Quick Introduction

dqlx is a fully featured Dgraph Schema and Query Builder for Go.
It aims to simplify the interaction with the awesome Dgraph database allowing you to fluently compose any queries and mutations of any complexity. It also comes with a rich Schema builder to easily develop and maintain your Dgraph schema.

Installation#

go get -u github.com/fenos/dqlx

Connecting#

Once we installed the library we can quickly connect to a DGraph Cluster

import "github.com/fenos/dqlx"

func main() {
    db, err := dqlx.Connect("localhost:8080")
    
    if err != nil {
        panic(err)  
    }
}

Inserting Data#

At this point we should be successfully connected to the cluster. Let's add some data so that we can query it later.

import "github.com/fenos/dqlx"

func main() {
    db, err := dqlx.Connect("localhost:8080")
    
    if err != nil {
        panic(err)
    }

    ctx := context.Background()

    data := []map[string]interface{}{
        {
            "uid": "_:leo",
            "name": "Leo",
            "animal": "Cat",
            "age": 6,
        },
        {
            "uid": "_:ollie",
            "name": "Ollie",
            "animal": "Cat",
            "age": 2,
        },
        {
            "uid": "_:charlie",
            "name": "Charlie",
            "animal": "Dog",
            "age": 3,
        },
    }
    
    resp, err := db.Mutation().Set(data).Execute(ctx)
    
    if err != nil {
        panic(err)
    }

    println(fmt.Sprintf("Leo ID %s", resp.Raw.Uids["leo"]))
    println(fmt.Sprintf("Ollie ID %s", resp.Raw.Uids["ollie"]))
    println(fmt.Sprintf("Charlie ID %s", resp.Raw.Uids["charlie"]))
}

Querying Data#

Now that we have some data to work with, let's write some queries!
We are going to have the following criterias in our query:

Must be a Cat
Younger than 5 years old

Spoiler: We should be getting back only Ollie!

func main() {
    // ... rest of the function

    var animals []map[string]interface{}

    _, err = db.Query(dqlx.HasFn("animal")).
        Filter(
            dqlx.Eq{"animal": "Cat"},
            dqlx.Lt{"age": 5},
        ).
        Select(`
            uid
            name
            animal
            age
        `).
        UnmarshalInto(&animals).
        Execute(ctx)

    if err != nil { panic(err) }

    println(fmt.Sprintf("The animals are %v", animals))
}

The Final Script#

When putting all our code together, we'll get this lovely program:

package main

import (
    "context"
    "fmt"
    "github.com/fenos/dqlx"
    "log"
)

func main() {
    db, err := dqlx.Connect("localhost:9080")

    if err != nil {
        log.Fatal()
    }

    ctx := context.Background()

    data := []map[string]interface{}{
        {
            "uid": "_:leo",
            "name": "Leo",
            "species": "Cat",
            "age": 6,
        },
        {
            "uid": "_:ollie",
            "name": "Ollie",
            "species": "Cat",
            "age": 2,
        },
        {
            "uid": "_:charlie",
            "name": "Charlie",
            "species": "Dog",
            "age": 3,
        },
    }

    resp, err := db.Mutation().Set(data).Execute(ctx)

    if err != nil {
        panic(err)
    }

    println(fmt.Sprintf("Leo ID %s", resp.Raw.Uids["leo"]))
    println(fmt.Sprintf("Ollie ID %s", resp.Raw.Uids["ollie"]))
    println(fmt.Sprintf("Charlie ID %s", resp.Raw.Uids["charlie"]))

    var animals []map[string]interface{}

    _, err = db.Query(dqlx.HasFn("species")).
        Filter(
            dqlx.Eq{"species": "Cat"},
            dqlx.Lt{"age": 5},
        ).
        Select(`
            uid
            name
            species
            age
        `).
        UnmarshalInto(&animals).
        Execute(ctx)

    if err != nil { panic(err) }

    println(fmt.Sprintf("The animals are: %v", animals))
}

Congratulations!
You now have the basics to deep dive into the various aspects of the Queries & Mutations.