fastapi-silk 1.0.5.1

SQL profiler middleware for FastAPI

FastAPI-Silk

Lightweight SQL profiling middleware for FastAPI + SQLAlchemy
Track query count, database time, and total request time per request.

Installation | Quick Start | How It Works | Development

Why FastAPI-Silk

Capability	Details
SQL instrumentation	setup_sql_profiler(engine) hooks into SQLAlchemy engine events (before_cursor_execute / after_cursor_execute) so SQL executed through that engine is captured per request.
Request-level metrics	Adds X-DB-Queries, X-DB-Time, and X-Total-Time response headers.
Slow query visibility	Logs queries slower than 0.1s to stdout for quick diagnostics.
Context isolation	Uses contextvars for per-request query storage.
Minimal setup	One profiler setup call + one middleware registration.

Installation

pip install fastapi-silk

PyPI: https://pypi.org/project/fastapi-silk/

Quick Start

from fastapi import FastAPI
from sqlalchemy import create_engine, text

from fastapi_silk import SQLDebugMiddleware, setup_sql_profiler, silk_router

app = FastAPI()
engine = create_engine("sqlite:///./app.db")

# Profiles SQL that goes through this engine
setup_sql_profiler(engine)
app.add_middleware(SQLDebugMiddleware)

# For the UI use
app.include_router(silk_router)

@app.get("/health")
def health() -> dict[str, bool]:
    with engine.connect() as conn:
        conn.execute(text("SELECT 1"))
    return {"ok": True}

Example response headers:

X-DB-Queries: 1
X-DB-Time: 0.0012s
X-Total-Time: 0.0049s

Docs

• Use /_silk link to move for docs where you can find all profiling requests with detailed data

How It Works

flowchart TD
  A[Incoming request] --> B[SQLDebugMiddleware starts request timer]
  B --> C[Endpoint runs SQL through profiled SQLAlchemy Engine]
  C --> D[setup_sql_profiler listeners capture query start/end]
  D --> E[Query data stored in request-local context]
  E --> F[Middleware sets X-DB-Queries, X-DB-Time, X-Total-Time]

Requirements

Item	Requirement
Python	>=3.10 (CI runs 3.10 through 3.14)
Framework	FastAPI
Database layer	SQLAlchemy Engine

Code Convention / Style

• Use Ruff for linting and formatting.
• Use MyPy (strict mode) for type checks.
• Keep changes small and typed where possible.

Development

Install dev dependencies and run checks:

uv sync --locked --all-extras --dev
make ci
python -m pytest

make ci runs:

• Ruff lint/format checks
• MyPy strict type checks

Contributing

1. Create a branch from development (for example, feature/<name> or fix/<name>).
2. Keep the pull request focused on a single change.
3. Add or update tests when behavior changes.
4. Run checks locally (make ci and python -m pytest).
5. Open a PR with a clear summary of what changed, why, and how it was tested.

Scope

FastAPI-Silk focuses on SQL profiling and request timing headers. It does not provide a built-in dashboard UI.

License

GNU General Public License v3.0 (GPL-3.0). See LICENSE.