sqlc — Generate Type-Safe Go Code from SQL

What it is

sqlc is a code generation tool that reads your SQL schema and query files, validates them, and produces type-safe Go functions. Instead of using an ORM or embedding SQL strings with manual type assertions, you write plain SQL and let sqlc generate the Go structs and methods. The generated code has zero runtime reflection and catches type errors at compile time.

sqlc is built for Go developers who prefer writing raw SQL over ORM abstractions. It supports PostgreSQL, MySQL, and SQLite, and integrates into standard Go build pipelines.

How it saves time or tokens

sqlc eliminates the boilerplate of hand-writing Go structs for query results and scanning rows into typed variables. A single sqlc generate command produces all the data access code from your SQL files. Schema changes are caught at generation time rather than at runtime, reducing debugging cycles. The generated code is straightforward and readable, so there is no ORM magic to debug.

How to use

1. Install sqlc: go install github.com/sqlc-dev/sqlc/cmd/sqlc@latest or brew install sqlc.
2. Create a sqlc.yaml config file and write your SQL schema and query files with sqlc annotations like -- name: GetUser :one.
3. Run sqlc generate to produce Go source files with typed functions for each query.

Example

-- schema.sql
CREATE TABLE users (
  id   SERIAL PRIMARY KEY,
  name TEXT NOT NULL,
  email TEXT NOT NULL
);

-- query.sql
-- name: GetUser :one
SELECT id, name, email FROM users WHERE id = $1;

-- name: ListUsers :many
SELECT id, name, email FROM users ORDER BY name;

-- name: CreateUser :one
INSERT INTO users (name, email) VALUES ($1, $2) RETURNING *;

After running sqlc generate, you get Go functions like GetUser(ctx, id) returning a typed User struct.

Related on TokRepo

• AI Tools for Database -- explore AI-powered database tools and query assistants
• AI Tools for Coding -- discover coding workflows that complement SQL-first development

Common pitfalls

• sqlc validates queries against your schema at generation time, so your schema file must be kept in sync with your actual database.
• Complex dynamic queries with conditional WHERE clauses are harder to express in sqlc; consider using sqlc for standard CRUD and a query builder for dynamic filters.
• sqlc's MySQL support is less mature than PostgreSQL; some MySQL-specific syntax may not parse correctly.