Dgman
Dgraph schema manager, with mutate and query helpers
Install / Use
/learn @dolan-in/DgmanREADME
Dgman is a schema manager for Dgraph using the Go Dgraph client (dgo), which manages Dgraph types, schema, and indexes from Go tags in struct definitions, allowing ORM-like convenience for developing Dgraph clients in Go.
Features
- Create types (Dgraph v24.1+), schemas, and indexes from struct tags.
- Detect conflicts from existing schema and defined schema.
- Mutate Helpers (Mutate, MutateOrGet, Upsert).
- Autoinject node type from struct.
- Field unique checking (e.g: emails, username).
- Query helpers.
- Delete helpers (Delete n-quads generator, Delete Query, Delete Node, Delete Edge).
Roadmap
- Support for Dgraph v25's new namespace mechanism and other dgo v25 features.
Table of Contents
Installation
Using go modules:
go get -u github.com/dolan-in/dgman/v2
Usage
import(
"github.com/dolan-in/dgman/v2"
)
Schema Definition
Schemas are defined using Go structs which defines the predicate name from the json tag, indices and directives using the dgraph tag. To define a dgraph node struct, json fields uid and dgraph.type is required.
Node Types
Node types will be inferred from the struct name.
If you need to define a custom name for the node type, you can define it on the dgraph tag on the dgraph.type field.
type CustomNodeType struct {
UID string `json:"uid,omitempty"`
Name string `json:"name,omitempty"`
DType []string `json:"dgraph.type" dgraph:"MyNodeType"`
}
CreateSchema
Using the CreateSchema function, it will install the schema, and detect schema and index conflicts within the passed structs and with the currently existing schema in the specified Dgraph database.
// User is a node, nodes have a uid and a dgraph.type json field
type User struct {
UID string `json:"uid,omitempty"`
Name string `json:"name,omitempty" dgraph:"index=term"` // use term index
Username string `json:"username,omitempty" dgraph:"index=hash"` // use hash index
Email string `json:"email,omitempty" dgraph:"index=hash upsert"` // use hash index, use upsert directive
Password string `json:"password,omitempty" dgraph:"type=password"` // password type
Height *int `json:"height,omitempty"`
Description string `json:"description" dgraph:"lang"` // multi language support on predicate
DescriptionEn string `json:"description@en"` // will not be parsed as schema
Dob *time.Time `json:"dob,omitempty"` // will be inferred as dateTime schema type
Status EnumType `json:"status,omitempty" dgraph="type=int"`
Created time.Time `json:"created,omitempty" dgraph:"index=day"` // will be inferred as dateTime schema type, with day index
Mobiles []string `json:"mobiles,omitempty"` // will be inferred as using the [string] schema type, slices with primitive types will all be inferred as lists
Schools []School `json:"schools,omitempty" dgraph:"count reverse"` // defines an edge to other nodes, add count index, add reverse edges
DType []string `json:"dgraph.type,omitempty"`
}
// School is another node, that will be connected to User node using the schools predicate
type School struct {
UID string `json:"uid,omitempty"`
Name string `json:"name,omitempty"`
Location *GeoLoc `json:"location,omitempty" dgraph:"type=geo"` // for geo schema type, need to specify explicitly
DType []string `json:"dgraph.type,omitempty"`
}
type GeoLoc struct {
Type string `json:"type"`
Coord []float64 `json:"coordinates"`
}
func main() {
d, err := grpc.Dial("localhost:9080", grpc.WithInsecure())
if err != nil {
panic(err)
}
c := dgo.NewDgraphClient(api.NewDgraphClient(d))
// create the schema,
// it will only install non-existing schema in the specified database
schema, err := dgman.CreateSchema(c, &User{})
if err != nil {
panic(err)
}
// Check the generated schema
fmt.Println(schema)
}
On an empty database, the above code will return the generated type and schema string used to create the schema, logging the conflicting schemas in the process:
2018/12/14 02:23:48 conflicting schema name, already defined as "name: string @index(term) .", trying to define "name: string ."
status: int .
mobiles: [string] .
email: string @index(hash) @upsert .
password: string .
height: int .
dob: datetime .
schools: [uid] @count @reverse .
name: string @index(term) .
username: string @index(hash) .
created: datetime @index(day) .
location: geo .
type School {
location
name
}
type User {
status
created
username
password
height
dob
name
email
mobiles
schools
}
When schema conflicts is detected with the existing schema already installed in the database, it will only log the differences. You would need to manually correct the conflicts by dropping or updating the schema manually.
This may be useful to prevent unnecessary or unwanted re-indexing of your data.
MutateSchema
To overwrite/update index definitions, you can use the MutateSchema function, which will update the schema indexes.
// update the schema indexes
schema, err := dgman.MutateSchema(c, &User{})
if err != nil {
panic(err)
}
// Check the generated schema
fmt.Println(schema)
Mutate Helpers
Mutate
Using the Mutate function, before sending a mutation, it will marshal a struct into JSON, injecting the Dgraph node type ("dgraph.type" predicate), and do unique checking on the specified fields.
If you need unique checking for a particular field of a node with a certain node type, e.g: Email of users, you can add unique in the dgraph tag on the struct definition.
type User struct {
UID string `json:"uid,omitempty"`
Name string `json:"name,omitempty" dgraph:"index=term"`
Email string `json:"email,omitempty" dgraph:"index=hash unique"`
Username string `json:"username,omitempty" dgraph:"index=term unique"`
DType []string `json:"dgraph.type"`
}
...
user := User{
Name: "Alexander",
Email: "alexander@gmail.com",
Username: "alex123",
}
// Create a transaction with context.Background() as the context
// can be shorthened to dgman.NewTxn(c)
tx := dgman.NewTxnContext(context.Background(), c).
SetCommitNow() // set transaction to CommitNow: true, which will autocommit, leaving the transaction to only can be used once
uids, err := tx.Mutate(&user)
if err != nil {
panic(err)
}
// UID will be set
fmt.Println(user.UID)
// list of created UIDs
fmt.Println(uids)
// try to create user with a duplicate email
duplicateEmail := User{
Name: "Alexander",
Email: "alexander@gmail.com",
Username: "alexa",
}
// will return a dgman.UniqueError
tx = dgman.NewTxn(c)
_, err = tx.Mutate(&duplicateEmail)
if err != nil {
if uniqueErr, ok := err.(*dgman.UniqueError); ok {
// check the duplicate field
fmt.Println(uniqueErr.Field, uniqueErr.Value)
}
}
The above mutation will result in the following json, with dgraph.type automatically injected:
{"name":"Alexander","email":"alexander@gmail.com","username":"alex123","dgraph.type":["User"]}
Updating a Node
If you want to update an existing node, just set the UID on the struct node data being passed to Mutate. It will also do unique checking on predicates set to be unique.
type User struct {
UID string `json:"uid,omitempty"`
Name string `json:"name,omitempty"`
Email string `json:"email,omitempty" dgraph:"index=hash unique"`
Username string `json:"username,omitempty" dgraph:"index=term unique"`
Dob time.Time `json:"dob" dgraph:"index=day"`
DType []string `json:"dgraph.type"`
}
...
users := []*User{
{
Name: "Alexander",
Email: "alexander@gmail.com",
Username: "alex123",
},
{
Name: "Fergusso",
Email: "fergusso@gmail.com",
Username: "fergusso123",
},
}
tx := dgman.NewTxn(c).SetCommitNow()
_, err := tx.Mutate(&users)
if err != nil {
panic(err)
}
// try to update the user with existing username
alexander := users[0]
alexander.Username = "fergusso123"
// UID should have a value
fmt.Println(alexander.UID)
// will return a dgman.UniqueError
tx := dgman.NewTxn(c).SetCommitNow()
_, err = tx.Mutate(&alexander)
if err != nil {
if uniqueErr, ok := err.(*dgman.UniqueError); ok {
// will return duplicate error for username
fmt.Println(u
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