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主要言語: Go
Go Postgres Data Access Toolkit
- star 数
- 611
- watcher 数
- 20
- fork 数
- 60
- issue 数
- 25
- 最終更新
- 2020/10/25
gem-hunter主要言語: Go
Go Postgres Data Access Toolkit
dat (Data Access Toolkit) is a fast, lightweight Postgres library for Go.
Focused on Postgres. See Insect, Upsert, SelectDoc, QueryJSON
Built on a solid foundation sqlx
// child DB is *sqlx.DB DB.DB.Queryx(`SELECT * FROM users`)
SQL and backtick friendly
DB.SQL(`SELECT * FROM people LIMIT 10`).QueryStructs(&people)
JSON Document retrieval (single trip to Postgres, requires Postgres 9.3+)
DB.SelectDoc("id", "user_name", "avatar"). Many("recent_comments", `SELECT id, title FROM comments WHERE id = users.id LIMIT 10`). Many("recent_posts", `SELECT id, title FROM posts WHERE author_id = users.id LIMIT 10`). One("account", `SELECT balance FROM accounts WHERE user_id = users.id`). From("users"). Where("id = $1", 4). QueryStruct(&obj) // obj must be agreeable with json.Unmarshal()
results in
{
"id": 4,
"user_name": "mario",
"avatar": "https://imgur.com/a23x.jpg",
"recent_comments": [{"id": 1, "title": "..."}],
"recent_posts": [{"id": 1, "title": "..."}],
"account": {
"balance": 42.00
}
}JSON marshalable bytes (requires Postgres 9.3+)
var b []byte b, _ = DB.SQL(`SELECT id, user_name, created_at FROM users WHERE user_name = $1 `, "mario", ).QueryJSON() // straight into map var obj map[string]interface{} DB.SQL(`SELECT id, user_name, created_at FROM users WHERE user_name = $1 `, "mario", ).QueryObject(&obj)
Ordinal placeholders
DB.SQL(`SELECT * FROM people WHERE state = $1`, "CA").Exec()
SQL-like API
err := DB. Select("id, user_name"). From("users"). Where("id = $1", id). QueryStruct(&user)
Redis caching
// cache result for 30 seconds key := "user:" + strconv.Itoa(user.id) err := DB. Select("id, user_name"). From("users"). Where("id = $1", user.id). Cache(key, 30 * time.Second, false). QueryStruct(&user)
Nested transactions
Per query timeout with database cancellation logic pg_cancel_backend
SQL and slow query logging
Performant
?dat can interpolate queries locally resulting in performance increase
over plain database/sql and sqlx. BenchmarksGet it
dat.v1 uses glide package dependency manager.
Earlier builds relied on gopkg.in which at the time was as good a solution as any.
Will move to dep once it is stable.
glide get gopkg.in/mgutz/dat.v1/sqlx-runner
Use it
import ( "database/sql" _ "github.com/lib/pq" "gopkg.in/mgutz/dat.v1" "gopkg.in/mgutz/dat.v1/sqlx-runner" ) // global database (pooling provided by SQL driver) var DB *runner.DB func init() { // create a normal database connection through database/sql db, err := sql.Open("postgres", "dbname=dat_test user=dat password=!test host=localhost sslmode=disable") if err != nil { panic(err) } // ensures the database can be pinged with an exponential backoff (15 min) runner.MustPing(db) // set to reasonable values for production db.SetMaxIdleConns(4) db.SetMaxOpenConns(16) // set this to enable interpolation dat.EnableInterpolation = true // set to check things like sessions closing. // Should be disabled in production/release builds. dat.Strict = false // Log any query over 10ms as warnings. (optional) runner.LogQueriesThreshold = 10 * time.Millisecond DB = runner.NewDB(db, "postgres") } type Post struct { ID int64 `db:"id"` Title string `db:"title"` Body string `db:"body"` UserID int64 `db:"user_id"` State string `db:"state"` UpdatedAt dat.NullTime `db:"updated_at"` CreatedAt dat.NullTime `db:"created_at"` } func main() { var post Post err := DB. Select("id, title"). From("posts"). Where("id = $1", 13). QueryStruct(&post) fmt.Println("Title", post.Title) }
Query Builder
var posts []*Post err := DB. Select("title", "body"). From("posts"). Where("created_at > $1", someTime). OrderBy("id ASC"). Limit(10). QueryStructs(&posts)
Plain SQL
err = DB.SQL(` SELECT title, body FROM posts WHERE created_at > $1 ORDER BY id ASC LIMIT 10`, someTime, ).QueryStructs(&posts)
Note: dat does not trim the SQL string, thus any extra whitespace is
transmitted to the database.
In practice, SQL is easier to write with backticks. Indeed, the reason this library exists is most SQL builders introduce a DSL to insulate the user from SQL.
Query builders shine when dealing with data transfer objects, structs.
Query then scan result to struct(s)
var post Post err := DB. Select("id, title, body"). From("posts"). Where("id = $1", id). QueryStruct(&post) var posts []*Post err = DB. Select("id, title, body"). From("posts"). Where("id > $1", 100). QueryStructs(&posts)
Query scalar values or a slice of values
var n int64 DB.SQL("SELECT count(*) FROM posts WHERE title=$1", title).QueryScalar(&n) var ids []int64 DB.SQL("SELECT id FROM posts", title).QuerySlice(&ids)
dat DOES NOT map fields automatically like sqlx.
You must explicitly set db struct tags in your types.
Embedded fields are mapped breadth-first.
type Realm struct { RealmUUID string `db:"realm_uuid"` } type Group struct { GroupUUID string `db:"group_uuid"` *Realm } g := &Group{Realm: &Realm{"11"}, GroupUUID: "22"} sql, args := InsertInto("groups").Columns("group_uuid", "realm_uuid").Record(g).ToSQL() expected := ` INSERT INTO groups ("group_uuid", "realm_uuid") VALUES ($1, $2) `
Control which columns get inserted or updated when processing external data
// userData came in from http.Handler, prevent them from setting protected fields DB.InsertInto("payments"). Blacklist("id", "updated_at", "created_at"). Record(userData). Returning("id"). QueryScalar(&userData.ID) // ensure session user can only update his information DB.Update("users"). SetWhitelist(user, "user_name", "avatar", "quote"). Where("id = $1", session.UserID). Exec()
applicable when dat.EnableInterpolation == true
Simpler IN queries which expand correctly
ids := []int64{10,20,30,40,50} b := DB.SQL("SELECT * FROM posts WHERE id IN $1", ids) b.MustInterpolate() == "SELECT * FROM posts WHERE id IN (10,20,30,40,50)"
dat uses logxi for logging. By default,
logxi logs all warnings and errors to the console. dat logs the
SQL and its arguments on any error. In addition, dat logs slow queries
as warnings if runner.LogQueriesThreshold > 0
To trace all SQL, set environment variable
LOGXI=dat* yourappUse Returning and QueryStruct to insert and update struct fields in one
trip
var post Post err := DB. InsertInto("posts"). Columns("title", "state"). Values("My Post", "draft"). Returning("id", "created_at", "updated_at"). QueryStruct(&post)
Use Blacklist and Whitelist to control which record (input struct) fields
are inserted.
post := Post{Title: "Go is awesome", State: "open"} err := DB. InsertInto("posts"). Blacklist("id", "user_id", "created_at", "updated_at"). Record(&post). Returning("id", "created_at", "updated_at"). QueryStruct(&post) // use wildcard to include all columns err := DB. InsertInto("posts"). Whitelist("*"). Record(&post). Returning("id", "created_at", "updated_at"). QueryStruct(&post)
Insert Multiple Records
// create builder b := DB.InsertInto("posts").Columns("title") // add some new posts for i := 0; i < 3; i++ { b.Record(&Post{Title: fmt.Sprintf("Article %s", i)}) } // OR (this is more efficient as it does not do any reflection) for i := 0; i < 3; i++ { b.Values(fmt.Sprintf("Article %s", i)) } // execute statement _, err := b.Exec()
Inserts if not exists or select in one-trip to database
sql, args := DB. Insect("tab"). Columns("b", "c"). Values(1, 2). Where("d = $1", 3). Returning("id", "f", "g"). ToSQL() sql == ` WITH sel AS (SELECT id, f, g FROM tab WHERE (d = $1)), ins AS ( INSERT INTO "tab"("b","c") SELECT $2,$3 WHERE NOT EXISTS (SELECT 1 FROM sel) RETURNING "id","f","g" ) SELECT * FROM ins UNION ALL SELECT * FROM sel `
var other Post err = DB. Select("id, title"). From("posts"). Where("id = $1", post.ID). QueryStruct(&other) published := ` WHERE user_id = $1 AND state = 'published' ` var posts []*Post err = DB. Select("id, title"). From("posts"). Scope(published, 100). QueryStructs(&posts)
Use Returning to fetch columns updated by triggers. For example,
an update trigger on "updated_at" column
err = DB. Update("posts"). Set("title", "My New Title"). Set("body", "markdown text here"). Where("id = $1", post.ID). Returning("updated_at"). QueryScalar(&post.UpdatedAt)
Upsert - Update or Insert
sql, args := DB. Upsert("tab"). Columns("b", "c"). Values(1, 2). Where("d=$1", 4). Returning("f", "g"). ToSQL() expected := ` WITH upd AS ( UPDATE tab SET "b" = $1, "c" = $2 WHERE (d=$3) RETURNING "f","g" ), ins AS ( INSERT INTO "tab"("b","c") SELECT $1,$2 WHERE NOT EXISTS (SELECT 1 FROM upd) RETURNING "f","g" ) SELECT * FROM ins UNION ALL SELECT * FROM upd `
applicable when dat.EnableInterpolation == true
To reset columns to their default DDL value, use DEFAULT. For example,
to reset payment\_type
res, err := DB. Update("payments"). Set("payment_type", dat.DEFAULT). Where("id = $1", 1). Exec()
Use SetBlacklist and SetWhitelist to control which fields are updated.
// create blacklists for each of your structs blacklist := []string{"id", "created_at"} p := paymentStructFromHandler err := DB. Update("payments"). SetBlacklist(p, blacklist...) Where("id = $1", p.ID). Exec()
Use a map of attributes
attrsMap := map[string]interface{}{"name": "Gopher", "language": "Go"} result, err := DB. Update("developers"). SetMap(attrsMap). Where("language = $1", "Ruby"). Exec()
result, err = DB. DeleteFrom("posts"). Where("id = $1", otherPost.ID). Exec()
Define JOINs in argument to From
err = DB. Select("u.*, p.*"). From(` users u INNER JOIN posts p on (p.author_id = u.id) `). WHERE("p.state = 'published'"). QueryStructs(&liveAuthors)
Scopes predefine JOIN and WHERE conditions.
Scopes may be used with DeleteFrom, Select and Update.
As an example, a "published" scope might define published posts by user.
publishedPosts := ` INNER JOIN users u on (p.author_id = u.id) WHERE p.state == 'published' AND p.deleted_at IS NULL AND u.user_name = $1 ` unpublishedPosts := ` INNER JOIN users u on (p.author_id = u.id) WHERE p.state != 'published' AND p.deleted_at IS NULL AND u.user_name = $1 ` err = DB. Select("p.*"). // must qualify columns From("posts p"). Scope(publishedPosts, "mgutz"). QueryStructs(&posts)
All queries are made in the context of a connection which is acquired from the underlying SQL driver's pool
For one-off operations, use DB directly
err := DB.SQL(sql).QueryStruct(&post)
For multiple operations, create a Tx transaction.
defer Tx.AutoCommit() or defer Tx.AutoRollback() MUST be called
func PostsIndex(rw http.ResponseWriter, r *http.Request) { tx, _ := DB.Begin() defer tx.AutoRollback() // Do queries with the session var post Post err := tx.Select("id, title"). From("posts"). Where("id = $1", post.ID). QueryStruct(&post) ) if err != nil { // `defer AutoRollback()` is used, no need to rollback on error r.WriteHeader(500) return } // do more queries with transaction ... // MUST commit or AutoRollback() will rollback tx.Commit() }
DB and Tx implement runner.Connection interface to keep code DRY
func getUsers(conn runner.Connection) ([]*dto.Users, error) {
sql := `
SELECT *
FROM users
`
var users []*dto.Users
err := conn.SQL(sql).QueryStructs(&users)
if err != nil {
return err
}
return users
}
Nested transaction logic is as follows:
If Commit is called in a nested transaction, the operation results in no operation (NOOP).
Only the top level Commit commits the transaction to the database.
If Rollback is called in a nested transaction, then the entire
transaction is rolled back. Tx.IsRollbacked is set to true.
Either defer Tx.AutoCommit() or defer Tx.AutoRollback() MUST BE CALLED
for each corresponding Begin. The internal state of nested transactions is
tracked in these two methods.
func nested(conn runner.Connection) error { tx, err := conn.Begin() if err != nil { return err } defer tx.AutoRollback() _, err := tx.SQL(`INSERT INTO users (email) values $1`, "me@home.com").Exec() if err != nil { return err } // prevents AutoRollback tx.Commit() } func top() { tx, err := DB.Begin() if err != nil { logger.Fatal("Could not create transaction") } defer tx.AutoRollback() err := nested(tx) if err != nil { return } // top level commits the transaction tx.Commit() }
A timeout may be set on any Query* or Exec with the Timeout method. When a
timeout is set, the query is run in a separate goroutine and should a timeout
occur dat will cancel the query via Postgres' pg_cancel_backend.
err := DB.Select("SELECT pg_sleep(1)").Timeout(1 * time.Millisecond).Exec() err == dat.ErrTimedout
Use dat.NullTime type to properly handle nullable dates
from JSON and Postgres.
applicable when dat.EnableInterpolation == true
dat provides often used constants in SQL statements
dat.DEFAULT - inserts DEFAULTdat.NOW - inserts NOW()UnsafeStrings and constants will panic unless dat.EnableInterpolation == true
To define SQL constants, use UnsafeString
const CURRENT_TIMESTAMP = dat.UnsafeString("NOW()") DB.SQL("UPDATE table SET updated_at = $1", CURRENT_TIMESTAMP)
UnsafeString is exactly that, UNSAFE. If you must use it, create a
constant and NEVER use UnsafeString directly as an argument like this
DB.SQL("UPDATE table SET updated_at = $1", dat.UnsafeString(someVar))
Load scalar and slice values.
var id int64 var userID string err := DB. Select("id", "user_id").From("posts").Limit(1).QueryScalar(&id, &userID) var ids []int64 err = DB.Select("id").From("posts").QuerySlice(&ids)
dat implements caching backed by an in-memory or Redis store. The in-memory store is not recommended for production use. Caching can cache any struct or primitive type that can be marshaled/unmarshaled cleanly with the json package due to Redis being a string value store.
Time is especially problematic as JavaScript, Postgres and Go
have different time formats. Use the type dat.NullTime if you are
getting cannot parse time errors.
Caching is performed before the database driver lessening the workload on the database.
// key-value store (kvs) package import "gopkg.in/mgutz/dat.v1/kvs" func init() { // Redis: namespace is the prefix for keys and should be unique store, err := kvs.NewRedisStore("namespace:", ":6379", "passwordOrEmpty") // Or, in-memory store provided by [go-cache](https://github.com/pmylund/go-cache) cleanupInterval := 30 * time.Second store = kvs.NewMemoryStore(cleanupInterval) runner.SetCache(store) } // Cache states query for a year using key "namespace:states" b, err := DB. SQL(`SELECT * FROM states`). Cache("states", 365 * 24 * time.Hour, false). QueryJSON() // Without a key, the checksum of the query is used as the cache key. // In this example, the interpolated SQL will contain their user_name // (if EnableInterpolation is true) effectively caching each user. // // cacheID == checksum("SELECT * FROM users WHERE user_name='mario'") b, err := DB. SQL(`SELECT * FROM users WHERE user_name = $1`, user). Cache("", 365 * 24 * time.Hour, false). QueryJSON() // Prefer using known unique IDs to avoid the computation cost // of the checksum key. key = "user" + user.UserName b, err := DB. SQL(`SELECT * FROM users WHERE user_name = $1`, user). Cache(key, 15 * time.Minute, false). QueryJSON() // Set invalidate to true to force setting the key statesUpdated := true b, err := DB. SQL(`SELECT * FROM states`). Cache("states", 365 * 24 * time.Hour, statesUpdated). QueryJSON() // Clears the entire cache runner.Cache.FlushDB() runner.Cache.Del("fookey")
Interpolation is DISABLED by default. Set dat.EnableInterpolation = true
to enable.
dat can interpolate locally to inline query arguments. For example,
this statement
go
db.Exec(
"INSERT INTO (a, b, c, d) VALUES ($1, $2, $3, $4)",
[]interface{}[1, 2, 3, 4],
)
is sent to the database with inlined args bypassing prepared statement logic in the lib/pq layer
"INSERT INTO (a, b, c, d) VALUES (1, 2, 3, 4)"Interpolation provides these benefits:
dat.NOW and dat.DEFAULT$1 => (1, 2, 3)Read SQL Interpolation in wiki for more details and SQL injection.