Describe the bug
If you pass debug=True to the PterodactylClient class when initializing it, all loggers running in your codebase will be forced to debug level. If you do not pass debug to the PterodactylClient class, or pass it with the value False, all loggers in your codebase will be forced to error level.
Relevant broken code: https://github.com/iamkubi/pydactyl/blob/6f7d30089841791fb277bc4998a29b9cd91b43c1/pydactyl/api_client.py#L32
To Reproduce
Create a logger that logs to the info level, and initialize a PterodactylClient instance. Any info level logging messages output by the initial logger will be ignored.
Expected behavior
Pydactl shouldn't interfere with loggers outside of Pydactl.
Environment
pydactyl 2.0.4
Python 3.11.8
Additional context
This could easily be solved by allowing us to pass our own instance of logging.Logger to the PterodactylClient class, instead of using a custom logger.
Describe the bug If you pass
debug=True
to the PterodactylClient class when initializing it, all loggers running in your codebase will be forced to debug level. If you do not passdebug
to the PterodactylClient class, or pass it with the valueFalse
, all loggers in your codebase will be forced to error level.Relevant broken code: https://github.com/iamkubi/pydactyl/blob/6f7d30089841791fb277bc4998a29b9cd91b43c1/pydactyl/api_client.py#L32
To Reproduce Create a logger that logs to the info level, and initialize a PterodactylClient instance. Any info level logging messages output by the initial logger will be ignored.
Expected behavior Pydactl shouldn't interfere with loggers outside of Pydactl.
Environment
Additional context This could easily be solved by allowing us to pass our own instance of
logging.Logger
to the PterodactylClient class, instead of using a custom logger.