LogEverything Documentation

PyPI version Python versions Build Status Coverage License: MIT

High-performance, production-ready Python logging with zero configuration.

LogEverything is a comprehensive, high-performance Python logging library designed to provide detailed logging with minimal code changes and exceptional performance. Simply add decorators to your functions for automatic, comprehensive logging with industry-leading performance.

✨ Key Features

🚀 High Performance

  • 10k ops/sec core logging throughput

  • 7.9k ops/sec print capture throughput

  • 454 ops/sec async-native logging with task isolation

  • <0.5ms decorator overhead

  • Zero overhead when logging is disabled

🛡️ Smart & Safe

  • Zero configuration - works immediately with intelligent defaults

  • Automatic thread safety with smart isolation

  • Async task isolation prevents logging contamination

🎨 Beautiful Output

  • Rich visual formatting with colors and symbols

  • Cross-platform terminal support

  • Hierarchical indentation and aligned columns

⚡ Modern API

  • Unified @log decorator that adapts to any context

  • Smart logger selection with the using parameter

  • Intelligent type casting between sync/async loggers and functions

  • AsyncLogger class for async applications

  • Drop-in replacement for Python’s logging module

🔗 Smart Binding

  • Loguru-style binding with log.bind(key=value)

  • Registry-safe - bound loggers don’t pollute global registry

  • Memory-safe - automatic cleanup with no manual management

  • Additive context - chain bindings for rich structured data

🔗 Distributed & Framework Integrations

  • Correlation IDs propagated across requests and threads

  • ASGI / WSGI middleware for FastAPI, Starlette, Flask, Django

  • Celery signal-based task logging with correlation propagation

  • Log transports (HTTP, TCP, UDP) ship logs to a central collector

📊 Monitoring Dashboard

  • Multi-page layout with sidebar navigation (Overview, Logs, Operations, System)

  • Web-based dashboard with CPU/memory trend charts and log distribution

  • Hierarchical log tree view with expand/collapse and duration badges

  • Operation analytics with failure rates and duration tracking

  • Time-range filtering, full-text log search, and JSON data export

  • Auto-refresh toggle, keyboard shortcuts, dark/light themes

🌐 Production Ready

  • Comprehensive test suite with 65% coverage (395 tests)

  • Structured logging with JSON output

  • Monitoring API with ingestion endpoint and real-time WebSocket streaming

Quick Start

Installation

pip install logeverything

Basic Usage

Logger Classes (Recommended)

from logeverything import Logger

# Simple logging
log = Logger("my_app")
log.info("Application started")
log.warning("This is a warning")
log.error("Something went wrong")

Output:

2026-05-01 05:38:52 | [  ℹ️ INFO  ] | my_app     | Application started
2026-05-01 05:38:52 | [⚠️ WARNING ] | my_app     | This is a warning
2026-05-01 05:38:52 | [ ❌ ERROR  ] | my_app     | Something went wrong

Structured Logging with Binding

from logeverything import Logger

# Create a base logger
log = Logger("api_service")

# Bind context for structured logging
user_log = log.bind(user_id=12345, session_id="abc123")
user_log.info("User logged in")

# Chain bindings for richer context
request_log = user_log.bind(request_id="req-789", endpoint="/api/users")
request_log.info("Processing API request")

# Original logger unchanged
log.info("Service status check")

Output:

2026-05-01 05:38:52 | [  ℹ️ INFO  ] | api_service | [user_id=12345 | session_id=abc123] User logged in
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | api_service | [user_id=12345 | session_id=abc123 | request_id=req-789 | endpoint=/api/users] Processing API request
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | api_service | Service status check

Smart Decorators

from logeverything import Logger
from logeverything.decorators import log

# Create a logger
app_logger = Logger("my_app")

@log(using="my_app")  # Use specific logger
def calculate_total(a, b):
    """Calculate total with targeted logging."""
    return a + b

@log  # Automatic logger selection
def process_data(items):
    """Process data with automatic logger selection."""
    return [item * 2 for item in items]

result1 = calculate_total(5, 10)
result2 = process_data([1, 2, 3])
print(f"Results: {result1}, {result2}")

Output:

2026-05-01 05:38:52 | [  ℹ️ INFO  ] | my_app     | 🔵 CALL calculate_total(a=5, b=10) [tmpsbom8uai.py:62]
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | my_app     | ✅ DONE calculate_total (4.27ms) ➜ 15
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | my_app     | 🔵 CALL process_data(items=[1, 2, 3]) [tmpsbom8uai.py:63]
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | my_app     | ✅ DONE process_data (0.00ms) ➜ [2, 4, 6]
Results: 15, [2, 4, 6]

Async Applications

import asyncio
from logeverything.asyncio import AsyncLogger

async def main():
    log = AsyncLogger("async_app")

    log.info("Starting async operation")
    await asyncio.sleep(0.1)  # Simulate async work
    log.info("Operation completed")

    return "Done"

result = await main()
print(f"Result: {result}")

Output:

2026-05-01 05:38:52 | [  ℹ️ INFO  ] | async_app  | Starting async operation
2026-05-01 05:38:52 | [  ℹ️ INFO  ] | async_app  | Operation completed
Result: Done

Performance Comparison

LogEverything delivers solid performance across all logging operations:

Performance Benchmarks

Component

Throughput

Avg Latency

Core Logging

10,027 ops/sec

0.10 ms

Print Capture

7,896 ops/sec

0.13 ms

Async Logging (decorator)

454 ops/sec

2.20 ms

Async Queue Handler

7,565 ops/sec

0.13 ms

Decorator Overhead (@log_function)

2,500 ops/sec

0.40 ms

Why LogEverything?

Zero Configuration

Works immediately with intelligent defaults that adapt to your environment

High Performance

Industry-leading performance with automatic optimizations and fast-path execution

Thread Safe

Automatic isolation prevents logging contamination in concurrent applications

Beautiful Output

Color themes, visual hierarchy, Unicode symbols, and smart formatting

Async Optimized

Native async/await support with 6.8x performance improvement

Production Ready

Optimized for high-throughput applications and web services

Documentation

Getting Started

User Guide

Monitoring Dashboard

Advanced Topics

API Reference

Indices and tables