to cache the log and output them at once after some interval or a number of cached lines reached a threshold. This significantly reduces the overhead on the widget side and makes the app responsive. The solution is implemented in the new StreamHandlerWithBuffer which is inside logger_tt.handlers. There are 2 steps to use this handler.

• config the handler in the log_config file.

  handlers:
    buffer_stream_handler:
      class: logger_tt.handlers.StreamHandlerWithBuffer
      level: DEBUG
      formatter: brief
      stream: ext://sys.stdout
      buffer_time: 0.5
      buffer_lines: 0
      debug: False
  
  root:
    level: DEBUG
    handlers: [console, error_file_handler, buffer_stream_handler]

  Its parameters look exactly like the console handler except the last 3 ones.

  • buffer_time: the cache time interval in seconds before it flush the log out
  • buffer_line: the number of line to cache before it flush the log out
  • debug: log the time that it flush the log out or not
    

  For buffer_line, to avoid the last lines of log not printed out as the number of line is below threshold, you should set buffer_time to a certain number too.

  Then, you need to add this handler to the root logger's handlers list.

• replace the stream: you need to replace the stdout with your GUI widget stream. You cannot do this in the config file since your widget is only appear during runtime. You have to do this in the code.

  config = setup_logging(config_path='log_config.json')
  config.replace_handler_stream(index=HANDLER_INDEX, stream=WIDGET_STREAM)

  Setup your logging as usual with your config file, then call replace_handler_stream to replace the with your widget's stream.

  • index: the index of the handler, in the root logger' handlers list, that you want to replace the stream
  • stream: the stream that you want to put into this handler.

Below is the example with PySimpleGUI v4.57.0 with the above config.

import time
from threading import Thread

import PySimpleGUI as sg
from logger_tt import setup_logging, logger

stop_flag = False

# GUI config
sg.theme('DarkAmber')
layout = [
 [[sg.Button("Show Log", key="-show_log-"),
  sg.Button("stop", key="-stop-", button_color='red')],
  sg.Multiline(size=(80, 30), font='Courier 10', key='log', autoscroll=True)]
]
window = sg.Window('Logging tool', layout, finalize=True)

# logging config
config = setup_logging(config_path='log_config.json')
config.replace_handler_stream(index=2, stream=window["log"])


def my_func():
 """long running task in the background"""
 while not stop_flag:
     for i in range(1000):
         logger.warning(f" {i} Function is empty")
     time.sleep(1)


while True:
 event, values = window.read()
 if event == sg.WINDOW_CLOSED:
     break
 if event == "-show_log-":
     logger.info(__name__)
     Thread(target=my_func).start()
 if event == "-stop-":
     stop_flag = True
     logger.info(f"stop button pressed")

window.close()

You could set index=0 to use the normal StreamHandler and see the difference while clicking the stop button for yourself.

12. Telegram Handler:

This handler enables you to send log messages directly to telegram users or groups. For telegram groups, you can specify a certain topic to send to, too. This handler uses web API, so there is no third-party dependency.

To set up this handler, you need the following information:

• Your bot token: if you don't have one, create a new bot with https://t.me/botfather.
• Destination unique_id: a chat_id (user id or group id) and optionally message_thread_idof a topic in that group. You can chat with or add @RawDataBot to your group to get these ids.
• Log level to be sent: above a level or only a specific level.

From here you have 2 options, put the token and unique_id directly in the config file or in the environment. If you specify both ways, if the data exists in the environment variables, it will replace the one specified in the config file. The default environment variable names are:

• token: TELEGRAM_BOT_LOG_TOKEN
• unique_ids: TELEGRAM_BOT_LOG_DEST

These above names are specified in env_token_key and env_unique_ids_key in the default config file. You may edit them to suit your environment.

For the values, unique_ids accepts the format [name:]chat_id[@message_thread_id], multiple values must be separated by a semicolon (space after a semicolon will be ignored). Which means the following examples are possible:

• a single chat_id: 123456789 (user id) or -987654321 (group id)
• a specified topic within a group: -987654321@2
• multiple values: 123456789; 102345678; -987654321@2; -987654322@4
• multiple values with names: Alex:123456789; Bob:102345678; support:-987654321@2; admin:-987654322@4

After having all needed information, the next step is configuring the handler and adding it into the root logger.

handlers:
  telegram_handler:
    class: logger_tt.handlers.TelegramHandler
    level: NOTICE
    formatter: brief
    debug: False
    token: ""
    unique_ids: ""
    env_token_key: "TELEGRAM_BOT_LOG_TOKEN",
    env_unique_ids_key: "TELEGRAM_BOT_LOG_DEST"
  
root:
  level: DEBUG
  handlers: [console, error_file_handler, telegram_handler]

Sending too many messages within a second will lead to HTTP 429 error. Even though it will resend later, you can avoid the error from the beginning by adding the param grouping_interval: 1 to the configuration above. By doing that, all log messages whose timestamp are in the same second will be sent as one telegram message.

From here, it should already work. If you need certain messages to go to a certain people/group, besides adding a new handler, you can add a filter that adds the dest_name attribute to the log record.

def telegram_filter(record):
    if 'over threshold' in record.msg:
        record.dest_name = 'support'
    elif 'unauthorized' in record.msg:
        record.dest_name = 'admin'
    elif 'Alex' in record.msg:
        record.dest_name = 'Alex'
    else:
        pass
    
    # return False will discard this record
    return True

log_config = setup_logging()
log_config.set_context_injector(telegram_filter)

logger.warning(f'Memory usage is over threshold')
logger.error(f'This deleting action is unauthorized')
logger.notice(f"Alex's files are ready to be collected")

dest_name should be only one name that has been registered in unique_ids. If the name is not registered, the log record is simply ignored totally. If you want to send to multiple people, create a telegram group for them and registered the group name.

Sample config:

Below are default config files that used by logger-tt. You can copy and modify them as needed.

1. Yaml format:

log_config.yaml:

# This is an example of config file
# In case of no config provided, log_config.json file will be loaded
# If you need a yaml file, install pyyaml or ruamel.yaml package and copy this file
version: 1
disable_existing_loggers: False
formatters:
  simple:
    format: "[%(asctime)s] [%(name)s:%(lineno)d %(levelname)s] %(message)s"
    datefmt: "%Y-%m-%d %H:%M:%S"
  brief:
    format: "[%(asctime)s] %(levelname)s: %(message)s"
    datefmt: "%Y-%m-%d %H:%M:%S"

handlers:
  console:
    class: logging.StreamHandler
    level: INFO
    formatter: brief
    stream: ext://sys.stdout

  error_file_handler:
    class: logging.handlers.TimedRotatingFileHandler
    level: DEBUG
    formatter: simple
    filename: logs/log.txt
    backupCount: 15
    encoding: utf8
    when: midnight
  
  buffer_stream_handler:
    class: logger_tt.handlers.StreamHandlerWithBuffer
    level: DEBUG
    formatter: brief
    stream: ext://sys.stdout
    buffer_time: 0.5
    buffer_lines: 0
    debug: False
    
  telegram_handler:
    class: logger_tt.handlers.TelegramHandler
    level: NOTICE
    formatter: brief
    debug: False
    token: "your bot token here or set the below env key to fetch from environ for better security"
    unique_ids: "semicolon separated of [name:]chat_id[@message_thread_id]"
    env_token_key: "TELEGRAM_BOT_LOG_TOKEN"
    env_unique_ids_key: "TELEGRAM_BOT_LOG_DEST"

loggers:
  urllib3:
    level: WARNING
    handlers: [console, error_file_handler]
    propagate: no

root:
  level: DEBUG
  handlers: [console, error_file_handler]

logger_tt:
  suppress: ["exchangelib"]
  suppress_level_below: "WARNING"
  capture_print: False
  strict: False
  guess_level: False
  full_context: 0
  use_multiprocessing: False
  limit_line_length: 1000
  analyze_raise_statement: False
  default_logger_formats:
    normal: ["%(name)s", "%(filename)s"]
    thread: ["%(message)s", "%(threadName)s %(message)s"]
    multiprocess: ["%(message)s", "%(processName)s %(message)s"]
    both: ["%(message)s", "%(processName)s %(threadName)s %(message)s"]

2. Json format:

log_config.json:

{
 "version": 1,
 "disable_existing_loggers": false,
 "formatters": {
   "simple": {
     "format": "[%(asctime)s] [%(name)s:%(lineno)d %(levelname)s] %(message)s",
     "datefmt": "%Y-%m-%d %H:%M:%S"
   },
   "brief": {
     "format": "[%(asctime)s] %(levelname)s: %(message)s",
     "datefmt": "%Y-%m-%d %H:%M:%S"
   }
 },

 "handlers": {
   "console": {
     "class": "logging.StreamHandler",
     "level": "INFO",
     "formatter": "brief",
     "stream": "ext://sys.stdout"
   },

   "error_file_handler": {
     "class": "logging.handlers.TimedRotatingFileHandler",
     "level": "DEBUG",
     "formatter": "simple",
     "filename": "logs/log.txt",
     "backupCount": 15,
     "encoding": "utf8",
     "when": "midnight"
   },

   "buffer_stream_handler": {
     "class": "logger_tt.handlers.StreamHandlerWithBuffer",
     "level": "INFO",
     "formatter": "simple",
     "stream": "ext://sys.stdout",
     "buffer_time": 0.5,
     "buffer_lines": 0,
     "debug": false
    }, 
     
   "telegram_handler": {
     "class": "logger_tt.handlers.TelegramHandler",
     "level": "NOTICE",
     "formatter": "brief",
     "debug": false,
     "token": "your bot token here or set the below env key to fetch from environ for better security",
     "unique_ids": "semicolon separated of [name:]chat_id[@message_thread_id]",
     "env_token_key": "TELEGRAM_BOT_LOG_TOKEN",
     "env_unique_ids_key": "TELEGRAM_BOT_LOG_DEST"
    }
 },

 "loggers": {
   "urllib3": {
     "level": "ERROR",
     "handlers": ["console", "error_file_handler"],
     "propagate": false
   }
 },

 "root": {
   "level": "DEBUG",
   "handlers": ["console", "error_file_handler"]
 },

 "logger_tt": {
   "suppress": ["exchangelib"],
   "suppress_level_below": "WARNING",
   "capture_print": false,
   "strict": false,
   "guess_level": false,
   "full_context": 0,
   "use_multiprocessing": false,
   "limit_line_length": 1000,
   "analyze_raise_statement": false,
   "default_logger_formats": {
      "normal": ["%(name)s", "%(filename)s"],
      "thread": ["%(message)s", "%(threadName)s %(message)s"],
      "multiprocess": ["%(message)s", "%(processName)s %(message)s"],
      "both": ["%(message)s", "%(processName)s %(threadName)s %(message)s"]
   }
 }
}

Changelog

1.7.4:

• Fixed: TelegramHandler re-group again an already grouped message
• Usability:
  • Pyinstaller: Changed the method of detecting child process, potentially fix all issues related to multiprocessing and pyinstaller
  • Multiprocessing: logger's server port now automatically picks up a random available port instead of DEFAULT_TCP_LOGGING_PORT. This means in the case of running many multiprocessing application at the same time, user doesn't need to care about the port parameter anymore. Each application will pick it own port, their child processes will connect to the correct port, and thus log to the correct log file.

1.7.3:

• Usability:
  • Not to import custom handlers (StreamHandlerWithBuffer, TelegramHandler, etc) if they are not used in any logger.
  • TelegramHandler:
    • Better network error handling.
    • Added grouping_interval to group many log messages that are within the same x seconds interval into one before sending. This reduces the number of times it sends messages to Telegram server and helps to avoid HTTP 429 error.

1.7.2:

• Fixed: TelegramHandler crashed instead of ignoring the unregistered unique_id

1.7.1

• Fixed: exception raised while handling another exception is now shown correctly (thank ZeroRin).
• New functionality:
  • Added TelegramHandler. Now you can send logs directly to telegram users/groups.
  • Support Python 3.11 Fine-grained error locations in tracebacks.
• Usability:
  • Added level NOTICE = INFO + 5. You can do logger.notice("your message").
  • Add set/remove context injector methods. You can add additional information to the log record before it is actually handled. Refer to the TelegramHandler for a usage sample.
  • You can now set different log paths for different handlers by passing a dict to setup_logging (thank ZeroRin).

1.7.0

• Fixed:

  • multiprocessing: log file rollover fails as child process keep opening the file.
  • multiprocessing: if the log path is set by a variable with time, child process creates a new redundant log path.

• New functionality: Added StreamHandlerWithBuffer. Buffer the log output by time or by line number. GUI app could use this handler to keep the app responsive while having a tremendous log output.

• Usability: In multiprocessing logging, users can set the log server address themselves through setup_logging or log config file.

1.6.1

• Added limit_line_length parameter: log only maximum n characters for each traceback line. This prevents dumping the whole huge content of the variable into the log. n=1000 by default.

• Added analyze_raise_statement parameter: logger-tt no longer analyze the raise statement by default. This avoids logging value of variables on the raise statement two time, especially when the content of these variables are huge.

1.6.0

• Fixed: If an exception happened on the multiline statement, py3.6 and py3.7 return the last line while py3.9 returns the first line. Plus the tokenize module's behavior has changed, so it made grabbing the all the lines of the statement inconsistent and sometime buggy. Now logger-tt only grabs maximum of 10 lines and grabs more accurately, more consistent between different python version.

• Added support for ruamel.yaml package. If you already have it installed, you don't need to install pyyaml to use config.yaml file

• New feature: Uncaught exception happened in child thread of multi-threading program will also be logged. For python 3.8+, threading.excepthook will not run as the exception is already caught by logger-tt.

1.5.2

Improved the pre-made logger named logger_tt

• logger_tt now can detect the qualified __name__ of the module that calls it. Instead of filename, output log line will have the __name__ as regular logger.

  For example:

  [2020-07-21 11:24:19] [my_module.py:5 DEBUG] Module is initialized
  [2020-07-21 11:24:19] [sub_module.py:15 DEBUG] Entering sub module
  

  Now becomes

  [2020-07-21 11:24:19] [__main__:5 DEBUG] Module is initialized
  [2020-07-21 11:24:19] [my_module.submodule:15 DEBUG] Entering sub module
  

• Suppressing loggers also works with log records output by logger_tt by using the qualified __name__ too. For example, suppressing my_module.submodule will tell logger_tt not to output the second line.

  This is much better than suppressing logger_tt if you use this same logger in other modules too.

• You now can define fields of log record for logger_tt in the log config file too. Just looks for default_logger_formats section. It works by replacing the field in the formatters that are used by any handler of the root logger.

Pre-existing loggers:
Before this version, if you import submodules before importing logger_tt and there are loggers in submodules, these loggers do not inspect exception when you call logger.exception(). That is because there class was different from the loggers created after importing logger_tt. Now all loggers have the same new class regardless the point of importing logger_tt.

setup_logging(): This function should only be called once. Add a warning if it is called more than one time.

1.5.1

• Use socketHandler as default for multiprocessing. Under linux, to use queueHandler, user must pass use_multiprocessing="fork" to setup_logging
• Expose logging_disabled function to user: from logger_tt import logging_disabled. Then this function can be used as a context with with statement.
• For convenient, user can import a pre-made logger from logger_tt to use right away in sub modules. The built-in getLogger function can be imported from logger_tt, too.
• Added line number to a default simple log record formatter in the config file.
• Most parameters of setup_logging() function can be specified in the config file, too. If the same parameter is specified in both setup_logging() function and in the config file, the parameter passed in setup_logging() will be used.

1.5.0

• Logging is off-loaded to another thread and uses Queue to communicate. This allow critical thread can do there job why time-consuming logging can be done later or in parallel.
• Support for multiprocessing logging. For linux, a multiprocessing queue is used. For Windows and macOS, a socket server is used instead.
• setup_logging now return a LogConfig object. You can set/change parameters of this object instead of passing arguments directly to setup_logging.
  Only config_path, log_path and use_multiprocessing argument must be set with setup_logging.

Behaviors changed:

• full_context is now an int that indicate the depth level from the bottom, where surrounding variables should be parsed.
• Turned off parsing full context for raise exception since many exception names are enough to understand the problem.
• log_config file: move suppress section into logger_tt section. Future settings will also be put into this section for the sake of managing. If you need to hanging the logging framework, you just need to delete this section and move on.

1.4.2

To prevent exception during logging, the following actions have been applied:

• Catch exception while parsing for object's value (property of a class)
• Catch exception while evaluating __repr__ and __str__ of object
• Disable logging while inspecting objects' value and representation
• Disable logging after an uncaught exception is logged. Because the interpreter is shutting down, objects get deleted. Logging put inside magic function __del__ will raise error.

1.4.1

• Fix print_capture ignoring print() line in global scope due to lacking code_context frame
• If __str__ of an object has multiple lines, also indent the second line and so on accordingly.
• If there is an exception during getting object's representation, return !!! Attribute error instead of Error in sys.excepthook

1.4.0

• Add an extra field suppress in config file. Any logger's name appeared in this list will have its messages suppressed.

1.3.2

• change extended ascii dash ─ to normal dash - so that it is displayed consistently in different encoding

1.3.1

• change extended ascii vertical bar ├ to normal bar | so that it is displayed consistently in different encoding

1.3.0

• Exception analyzing now fetch full multi-line python statement. This means that variables lie at seconds and below of the same statement can also be seen without the need of full_context=True.

1.2.1

• Extend logging context to logger.exception() as well. Now you can do try-except a block of code and still have a full context at error line.

1.2.0

• Add logging context for uncaught exception. Now automatically log variables surrounding the error line, too.
• Add test cases for logging exception

1.1.1

• Fixed typos and grammar
• Add config file sample to README
• using full name log_config.json instead of log_conf.json, the same for yaml file
• add test cases for capture print

1.1.0

• Add capture print functionality with guess level for the message.