Quick Start Examples
This page demonstrates Pretty-Loguru's quick start examples.
Hello World
The simplest way to use:
python
#!/usr/bin/env python3
"""
🎯 Pretty-Loguru Hello World
The simplest usage example - beautify logs with just 3 lines of code
"""
from pretty_loguru import create_logger
# Create logger
logger = create_logger("hello_world")
# Start logging
logger.info("Hello, Pretty-Loguru! 🌟")
logger.success("Congratulations! You've successfully used Pretty-Loguru")
logger.warning("This is a warning message")
logger.error("This is an error message")Output:
2025-07-12 21:47:50 | INFO | hello_world:main:27 - Hello, Pretty-Loguru! 🌟
2025-07-12 21:47:50 | SUCCESS | hello_world:main:28 - Congratulations! You've successfully used Pretty-Loguru
2025-07-12 21:47:50 | WARNING | hello_world:main:29 - This is a warning message
2025-07-12 21:47:50 | ERROR | hello_world:main:30 - This is an error messageConsole Logging
Console-only output configuration:
python
from pretty_loguru import create_logger
# Create console-only logger (no log_path specified)
logger = create_logger("console_app")
# Basic log levels
logger.debug("Debug message - detailed info for development")
logger.info("Info message - normal program operation info")
logger.success("Success message - operation completed successfully")
logger.warning("Warning message - needs attention but doesn't affect operation")
logger.error("Error message - error occurred but program can continue")
logger.critical("Critical error - program may not continue")
# Use visual features
logger.block(
"System Status",
[
"🟢 Service Status: Running",
"📊 CPU Usage: 45%",
"💾 Memory Usage: 2.3GB / 8GB",
"🌡️ System Temperature: Normal"
],
border_style="green"
)File Logging
Output to both console and file:
python
from pretty_loguru import create_logger
# Create logger that outputs to both console and file
logger = create_logger(
"file_app",
log_path="logs", # Log directory
rotation="1 day", # Daily rotation
retention="7 days", # Keep for 7 days
compression="zip" # Compress old files
)
# Log different types of messages
logger.info("Application started")
logger.debug("Loading config file: config.json")
logger.success("Database connection successful")
logger.warning("Cache about to expire")
logger.error("Unable to connect to external API")
# ASCII art header (appears in both console and file)
logger.ascii_header("APP START", font="small")
# Structured logging
logger.block(
"Startup Info",
[
"Version: 1.0.0",
"Environment: Production",
"Config: Loaded",
"Services: All running"
]
)
# Target-specific output
logger.console_info("This only shows in console")
logger.file_info("This only goes to the log file")Configuration Templates
Using predefined configuration templates:
python
from pretty_loguru import ConfigTemplates
# Development configuration - detailed logs for debugging
dev_config = ConfigTemplates.development()
dev_logger = dev_config.apply_to("dev_app")
# Production configuration - optimized for performance
prod_config = ConfigTemplates.production()
prod_logger = prod_config.apply_to("prod_app")
# Daily rotation - perfect for regular applications
daily_config = ConfigTemplates.daily()
daily_logger = daily_config.apply_to("daily_app")
# Quick comparison
dev_logger.debug("This appears in development") # ✅ Logged
prod_logger.debug("This won't appear in production") # ❌ Not logged
# Visual demonstration
dev_logger.console_block(
"Development Mode",
[
"Log Level: DEBUG",
"Rotation: 10 MB",
"Retention: 7 days",
"Compression: None"
],
border_style="yellow"
)
prod_logger.console_block(
"Production Mode",
[
"Log Level: INFO",
"Rotation: 50 MB",
"Retention: 30 days",
"Compression: ZIP"
],
border_style="green"
)Visual Features
Quick examples of visual features:
python
from pretty_loguru import create_logger
logger = create_logger("visual_demo")
# 1. Rich Blocks
logger.block(
"📊 Server Statistics",
[
"Uptime: 15 days",
"Requests: 1.2M",
"Errors: 0.01%",
"Avg Response: 45ms"
],
border_style="blue"
)
# 2. Panel with Rich objects
from rich.table import Table
table = Table(title="Performance Metrics")
table.add_column("Metric", style="cyan")
table.add_column("Value", style="green")
table.add_row("QPS", "1,500")
table.add_row("Latency", "25ms")
logger.panel(
table,
title="Real-time Performance",
border_style="green"
)
# 3. ASCII Art Headers
logger.ascii_header("WELCOME", font="slant", border_style="purple")
# 4. Combined visual elements
logger.ascii_block(
"Deployment Status",
[
"✅ Code: Updated",
"✅ Tests: Passed",
"✅ Build: Successful",
"✅ Deploy: Complete"
],
ascii_header="DEPLOYED",
ascii_font="small",
border_style="green"
)Error Handling
Basic error handling with Pretty-Loguru:
python
from pretty_loguru import create_logger
logger = create_logger("error_demo", log_path="logs/errors")
# Automatic exception catching
@logger.catch
def risky_function(x):
"""This function will log exceptions automatically"""
return 10 / x
# Test the function
try:
result = risky_function(0) # This will cause an error
except Exception:
# The error is already logged by @logger.catch
pass
# Manual error logging
try:
# Some operation that might fail
import requests
response = requests.get("https://api.example.com", timeout=1)
except Exception as e:
logger.error(f"API call failed: {e}")
logger.exception("Detailed error information:")
# Visual error report
logger.block(
"❌ Error Report",
[
f"Type: {type(e).__name__}",
f"Message: {str(e)}",
"Action: Check network connection",
"Retry: In 5 minutes"
],
border_style="red"
)FastAPI Quick Start
Quick FastAPI integration:
python
from fastapi import FastAPI
from pretty_loguru.integrations.fastapi import setup_fastapi_logging
# Create FastAPI app
app = FastAPI()
# Setup Pretty-Loguru logging
logger = setup_fastapi_logging(app, log_path="logs/api")
@app.get("/")
async def root():
logger.info("Root endpoint accessed")
return {"message": "Hello World"}
@app.get("/status")
async def status():
# Visual status display
logger.console_block(
"API Status",
[
"🟢 API: Online",
"🟢 Database: Connected",
"🟢 Cache: Active",
"📊 Requests Today: 10,432"
],
border_style="green"
)
return {"status": "healthy"}
# Run with: uvicorn quickstart_api:app --reloadMulti-Logger Quick Start
Managing multiple loggers:
python
from pretty_loguru import create_logger, LoggerConfig
# Create a shared configuration
config = LoggerConfig(
level="INFO",
log_path="logs",
rotation="1 day",
retention="7 days"
)
# Create multiple loggers with the same config
app_logger = create_logger("app", config=config)
db_logger = create_logger("database", config=config)
api_logger = create_logger("api", config=config)
# Use different loggers for different components
app_logger.info("Application started")
db_logger.success("Database connected")
api_logger.warning("API rate limit approaching")
# Update all loggers at once
config.update(level="DEBUG") # All three loggers now log DEBUG messages
# Visual summary
from pretty_loguru import list_loggers
logger = create_logger("summary")
logger.console_block(
"Active Loggers",
list_loggers(),
border_style="cyan"
)Next Steps
Now that you've seen the basics, explore more:
- Basic Features - Core functionality in detail
- Visual Features - Rich blocks, ASCII art, and more
- Configuration - Advanced configuration options
- FastAPI Integration - Web framework integration