arlogi - Advanced Logging Library

arlogi is a robust, type-safe logging library for Python that extends the standard logging module with modern features, caller attribution, file rotation, and premium aesthetics.

Full Documentation

Features

• Caller Attribution: Track log calls across function boundaries using caller_depth.
• Custom TRACE Level: Level 5 logging for ultra-detailed debugging.
• Premium Colored Output: Uses rich for beautiful, readable console logs with automatic traceback support.
• Structured JSON Logging: Out-of-the-box support for JSON logging, file rotation, and log retention.
• Module-Specific Configuration: Easily set different log levels for different parts of your application.
• Dedicated Destination Loggers: Log specific events only to JSON or Syslog without cluttering the console.
• Type Safety: Fully type-checked with LoggerProtocol and supports modern Python types.

Installation

# Using uv (recommended)
uv add arlogi

# Or using pip
pip install arlogi

Usage

Basic Setup

from arlogi import setup_logging, get_logger

# 1. Initialize logging
setup_logging(level="INFO")

# 2. Get a logger
logger = get_logger("my_app")
logger.info("Application started", caller_depth=0)
logger.trace("This won't be visible because level is INFO")

Module-Specific Levels

from arlogi import setup_logging, TRACE

setup_logging(
    level="INFO",
    module_levels={
        "my_app.db": "DEBUG",
        "my_app.network": TRACE
    }
)

JSON File Rotation and Syslog

from arlogi import setup_logging

setup_logging(
    level="INFO",
    json_file_name="logs/app.jsonl",
    rotate_schedule="day",
    rotate_retention_count=7,
    use_syslog=True,
    syslog_address="/dev/log"
)

Dedicated Loggers

Sometimes you want to log specific data ONLY to a file or a remote system:

from arlogi import get_json_logger, get_syslog_logger, cleanup_json_logger

# Logs only to JSON, not to console
audit_logger = get_json_logger("audit", "logs/audit.jsonl")
audit_logger.info("User logged in", user_id=123)

# Logs only to Syslog
syslog_logger = get_syslog_logger("security")
syslog_logger.warning("Failed login attempt")

# Resource cleanup when done
cleanup_json_logger("audit")

Integration with Other Libraries

arlogi works seamlessly with any third‑party library that uses the standard logging module.

Default INFO when arlogi is not imported

If your application never imports arlogi, the standard logging defaults (WARNING) remain unchanged. To get a simple INFO level without pulling in arlogi, add a tiny bootstrap:

import logging
logging.basicConfig(level=logging.INFO)

Overriding the level when you do use arlogi

Initialize arlogi with setup_logging() early in your program. setup_logging() allows fine-grained control over levels and handlers.

Making third‑party libraries respect the chosen level

All libraries that obtain a logger via logging.getLogger(name) inherit the level from the nearest ancestor – usually the root logger configured via setup_logging(). If a library forces its own level, reset it:

import logging
logging.getLogger("some_lib").setLevel(logging.NOTSET)  # inherit from root

Quick bootstrap example

# bootstrap.py
import os, logging
from arlogi import setup_logging

def configure_logging():
    if os.getenv("USE_ARLOGI", "0") == "1":
        level = os.getenv("ARLOGI_LEVEL", "INFO").upper()
        setup_logging(level=level)
    else:
        logging.basicConfig(level=logging.INFO)

# main.py
from bootstrap import configure_logging
configure_logging()

With this pattern you get:

• Default INFO when arlogi is absent.
• Full control over the log level when you import arlogi.
• Automatic inheritance for any library that uses logging.

Using TRACE in your library

If you are developing a library and want to use the TRACE level:

1. The Safe Way (Recommended): Use logger.log(TRACE, ...) This works regardless of when your library is imported relative to arlogi setup.

   import logging
   try:
       from arlogi import TRACE
   except ImportError:
       TRACE = 5
   
   logger = logging.getLogger(__name__)
   
   def complex_operation():
       logger.log(TRACE, "Step 1 of complex operation...")
   

2. The method way: logger.trace(...) This only works if arlogi is configured before your library creates its logger instance.

Lazy Initialization (Safe Use of .trace)

If you must use .trace() in your library but aren't sure if arlogi is setup yet, you can use lazy initialization with LoggerProtocol for type safety:

from arlogi import LoggerProtocol, get_logger

_logger: LoggerProtocol | None = None

def log() -> LoggerProtocol:
    """Get or create the logger for this module lazily."""
    global _logger
    if _logger is None:
        _logger = get_logger("my_lib.cache")
    return _logger

Advanced Configuration

Centralized Logging Setup

For full control over console output, file paths, and remote handlers:

from arlogi import setup_logging

setup_logging(
    level="INFO",
    module_levels={"app.db": "DEBUG"},
    json_file_name="logs/app.jsonl",
    show_time=True,
    show_level=True,
    show_path=False
)

Direct Factory API

Alternatively, LoggerFactory.setup(...) provides the exact same functionality via the factory class:

from arlogi import LoggerFactory

LoggerFactory.setup(
    level="INFO",
    module_levels={"app.db": "DEBUG"}
)

Color Schemes

arlogi comes with a refined default color scheme:

• TRACE / DEBUG: Grey / Cyan
• INFO: Green
• WARNING: Yellow
• ERROR / CRITICAL: Red

Development

Run tests with pytest:

uv run pytest

Check code formatting and linting:

uv run ruff check .

Build local documentation:

uv run mkdocs build

License

MIT License - see LICENSE file for details.