SchemQl simplifies database interactions by allowing you to write advanced SQL queries that fully leverage the features of your DBMS, while providing type safety through the use of schemas and offering convenient execution methods.
Key features:
- Database agnostic: Compatible with any DBMS.
- SQL-first: Write SQL with precise type checks on literals like tables, columns (JSON fields & some JSONPath included), and parameters.
- Flexible parameters Supports single objects, arrays of objects, and asynchronous generators for parameters.
- Zod integration Use Zod schemas to validate and parse parameters and query results. (JSON fields included).
- Iterative Execution Process large datasets efficiently using asynchronous generators.
To install SchemQl, use:
npm i @a2lix/schemql
Here's a basic example of how to use SchemQl:
1. Create your database schema and expose it with a DB interface
Tip: Use your favorite AI to generate a Zod schema from your SQL.
If using JSON data, leverage the built-in parseJsonPreprocessor
.
import { parseJsonPreprocessor } from '@a2lix/schemql'
import { z } from 'zod'
export const zUserDb = z.object({
id: z.string(),
email: z.string(),
metadata: z.preprocess(
parseJsonPreprocessor, // ! Zod handles JSON parsing for this JSON columns 'metadata'
z.object({
role: z.enum(['user', 'admin']).default('user'),
})
),
created_at: z.number().int(),
disabled_at: z.number().int().nullable(),
})
type UserDb = z.infer<typeof zUserDb>
// ...
export interface DB {
users: UserDb
// ...other mappings
}
2. Initialize your instance of SchemQl with the DB interface typing
Example with better-sqlite3 adapter.
import { SchemQl } from '@a2lix/schemql'
import { BetterSqlite3Adapter } from '@a2lix/schemql/adapters/better-sqlite3'
import type { DB } from '@/schema'
const schemQl = new SchemQl<DB>({
adapter: new BetterSqlite3Adapter('sqlite.db'),
shouldStringifyObjectParams: true, // Optional. Automatically stringify objects (useful for JSON)
})
3. Use your instance of SchemQl with `.first()` / `.firstOrThrow()` / `.all()` / `.iterate()`
Simple use with resultSchema only and no SQL literal string
const allUsers = await schemQl.all({
resultSchema: zUserDb.array(),
})(`
SELECT *
FROM users
`)
More advanced example
const firstUser = await schemQl.first({
params: { id: 'uuid-1' },
paramsSchema: zUserDb.pick({ id: true }),
resultSchema: z.object({ user_id: zUserDb.shape.id, length_id: z.number() }),
})((s) => s.sql`
SELECT
${'@users.id'} AS ${'$user_id'},
LENGTH(${'@users.id'}) AS ${'$length_id'}
FROM ${'@users'}
WHERE
${'@users.id'} = ${':id'}
`);
const allUsersLimit = await schemQl.all({
params: { limit: 10 },
resultSchema: zUserDb.array(), // ! Note the array() use for .all() case
})((s) => s.sql`
SELECT
${'@users.*'}
FROM ${'@users'}
LIMIT ${':limit'}
`)
const allUsersPaginated = await schemQl.all({
params: {
limit: data.query.limit + 1,
cursor: data.query.cursor,
dir: data.query.dir,
},
paramsSchema: zRequestQuery,
resultSchema: zUserDb.array(), // ! Note the array() use for .all() case
})((s) => s.sql`
SELECT
${'@users.*'}
FROM ${'@users'}
${s.sqlCond(
!!data.query.cursor,
s.sql`WHERE ${'@users.id'} ${s.sqlRaw(data.query.dir === 'next' ? '>' : '<')} ${':cursor'}`
)}
ORDER BY ${'@users.id'} ${s.sqlCond(data.query.dir === 'prev', 'DESC', 'ASC')}
LIMIT ${':limit'}
`)
Automatically stringify JSON params 'metadata' (by schemQl if enabled) and get parsed JSON metadata, as well (if Zod preprocess set rightly)
const firstSession = await schemQl.firstOrThrow({
params: {
id: uuidv4(),
user_id: 'uuid-1',
metadata: {
account: 'credentials',
},
expiresAtAdd: 10000,
},
paramsSchema: zSessionDb.pick({ id: true, user_id: true, metadata: true }).and(z.object({
expiresAtAdd: z.number().int(),
})),
resultSchema: zSessionDb,
})((s) => s.sql`
INSERT INTO
${{ sessions: ['id', 'user_id', 'metadata', 'expires_at'] }}
VALUES
(
${':id'}
, ${':user_id'}
, JSON(${':metadata'})
, STRFTIME('%s', 'now') + ${':expiresAtAdd'}
)
RETURNING *
`)
Handle iteration when required
const iterResults = await schemQl.first({
params: [
{ id: 'uuid-1' },
{ id: 'uuid-2' }
],
paramsSchema: zUserDb.pick({ id: true }).array(), // ! Note the array() use when array of params
resultSchema: zUserDb,
})((s) => s.sql`
SELECT *
FROM ${'@users'}
WHERE
${'@users.id'} = ${':id'}
`)
const iterResults = await schemQl.first({
params: function* () {
yield { id: 'uuid-1' }
yield { id: 'uuid-2' }
},
paramsSchema: zUserDb.pick({ id: true }),
resultSchema: zUserDb,
})((s) => s.sql`
SELECT *
FROM ${'@users'}
WHERE
${'@users.id'} = ${':id'}
`)
const iterResults = await schemQl.iterate({
resultSchema: zUserDb,
})((s) => s.sql`
SELECT *
FROM ${'@users'}
LIMIT 10
`)
Helper Syntax | Raw SQL Result | Description |
---|---|---|
${'@table1'} |
table1 |
Table Selection: Prefix @ eases table selection/validation |
${'@table1.col1'} |
table1.col1 |
Column Selection: Use @ for table and column validation |
${'@table1.col1-'} |
col1 |
Final - excludes table name (useful if table is aliased) |
${'@table1.col1 ->jsonpath1'} |
table1.col1 ->'jsonpath1' |
JSON Field Selection: Use -> for JSON paths |
${'@table1.col1 ->>jsonpath1'} |
table1.col1 ->>'jsonpath1' |
JSON field (raw) with ->> syntax |
${'@table1.col1 $.jsonpath1'} |
'$.jsonpath1' |
JSONPath with $ prefix |
${'$resultCol1'} |
resultCol1 |
Result Selection: $ prefix targets resultSchema fields |
${':param1'} |
:param1 |
Parameter Selection: : prefix eases parameter validation |
${{ table1: ['col1', 'col2'] }} |
table1 (col1, col2) |
Batch Column Selection: Object syntax useful for INSERT |
${s.sqlCond(1, 'ASC', 'DESC')} |
ASC |
Conditional SQL: s.sqlCond for conditional clauses |
${s.sqlRaw(var)} |
var |
Raw SQL: Use s.sqlRaw for unprocessed SQL fragments |
Contributions are welcome! This library aims to remain lightweight and focused, so please keep PRs concise and aligned with this goal.
This library relies solely on Zod, but it could also include support for other schema libraries, such as @effect/schema.
This project is licensed under the MIT License.