LogFrog is an efficient, thread-safe logging library in Python. This nimble logger, designed with simplicity, offers non-blocking, asynchronous logging, making it perfect for applications that prioritize performance.
- Asynchronous Logging: Dispatch logs to a separate thread, freeing your application from waiting on IO operations.
- Log Levels: Differentiate the importance of messages with
INFO,DEBUG,WARNING,ERROR, andCRITICALlevels. - Function Logging: Automatically log function calls, tracking names, arguments, and return values.
- Stack Tracing: Log the current stack trace, invaluable for debugging and understanding complex code execution paths.
pip install logfrog
from logfrog import LogFrog
logger = LogFrog(filename="app.log")
# Dispatch logs
logger.info("Info message")
logger.debug("Debug message")
logger.warning("Warning message")
logger.error("Error message")
logger.critical("Critical message")
# Log function calls
@logger.log_function
def test_function(a, b):
return a + b
test_function(2, 3)
# Log current stack
logger.log_stack()
# Gracefully stop the logger
logger.stop()Thanks for making it this far! Here are some pointers to get you started -
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Configurable Log Formats: Allow users to customize the format of the log output, such as including the file name and line number, or changing the timestamp format.
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Remote Logging: Add support for logging to remote systems, such as logging servers or cloud storage.
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Performance Metrics: Log system performance metrics like memory and CPU usage.
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Integration with Monitoring Tools: Provide easy integration with popular monitoring and alerting tools.
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Log Rotation: Implement automatic log rotation to prevent logs from consuming too much disk space.
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Filtering and Searching: Provide capabilities to filter and search logs based on certain criteria, such as log level, timestamp, or content.
Thank you for your interest in LogFrog. We look forward to your contributions!