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go-database

go-database

github.com/eduardo-slData & databases83165 installsUpdated 2w ago
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About go-database

go-database is a Go project skill for developers designing database access in Go services. It provides operational guidance and on-demand references covering queries, transactions, concurrency, performance, tooling, and testing.

Key features

  1. 01Connection pool configuration
  2. 02Safe query and row handling
  3. 03Transaction and locking patterns
  4. 04SQL tooling and migrations
  5. 05Performance and testing guidance

Use cases

  1. 01Reviewing Go database access code
  2. 02Building transaction and retry logic
  3. 03Preventing query and connection pitfalls

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/eduardo-sl/go-agent-skills --skill go-database

After installing, type/go-databasein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
locking-and-retries.md
performance.md
query-patterns.md
testing.md
tooling.md

Details

From the project README

Go Database Patterns

Database access is where most Go services spend their complexity budget. Get connection management, transactions, and query patterns right.

Community default. A project skill or agent-config rule that explicitly supersedes go-database takes precedence over this one.

Detailed reference material, loaded on demand:

  • references/query-patterns.md — full query/scan/rows patterns, null handling, N+1 avoidance, connection-leak examples.
  • references/tooling.md — repository pattern implementation, sqlc annotated queries, migration tooling and rules.
  • references/locking-and-retries.md — FOR UPDATE/SKIP LOCKED, optimistic versioning, retrying 40001/40P01, constraint errors.
  • references/performance.md — COPY and batched inserts, keyset pagination, pool statistics, sql.Null[T].
  • references/testing.md — choosing fakes vs a real database, testcontainers setup, isolation strategies.

Read a reference file only when the summary below is not enough.

1. Connection Management

Configure the pool explicitly — the default is unbounded connections:

func OpenDB(dsn string) (*sql.DB, error) {
    db, err := sql.Open("postgres", dsn)
    if err != nil {
        return nil, fmt.Errorf("open db: %w", err)
    }

    db.SetMaxOpenConns(25)
    db.SetMaxIdleConns(10)
    db.SetConnMaxLifetime(5 * time.Minute)
    db.SetConnMaxIdleTime(1 * time.Minute)

    if err := db.PingContext(context.Background()); err != nil {
        return nil, fmt.Errorf("ping db: %w", err)
    }

    return db, nil
}
SettingGuideline
MaxOpenConnsMatch your DB's max connections / number of app instances
MaxIdleConns40-50% of MaxOpenConns
ConnMaxLifetime5-10 minutes (prevents stale connections behind load balancers)
ConnMaxIdleTime1-2 minutes

2. Query Rules

  1. Parameterized queries only — string concatenation into SQL is an injection vulnerability, no exceptions.
  2. Always pass context — use the *Context variants (QueryContext, QueryRowContext, ExecContext) so queries respect cancellation and timeouts.
  3. defer rows.Close() immediately after the error check, and check rows.Err() after the iteration loop.
  4. Handle sql.ErrNoRows explicitly with errors.Is, mapping it to a domain error like ErrUserNotFound.
var user User
err := db.QueryRowContext(ctx,
    "SELECT id, name, email FROM users WHERE id = $1", id,
).Scan(&user.ID, &user.Name, &user.Email)

if errors.Is(err, sql.ErrNoRows) {
    return nil, ErrUserNotFound
}
if err != nil {
    return nil, fmt.Errorf("get user %s: %w", id, err)
}

Multi-row iteration patterns: references/query-patterns.md.

3. Transactions

Use a helper that guarantees rollback on error:

func WithTx(ctx context.Context, db *sql.DB, fn func(tx *sql.Tx) error) (err error) {
    tx, err := db.BeginTx(ctx, nil)
    if err != nil {
        return fmt.Errorf("begin tx: %w", err)
    }
    defer func() {
        if p := recover(); p != nil {
            _ = tx.Rollback() // release the connection, then keep panicking
            panic(p)
        }
        if err != nil {
            if rbErr := tx.Rollback(); rbErr != nil && !errors.Is(rbErr, sql.ErrTxDone) {
                err = errors.Join(err, fmt.Errorf("rollback: %w", rbErr))
            }
        }
    }()

    if err := fn(tx); err != nil {
        return err
    }
    if err := tx.Commit(); err != nil {
        return fmt.Errorf("commit tx: %w", err)
    }
    return nil
}

The deferred rollback covers a panic inside fn, which would otherwise leave the transaction open and its connection out of the pool until the context ends. errors.Join keeps both errors inspectable.

Set isolation explicitly for critical operations: sql.TxOptions{Isolation: sql.LevelSerializable}.

4. Concurrency Control and Errors

  • Read-then-write in one transaction with SELECT ... FOR UPDATE; job queues claim rows with FOR UPDATE SKIP LOCKED; lock rows in a consistent order to avoid deadlocks.
  • For user-facing edits, optimistic concurrency: a version column in the WHERE, and zero rows affected means conflict.
  • 40001 (serialization failure) and 40P01 (deadlock) are retryable: retry the whole transaction function with jittered backoff and a cap. The function must have no side effects outside the transaction.
  • Map constraint violations to domain errors (23505 unique → ErrEmailTaken → 409). Let the database enforce uniqueness; check-then- insert races.

Code: references/locking-and-retries.md.

5. Structure and Tooling

  • Repository pattern: define the interface at the consumer side, implement it with concrete database access, map driver errors to domain errors at this boundary.
  • sqlc: prefer it for raw-SQL projects — generates type-safe Go from annotated SQL, catching query/schema mismatches at build time.
  • Migrations: use a tool (goose, golang-migrate, atlas), one migration per change, forward-only in production, with down SQL, run as a separate step — not at server startup.

Implementations and examples: references/tooling.md.

6. Common Pitfalls

  • Null columns: use sql.NullString/sql.NullInt64 or pointer fields (*string, nil = SQL NULL). Scanning NULL into a plain string errors at runtime.
  • N+1 queries: a query inside a loop over query results. Replace with a JOIN or a batch query (WHERE id = ANY($1)).
  • Connection leaks: any early return between Query and defer rows.Close() leaks a connection from the pool — and so does db.Query for a statement that returns no rows; use ExecContext.

Worked examples of each pitfall: references/query-patterns.md.

7. Performance

  • Bulk writes: pgx CopyFrom, or multi-row INSERT in batches of a few hundred rows — never one round trip per row.
  • Paginate with a keyset cursor (WHERE (created_at, id) < ($1, $2)), not OFFSET, which scans skipped rows and shifts under inserts.
  • Export db.Stats(): a rising WaitCount means the pool, or something holding connections, is the bottleneck.
  • sql.Null[T] (Go 1.22+) replaces the per-type NullString family.

Examples: references/performance.md.

8. Testing

Fake the consumer-side repository interface for service logic; test SQL against a real database in a container (testcontainers, behind //go:build integration), running the production migrations. Isolate tests with a transaction per test, a template database, or truncation. Examples: references/testing.md.

Verification Checklist

  1. Connection pool configured with explicit limits (MaxOpenConns, MaxIdleConns, lifetimes)
  2. All queries use parameterized placeholders, never string concatenation
  3. All QueryContext results have defer rows.Close() immediately after error check
  4. rows.Err() checked after row iteration loop
  5. sql.ErrNoRows handled explicitly with errors.Is
  6. Transactions use a helper that guarantees rollback on error
  7. Context propagated to all database calls (*Context variants)
  8. Nullable columns use sql.NullString / sql.NullInt64 or pointer types
  9. No N+1 query patterns — use JOINs or batch queries
  10. Migrations are versioned, reversible, and run separately from app startup
  11. No OFFSET pagination on large tables; bulk writes batched
  12. SQL is tested against a real database, not mocked query strings

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