Lacinia Manual | Lacinia Tutorial | API Documentation

This library is a full implementation of Facebook's GraphQL specification.

Lacinia should be viewed as roughly analogous to the official reference JavaScript implementation. In other words, it is a backend-agnostic GraphQL query execution engine. Lacinia is not an Object Relational Mapper ... it's simply the implementation of a contract sitting between the GraphQL client and your data.

Lacinia features:

• An EDN-based schema language, or use GraphQL's Interface Definition Language.

• High performance parser for GraphQL queries, built on Antlr4.

• Efficient and asynchronous query execution.

• Full support for GraphQL types, interfaces, unions, enums, input objects, and custom scalars.

• Full support for GraphQL subscriptions.

• Full support of inline and named query fragments.

• Full support for GraphQL Schema Introspection.

Lacinia has been developed with a set of core philosophies:

• Prefer data over macros and other tricks: Compose your schema in whatever mix of data and code works for you.

• Embrace Clojure: Use EDN data, keywords, functions, and persistent data structures.

• Keep it simple: You provide the schema and a handful of functions to resolve data, and Lacinia does the rest.

• Do the right thing: apply reasonable defaults without a lot of "magic".

This library can be plugged into any Clojure HTTP pipeline. The companion library lacinia-pedestal provides full HTTP support, including GraphQL subscriptions, for Pedestal.

An externally developed library, duct-lacinia, provides similar capability for Duct.

For more detailed documentation, read the manual.

GraphQL starts with a schema definition of types that can be queried.

A schema starts as an EDN file; the example below demonstrates a small subset of the available options:

{:enums
 {:Episode
  {:description "The episodes of the original Star Wars trilogy."
   :values [:NEWHOPE :EMPIRE :JEDI]}}

 :objects
 {:Droid
  {:fields {:id {:type Int}
            :primaryFunctions {:type (list String)}
            :name {:type String}
            :appearsIn {:type (list :Episode)}}}

  :Human
  {:fields {:id {:type Int}
            :name {:type String}
            :homePlanet {:type String}
            :appearsIn {:type (list :Episode)}}}
  :Query
  {:fields {:hero {:type (non-null :Human)
                   :args {:episode {:type :Episode}}}
            :droid {:type :Droid
                    :args {:id {:type String 
                                :default-value "2001"}}}}}}}

The fields of the special Query object define the query operations available; with this schema, a client can find the Human hero of an episode, or find a Droid by its id.

A schema alone describes what data is available to clients, but doesn't identify where the data comes from; that's the job of a field resolver.

A field resolver is just a function which is passed the application context, a map of arguments values, and a resolved value from a parent field. The field resolver returns a value consistent with the type of the field; most field resolvers return a Clojure map or record, or a list of those. Lacinia then uses the GraphQL query to select fields of that value to return in the response.

Here's what a very opinionated get-hero field resolver might look like:

(defn get-hero 
  [context arguments value]
  (let [{:keys [episode]} arguments]
    (if (= episode :NEWHOPE)
      {:id 1000
       :name "Luke"
       :homePlanet "Tatooine"
       :appearsIn ["NEWHOPE" "EMPIRE" "JEDI"]}
      {:id 2000
       :name "Lando Calrissian"
       :homePlanet "Socorro"
       :appearsIn ["EMPIRE" "JEDI"]})))

In this greatly simplified example, the field resolver can simply return the resolved value. Field resolvers that return multiple values return a list, vector, or set of values.

In real applications, a field resolver might execute a query against a database, or send a request to another web service.

After injecting resolvers, it is necessary to compile the schema; this step performs validations, provides defaults, and organizes the schema for efficient execution of queries.

This needs only be done once, in application startup code:

(require '[clojure.edn :as edn]
         '[com.walmartlabs.lacinia.util :refer [inject-resolvers]]
         '[com.walmartlabs.lacinia.schema :as schema])

(def star-wars-schema
  (-> "schema.edn"
      slurp
      edn/read-string
      (inject-resolvers {:Query/hero get-hero
                         :Query/droid (constantly {})})
      schema/compile))

With the compiled application available, it can be used to execute requests; this typically occurs inside a Ring handler function:

(require '[com.walmartlabs.lacinia :refer [execute]]
         '[clojure.data.json :as json])

(defn handler [request]
  {:status 200
   :headers {"Content-Type" "application/json"}
   :body (let [query (get-in request [:query-params :query])
               result (execute star-wars-schema query nil nil)]
           (json/write-str result))})

Lacinia doesn't know about the web tier at all, it just knows about parsing and executing queries against a compiled schema. A companion library, lacinia-pedestal, is one way to expose your schema on the web.

Clients will typically send a JSON POST request, with a query key containing the GraphQL query document:

{
  hero {
    id
    name
  }
}

The execute function returns EDN data that can be easily converted to JSON. The :data key contains the value requested for the hero query in the request.

{:data
  {:hero {:id 2000
          :name "Lando Calrissian"}}}

This example request has no errors, and contained only a single query. GraphQL supports multiple queries in a single request. There may be errors executing the query, Lacinia will process as much as it can, and will report errors in the :errors key.

One of the benefits of GraphQL is that the client has the power to rename fields in the response:

{
  hero(episode: NEWHOPE) {
    movies: appearsIn
  }
}

{:data {:hero {:movies [:NEWHOPE :EMPIRE :JEDI]}}}

This is just an overview, far more detail is available in the manual.

This library has been used in production at Walmart since 2017, going through a very long beta period as it evolved; we transitioned to a 1.0 release on 9 Oct 2021.

To use this library with Clojure 1.8, you must include a dependency on clojure-future-spec.

More details are in the manual.

Copyright © 2017-2023 WalmartLabs

Distributed under the Apache License, Version 2.0.