log-added-func 0.1.7

log can be inserted at the desired location.

log_added_func

• 可以在程式碼中間插入想要的log，或者直接把裝飾器放在函數前，其會自動記錄其輸入和輸出資訊。

Getting Started

• 輸出的log會自動存取其log時間、file_name、func_name。
• 輸出內容：

%(asctime)s $ %(levelname)-10s $(mem_percent) $%(threadName)s $ %(filename)s $ %(funcName)s $ %(message)s

• 客製化log：在想要的地方下Log，可以設定等級。
• 通用型log：用裝飾器包裝，可以將該func運行error列印出來，也會列印輸入的參數和輸出的值。
• log的存放位置：當前執行的檔案目錄

  ./logs_dir/

Installing：

pip install log_added_func

• 相依套件
  • concurrent-log-handler
  • psutil
  • pywin32 (If you are using Mac or Linux, ignore this key point.)

Examples

範例1:class內有錯誤raise的log

from log_added_func import log
from log_added_func import log_decorator

class Calculator():
    def __init__(self, first=0, second=0):
        self.first = first
        self.second = second

        # Initializing logger object to write custom logs
        self.logger_obj = log.get_logger()

    # let self.logger_obj remove from __dict__, it will not pickle.
    def __getstate__(self):
        d = dict(self.__dict__)
        del d['logger_obj']
        return d

    def __setstate__(self, d):
        self.__dict__.update(d)  # I *think* this is a safe way to do it

    @log_decorator.log_decorator()
    def add(self, third=0, fourth=0):
        # writing custom logs specific to function, outside of log decorator, if needed
        self.logger_obj.critical("Add function custom log, outside decorator")
        self.logger_obj.error("Add function custom log, outside decorator")
        self.logger_obj.warning("Add function custom log, outside decorator")
        self.logger_obj.info("Add function custom log, outside decorator")
        self.logger_obj.debug("Add function custom log, outside decorator")

        try:
            return self.first + self.second + third + fourth
        except:
            raise

    @log_decorator.log_decorator()
    def divide(self):
        self.logger_obj.info("Divide function custom log, outside decorator")
        try:
            return self.first / self.second
        except:
            raise
        
        
if __name__ == '__main__':
    calculator = Calculator(5, 0)
    calculator.add(third=2,fourth=3)
    calculator.divide()

• 輸出

2023-01-11 12:19:42,012 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Arguments: <main.Calculator object at 0x000001969ABF2200>, third=2, fourth=3 - Begin function
2023-01-11 12:19:42,017 $ CRITICAL $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator
2023-01-11 12:19:42,021 $ ERROR $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator
2023-01-11 12:19:42,025 $ WARNING $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator
2023-01-11 12:19:42,029 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator
2023-01-11 12:19:42,033 $ DEBUG $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator
2023-01-11 12:19:42,038 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Returned: - End function 10
2023-01-11 12:19:42,042 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ divide $ Arguments: <main.Calculator object at 0x000001969ABF2200> - Begin function
2023-01-11 12:19:42,046 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ divide $ Divide function custom log, outside decorator
2023-01-11 12:19:42,050 $ ERROR $ 64.6 $MainThread $ calculator_sample.py $ divide $ Exception: division by zero

範例2: 多進程放log，並且修改log檔名為test_log.log

import multiprocessing as mp
from log_added_func import log
from log_added_func import log_decorator

@log_decorator.log_decorator()
def task(num):
    logger_obj = log.get_logger(log_file_name='test_log')
    print('This is Process: ', num)
    logger_obj.info(f"This is Process: {num}")


if __name__=='__main__':
    num_process = 5
    process_list = []
    for i in range(num_process):
        process_list.append(mp.Process(target=task, args=(i,)))
        process_list[i].start()

    for i in range(num_process):
        process_list[i].join()

• 輸出

2023-01-11 12:23:49,417 $ INFO $ 64.7 $MainThread $ multiprocess_sample.py $ task $ This is Process: 1
2023-01-11 12:23:49,416 $ INFO $ 64.7 $MainThread $ multiprocess_sample.py $ task $ This is Process: 0
2023-01-11 12:23:49,423 $ INFO $ 64.7 $MainThread $ multiprocess_sample.py $ task $ This is Process: 2
2023-01-11 12:23:49,425 $ INFO $ 64.7 $MainThread $ multiprocess_sample.py $ task $ This is Process: 3
2023-01-11 12:23:49,433 $ INFO $ 64.7 $MainThread $ multiprocess_sample.py $ task $ This is Process: 4

客製化log

1. 載入：

from log_added_func import log
from log_added_func import log_decorator

3. 初始化：

logger_obj = log.get_logger()

4. 在想要的地方放log：

logger_obj.info("Add function custom log, outside decorator")

5. log輸出範例：

   2023-01-11 12:19:42,029 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Add function custom log, outside decorator

6. 設定等級：
   • 可以設定debug < info < warning < error < critical
   • 範例：logger_obj.warning("Add function custom log, outside decorator")

通用型log

1. 載入：

from log_added_func import log
from log_added_func import log_decorator

2. 在想要的method放:

@log_decorator.log_decorator()
def smaple():
    pass

3. log輸出範例:

   2023-01-11 12:19:42,012 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Arguments: <main.Calculator object at 0x000001969ABF2200>, third=2, fourth=3 - Begin function
   2023-01-11 12:19:42,038 $ INFO $ 64.6 $MainThread $ calculator_sample.py $ add $ Returned: - End function 10

4. 在通用型的其log等級會自動戴入，規則如下：
   • 沒有Error的正常都會是INFO等級。
   • 若有except則會是ERRPR等級

其他說明

1. 可以設定log單檔儲存的大小
   • 1 * 1024 * 1024 = 1MB
   • ConcurrentRotatingFileHandler(logPath, maxBytes=50 * 1024 * 1024, backupCount=2)
2. log存放的位置
   • window: c:\logs_dir\
   • linux: ./logs_dir/ # 當前目錄
   • 若要修改可以在log.py的get_logger調整
3. log檔案名稱
   • 預設:main_log
   • 客製化:在初始化時設定get_logger(log_file_name="sample_name_log")
   • 通用型:@log_decorator.log_decorator(log_file_name="sample_name_log")
4. log以資料夾存放
   • 預設:無資料夾
   • 若要依資料夾分類log也可以對get_logger下參數log_sub_dir
5. log也可以用類似print的方式show在terminal
   • 只要參數DEBUG_flag設為True即可，預設:False
   • 客製化:在初始化時設定get_logger(DEBUG_flag=True)
   • 通用型：@log_decorator.log_decorator(DEBUG_flag=True)
6. log的等級寫入說明
   • 預設會寫入所有等級(debug < info < warning < error < critical)
   • 若要只寫入部分，可以將參數set_level設為想要的等級，e.g.設為"warning"那就是warning、error、critical才會寫入
   • 客製化:在初始化時設定get_logger(set_level="warning")
   • 通用型：@log_decorator.log_decorator(set_level="warning")
7. 縮減log資訊
   • 可透過hide_threadname_flag、hide_filename_flag、hide_funcname_flag省略log資訊，預設如下：
   • get_logger(hide_threadname_flag=False, hide_filename_flag=False, hide_funcname_flag=False)

TODO

• 目前不會show實例化的class名稱

other

• pickle包裝logger會有問題 # 在calculator.py有解決範例
  • https://stackoverflow.com/questions/2999638/how-to-stop-attributes-from-being-pickled-in-python
• 多進程會有logging同時讀寫問題: # 理論上已經透過ConcurrentRotatingFileHandler解決
  • https://www.qnjslm.com/ITHelp/996.html
  • https://stackoverflow.com/questions/22459850/permissionerror-when-using-python-3-3-4-and-rotatingfilehandler
  • https://blog.gdyshi.top/2018/06/27/logging_multiprocess/
  • https://www.programmersought.com/article/43941158027/