structured-logger-railway 1.2.0

A flexible structured JSON logger for Python applications

Structured Logger

A flexible, configurable structured JSON logger for Python applications. Perfect for cloud deployments, containerized applications, and log aggregation systems like ELK, Splunk, or cloud logging services.

Features

• 🚀 Structured JSON logging with automatic serialization of complex objects
• ⚙️ Highly configurable with sensible defaults
• 🌍 Environment-aware formatting (JSON for production, readable for development)
• 🔧 Custom field support for tracing, user context, and more
• 📦 Easy integration with existing Python logging
• 🎯 Type-safe with full type hints
• ⚡ Zero dependencies - uses only Python standard library

Installation

pip install structured-logger-railway

Quick Start

Basic Usage

from structured_logger import get_logger

logger = get_logger(__name__)

logger.info("Application started")
logger.error("Something went wrong", extra={"user_id": "12345"})

Output in development:

2024-01-15 10:30:45,123 [INFO] myapp: Application started
2024-01-15 10:30:45,124 [ERROR] myapp: Something went wrong

Output in production:

{"time": "2024-01-15 10:30:45,123", "level": "INFO", "message": "Application started", "module": "myapp"}
{"time": "2024-01-15 10:30:45,124", "level": "ERROR", "message": "Something went wrong", "module": "myapp", "user_id": "12345"}

Custom Configuration

from structured_logger import get_logger, LoggerConfig

# Custom configuration
config = LoggerConfig(
    custom_fields=["user_id", "request_id", "trace_id"],
    production_env_vars=["ENV", "ENVIRONMENT"],
    production_env_values=["prod", "production", "staging"],
    dev_format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
)

logger = get_logger(__name__, config=config)

Force JSON or Development Format

# Always use JSON formatting
logger = get_logger(__name__, force_json=True)

# Always use development formatting
logger = get_logger(__name__, force_dev=True)

Root Logger Setup

from structured_logger import setup_root_logger

# Setup root logger for entire application
setup_root_logger()

# Now all loggers will use structured format
import logging
logger = logging.getLogger("myapp")
logger.info("This will be structured")

Advanced Usage

Custom Serializers

from datetime import datetime
from structured_logger import LoggerConfig, get_logger

def serialize_datetime(dt):
    return dt.isoformat()

config = LoggerConfig(
    custom_serializers={
        datetime: serialize_datetime
    }
)

logger = get_logger(__name__, config=config)
logger.info("Current time", extra={"timestamp": datetime.now()})

Context Fields

import logging
from structured_logger import get_logger

logger = get_logger(__name__)

# Add context to log record
class ContextFilter(logging.Filter):
    def filter(self, record):
        record.user_id = getattr(self, 'user_id', None)
        record.request_id = getattr(self, 'request_id', None)
        return True

context_filter = ContextFilter()
logger.addFilter(context_filter)

# Set context
context_filter.user_id = "user123"
context_filter.request_id = "req456"

logger.info("Processing request")  # Will include user_id and request_id

Exception Logging

try:
    raise ValueError("Something went wrong")
except Exception:
    logger.exception("An error occurred", extra={"operation": "data_processing"})

JSON Output:

{
  "time": "2024-01-15 10:30:45,123",
  "level": "ERROR", 
  "message": "An error occurred",
  "module": "myapp",
  "operation": "data_processing",
  "exception": "Traceback (most recent call last):\n  File \"example.py\", line 2, in <module>\n    raise ValueError(\"Something went wrong\")\nValueError: Something went wrong"
}

Configuration Options

LoggerConfig Parameters

Parameter	Type	Default	Description
production_env_vars	List[str]	["RAILWAY_ENVIRONMENT", "ENV", "ENVIRONMENT", "NODE_ENV"]	Environment variables to check for production
production_env_values	List[str]	["prod", "production", "staging"]	Values that indicate production environment
log_level_env_var	str	"LOG_LEVEL"	Environment variable for log level
default_log_level	str	"INFO"	Default log level
custom_fields	List[str]	["user_id", "company_id", "request_id", "trace_id", "span_id"]	Fields to extract from log records
time_format	Optional[str]	None	Custom time format
dev_format	str	"%(asctime)s [%(levelname)s] %(name)s: %(message)s"	Format string for development
custom_serializers	Dict[type, Callable]	{}	Custom serializers for specific types
include_extra_attrs	bool	True	Whether to include extra attributes
excluded_attrs	List[str]	Standard logging fields	Fields to exclude from extra attributes

Environment Variables

Variable	Description	Default
LOG_LEVEL	Set logging level	INFO
RAILWAY_ENVIRONMENT	Railway deployment indicator	-
ENV	Environment indicator	-
ENVIRONMENT	Environment indicator	-
NODE_ENV	Node.js style environment	-

Framework Integration

Flask

from flask import Flask, request, g
from structured_logger import get_logger
import uuid

app = Flask(__name__)
logger = get_logger(__name__)

@app.before_request
def before_request():
    g.request_id = str(uuid.uuid4())

@app.after_request
def after_request(response):
    logger.info(
        "Request processed",
        extra={
            "request_id": getattr(g, 'request_id', None),
            "method": request.method,
            "path": request.path,
            "status": response.status_code
        }
    )
    return response

FastAPI

from fastapi import FastAPI, Request
from structured_logger import get_logger
import uuid
import time

app = FastAPI()
logger = get_logger(__name__)

@app.middleware("http")
async def log_requests(request: Request, call_next):
    request_id = str(uuid.uuid4())
    start_time = time.time()
    
    response = await call_next(request)
    
    process_time = time.time() - start_time
    logger.info(
        "Request processed",
        extra={
            "request_id": request_id,
            "method": request.method,
            "path": request.url.path,
            "status": response.status_code,
            "duration": process_time
        }
    )
    
    return response

Django

# settings.py
LOGGING = {
    'version': 1,
    'disable_existing_loggers': False,
    'handlers': {
        'structured': {
            'level': 'INFO',
            'class': 'structured_logger.logger.StructuredLogHandler',
        },
    },
    'loggers': {
        'django': {
            'handlers': ['structured'],
            'level': 'INFO',
            'propagate': True,
        },
        'myapp': {
            'handlers': ['structured'],
            'level': 'INFO',
            'propagate': True,
        },
    },
}

Railway.app Compatibility

This library maintains full compatibility with Railway.app deployments. The original Railway-specific functionality is preserved:

# These work exactly like before
from structured_logger import get_railway_logger

logger = get_railway_logger(__name__)
logger.info("Deployed to Railway!")

Development

# Clone the repository
git clone https://github.com/zee229/structured-logger.git
cd structured-logger

# Install development dependencies
pip install -e .

# Run examples
python examples/basic_usage.py
python examples/custom_config.py

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

1.0.0

• Initial release
• Flexible configuration system
• Environment-aware formatting
• Custom serializers support
• Full backward compatibility with Railway logger