Jupyter Notebook运行Python包报错AttributeError: logging无config属性求替代方案

Hey there, let's tackle this frustrating logging issue without resorting to downgrading your Python or Conda environment. Here are actionable, alternative solutions to try:

• Check for naming conflicts with the standard logging module
  The most common culprit here is having a local file or module named logging.py (or a directory named logging with an __init__.py) in your Jupyter working directory or your package's path. This overrides Python's built-in logging module, which won't have the config submodule.
  To verify this, run this in a Jupyter cell:

  import logging
  print(logging.__file__)
  

  If the output isn't pointing to your Python installation's standard library logging.py (e.g., something like /usr/lib/python3.x/logging/__init__.py), rename your local logging.py or directory to something else (like my_project_logging.py).

• Force a reload of the logging module
  Jupyter's kernel caches imported modules, so it might be holding onto a corrupted or incomplete version of logging. Try reloading it before importing your package:

  import importlib
  import logging
  importlib.reload(logging)
  # Now import your custom package
  import your_custom_package
  

  This ensures you're getting a fresh, unmodified version of the standard logging module.

• Verify your Jupyter kernel is using the correct environment
  Sometimes Jupyter is running in a different Python environment than the one where you installed your custom package. To check the kernel's Python path:

  import sys
  print(sys.executable)
  

  Compare this to the path of the environment where you developed your package. If they don't match, switch to the correct kernel (via Jupyter's "Kernel > Change Kernel" menu) or install the kernel for your target environment:

  # Activate your environment first, then run:
  pip install ipykernel
  python -m ipykernel install --user --name=your-environment-name
  

• Audit your custom package's import logic
  Double-check if any code in your package is accidentally modifying the logging module. For example, look for lines like del logging.config or accidental reassignments of logging to another object. Add debug prints in your package's import sections to confirm the state of logging:

  # At the top of your package's main module
  import logging
  print("Logging module contents:", dir(logging))
  

  If config isn't listed here, you'll know the issue is occurring before your code tries to use logging.config.

• Explicitly import the config submodule
  Instead of relying on implicit import of logging.config, try explicitly importing it in your package before using it:

  import logging
  import logging.config  # Explicitly load the config submodule
  

  This ensures the submodule is loaded even if there's some quirk in how Jupyter handles module imports.

内容的提问来源于stack exchange，提问作者ava_punksmash