
Fastapi Logging
- 1 installs
- 3 repo stars
- Updated March 24, 2026
- agusmdev/burntop
fastapi-logging is a Claude Code skill that configures structured JSON logging with correlation IDs and request context for a FastAPI app.
About
fastapi-logging is a Claude Code skill that configures structured JSON logging with correlation IDs and request context for a FastAPI app. It provides a logging.py with a custom JSON formatter, a correlation-ID middleware for request tracing, dev vs production formats, and suppression of noisy third-party loggers. A developer uses it while building a FastAPI backend to get traceable, structured logs.
- Sets up structured JSON logging for a FastAPI application
- Adds correlation-ID middleware for request tracing
- Provides a CustomJsonFormatter and dev vs production log formats
Fastapi Logging by the numbers
- 1 all-time installs (skills.sh)
- Ranked #3,830 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
- Data as of Jul 7, 2026 (Skillselion catalog sync)
fastapi-logging capabilities & compatibility
- Capabilities
- structured logging · request tracing · api development
- Use cases
- api development · devops
What fastapi-logging says it does
Configure structured JSON logging with correlation IDs and request context for FastAPI
This skill covers setting up structured JSON logging with correlation ID middleware for request tracing across the application.
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| Installs | 1 |
|---|---|
| repo stars | ★ 3 |
| Last updated | March 24, 2026 |
| Repository | agusmdev/burntop ↗ |
What it does
Configure structured JSON logging with correlation IDs and request context for a FastAPI backend.
When should I use this skill?
setting up logging and request tracing in a FastAPI backend
What you get
Structured JSON logs with per-request correlation IDs and quieted third-party loggers.
- logging.py
- correlation_id middleware
By the numbers
- 2 files created (logging.py + correlation_id.py)
Files
FastAPI Logging & Correlation IDs
Overview
This skill covers setting up structured JSON logging with correlation ID middleware for request tracing across the application.
Create logging.py
Create src/app/logging.py:
import logging
import sys
from typing import Any
from pythonjsonlogger import jsonlogger
from app.config import settings
class CustomJsonFormatter(jsonlogger.JsonFormatter):
"""
Custom JSON formatter that adds standard fields to all log records.
Output format:
{
"timestamp": "2025-01-05T12:00:00.000Z",
"level": "INFO",
"message": "Request completed",
"logger": "app.api.v1.items",
"correlation_id": "uuid",
...additional fields
}
"""
def add_fields(
self,
log_record: dict[str, Any],
record: logging.LogRecord,
message_dict: dict[str, Any],
) -> None:
super().add_fields(log_record, record, message_dict)
# Standard fields
log_record["timestamp"] = self.formatTime(record, self.datefmt)
log_record["level"] = record.levelname
log_record["logger"] = record.name
# Remove default fields we're replacing
log_record.pop("levelname", None)
log_record.pop("name", None)
# Add correlation_id from context if available
from app.middleware.correlation_id import get_correlation_id
correlation_id = get_correlation_id()
if correlation_id:
log_record["correlation_id"] = correlation_id
def setup_logging() -> None:
"""
Configure application logging.
Call this early in application startup, before creating the FastAPI app.
Configures:
- JSON format for production (LOG_JSON_FORMAT=true)
- Human-readable format for development
- Log level from settings
- Suppresses noisy third-party loggers
"""
log_level = getattr(logging, settings.log_level.upper(), logging.INFO)
# Root logger configuration
root_logger = logging.getLogger()
root_logger.setLevel(log_level)
# Remove existing handlers
root_logger.handlers.clear()
# Create handler
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(log_level)
if settings.log_json_format:
# JSON format for production
formatter = CustomJsonFormatter(
fmt="%(timestamp)s %(level)s %(name)s %(message)s",
datefmt="%Y-%m-%dT%H:%M:%S.%f",
)
else:
# Human-readable format for development
formatter = logging.Formatter(
fmt="%(asctime)s | %(levelname)-8s | %(name)s | %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
handler.setFormatter(formatter)
root_logger.addHandler(handler)
# Suppress noisy loggers
logging.getLogger("uvicorn.access").setLevel(logging.WARNING)
logging.getLogger("uvicorn.error").setLevel(logging.WARNING)
logging.getLogger("sqlalchemy.engine").setLevel(
logging.INFO if settings.database_echo else logging.WARNING
)
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("httpcore").setLevel(logging.WARNING)
def get_logger(name: str) -> logging.Logger:
"""
Get a logger instance for a module.
Usage:
logger = get_logger(__name__)
logger.info("Something happened", extra={"user_id": "123"})
Args:
name: Logger name (typically __name__)
Returns:
Configured logger instance
"""
return logging.getLogger(name)Create middleware/correlation_id.py
Create src/app/middleware/correlation_id.py:
import contextvars
from uuid import uuid4
from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint
from starlette.requests import Request
from starlette.responses import Response
# Context variable to store correlation ID for the current request
_correlation_id_ctx: contextvars.ContextVar[str | None] = contextvars.ContextVar(
"correlation_id",
default=None,
)
# Header name for correlation ID
CORRELATION_ID_HEADER = "X-Correlation-ID"
def get_correlation_id() -> str | None:
"""
Get the correlation ID for the current request context.
Returns None if called outside of a request context.
Usage:
from app.middleware.correlation_id import get_correlation_id
correlation_id = get_correlation_id()
logger.info("Processing", extra={"correlation_id": correlation_id})
"""
return _correlation_id_ctx.get()
def set_correlation_id(correlation_id: str) -> None:
"""
Set the correlation ID for the current context.
Typically called by middleware, but can be used in tests
or background tasks.
"""
_correlation_id_ctx.set(correlation_id)
class CorrelationIdMiddleware(BaseHTTPMiddleware):
"""
Middleware that manages correlation IDs for request tracing.
Behavior:
1. Checks for X-Correlation-ID header in incoming request
2. If present, uses that ID (for distributed tracing)
3. If absent, generates a new UUID
4. Stores ID in context variable (accessible via get_correlation_id())
5. Adds ID to response headers
This enables tracing requests across:
- Multiple services (when ID is passed in headers)
- Log aggregation systems
- Error tracking systems
"""
async def dispatch(
self,
request: Request,
call_next: RequestResponseEndpoint,
) -> Response:
# Get correlation ID from header or generate new one
correlation_id = request.headers.get(CORRELATION_ID_HEADER)
if not correlation_id:
correlation_id = str(uuid4())
# Store in context variable
set_correlation_id(correlation_id)
# Process request
response = await call_next(request)
# Add to response headers
response.headers[CORRELATION_ID_HEADER] = correlation_id
return responseCreate middleware/__init__.py
Create src/app/middleware/__init__.py:
from app.middleware.correlation_id import (
CORRELATION_ID_HEADER,
CorrelationIdMiddleware,
get_correlation_id,
set_correlation_id,
)
__all__ = [
"CORRELATION_ID_HEADER",
"CorrelationIdMiddleware",
"get_correlation_id",
"set_correlation_id",
]Usage in Application
In main.py
from app.logging import setup_logging
from app.middleware import CorrelationIdMiddleware
# Setup logging BEFORE creating app
setup_logging()
def create_app() -> FastAPI:
app = FastAPI(...)
# Add correlation ID middleware
app.add_middleware(CorrelationIdMiddleware)
return appIn Services/Routers
from app.logging import get_logger
logger = get_logger(__name__)
class ItemService:
async def create(self, obj_in: ItemCreate) -> Item:
logger.info(
"Creating item",
extra={
"item_name": obj_in.name,
"category_id": str(obj_in.category_id),
},
)
item = await self._repository.create(obj_in)
logger.info(
"Item created successfully",
extra={"item_id": str(item.id)},
)
return itemIn Exception Handlers
from app.middleware.correlation_id import get_correlation_id
async def app_exception_handler(request: Request, exc: AppException):
correlation_id = get_correlation_id()
logger.warning(
"Application error",
extra={
"error_code": exc.error_code,
"correlation_id": correlation_id,
},
)
return JSONResponse(
content={
"detail": exc.message,
"correlation_id": correlation_id,
...
}
)Log Output Examples
JSON Format (Production)
{
"timestamp": "2025-01-05T12:00:00.123456",
"level": "INFO",
"logger": "app.items.service",
"message": "Creating item",
"correlation_id": "550e8400-e29b-41d4-a716-446655440000",
"item_name": "Widget",
"category_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}Human-Readable Format (Development)
2025-01-05 12:00:00 | INFO | app.items.service | Creating itemLogging Best Practices
1. Use Appropriate Log Levels
| Level | Use Case |
|---|---|
DEBUG | Detailed diagnostic information |
INFO | Routine operations, state changes |
WARNING | Unexpected but handled situations |
ERROR | Errors that need attention |
CRITICAL | System failures |
2. Include Contextual Information
# Good - includes context
logger.info(
"Order processed",
extra={
"order_id": str(order.id),
"total": order.total,
"items_count": len(order.items),
},
)
# Bad - no context
logger.info("Order processed")3. Log at Boundaries
- Log at entry/exit of services
- Log external API calls
- Log database operations (sparingly)
4. Don't Log Sensitive Data
# Bad - logs password
logger.info(f"User login: {user.email}, password: {user.password}")
# Good - no sensitive data
logger.info("User login attempt", extra={"email": user.email})5. Use Structured Fields
# Good - structured
logger.error(
"Database query failed",
extra={
"query": "SELECT * FROM items",
"duration_ms": 1500,
"error": str(e),
},
)
# Bad - unstructured
logger.error(f"Database query failed: {e}")Request Logging Middleware (Optional)
For detailed request/response logging:
import time
from app.logging import get_logger
logger = get_logger("app.http")
class RequestLoggingMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
start_time = time.perf_counter()
response = await call_next(request)
duration_ms = (time.perf_counter() - start_time) * 1000
logger.info(
"Request completed",
extra={
"method": request.method,
"path": request.url.path,
"status_code": response.status_code,
"duration_ms": round(duration_ms, 2),
},
)
return responseRelated skills
FAQ
What logging format does fastapi-logging produce?
JSON format in production (LOG_JSON_FORMAT=true) and a human-readable format in development, both via a CustomJsonFormatter.
How does it trace requests?
A correlation-ID middleware stores a per-request UUID in a context var that the formatter injects into every log record.