pgsql-test

pgsql-test gives you instant, isolated PostgreSQL databases for each test — with automatic transaction rollbacks, context switching, and clean seeding. Forget flaky tests and brittle environments. Write real SQL. Get real coverage. Stay fast.

Install

npm install pgsql-test

Features

• ⚡ Instant test DBs — each one seeded, isolated, and UUID-named
• 🔄 Per-test rollback — every test runs in its own transaction or savepoint
• 🛡️ RLS-friendly — test with role-based auth via .setContext()
• 🌱 Flexible seeding — run .sql files, programmatic seeds, or even load fixtures
• 🧪 Compatible with any async runner — works with Jest, Mocha, etc.
• 🧹 Auto teardown — no residue, no reboots, just clean exits

Tutorials

📚 Learn how to test PG with pgsql-test →

Using with Supabase

If you're writing tests for Supabase, check out supabase-test for Supabase-optimized defaults.

pgpm migrations

Part of the pgpm ecosystem, pgsql-test is built to pair seamlessly with our TypeScript-based package manager and migration tool. pgpm gives you modular Postgres packages, deterministic plans, and tag-aware releases—perfect for authoring the migrations that pgsql-test runs.

Table of Contents

1. Install
2. Features
3. Quick Start
4. getConnections() Overview
5. PgTestClient API Overview
6. Usage Examples
   • Basic Setup
   • Role-Based Context
   • Seeding System
   • SQL File Seeding
   • Programmatic Seeding
   • CSV Seeding
   • JSON Seeding
   • LaunchQL Seeding
7. getConnections() Options
8. Disclaimer

✨ Quick Start

import { getConnections } from 'pgsql-test';

let db, teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections());
  await db.query(`SELECT 1`); // ✅ Ready to run queries
});

afterAll(() => teardown());

getConnections() Overview

import { getConnections } from 'pgsql-test';

// Complete object destructuring
const { pg, db, admin, teardown, manager } = await getConnections();

// Most common pattern
const { db, teardown } = await getConnections();

The getConnections() helper sets up a fresh PostgreSQL test database and returns a structured object with:

• pg: a PgTestClient connected as the root or superuser — useful for administrative setup or introspection
• db: a PgTestClient connected as the app-level user — used for running tests with RLS and granted permissions
• admin: a DbAdmin utility for managing database state, extensions, roles, and templates
• teardown(): a function that shuts down the test environment and database pool
• manager: a shared connection pool manager (PgTestConnector) behind both clients

Together, these allow fast, isolated, role-aware test environments with per-test rollback and full control over setup and teardown.

The PgTestClient returned by getConnections() is a fully-featured wrapper around pg.Pool. It provides:

• Automatic transaction and savepoint management for test isolation
• Easy switching of role-based contexts for RLS testing
• A clean, high-level API for integration testing PostgreSQL systems

PgTestClient API Overview

let pg: PgTestClient;
let teardown: () => Promise<void>;

beforeAll(async () => {
  ({ pg, teardown } = await getConnections());
});

beforeEach(() => pg.beforeEach());
afterEach(() => pg.afterEach());
afterAll(() => teardown());

The PgTestClient returned by getConnections() wraps a pg.Client and provides convenient helpers for query execution, test isolation, and context switching.

Common Methods

• query(sql, values?) – Run a raw SQL query and get the QueryResult
• beforeEach() – Begins a transaction and sets a savepoint (called at the start of each test)
• afterEach() – Rolls back to the savepoint and commits the outer transaction (cleans up test state)
• setContext({ key: value }) – Sets PostgreSQL config variables (like role) to simulate RLS contexts
• any, one, oneOrNone, many, manyOrNone, none, result – Typed query helpers for specific result expectations

These methods make it easier to build expressive and isolated integration tests with strong typing and error handling.

The PgTestClient returned by getConnections() is a fully-featured wrapper around pg.Pool. It provides:

• Automatic transaction and savepoint management for test isolation
• Easy switching of role-based contexts for RLS testing
• A clean, high-level API for integration testing PostgreSQL systems

Usage Examples

⚡ Basic Setup

import { getConnections } from 'pgsql-test';

let db; // A fully wrapped PgTestClient using pg.Pool with savepoint-based rollback per test
let teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections());

  await db.query(`
    CREATE TABLE users (id SERIAL PRIMARY KEY, name TEXT);
    CREATE TABLE posts (id SERIAL PRIMARY KEY, user_id INT REFERENCES users(id), content TEXT);

    INSERT INTO users (name) VALUES ('Alice'), ('Bob');
    INSERT INTO posts (user_id, content) VALUES (1, 'Hello world!'), (2, 'Graphile is cool!');
  `);
});

afterAll(() => teardown());

beforeEach(() => db.beforeEach());
afterEach(() => db.afterEach());

test('user count starts at 2', async () => {
  const res = await db.query('SELECT COUNT(*) FROM users');
  expect(res.rows[0].count).toBe('2');
});

🔐 Role-Based Context

The pgsql-test framework provides powerful tools to simulate authentication contexts during tests, which is particularly useful when testing Row-Level Security (RLS) policies.

Setting Test Context

Use setContext() to simulate different user roles and JWT claims:

db.setContext({
  role: 'authenticated',
  'jwt.claims.user_id': '123',
  'jwt.claims.org_id': 'acme'
});

This applies the settings using SET LOCAL statements, ensuring they persist only for the current transaction and maintain proper isolation between tests.

Testing Role-Based Access

describe('authenticated role', () => {
  beforeEach(async () => {
    db.setContext({ role: 'authenticated' });
    await db.beforeEach();
  });

  afterEach(() => db.afterEach());

  it('runs as authenticated', async () => {
    const res = await db.query(`SELECT current_setting('role', true) AS role`);
    expect(res.rows[0].role).toBe('authenticated');
  });
});

Database Connection Options

For non-superuser testing, use the connection options described in the options section. The db.connection property allows you to customize the non-privileged user account for your tests.

Use setContext() to simulate Role-Based Access Control (RBAC) during tests. This is useful when testing Row-Level Security (RLS) policies. Your actual server should manage role/user claims via secure tokens (e.g., setting current_setting('jwt.claims.user_id')), but this interface helps emulate those behaviors in test environments.

Common Testing Scenarios

This approach enables testing various access patterns:

• Authenticated vs. anonymous user access
• Per-user data filtering
• Admin privilege bypass behavior
• Custom claim-based restrictions (organization membership, admin status)

Note: While this interface helps simulate RBAC for testing, your production server should manage user/role claims via secure authentication tokens, typically by setting values like current_setting('jwt.claims.user_id') through proper authentication middleware.

🌱 Seeding System

The second argument to getConnections() is an optional array of SeedAdapter objects:

const { db, teardown } = await getConnections(getConnectionOptions, seedAdapters);

This array lets you fully customize how your test database is seeded. You can compose multiple strategies:

• seed.sqlfile() – Execute raw .sql files from disk
• seed.fn() – Run JavaScript/TypeScript logic to programmatically insert data
• seed.csv() – Load tabular data from CSV files
• seed.json() – Use in-memory objects as seed data
• seed.launchql() – Apply a LaunchQL project or set of packages (compatible with sqitch)

✨ Default Behavior: If no SeedAdapter[] is passed, LaunchQL seeding is assumed. This makes pgsql-test zero-config for LaunchQL-based projects.

This composable system allows you to mix-and-match data setup strategies for flexible, realistic, and fast database tests.

Two Seeding Patterns

You can seed data using either approach:

1. Adapter Pattern (setup phase via getConnections)

const { db, teardown } = await getConnections({}, [
  seed.json({ 'users': [{ id: 1, name: 'Alice' }] })
]);

2. Direct Load Methods (runtime via PgTestClient)

await db.loadJson({ 'users': [{ id: 1, name: 'Alice' }] });
await db.loadCsv({ 'users': '/path/to/users.csv' });
await db.loadSql(['/path/to/schema.sql']);

Note: loadCsv() and loadLaunchql() do not apply RLS context (PostgreSQL limitation). Use loadJson() or loadSql() for RLS-aware seeding.

🔌 SQL File Seeding

Adapter Pattern:

const { db, teardown } = await getConnections({}, [
  seed.sqlfile(['schema.sql', 'fixtures.sql'])
]);

Direct Load Method:

await db.loadSql(['schema.sql', 'fixtures.sql']);

import path from 'path';
import { getConnections, seed } from 'pgsql-test';

const sql = (f: string) => path.join(__dirname, 'sql', f);

let db;
let teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections({}, [
      seed.sqlfile([
        sql('schema.sql'),
        sql('fixtures.sql')
      ])
  ]));
});

afterAll(async () => {
  await teardown();
});

🧠 Programmatic Seeding

Adapter Pattern:

const { db, teardown } = await getConnections({}, [
  seed.fn(async ({ pg }) => {
    await pg.query(`INSERT INTO users (name) VALUES ('Seeded User')`);
  })
]);

Direct Load Method:

// Use any PgTestClient method directly
await db.query(`INSERT INTO users (name) VALUES ('Seeded User')`);

import { getConnections, seed } from 'pgsql-test';

let db;
let teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections({}, [
    seed.fn(async ({ pg }) => {
      await pg.query(`
        INSERT INTO users (name) VALUES ('Seeded User');
      `);
    })
  ]));
});

🗃️ CSV Seeding

Adapter Pattern:

const { db, teardown } = await getConnections({}, [
  seed.csv({
    'users': '/path/to/users.csv',
    'posts': '/path/to/posts.csv'
  })
]);

Direct Load Method:

await db.loadCsv({
  'users': '/path/to/users.csv',
  'posts': '/path/to/posts.csv'
});

Note: CSV loading uses PostgreSQL COPY which does not support RLS context.

import path from 'path';
import { getConnections, seed } from 'pgsql-test';

const csv = (file: string) => path.resolve(__dirname, '../csv', file);

let db;
let teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections({}, [
    // Create schema
    seed.fn(async ({ pg }) => {
      await pg.query(`
        CREATE TABLE users (
          id SERIAL PRIMARY KEY,
          name TEXT NOT NULL
        );

        CREATE TABLE posts (
          id SERIAL PRIMARY KEY,
          user_id INT REFERENCES users(id),
          content TEXT NOT NULL
        );
      `);
    }),
    // Load from CSV
    seed.csv({
      users: csv('users.csv'),
      posts: csv('posts.csv')
    }),
    // Adjust SERIAL sequences to avoid conflicts
    seed.fn(async ({ pg }) => {
      await pg.query(`SELECT setval(pg_get_serial_sequence('users', 'id'), (SELECT MAX(id) FROM users));`);
      await pg.query(`SELECT setval(pg_get_serial_sequence('posts', 'id'), (SELECT MAX(id) FROM posts));`);
    })
  ]));
});

afterAll(() => teardown());

it('has loaded rows', async () => {
  const res = await db.query('SELECT COUNT(*) FROM users');
  expect(+res.rows[0].count).toBeGreaterThan(0);
});

🗃️ JSON Seeding

Adapter Pattern:

const { db, teardown } = await getConnections({}, [
  seed.json({
    'custom.users': [
      { id: 1, name: 'Alice' },
      { id: 2, name: 'Bob' }
    ]
  })
]);

Direct Load Method:

await db.loadJson({
  'custom.users': [
    { id: 1, name: 'Alice' },
    { id: 2, name: 'Bob' }
  ]
});

import { getConnections, seed } from 'pgsql-test';

let db;
let teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections({}, [
    // Create schema
    seed.fn(async ({ pg }) => {
      await pg.query(`
        CREATE SCHEMA custom;
        CREATE TABLE custom.users (
          id SERIAL PRIMARY KEY,
          name TEXT NOT NULL
        );

        CREATE TABLE custom.posts (
          id SERIAL PRIMARY KEY,
          user_id INT REFERENCES custom.users(id),
          content TEXT NOT NULL
        );
      `);
    }),
    // Seed with in-memory JSON
    seed.json({
      'custom.users': [
        { id: 1, name: 'Alice' },
        { id: 2, name: 'Bob' }
      ],
      'custom.posts': [
        { id: 1, user_id: 1, content: 'Hello world!' },
        { id: 2, user_id: 2, content: 'Graphile is cool!' }
      ]
    }),
    // Fix SERIAL sequences
    seed.fn(async ({ pg }) => {
      await pg.query(`SELECT setval(pg_get_serial_sequence('custom.users', 'id'), (SELECT MAX(id) FROM custom.users));`);
      await pg.query(`SELECT setval(pg_get_serial_sequence('custom.posts', 'id'), (SELECT MAX(id) FROM custom.posts));`);
    })
  ]));
});

afterAll(() => teardown());

it('has loaded rows', async () => {
  const res = await db.query('SELECT COUNT(*) FROM custom.users');
  expect(+res.rows[0].count).toBeGreaterThan(0);
});

🚀 LaunchQL Seeding

Zero Configuration (Default):

// LaunchQL migrate is used automatically
const { db, teardown } = await getConnections();

Adapter Pattern (Custom Path):

const { db, teardown } = await getConnections({}, [
  seed.launchql('/path/to/launchql', true) // with cache
]);

Direct Load Method:

await db.loadLaunchql('/path/to/launchql', true); // with cache

Note: LaunchQL deployment has its own client handling and does not apply RLS context.

import { getConnections } from 'pgsql-test';

let db, teardown;

beforeAll(async () => {
  ({ db, teardown } = await getConnections()); // LaunchQL module is deployed automatically
});

import path from 'path';
import { getConnections, seed } from 'pgsql-test';

const cwd = path.resolve(__dirname, '../path/to/launchql');

beforeAll(async () => {
  ({ db, teardown } = await getConnections({}, [
    seed.launchql(cwd)
  ]));
});

Why LaunchQL's Approach?

LaunchQL provides the best of both worlds:

1. Sqitch Compatibility: Keep your familiar Sqitch syntax and migration approach
2. TypeScript Performance: Our TS-rewritten deployment engine delivers up to 10x faster schema deployments
3. Developer Experience: Tight feedback loops with near-instant schema setup for tests
4. CI Optimization: Dramatically reduced test suite run times with optimized deployment

By maintaining Sqitch compatibility while supercharging performance, LaunchQL enables you to keep your existing migration patterns while enjoying the speed benefits of our TypeScript engine.

Why LaunchQL's Approach?

LaunchQL provides the best of both worlds:

1. Sqitch Compatibility: Keep your familiar Sqitch syntax and migration approach
2. TypeScript Performance: Our TS-rewritten deployment engine delivers up to 10x faster schema deployments
3. Developer Experience: Tight feedback loops with near-instant schema setup for tests
4. CI Optimization: Dramatically reduced test suite run times with optimized deployment

By maintaining Sqitch compatibility while supercharging performance, LaunchQL enables you to keep your existing migration patterns while enjoying the speed benefits of our TypeScript engine.

getConnections Options

This table documents the available options for the getConnections function. The options are passed as a combination of pg and db configuration objects.

db Options (PgTestConnectionOptions)

pg Options (PgConfig)

Environment variables will override these options when available:

• PGHOST, PGPORT, PGUSER, PGPASSWORD, PGDATABASE

Usage

const { conn, db, teardown } = await getConnections({
  pg: { user: 'postgres', password: 'secret' },
  db: {
    extensions: ['uuid-ossp'],
    cwd: '/path/to/project',
    connection: { user: 'test_user', password: 'secret', role: 'authenticated' },
    template: 'test_template',
    prefix: 'test_',
    rootDb: 'postgres'
  }
});

Snapshot Utilities

The pgsql-test/utils module provides utilities for sanitizing database query results for snapshot testing. These helpers replace dynamic values (IDs, UUIDs, dates, hashes) with stable placeholders, making snapshots deterministic.

import { snapshot } from 'pgsql-test/utils';

const result = await db.any('SELECT * FROM users');
expect(snapshot(result)).toMatchSnapshot();

Available Functions

Example

import { snapshot, pruneIds, pruneDates } from 'pgsql-test/utils';

// Full sanitization
const users = await db.any('SELECT * FROM users');
expect(snapshot(users)).toMatchSnapshot();

// Selective sanitization
const row = await db.one('SELECT id, name, created_at FROM users WHERE id = $1', [1]);
const sanitized = pruneDates(pruneIds(row));
// { id: '[ID]', name: 'Alice', created_at: '[DATE]' }

Education and Tutorials

1. 🚀 Quickstart: Getting Up and Running Get started with modular databases in minutes. Install prerequisites and deploy your first module.

2. 📦 Modular PostgreSQL Development with Database Packages Learn to organize PostgreSQL projects with pgpm workspaces and reusable database modules.

3. ✏️ Authoring Database Changes Master the workflow for adding, organizing, and managing database changes with pgpm.

4. 🧪 End-to-End PostgreSQL Testing with TypeScript Master end-to-end PostgreSQL testing with ephemeral databases, RLS testing, and CI/CD automation.

5. ⚡ Supabase Testing Use TypeScript-first tools to test Supabase projects with realistic RLS, policies, and auth contexts.

6. 💧 Drizzle ORM Testing Run full-stack tests with Drizzle ORM, including database setup, teardown, and RLS enforcement.

7. 🔧 Troubleshooting Common issues and solutions for pgpm, PostgreSQL, and testing.

Related Constructive Tooling

🧪 Testing

• pgsql-test: 📊 Isolated testing environments with per-test transaction rollbacks—ideal for integration tests, complex migrations, and RLS simulation.
• supabase-test: 🧪 Supabase-native test harness preconfigured for the local Supabase stack—per-test rollbacks, JWT/role context helpers, and CI/GitHub Actions ready.
• graphile-test: 🔐 Authentication mocking for Graphile-focused test helpers and emulating row-level security contexts.
• pg-query-context: 🔒 Session context injection to add session-local context (e.g., SET LOCAL) into queries—ideal for setting role, jwt.claims, and other session settings.

🧠 Parsing & AST

• pgsql-parser: 🔄 SQL conversion engine that interprets and converts PostgreSQL syntax.
• libpg-query-node: 🌉 Node.js bindings for libpg_query, converting SQL into parse trees.
• pg-proto-parser: 📦 Protobuf parser for parsing PostgreSQL Protocol Buffers definitions to generate TypeScript interfaces, utility functions, and JSON mappings for enums.
• @pgsql/enums: 🏷️ TypeScript enums for PostgreSQL AST for safe and ergonomic parsing logic.
• @pgsql/types: 📝 Type definitions for PostgreSQL AST nodes in TypeScript.
• @pgsql/utils: 🛠️ AST utilities for constructing and transforming PostgreSQL syntax trees.
• pg-ast: 🔍 Low-level AST tools and transformations for Postgres query structures.

🚀 API & Dev Tools

• launchql/server: ⚡ Express-based API server powered by PostGraphile to expose a secure, scalable GraphQL API over your Postgres database.
• launchql/explorer: 🔎 Visual API explorer with GraphiQL for browsing across all databases and schemas—useful for debugging, documentation, and API prototyping.

🔁 Streaming & Uploads

• launchql/s3-streamer: 📤 Direct S3 streaming for large files with support for metadata injection and content validation.
• launchql/etag-hash: 🏷️ S3-compatible ETags created by streaming and hashing file uploads in chunks.
• launchql/etag-stream: 🔄 ETag computation via Node stream transformer during upload or transfer.
• launchql/uuid-hash: 🆔 Deterministic UUIDs generated from hashed content, great for deduplication and asset referencing.
• launchql/uuid-stream: 🌊 Streaming UUID generation based on piped file content—ideal for upload pipelines.
• launchql/upload-names: 📂 Collision-resistant filenames utility for structured and unique file names for uploads.

🧰 CLI & Codegen

• pgpm: 🖥️ PostgreSQL Package Manager for modular Postgres development. Works with database workspaces, scaffolding, migrations, seeding, and installing database packages.
• @launchql/cli: 🖥️ Command-line toolkit for managing LaunchQL projects—supports database scaffolding, migrations, seeding, code generation, and automation.
• constructive-io/constructive-gen: ✨ Auto-generated GraphQL mutations and queries dynamically built from introspected schema data.
• @launchql/query-builder: 🏗️ SQL constructor providing a robust TypeScript-based query builder for dynamic generation of SELECT, INSERT, UPDATE, DELETE, and stored procedure calls—supports advanced SQL features like JOIN, GROUP BY, and schema-qualified queries.
• @launchql/query: 🧩 Fluent GraphQL builder for PostGraphile schemas. ⚡ Schema-aware via introspection, 🧩 composable and ergonomic for building deeply nested queries.

Credits

🛠 Built by Constructive — if you like our tools, please checkout and contribute to our github ⚛️

Disclaimer

AS DESCRIBED IN THE LICENSES, THE SOFTWARE IS PROVIDED "AS IS", AT YOUR OWN RISK, AND WITHOUT WARRANTIES OF ANY KIND.

No developer or entity involved in creating this software will be liable for any claims or damages whatsoever associated with your use, inability to use, or your interaction with other users of the code, including any direct, indirect, incidental, special, exemplary, punitive or consequential damages, or loss of profits, cryptocurrencies, tokens, or anything else of value.