gotosocial/vendor/github.com/uptrace/bun

SQL-first Golang ORM for PostgreSQL, MySQL, MSSQL, and SQLite

Bun is brought to you by ⭐ uptrace/uptrace. Uptrace is an open source and blazingly fast distributed tracing tool powered by OpenTelemetry and ClickHouse. Give it a star as well!

Features

• Works with PostgreSQL, MySQL (including MariaDB), MSSQL, SQLite.
• ORM-like experience using good old SQL. Bun supports structs, map, scalars, and slices of map/structs/scalars.
• Bulk inserts.
• Bulk updates using common table expressions.
• Bulk deletes.
• Fixtures.
• Migrations.
• Soft deletes.

Resources:

• Get started
• Examples
• Discussions
• Chat
• Reference
• Starter kit

Featured projects using Bun:

• uptrace - Distributed tracing and metrics.
• paralus - All-in-one Kubernetes access manager.
• inovex/scrumlr.io - Webapp for collaborative online retrospectives.
• gotosocial - Golang fediverse server.
• lorawan-stack - The Things Stack, an Open Source LoRaWAN Network Server.
• anti-phishing-bot - Discord bot for deleting Steam/Discord phishing links.
• emerald-web3-gateway - Web3 Gateway for the Oasis Emerald paratime.
• lndhub.go - accounting wrapper for the Lightning Network.
• penguin-statistics - Penguin Statistics v3 Backend.
• And hundreds more.

Why another database client?

So you can elegantly write complex queries:

regionalSales := db.NewSelect().
	ColumnExpr("region").
	ColumnExpr("SUM(amount) AS total_sales").
	TableExpr("orders").
	GroupExpr("region")

topRegions := db.NewSelect().
	ColumnExpr("region").
	TableExpr("regional_sales").
	Where("total_sales > (SELECT SUM(total_sales) / 10 FROM regional_sales)")

var items []map[string]interface{}
err := db.NewSelect().
	With("regional_sales", regionalSales).
	With("top_regions", topRegions).
	ColumnExpr("region").
	ColumnExpr("product").
	ColumnExpr("SUM(quantity) AS product_units").
	ColumnExpr("SUM(amount) AS product_sales").
	TableExpr("orders").
	Where("region IN (SELECT region FROM top_regions)").
	GroupExpr("region").
	GroupExpr("product").
	Scan(ctx, &items)

WITH regional_sales AS (
    SELECT region, SUM(amount) AS total_sales
    FROM orders
    GROUP BY region
), top_regions AS (
    SELECT region
    FROM regional_sales
    WHERE total_sales > (SELECT SUM(total_sales)/10 FROM regional_sales)
)
SELECT region,
       product,
       SUM(quantity) AS product_units,
       SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product

And scan results into scalars, structs, maps, slices of structs/maps/scalars:

users := make([]User, 0)
if err := db.NewSelect().Model(&users).OrderExpr("id ASC").Scan(ctx); err != nil {
	panic(err)
}

user1 := new(User)
if err := db.NewSelect().Model(user1).Where("id = ?", 1).Scan(ctx); err != nil {
	panic(err)
}

See Getting started guide and check examples.

See also

• Golang HTTP router
• Golang ClickHouse ORM
• Golang msgpack

Contributors

Thanks to all the people who already contributed!