Logging in Python
How many times have you found yourself staring at your screen, surrounded by a sea of hastily added print statements, thinking "There's got to be a better way"? If you're like me, the answer is probably "more times than I'd care to admit."
Sick of finding myself in this situation more often than I'd like, I decided to take action. Python's default logging module is powerful, but it just didn't cut it for my needs. I was looking for something more.
Why Logging Matters
Before we dive in, let's look at why logging is crucial:
- Debugging: Logs provide a trail of breadcrumbs to track down issues.
- Monitoring: They help you understand your application's behavior.
- Auditing: Logs can serve as a record of important events or actions.
- Performance Tracking: You can use logs to identify bottlenecks and optimize your code.
Introducing PyLogger
With these benefits in mind, I set out to build a custom logging class that would meet all my requirements. The result is PyLogger
, a Python logging class that aims to make logging both powerful and user-friendly.
Key Features
Below are some of the key features that make pylogger
appealing:
- Flexible Continue reading