@flowblade/sqlduck

> Currently experimental

Quick start

$3

``typescript import { SqlDuck } from "@flowblade/sqlduck"; import * as z from "zod"; import { dbDuckDbMemoryConn } from "./db.duckdb-memory.config";

const sqlDuck = new SqlDuck({ conn: duckDbConnection });

// Schema of the table, not that you can use meta to add information const userSchema = z.object({ id: z.number().int().meta({ primaryKey: true }), name: z.string(), });

// Async generator function that yields rows to insert async function* getUserRows(): AsyncIterableIterator< z.infer > { // database or api call }

const result = sqlDuck.toTable({ table: new Table({ name: "user", database: "mydb" }), // Table definition schema: userSchema, // The schema to use to create the table rowStream: getUserRows(), // The async iterable that yields rows // 👇Optional: chunkSize: 2048, // Number of rows to append when using duckdb appender. Default is 2048 onDataAppended: ({ total }) => { console.log(Appended ${total} rows so far); }, onDataAppendedBatchSize: 4096, // Call onDataAppended every 4096 rows // Optional table creation options createOptions: { create: "CREATE_OR_REPLACE", }, });

console.log(Inserted ${result.totalRows} rows in ${result.timeMs}ms); console.log(Table created with DDL: ${result.createTableDDL});

// You can now use the table in your queries const queryResult = await dbDuckDbMemoryConn.query<{ id: number; name: string; }>(
SELECT id, name FROM mydb.user WHERE id < 1000
);`

`$3`

| Name | Description | | ----------------- | ------------------------------ | |yarn build| | |yarn typecheck| | |yarn lint| Check for lint errors | |yarn lint --fix| Attempt to run linter auto-fix | |yarn test-unit| Run unit tests | |yarn test-e2e` | Run unit tests |

Quick start

typescript
import { SqlDuck } from "@flowblade/sqlduck";
import * as z from "zod";
import { dbDuckDbMemoryConn } from "./db.duckdb-memory.config";

const sqlDuck = new SqlDuck({ conn: duckDbConnection });

// Schema of the table, not that you can use meta to add information
const userSchema = z.object({
  id: z.number().int().meta({ primaryKey: true }),
  name: z.string(),
});

// Async generator function that yields rows to insert
async function* getUserRows(): AsyncIterableIterator<
  z.infer
> {
  // database or api call
}

const result = sqlDuck.toTable({
  table: new Table({ name: "user", database: "mydb" }), // Table definition
  schema: userSchema, // The schema to use to create the table
  rowStream: getUserRows(), // The async iterable that yields rows
  // 👇Optional:
  chunkSize: 2048, // Number of rows to append when using duckdb appender. Default is 2048
  onDataAppended: ({ total }) => {
    console.log(

Appended ${total} rows so far

);
  },
  onDataAppendedBatchSize: 4096, // Call onDataAppended every 4096 rows
  // Optional table creation options
  createOptions: {
    create: "CREATE_OR_REPLACE",
  },
});

console.log(Inserted ${result.totalRows} rows in ${result.timeMs}ms

);
console.log(

Table created with DDL: ${result.createTableDDL});

// You can now use the table in your queries
const queryResult = await dbDuckDbMemoryConn.query<{
  id: number;
  name: string;
}>(

SELECT id, name FROM mydb.user WHERE id < 1000

);

$3

| Name              | Description                    |
| ----------------- | ------------------------------ |
|

yarn build

      |                                |
|

yarn typecheck

  |                                |
|

yarn lint

       | Check for lint errors          |
|

yarn lint --fix

 | Attempt to run linter auto-fix |
|

yarn test-unit

  | Run unit tests                 |
|

yarn test-e2e` | Run unit tests |