pggen - generate type safe Go methods from Postgres SQL queries

pggen generates Go code to provide a typesafe wrapper to run Postgres queries. If Postgres can run the query, pggen can generate code for it. The generated code is strongly-typed with rich mappings between Postgres types and Go types without relying on interface{}. pggen uses prepared queries, so you don't have to worry about SQL injection attacks.

How to use pggen in three steps:

Write arbitrarily complex SQL queries with a name and a :one, :many, or :exec annotation. Declare inputs with pggen.arg('input_name').

-- name: SearchScreenshots :many
SELECT ss.id, array_agg(bl) AS blocks
FROM screenshots ss
  JOIN blocks bl ON bl.screenshot_id = ss.id
WHERE bl.body LIKE pggen.arg('body') || '%'
GROUP BY ss.id
ORDER BY ss.id
LIMIT pggen.arg('limit') OFFSET pggen.arg('offset');

Run pggen to generate Go code to create type-safe methods for each query.

pggen gen go \
    --schema-glob schema.sql \
    --query-glob 'screenshots/*.sql' \
    --go-type 'int8=int' \
    --go-type 'text=string'

That command generates methods and type definitions like below. The full example is in ./example/composite/query.sql.go.

type SearchScreenshotsParams struct {
    Body   string
    Limit  int
    Offset int
}

type SearchScreenshotsRow struct {
    ID     int      `json:"id"`
    Blocks []Blocks `json:"blocks"`
}

// Blocks represents the Postgres composite type "blocks".
type Blocks struct {
    ID           int    `json:"id"`
    ScreenshotID int    `json:"screenshot_id"`
    Body         string `json:"body"`
}

func (q *DBQuerier) SearchScreenshots(
    ctx context.Context,
    params SearchScreenshotsParams,
) ([]SearchScreenshotsRow, error) {
    /* omitted */
}

Use the generated code.

var conn *pgx.Conn
q := NewQuerier(conn)
rows, err := q.SearchScreenshots(ctx, SearchScreenshotsParams{
    Body:   "some_prefix",
    Limit:  50,
    Offset: 200,
})

Pitch

Why should you use pggen instead of the myriad of Go SQL bindings?

pggen generates code by introspecting the database system catalogs, so you can use any database extensions or custom methods and it will just work™. For database types that pggen doesn't recognize, you can provide your own type mappings.
pggen scales to Postgres databases of any size and supports incremental adoption. pggen is narrowly tailored to only generate code for queries you write in SQL. pggen will not create a model for every database object. Instead, pggen only generates structs necessary to run the queries you specify.
pggen works with any Postgres database with any extensions. Under the hood, pggen runs each query and uses the Postgres catalog tables, pg_type, pg_class, and pg_attribute, to get perfect type information for both the query parameters and result columns.
pggen works with all Postgres queries. If Postgres can run the query, pggen can generate Go code for the query.
pggen uses pgx, a faster replacement for lib/pq, the original Go Postgres library that's now in maintenance mode.
pggen provides a batch (aka query pipelining) interface for each generated query with pgx.Batch. Query pipelining is the reason Postgres sits atop the TechEmpower benchmarks. Using a batch enables sending multiple queries in a single network round-trip instead of one network round-trip per query.

Anti-pitch

I'd like to try to convince you why you shouldn't use pggen. Often, this is far more revealing than the pitch.

You want auto-generated models for every table in your database. pggen only generates code for each query in a query file. pggen requires custom SQL for even the simplest CRUD queries. Use gorm or any of alternatives listed at awesome Go ORMs.
You use database other than Postgres. pggen only supports Postgres. sqlc, a similar tool which inspired pggen, has early support for MySQL.
You want an active-record pattern where models have methods like find, create, update, and delete. pggen only generates code for queries you write. Use gorm.
You prefer building queries in a Go dialect instead of SQL. I'd recommend investing in really learning SQL; it will payoff. Otherwise, use squirrel, goqu, or go-sqlbuilder
You don't want to add a Postgres or Docker dependency to your build phase. Use sqlc, though you might still need Docker. sqlc generates code by parsing the schema file and queries in Go without using Postgres.

Install

Download precompiled binaries

Precompiled binaries from the latest release. Change ~/bin if you want to install to a different directory. All assets are listed on the releases page.

MacOS Apple Silicon (arm64)

mkdir -p ~/bin \
  && curl --silent --show-error --location --fail 'https://github.com/jschaf/pggen/releases/latest/download/pggen-darwin-arm64.tar.xz' \
  | tar -xJf - -C ~/bin/

MacOS Intel (amd64)

mkdir -p ~/bin \
  && curl --silent --show-error --location --fail 'https://github.com/jschaf/pggen/releases/latest/download/pggen-darwin-amd64.tar.xz' \
  | tar -xJf - -C ~/bin/

Linux (amd64)

mkdir -p ~/bin \
  && curl --silent --show-error --location --fail 'https://github.com/jschaf/pggen/releases/latest/download/pggen-linux-amd64.tar.xz' \
  | tar -xJf - -C ~/bin/

Windows (amd64)

mkdir -p ~/bin \
  && curl --silent --show-error --location --fail 'https://github.com/jschaf/pggen/releases/latest/download/pggen-windows-amd64.tar.xz' \
  | tar -xJf - -C ~/bin/

Make sure pggen works:

pggen gen go --help

Install from source

Requires Go 1.16 because pggen uses go:embed. Installs to $GOPATH/bin.

go install github.com/jschaf/pggen/cmd/pggen@latest

Make sure pggen works:

pggen gen go --help

Usage

Generate code using Docker to create the Postgres database from a schema file:

# --schema-glob runs all matching files on Dockerized Postgres during database 
# creation.
pggen gen go \
    --schema-glob author/schema.sql \
    --query-glob author/query.sql

# Output: author/query.go.sql

# Or with multiple schema files. The schema files run on Postgres
# in the order they appear on the command line.
pggen gen go \
    --schema-glob author/schema.sql \
    --schema-glob book/schema.sql \
    --schema-glob publisher/schema.sql \
    --query-glob author/query.sql

# Output: author/query.sql.go

Generate code using an existing Postgres database (useful for custom setups):

pggen gen go \
    --query-glob author/query.sql \
    --postgres-connection "user=postgres port=5555 dbname=pggen"

# Output: author/query.sql.go

Generate code for multiple query files. All the query files must reside in the same directory. If query files reside in different directories, you can use --output-dir to set a single output directory:

pggen gen go \
    --schema-glob schema.sql \
    --query-glob author/fiction.sql \
    --query-glob author/nonfiction.sql \
    --query-glob author/bestselling.sql

# Output: author/fiction.sql.go
#         author/nonfiction.sql.go
#         author/bestselling.sql.go

# Or, using a glob. Notice quotes around glob pattern to prevent shell 
# expansion.
pggen gen go \
    --schema-glob schema.sql \
    --query-glob 'author/*.sql'

Examples

Examples embedded in the repo:

./example/acceptance_test.go - End-to-end examples of how to call pggen.
./example/author - A single table schema with simple queries.
./example/composite - Arrays of composite (aka row or table) types.
./example/custom_types - Mapping new Postgres types to Go types.
./example/device - Complex queries with a 1:many relationship between a user table and device table.
./example/enums - Postgres and Go enums.
./example/erp - A few tables with mildly complex queries.
./example/go_pointer_types - Mapping to pointer types like *int instead of pgtype.Int8.
./example/ltree - Support for the ltree Postgres extension.
./example/nested - Complex, nested composite (aka row or table) types.
./example/pgcrypto - pgcrypto Postgres extension.
./example/syntax - A smoke test of interesting SQL syntax.
./example/void - Support for void in select columns.

Features

JSON struct tags: All <query_name>Row structs include JSON struct tags using the Postgres column name. To change the struct tag, use an SQL column alias.

-- name: FindAuthors :many
SELECT first_name, last_name as family_name FROM author;

Generates:

type FindAuthorsRow struct {
    FirstName   string `json:"first_name"`
    FamilyName  string `json:"family_name"`
}

Acronyms: Custom acronym support so that author_id renders as AuthorID instead of AuthorId. Supports two formats:
1. Long form: --acronym <word>=<relacement>: replaces <word> with <replacement> literally. Useful for plural acronyms like author_ids which should render as AuthorIDs, not AuthorIds. For the IDs example, use --acronym ids=IDs.
2. Short form: --acronym <word>: replaces <word> with uppercase <WORD>. Equivalent to --acronym <word>=<WORD>
By default, pggen includes --acronym id to render id as ID.

Enums: Postgres enums map to Go string constant enums. The Postgres type:

CREATE TYPE device_type AS ENUM ('undefined', 'phone', 'ipad');

Generates the following Go code when used in a query:

// DeviceType represents the Postgres enum device_type.
type DeviceType string

const (
    DeviceTypeUndefined DeviceType = "undefined"
    DeviceTypePhone     DeviceType = "phone"
    DeviceTypeIpad      DeviceType = "ipad"
)

func (d DeviceType) String() string { return string(d) }

Custom types: Use a custom Go type to represent a Postgres type with the --go-type flag. The format is <pg_type>=<qualified_go_type>. For example:
```
pggen gen go \
    --schema-glob example/custom_types/schema.sql \
    --query-glob example/custom_types/query.sql \
    --go-type 'int8=*int' \
    --go-type 'int4=int' \
    --go-type '_int4=[]int' \
    --go-type 'text=*github.com/jschaf/pggen/mytype.String' \
    --go-type '_text=[]*github.com/jschaf/pggen/mytype.String'
```
pgx must be able to decode the Postgres type using the given Go type. That means the Go type must fulfill at least one of following:
- The Go type is a wrapper around primitive type, like type AuthorID int. pgx will use the decode methods on the underlying primitive type.
- The Go type implements both pgtype.BinaryDecoder and pgtype.TextDecoder. pgx will use the correct decoder based on the wire format. See the pgtype repo for many example types.
- The pgx connection executing the query must have registered a data type using the Go type with ConnInfo.RegisterDataType. See the example/custom_types test for an example.
```
ci := conn.ConnInfo()

ci.RegisterDataType(pgtype.DataType{
	Value: new(pgtype.Int2),
	Name:  "my_int",
	OID:   myIntOID,
})
```
- The Go type implements sql.Scanner.
- pgx is able to use reflection to build an object to write fields into.

Nested structs (composite types): pggen creates child structs to represent Postgres composite types that appear in output columns.

-- name: FindCompositeUser :one
SELECT ROW (15, 'qux')::"user" AS "user";

Generates the following Go code:

// User represents the Postgres composite type "user".
type User struct {
    ID   pgtype.Int8
    Name pgtype.Text
}

func (q *DBQuerier) FindCompositeUser(ctx context.Context) (User, error) {}

IDE integration

If your IDE provides SQL autocomplete, you may want to get rid of its warnings by declaring the following DDL schema.

-- Exists solely so editors don't underline every pggen.arg() expression in
-- squiggly red.
CREATE SCHEMA pggen;

-- pggen.arg defines a named parameter that's eventually compiled into a
-- placeholder for a prepared query: $1, $2, etc.
CREATE FUNCTION pggen.arg(param TEXT) RETURNS text AS $$SELECT null$$ LANGUAGE sql;

Tutorial

Let's say we have a database with the following schema in author/schema.sql:

CREATE TABLE author (
  author_id  serial PRIMARY KEY,
  first_name text NOT NULL,
  last_name  text NOT NULL,
  suffix     text NULL
)

First, write a query in the file author/query.sql. The query name is FindAuthors and the query returns :many rows. A query can return :many rows, :one row, or :exec for update, insert, and delete queries.

-- FindAuthors finds authors by first name.
-- name: FindAuthors :many
SELECT * FROM author WHERE first_name = pggen.arg('first_name');

Second, use pggen to generate Go code to author/query.sql.go:

pggen gen go \
    --schema-glob author/schema.sql \
    --query-glob author/query.sql

We'll walk through the generated file author/query.sql.go:

The Querier interface defines the interface with methods for each SQL query. Each SQL query compiles into three methods, one method for to run query by itself, and two methods to support batching a query with pgx.Batch.

// Querier is a typesafe Go interface backed by SQL queries.
//
// Methods ending with Batch enqueue a query to run later in a pgx.Batch. After
// calling SendBatch on pgx.Conn, pgxpool.Pool, or pgx.Tx, use the Scan methods
// to parse the results.
type Querier interface {
    // FindAuthors finds authors by first name.
    FindAuthors(ctx context.Context, firstName string) ([]FindAuthorsRow, error)
    // FindAuthorsBatch enqueues a FindAuthors query into batch to be executed
    // later by the batch.
    FindAuthorsBatch(batch *pgx.Batch, firstName string)
    // FindAuthorsScan scans the result of an executed FindAuthorsBatch query.
    FindAuthorsScan(results pgx.BatchResults) ([]FindAuthorsRow, error)
}

To use the batch interface, create a *pgx.Batch, call the <query_name>Batch methods, send the batch, and finally get the results with the <query_name>Scan methods. See example/author/query.sql_test.go for complete example.

q := NewQuerier(conn)
batch := &pgx.Batch{}
q.FindAuthorsBatch(batch, "alice")
q.FindAuthorsBatch(batch, "bob")
results := conn.SendBatch(context.Background(), batch)
aliceAuthors, err := q.FindAuthorsScan(results)
bobAuthors, err := q.FindAuthorsScan(results)

The DBQuerier struct implements the Querier interface with concrete implementations of each query method.
```
type DBQuerier struct {
    conn genericConn
}
```
Create DBQuerier with NewQuerier. The genericConn parameter is an interface over the different pgx connection transports so that DBQuerier doesn't force you to use a specific connection transport. *pgx.Conn, pgx.Tx, and *pgxpool.Pool all implement genericConn.
```
// NewQuerier creates a DBQuerier that implements Querier. conn is typically
// *pgx.Conn, pgx.Tx, or *pgxpool.Pool.
func NewQuerier(conn genericConn) *DBQuerier {
    return &DBQuerier{
        conn: conn,
    }
}
```
pggen embeds the SQL query formatted for a Postgres PREPARE statement with parameters indicated by $1, $2, etc. instead of pggen.arg('first_name').
```
const findAuthorsSQL = `SELECT * FROM author WHERE first_name = $1;`
```
pggen generates a row struct for each query named <query_name>Row. pggen transforms the output column names into struct field names from lower_snake_case to UpperCamelCase in internal/casing/casing.go. pggen derives JSON struct tags from the Postgres column names. To change the JSON struct name, change the column name in the query.
```
type FindAuthorsRow struct {
    AuthorID  int32       `json:"author_id"`
    FirstName string      `json:"first_name"`
    LastName  string      `json:"last_name"`
    Suffix    pgtype.Text `json:"suffix"`
}
```
As a convenience, if a query only generates a single column, pggen skips creating the <query_name>Row struct and returns the type directly. For example, the generated query for SELECT author_id from author returns int32, not a <query_name>Row struct.

pggen infers struct field types by running the query. When Postgres returns query results, Postgres also sends the column types as a header for the results. pggen looks up the types in the header using the pg_type catalog table and chooses an appropriate Go type in internal/codegen/golang/gotype/types.go.

Choosing an appropriate type is more difficult than might seem at first glance due to null. When Postgres reports that a column has a type text, that column can have both text and null values. So, the Postgres text represented in Go can be either a string or nil. pgtype provides nullable types for all built-in Postgres types. pggen tries to infer if a column is nullable or non-nullable. If a column is nullable, pggen uses a pgtype Go type like pgtype.Text. If a column is non-nullable, pggen uses a more ergonomic type like string. pggen's nullability inference in internal/pginfer/nullability.go is rudimentary; a proper approach requires a full explain plan with some control flow analysis.

Lastly, pggen generates the implementation for each query.

As a convenience, if a there are only one or two query parameters, pggen inlines the parameters into the method definition, as with firstName below. If there are three or more parameters, pggen creates a struct named <query_name>Params to pass the parameters to the query method.

// FindAuthors implements Querier.FindAuthors.
func (q *DBQuerier) FindAuthors(ctx context.Context, firstName string) ([]FindAuthorsRow, error) {
    rows, err := q.conn.Query(ctx, findAuthorsSQL, firstName)
    if rows != nil {
        defer rows.Close()
    }
    if err != nil {
        return nil, fmt.Errorf("query FindAuthors: %w", err)
    }
    items := []FindAuthorsRow{}
    for rows.Next() {
        var item FindAuthorsRow
        if err := rows.Scan(&item.AuthorID, &item.FirstName, &item.LastName, &item.Suffix); err != nil {
            return nil, fmt.Errorf("scan FindAuthors row: %w", err)
        }
        items = append(items, item)
    }
    if err := rows.Err(); err != nil {
        return nil, err
    }
    return items, err
}

Contributing

See CONTRIBUTING.md and ARCHITECTURE.md.

Acknowledgments

pggen was directly inspired by sqlc. The primary difference between pggen and sqlc is how each tool infers the type and nullability of the input parameters and output columns for SQL queries.

sqlc parses the queries in Go code, using Cgo to call the Postgres parser.c library. After parsing, sqlc infers the types of the query parameters and result columns using custom logic in Go. In contrast, pggen gets the same type information by running the queries on Postgres and then fetching the type information for Postgres catalog tables.

Use sqlc if you don't wish to run Postgres to generate code or if you need better nullability analysis than pggen provides.

Use pggen if you can run Postgres for code generation, and you use complex queries that sqlc is unable to parse. Additionally, use pggen if you have a custom database setup that's difficult to replicate in a schema file. pggen supports running on any database with any extensions.

bweston92 / pggen