Open redex-ai opened 9 months ago
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https://github.com/redex-ai/django-scheduler/issues/13#issuecomment-1834569513
Implemented logging in 'schedule/utils.py' to enhance monitoring and troubleshooting capabilities by capturing key events, function calls, and exceptions.
Add import statement for Python's built-in logging module at the top of the file. Initialize the logger with a basic configuration at the module level. Add logging statements at the beginning and end of each function, as well as within exception handling blocks, to log function calls, important decision points, and exceptions. Use appropriate logging levels such as debug, info, warning, and error.
After implementing the logging changes, developers should lint the code to ensure it adheres to the project's coding standards. Run the existing test suite to verify that the changes have not introduced any regressions. If the project has a continuous integration (CI) pipeline, push the changes to trigger the CI build and automated tests. Once the changes pass all checks, prepare for deployment by updating any necessary documentation and communicating the changes to the team. Ensure that the logging configuration is suitable for the production environment and that log files are being written to the appropriate location with proper rotation and archiving set up.
Developers should verify that the logging statements are correctly capturing the desired information and that the log level is appropriate for the production environment. Adjust the logging configuration if necessary based on the output observed in the logs.
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Based on the provided context and the task requirement to add logs to one Python file, here are some clarification questions that would be relevant to backend development:
Which specific Python file requires logging to be implemented? Can you provide the file path?
What type of events or actions within the file should be logged? For example, should we log database queries, API calls, errors, or specific function calls?
What level of logging is required? Are we interested in debug, info, warning, error, or critical logs?
Should the logging be configurable, allowing the level of logging to be adjusted without changing the code?
Is there a preferred logging framework or library that should be used, or are we using Python's built-in logging
module?
Where should the log files be stored? Do we have a specific directory or file naming convention?
Do we need to consider log rotation and archiving to prevent log files from growing indefinitely?
Should the logs be formatted in a specific way, and do we need to include certain information such as timestamps, module names, or other metadata?
Is there a requirement for remote logging or integration with external logging services or monitoring tools?
Are there any performance considerations or restrictions on how logging should be implemented to minimize the impact on the application's performance?
Do we need to handle sensitive information in the logs, and if so, how should this be managed to ensure security and compliance with data protection regulations?
Is there an existing logging configuration or standard within the project that should be followed for consistency?
These questions aim to gather all necessary information to implement logging accurately and in alignment with the project's standards and requirements.
Add in any one file
Add logs in one python file