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Library to enrich structured logs

Project description

log-enricher

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This is a log enricher, useful for adding custom fields to log records.

This was developed at GRID for use with our python backend services and intended to emit structured logs.

installation

pip install log-enricher

configuration

The log-enricher takes in a list of functions that return a dictionary:

import os

from log_enricher import initialize_logging, Level
from app import current_user_context

def main():
    extra_log_properties = {
        "app_version": os.environ.get("APP_VERSION", "N/A"),
        "release_stage": os.environ.get("RELEASE_STAGE", "unknown"),
    }
    initialize_logging(
        loggers=["uvicorn", "sqlalchemy"],
        structured_logs=os.environ.get("STRUCTURED_LOGS", True),
        log_level=Level.INFO,
        enrichers=[current_user_context, lambda: extra_log_properties],
    )

Logs will be output in a structured JSON format if structured_logs is True, or in a plain, console-friendly format if it is False.

enrichers

To build a log enricher, make a subclass of Enricher, or Callable, and implement __call__(). Any method returning a dict can be used to enrich log records. See log_enricher/enrichers.py. The key-value pairs in the dict are added as attribute-value pairs to the log record. Of course, any method calls in the enrichers need to work in any subsequent context the logging system is called.

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