What methods and tools do you use for log collection and analysis in your projects?

For collecting and analyzing logs in Python projects, I usually use the following methods and tools:

• logging module — the standard way of logging in Python. It allows configuring log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL), message formats, and handlers (files, console, remote servers).

• Log rotation using logging.handlers.RotatingFileHandler or TimedRotatingFileHandler to manage log size and retention time.

• External log collection systems — integration with ELK Stack (Elasticsearch, Logstash, Kibana), Graylog, or cloud services (e.g., Sentry, Datadog) for centralized storage and analysis.

• Log analysis — using Kibana for visualization, filtering, and searching logs.

• Example of basic logging setup in Python:

import logging

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    filename='app.log',
    filemode='a'
)

logging.info('Application started')

Thus, by combining Python's standard tools and external systems, you can effectively collect and analyze logs for monitoring and debugging applications.