sag-py-execution-time-decorator 2.1.4

A decorator for methods to log the execution time (sync and async)

sag_py_execution_time_decorator

A decorator for methods to log the execution time (sync and async)

What it does

• Logs the execution time in milliseconds

Sample log entry:

decorated_sync_method took 1000 ms.

The entry contains "function_name" and "execution_time" as extra data.

Installation

pip install sag-py-execution-time-decorator

How to use

Decorate your methods like that:

from sag_py_execution_time_decorator.execution_time_decorator import log_execution_time

@log_execution_time()
def decorated_sync_method(param: str) -> str:
    time.sleep(SLEEP_TIME_MS / 1000)
    return f"test: {param}"


@log_execution_time(log_level=logging.ERROR, log_params=("param",))
async def decorated_async_method(param: str) -> str:
    await asyncio.sleep(SLEEP_TIME_MS / 1000)
    return f"test: {param}"

Optional arguments:

Argument	Description	Default
log_level	The log level integar. Use logging.* constants	logging.INFO
logger_name	The name of the logger that is internally used for logging.getLogger	execution_time_decorator
log_params	A tuple of parameter names to be logged with their values in 'extra'	()

How to start developing

With vscode

Just install vscode with dev containers extension. All required extensions and configurations are prepared automatically.

With pycharm

• Install latest pycharm
• Install pycharm plugin Mypy
• Configure the python interpreter/venv
• pip install requirements-dev.txt
• Restart pycharm

How to publish

• Update the version in setup.py and commit your change
• Create a tag with the same version number
• Let github do the rest

How to test

To avoid publishing to pypi unnecessarily you can do as follows

• Tag your branch however you like
• Use the chosen tag in the requirements.txt-file of the project you want to test this library in, eg. sag_py_execution_time_decorator==<your tag>
• Rebuild/redeploy your project