Frequently Asked Questions

General

What is Logly?

Logly is a high-performance logging library for Python powered by a Rust-native engine. It provides structured logging, flexible sinks, modern developer-friendly APIs, and comprehensive integrations with popular frameworks.

Why use Logly over stdlib logging?

• Rust-native performance for high-throughput logging
• 11 built-in log levels (including SUCCESS, NOTICE, FAIL, AUDIT)
• Automatic file rotation with size/time/clock policies
• Built-in compression (GZIP, ZIP, bz2, XZ, Zstd)
• Retention policies with automatic cleanup
• Context binding for structured logging
• Exception catching decorator pattern
• Framework integrations (FastAPI, Django, Rich, etc.)
• Zero configuration with sensible defaults

Is Logly production-ready?

Yes. Logly is built for high-performance, production-grade logging with:

• Zero unsafe Rust code
• Comprehensive test suite (185+ Rust tests, 247+ Python tests)
• Thread-safe concurrent operations
• Memory-efficient queue-based async logging
• Built-in error handling and recovery

Installation

How do I install Logly?

# uv (recommended)
uv add logly

# pip
pip install logly

What Python versions are supported?

Logly supports Python 3.10 and newer.

Do I need Rust installed?

No. Logly ships with pre-built binaries. You only need Rust if building from source.

Configuration

How do I add a file sink?

from logly import logger

logger.add("app.log", level="INFO")

How do I rotate files?

from logly import logger

# Size-based
logger.add("app.log", rotation="100 MB")

# Time-based
logger.add("app.log", rotation="daily")

# Clock-based
logger.add("app.log", rotation="00:00")  # Midnight

How do I compress old logs?

from logly import logger

logger.add(
    "app.log",
    rotation="daily",
    compression="gzip",  # gzip, zip, bz2, xz, zstd
)

How do I set retention policies?

from logly import logger

# Keep last 30 days
logger.add("app.log", retention="30 days")

# Keep last 100 MB
logger.add("app.log", retention="100 MB")

# Keep last 10 files
logger.add("app.log", retention=10)

Usage

How do I add context to logs?

from logly import logger

# Bind context
logger.bind(user_id="12345").info("User logged in")

# Scoped context
with logger.contextualize(request_id="abc"):
    logger.info("Processing request")
    logger.info("Request complete")

How do I catch exceptions?

from logly import logger

# As decorator
@logger.catch
def risky_operation():
    ...

# As context manager
with logger.catch():
    risky_operation()

# With exclude
@logger.catch(exclude=ValueError)
def another_operation():
    ...

How do I use lazy evaluation?

from logly import logger

# Lazy format
logger.opt(lazy=True).debug("Result: {}", lambda: expensive_computation())

How do I log JSON?

from logly import logger

logger.add("app.json", serialize=True)

How do I parse log files?

from logly import logger

# Parse with pattern
entries = logger.parse(
    "app.log",
    pattern="{time:YYYY-MM-DD HH:mm:ss} | {level} | {message}"
)

Integrations

How do I use with FastAPI?

from fastapi import FastAPI
from logly.integrations.fastapi import LoglyMiddleware

app = FastAPI()
app.add_middleware(LoglyMiddleware)

How do I use with Django?

# settings.py
LOGGING = {
    "version": 1,
    "handlers": {
        "logly": {
            "class": "logly.integrations.django.DjangoLoglyHandler",
        },
    },
    "root": {
        "handlers": ["logly"],
        "level": "DEBUG",
    },
}

How do I use with Rich?

from logly.integrations.rich import install_rich_handler

install_rich_handler()

Performance

How do I improve logging performance?

1. Use lazy evaluation for expensive computations
2. Use enqueue=True for I/O-bound sinks
3. Set appropriate log levels to filter messages early
4. Use simpler formats in high-throughput scenarios
5. Batch operations when possible

What is the overhead of Logly?

Logly adds minimal overhead:

• Synchronous mode: < 1μs per log call
• Enqueue mode: ~5μs per log call (queue overhead)
• Rust engine: Native performance for formatting and I/O

Troubleshooting

No output appears

See Troubleshooting: No output.

Messages appear twice

See Troubleshooting: Messages appear twice.

Memory usage growing

See Troubleshooting: Memory usage growing.

More Questions?

• Check the API Reference
• Read the Guides
• Compare with stdlib logging