pyDecLog

pyDecLog: a simple and easy to use Python module for logging via decorators.

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🚀Quick start

• Say we have the following workflow

from pyDecLog import arguments
from pyDecLog import signature
from pyDecLog import message
from pyDecLog import timing
from pyDecLog import lprint
from pyDecLog import description
import time

def workflow():

    # Set console level to the same level of the message level so it is shown in the console
    lprint(console_log_level="info").info("Workflow starts!")

    # Decorate function as needed
    @doscription
    @signature
    @arguments
    @timing
    @message
    def sum_two_int(first, second=2):
        """Sum two numbers."""

        print("Some message on console")
        result = first + second
        time.sleep(2)
        print("Result is: " + str(result))
        return result

    sum_tow_int(1, 1)

    # Set console level to the same level of the message so it is shown in the console
    lprint(console_log_level="info").info("Workflow ends!")


if __name__ == "__main__":
    workflow()

• Upon execution the following is printed on console:

Workflow starts!
Workflow ends!

• Upon execution a LOG.log file is written:

2023/06/24 | 18:20:50 | ERROR Workflow starts!
2023/06/24 | 18:20:50 | DEBUG Method's description: Sum two numbers.
2023/06/24 | 18:20:50 | DEBUG Method's name: sum_
2023/06/24 | 18:20:50 | DEBUG Method's signature:(first, second=2)
2023/06/24 | 18:20:50 | DEBUG Method's name: sum_
2023/06/24 | 18:20:50 | DEBUG Method's args: (1, 1)
2023/06/24 | 18:20:50 | DEBUG Method's kwargs: {}
2023/06/24 | 18:20:52 | INFO Some message on console
2023/06/24 | 18:20:52 | INFO Result is: 2
2023/06/24 | 18:20:52 | DEBUG sum_ was executed in: 2.006 sec
2023/06/24 | 18:20:52 | ERROR Workflow ends!

🚀Useful for

• Keep track of Python pipelines.
• Log info about a function during development both via Python script or Jupyter Notebook.

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⚙️Installation

• Create your own virtual environment and run pip install -r requirements.txt
• Via pip: pip install pyDecLog

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🔗Dependencies

• PyDevLog requires Python 3.5 or higher, and the following packages:
  • pympler
  • numpy

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🧑‍🤝‍🧑Contributions

• All contributions (bug, suggestion, new feature) are welcome.

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🎨Available decorators

• @arguments: log function's args and kwargs
• @comment: log all function's inner print statements
• @description: log function's output from the __doc__ dunder method
• @machine: log machine OS system and hardware
• @memory: log function's args, kwargs and output memory usage
• @message: log function's print statements
• @profile_locals: log function's local persistent variables
• @signature: log function's signature
• @timing: log function's elapsed time
• @typing: log function's args, kwargs and output type
• @user: log user info

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🪄Features

• Mix and match the decorators you want.
• Can control logging levels as a whole or individually. Choose from the following:
  • CRITICAL
  • ERROR
  • WARNING
  • INFO
  • DEBUG
• Can control where logging messages are piped: to log file or both log file and console. When controlling the message at the console level the following hierarchy is enforced:

CRITICAL : 50
ERROR    : 40
WARNING  : 30
INFO     : 20
DEBUG    : 10
NOTSET   : 0

• Can add comments directly to log file even outside a function.

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⚠️Known issues

• @profile_locals does not write to the log file. Its output needs to be piped separately to the LOG.log file. See the following example:

from pyDecLog import profile_locals as profile
from pyDecLog import lprint
from pympler.asizeof import asizeof

@profile
def func(x):
    local_1 = 1
    local_2 = 2
    return 1

func()

for key, value in func.locals.items():
    msg = f"Variable: {key} | value: {value} | type: {type(value)} | size: {asizeof(value)}"

    lprint(console_log_level="debug").debug(msg)

• The following LOG.log is the written:

2023/06/28 | 07:04:52 | DEBUG Variable: x | value: 1 | type: <class 'int'> | size: 32
2023/06/28 | 07:04:52 | DEBUG Variable: local_1 | value: 1 | type: <class 'int'> | size: 32
2023/06/28 | 07:04:52 | DEBUG Variable: local_2 | value: 2 | type: <class 'int'> | size: 32

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📚Tutorials

• See the examples folder.

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📚References

• Decorators with parameters?
• How to expose persistent local variables? Part#1
• How to expose persistent local variables? Part#2
• How to time your code

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📝Changelog

• 0.1.6 - First release (26/06/23).
• 0.1.7 - Added @machine and @user (29/06/23).

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📝To-do

• There is no planned development.

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🪪License

• MIT License

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Developers

• Doc string were generated via autoDocstring package using NumPy format style.
• Typing hints for function return type by Pylance.
• Testing was done via unittesting.

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