Vanilla Clojure

One of the core design goals of GraphQLize is not to tie to any web development library/framework and remain as a drop-in Clojure library. GraphQLize built on top of Lacinia, a de-facto library for implementing GraphQL APIs in Clojure.

Getting started with GraphQLize in vanilla Clojure is straight-forward and involves only three steps.

Adding Dependencies

Create a new Clojure project using deps (or leiningen) and add the GraphQLize and other dependencies.

Clojars Project

;; deps.edn
{:paths ["src" "resources"]
:deps {org.clojure/clojure {:mvn/version "1.10.1"}
org.graphqlize/graphqlize {:mvn/version "0.1.0-alpha20"}
;; db connection pool
hikari-cp {:mvn/version "2.10.0"}
;; for postgres
org.postgresql/postgresql {:mvn/version "42.2.8"}
;; for MySQL
mysql/mysql-connector-java {:mvn/version "8.0.19"}}}

Configuring DataSource

The next step is configuring the DataSource. In this example, we are going to use Hikari Connection Pool to manage the database connection.

note

For brevity, this sample uses def to define the states. In a real-world project, you can replace it with Component, Mount, or Integrant.

;; src/core.clj
(ns core
(:require [hikari-cp.core :as hikari]))
(def db-spec (hikari/make-datasource {:adapter "postgresql"
:database-name "sakila"
:server-name "localhost"
:port-number 5432
:maximum-pool-size 1
:username "postgres"
:password "postgres"}))
note

Make sure you are changing the above values to refer your database connection. The above example assumes that you are using the sakila database created from this JOOQ's example repository.

Creating Lacinia Schema

Then create a lacinia schema from the data source using GraphQLize.

(ns core
(:require ; ...
[graphqlize.lacinia.core :as l]))
(def db-spec ...)
(def lacinia-schema (l/schema db-spec))

Querying Database

With the lacinia-schema in place, we can query the underlying database using GraphQL by invoking the Lacinia's execute function.

(ns core
(:require ;...
[com.walmartlabs.lacinia :as lacinia]))
; ...
(defn execute
([query]
(lacinia/execute lacinia-schema query nil nil))
([query variables]
(lacinia/execute lacinia-schema query variables nil)))
=> (execute "query { actorByActorId(actorId: 1) { firstName, lastName } }")
;; {:data { :actorByActorId { :firstName "PENELOPE" :lastName "GUINESS" } } }

The execute function has an overload to support GraphQL variables as well. The above example can be re-written using variables as below.

=> (execute
"query($actorId: Int!) { actorByActorId(actorId: $actorId) { firstName, lastName } }"
{:actorId 1})
{:data { :actorByActorId { :firstName "PENELOPE" :lastName "GUINESS" } } }

We can also run the introspection queries to know what types and queries the GraphQLizeResolver supports.

To know all the types generated by the GraphQLize.

=> (execute "{__schema {types {name}}}")
{:data
{:__schema
{:types
({:name "Actor"}
{:name "ActorInfo"}
{:name "Address"} ...)}}}

To know more the fields of a given type, we can run the following introspection query.

=> (execute "{__type(name: \"Actor\") { fields { name type { name kind ofType { name kind }}}}}")
{:data
{:__type
{:fields
({:name "actorId"
:type {:name nil :kind :NON_NULL :ofType {:name "Int" :kind :SCALAR}}}
{:name "filmActors"
:type {:name nil :kind :NON_NULL :ofType {:name nil :kind :LIST}}}
{:name "films"
:type {:name nil :kind :NON_NULL :ofType {:name nil :kind :LIST}}}
{:name "firstName"
:type {:name nil :kind :NON_NULL :ofType {:name "String" :kind :SCALAR}}}
{:name "lastName"
:type {:name nil :kind :NON_NULL :ofType {:name "String" :kind :SCALAR}}}
{:name "lastUpdate"
:type {:name nil :kind :NON_NULL :ofType {:name "String" :kind :SCALAR}}})}}}

Next Steps

Congrats! You are on course to build impressive applications using GraphQLize in less time. To save yourself some more time, do refer this documentation to know more about how GraphQLize generates the GraphQL schema and the queries.

The sample code is available in this GitHub Repository.