greskell - Haskell binding for Gremlin graph query language

greskell is a toolset to build and execute Gremlin graph query language in Haskell.

Contents:

The Greskell type
Build variable binding
Submit to the Gremlin Server
DSL for graph traversals
Type parameters of GTraversal and Walk
Restrict effect of GTraversal by WalkType
Submit GTraversal
Graph structure types
GraphSON parser
Make your own graph structure types
Write and read properties to/from the graph

Prelude

Because this README is also a test script, first we import common modules.

{-# LANGUAGE OverloadedStrings, TypeFamilies, GeneralizedNewtypeDeriving, UndecidableInstances #-}
import Control.Applicative ((<$>), (<*>))
import Control.Category ((>>>))
import Control.Monad (guard)
import Data.Monoid (mempty, (<>))
import Data.Text (Text)
import qualified Data.Aeson as A
import qualified Data.Aeson.KeyMap as KM
import qualified Data.Aeson.Types as A
import Data.Function ((&))
import Test.Hspec

To run the examples in this README, run stack test test-readme. See test-readme directory to see how this works.

The Greskell type

At the core of greskell is the Greskell type. Greskell a represents a Gremlin expression that evaluates to the type a.

import Data.Greskell.Greskell (Greskell, toGremlin)

literalText :: Greskell Text
literalText = "foo"

literalInt :: Greskell Int
literalInt = 200

You can convert Greskell into Gremlin Text script by toGremlin function.

main = hspec $ specify "Greskell" $ do
  toGremlin literalText `shouldBe` "\"foo\""

Greskell implements instances of IsString, Num, Fractional etc. so you can use methods of these classes to build Greskell.

  toGremlin (literalInt + 30 * 20) `shouldBe` "(200)+((30)*(20))"

Build variable binding

Gremlin Server supports parameterized scripts, where a client can send a Gremlin script and variable binding.

greskell's Binder monad is a simple monad that manages bound variables and their values. With Binder, you can inject Haskell values into Greskell.

import Data.Greskell.Greskell (Greskell, toGremlin)
import Data.Greskell.Binder (Binder, newBind, runBinder)

plusTen :: Int -> Binder (Greskell Int)
plusTen x = do
  var_x <- newBind x
  return $ var_x + 10

newBind creates a new Gremlin variable unique in the Binder's monadic context, and returns that variable.

main = hspec $ specify "Binder" $ do
  let (script, binding) = runBinder $ plusTen 50
  toGremlin script `shouldBe` "(__v0)+(10)"
  binding `shouldBe` KM.fromList [("__v0", A.Number 50)]

runBinder function returns the Binder's monadic result and the created binding.

Submit to the Gremlin Server

To connect to the Gremlin Server and submit your Gremlin script, use greskell-websocket package.

import Control.Exception.Safe (bracket, try, SomeException)
import Data.Foldable (toList)
import Data.Greskell.Greskell (Greskell) -- from greskell package
import Data.Greskell.Binder -- from greskell package
  (Binder, newBind, runBinder)
import Network.Greskell.WebSocket -- from greskell-websocket package
  (connect, close, submit, slurpResults)
import System.IO (hPutStrLn, stderr)

submitExample :: IO [Int]
submitExample =
  bracket (connect "localhost" 8182) close $ \client -> do
    let (g, binding) = runBinder $ plusTen 50
    result_handle <- submit client g (Just binding)
    fmap toList $ slurpResults result_handle

plusTen :: Int -> Binder (Greskell Int)
plusTen x = do
  var_x <- newBind x
  return $ var_x + 10

main = hspec $ specify "submit" $ do
  egot <- try submitExample :: IO (Either SomeException [Int])
  case egot of
    Left e -> do
      hPutStrLn stderr ("submit error: " ++ show e)
      hPutStrLn stderr ("  We ignore the error. Probably there's no server running?")
    Right got -> do
      hPutStrLn stderr ("submit success: " ++ show got)
      got `shouldBe` [60]

submit function sends a Greskell to the server and returns a ResultHandle. ResultHandle is a stream of evaluation results returned by the server. slurpResults gets all items from ResultHandle.

DSL for graph traversals

greskell has a domain-specific language (DSL) for building Gremlin Traversal object. Two data types, GTraversal and Walk, are especially important in this DSL.

GTraversal is simple. It's just the greskell counterpart of GraphTraversal class in Gremlin.

Walk is a little tricky. It represents a chain of one or more method calls on a GraphTraversal object. In Gremlin, those methods are called "graph traversal steps." greskell defines those traversal steps as functions returning a Walk object.

For example,

import Data.Greskell.Greskell (toGremlin, Greskell)
import Data.Greskell.GTraversal
  ( GTraversal, Transform, Walk, source, sV,
    gHasLabel, gHas2, (&.), ($.)
  )
import Data.Greskell.Graph (AVertex)

allV :: GTraversal Transform () AVertex
allV = source "g" & sV []

isPerson :: Walk Transform AVertex AVertex
isPerson = gHasLabel "person"

isMarko :: Walk Transform AVertex AVertex
isMarko = gHas2 "name" "marko"

main = hspec $ specify "GTraversal" $ do
  toGremlin (allV &. isPerson &. isMarko)
    `shouldBe`
    "g.V().hasLabel(\"person\").has(\"name\",\"marko\")"

In the above example, allV is the GraphTraversal obtained by g.V(). isPerson and isMarko are method calls of .hasLabel and .has steps, respectively. (&.) operator combines a GTraversal and Walk to get an expression that the graph traversal steps are executed on the GraphTraversal.

The above example also uses AVertex type. AVertex is a type for a graph vertex. We will explain it in detail later in Graph structure types.

Note that we use (&) operator in the definition of allV. (&) operator from Data.Function module is just the flip of ($) operator. Likewise, greskell defines ($.) operator, so we could also write the above expression as follows.

  (toGremlin $ isMarko $. isPerson $. sV [] $ source "g")
    `shouldBe`
    "g.V().hasLabel(\"person\").has(\"name\",\"marko\")"

Type parameters of GTraversal and Walk

GTraversal and Walk both have the same type parameters.

GTraversal walk_type start end
Walk       walk_type start end

GTraversal and Walk both take the traversers with data of type start, and emit the traversers with data of type end. We will explain walk_type later.

Walk is very similar to function (->). That is why it is an instance of Category, so you can compose Walks together. The example in the previous section can also be written as

  let composite_walk = isPerson >>> isMarko
  toGremlin (source "g" & sV [] &. composite_walk)
    `shouldBe`
    "g.V().hasLabel(\"person\").has(\"name\",\"marko\")"

Restrict effect of GTraversal by WalkType

The first type parameter of GTraversal and Walk is called "walk type". Walk type is a type marker to describe effect of the graph traversal. There are three walk types, Filter, Transform and SideEffect. All of them are instance of WalkType class.

Walks of Filter type do filtering only. It takes input traversers and emits some of them. It does nothing else. Example: .has and .filter steps.
Walks of Transform type may transform the input traversers but have no side effects. Example: .map and .out steps.
Walks of SideEffect type may alter the "side effect" context of the Traversal object or the state outside the Traversal object. Example: .aggregate and .addV steps.

Walk types are hierarchical. Transform is more powerful than Filter, and SideEffect is more powerful than Transform. You can "lift" a walk with a certain walk type to one with a more powerful walk type by liftWalk function.

import Data.Greskell.GTraversal
  ( Walk, Filter, Transform, SideEffect, GTraversal,
    liftWalk, source, sV, (&.),
    gHasLabel, gHas1, gAddV, gValues, gIdentity
  )
import Data.Greskell.Graph (AVertex)
import Data.Greskell.Greskell (toGremlin)
import Network.Greskell.WebSocket (Client, ResultHandle, submit)

hasAge :: Walk Filter AVertex AVertex
hasAge = gHas1 "age"

hasAge' :: Walk Transform AVertex AVertex
hasAge' = liftWalk hasAge

Now what are these walk types useful for? Well, it allows you to build graph traversals in a safer way than you do with plain Gremlin.

In Haskell, we can distinguish pure and non-pure functions using, for example, IO monad. Likewise, we can limit power of traversals by using Filter or Transform walk types explicitly. That way, we can avoid executing unwanted side-effect accidentally.

nameOfPeople :: Walk Filter AVertex AVertex -> GTraversal Transform () Text
nameOfPeople pfilter =
  source "g" & sV [] &. gHasLabel "person" &. liftWalk pfilter &. gValues ["name"]

newPerson :: Walk SideEffect s AVertex
newPerson = gAddV "person"

main = hspec $ specify "liftWalk" $ do
  ---- This compiles
  toGremlin (nameOfPeople hasAge)
    `shouldBe` "g.V().hasLabel(\"person\").has(\"age\").values(\"name\")"

  ---- This doesn't compile.
  ---- It's impossible to pass a SideEffect walk to an argument that expects Filter.
  -- toGremlin (nameOfPeople newPerson)
  --   `shouldBe` "g.V().hasLabel(\"person\").addV(\"person\").values(\"name\")"

In the above example, nameOfPeople function takes a Filter walk and creates a Transform GTraversal. There is no way to pass a SideEffect walk (like gAddV) to nameOfPeople because Filter is weaker than SideEffect. That way, we can be sure that the result traversal of nameOfPeople function never has any side-effect (thus its walk type is just Transform.)

Submit GTraversal

You can submit GTraversal directly to the Gremlin Server. Submitting GTraversal c s e yeilds ResultHandle e, so you can get the traversal results in a stream.

getNameOfPeople :: Client -> IO (ResultHandle Text)
getNameOfPeople client = submit client (nameOfPeople gIdentity) Nothing

Graph structure types

Graph structure interfaces in Gremlin are represented as type-classes in greskell. We have Element, Vertex, Edge and Property type-classes for the interfaces of the same name.

The reason why we use type-classes is that it allows you to define your own data types as a graph structure. See "Make your own graph structure types" below in detail.

As the basis of graph structure types, we have AVertex, AEdge, AVertexProperty and AProperty types. You might need those types because some functions are too polymorphic for the compiler to infer the types for its "start" and "end".

import Data.Greskell.Greskell (toGremlin)
import Data.Greskell.Graph (AVertex)
import Data.Greskell.GTraversal
  ( GTraversal, Transform,
    source, (&.), sV, gOut, sV', gOut',
  )

main = hspec $ specify "monomorphic walk" $ do
  ---- This doesn't compile
  -- toGremlin (source "g" & sV [] &. gOut []) `shouldBe` "g.V().out()"

  -- This compiles, with type annotation.
  let gv :: GTraversal Transform () AVertex
      gv = source "g" & sV []
      gvo :: GTraversal Transform () AVertex
      gvo = gv &. gOut []
  toGremlin gvo `shouldBe` "g.V().out()"
  
  -- This compiles, with monomorphic functions.
  toGremlin (source "g" & sV' [] &. gOut' []) `shouldBe` "g.V().out()"

In the above example, sV and gOut are polymorphic with Vertex constraint, so the compiler would complain about the ambiguity. In that case, you can add explicit type annotations of AVertex type, or use monomorphic versions, sV' and gOut'.

GraphSON parser

A in AVertex stands for "Aeson". That means this type is based on the data type from Data.Aeson module. With Aeson, greskell implements parsers for GraphSON.

GraphSON is a format to encode graph structure types into JSON. greskell-websocket uses GraphSON to communicate with the Gremlin Server.

To support GraphSON decoding, we introduced the following symbols:

GraphSON type: GraphSON a has data of type a and optional "type string" that describes the type of that data.
GValue type: basically Aeson's Value enhanced with GraphSON.
FromGraphSON type-class: types that can be parsed from GValue. It's analogous to Aeson's FromJSON.

AVertex, AEdge, AVertexProperty and AProperty types implement FromGraphSON instance, so you can directly obtain those types from the Gremlin Server.

getAllVertices :: Client -> IO (ResultHandle AVertex)
getAllVertices client = submit client (source "g" & sV []) Nothing

Since greskell-1.0.0.0, AVertex, AEdge and AVertexProperty are just references to graph elements, and they don't keep any properties. To read properties from graph elements, see "Read properties" below.

Make your own graph structure types

Often your graph data model is heterogeneous, that is, you have more than one types of vertices and edges with different meanings. Just using AVertex and AEdge for them easily leads to invalid graph operations. Let's distinguish them by Haskell's type system.

To make your own graph structure types, just wrap the base types with newtype.

import Data.Greskell.Graph (AVertex, AEdge, ElementData, Element, Vertex, Edge)
import Data.Greskell.GraphSON (FromGraphSON)
import Data.Greskell.Greskell (toGremlin)
import Data.Greskell.GTraversal
  ( GTraversal, Walk, Transform, gOut, gOutE, gHasLabel,
    source, sV, (&.)
  )

-- | A @person@ vertex.
newtype VPerson = VPerson AVertex
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Vertex)

-- | A @software@ vertex.
newtype VSoftware = VSoftware AVertex
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Vertex)

-- | A @knows@ edge.
newtype EKnows = EKnows AEdge
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Edge)

-- | A @created@ edge.
newtype ECreated = ECreated AEdge
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Edge)

For each graph type, you need to derive FromGraphSON, ElementData, Element and Vertex or Edge. Note that you need to enable GeneralizedNewtypeDeriving and UndecidableInstances extensions of GHC to derive those instances.

With those graph element types, you can also define your own traversal steps.

allPersons :: GTraversal Transform () VPerson
allPersons = source "g" & sV [] &. gHasLabel "person"

gOutKnows :: Walk Transform VPerson VPerson
gOutKnows = gOut ["knows"]

gOutCreated :: Walk Transform VPerson VSoftware
gOutCreated = gOut ["created"]

gOutEKnows :: Walk Transform VPerson EKnows
gOutEKnows = gOutE ["knows"]

Using those customized traversal steps, you can make your Gremlin scripts more type-safe and rich in semantics.

main = hspec $ specify "own types" $ do
  toGremlin (allPersons &. gOutCreated)
    `shouldBe` "g.V().hasLabel(\"person\").out(\"created\")"

  toGremlin (allPersons &. gOutKnows)
    `shouldBe` "g.V().hasLabel(\"person\").out(\"knows\")"

  ---- This doesn't compile because the end of gOutCreated is VSoftware
  ---- but the start of gOutKnows is VPerson.
  -- toGremlin (allPersons &. gOutCreated &. gOutKnows)
  --   `shouldBe` "g.V().hasLabel(\"person\").out(\"created\").out(\"knows\")"

Write and read properties to/from the graph

Writing and reading complex properties to/from the graph database is a little tricky. This section explains how we do that with greskell.

As a prelude for this section, we import the following modules first.

import Control.Exception.Safe (bracket)
import Data.Foldable (toList)
import Data.Greskell.AsLabel (AsLabel)
import Data.Greskell.Binder (Binder, runBinder, newBind)
import Data.Greskell.Extra (writeKeyValues, (<=:>), (<=?>))
import Data.Greskell.Greskell (toGremlin)
import Data.Greskell.GraphSON (FromGraphSON(..), GValue)
import Data.Greskell.Graph
  ( AVertex, AEdge, ElementData, Element, Vertex, Edge,
    Key, Keys(KeysNil)
  )
import Data.Greskell.GTraversal
  ( Walk, GTraversal, SideEffect, Transform, liftWalk,
    source, sAddV, gValueMap, gProject, gByL,
    gOutV, gInV, gValues, sV, sV', sE,
    (<*.>), (&.), ($.), (<$.>),
    unsafeCastEnd,
    gHas2, gTo, gV, gAddE, gProperty, gDrop
  )
import Data.Greskell.PMap
  ( PMap, Multi, Single, PMapLookupException,
    lookupAs, lookupAs', pMapToFail
  )
import Network.Greskell.WebSocket
  ( connect, close, submit, submitPair,
    slurpResults, drainResults
  )

import Test.Hspec.NeedEnv (EnvMode(Want), needEnvHostPort)

main = hspec $ do
  specWrite
  specRead1
  specRead2
  specIO

Write properties

To write properties of graph elements into the database, you use ".property" step of Gremlin. greskell offers some utility functions to make it a little easier.

First, define a data type for your application, and its corresponding vertex type.

type Name = Text

data Person =
  Person
  { personName :: Name,
    personAge :: Int,
    personCompany :: Maybe Text
    -- ^ Name of the company the person works for, if any.
  }
  deriving (Show,Eq,Ord)

-- | A Vertex corresponding to 'Person'.
newtype VPerson = VPerson AVertex
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Vertex)

Then, define Keys for properties of Person.

keyName :: Key VPerson Name
keyName = "name"

keyAge :: Key VPerson Int
keyAge = "age"

keyCompany :: Key VPerson (Maybe Text)
keyCompany = "company"

We will use those Keys to write and read properties to/from the graph database. I know it's boring to define Keys manually like the above example. Future versions of greskell may support some ways to generate keys from a record type.

Anyway, once you set up the Keys, you can use writeKeyValues to make a series of ".property" steps for a Person.

-- | Write 'Person' properties into a 'VPerson' vertex.
writePerson :: Person -> Binder (Walk SideEffect VPerson VPerson)
writePerson p = fmap writeKeyValues $ sequence $
                [ keyName <=:> personName p,
                  keyAge <=:> personAge p,
                  keyCompany <=?> personCompany p
                ]

-- | Add a new 'VPerson' vertex.
addPerson :: Person -> Binder (GTraversal SideEffect () VPerson)
addPerson p = writePerson p <*.> (pure $ sAddV "person" $ source "g")

specWrite :: Spec
specWrite =
  specify "property writers" $ do
    let p1 = Person "josh" 32 (Just "marko")
        (script1, binding1) = runBinder $ addPerson p1
    toGremlin script1 `shouldBe`
      "g.addV(\"person\").property(\"name\",__v0).property(\"age\",__v1).property(\"company\",__v2).identity()"
    binding1 `shouldBe`
      KM.fromList [ ("__v0", A.String "josh"),
                    ("__v1", A.Number 32),
                    ("__v2", A.String "marko")
                  ]

Note that properties in the Haskell program are sent to the Gremlin Server using variable binding. That is why we use Binder monad and monadic operators like <=:>, <=?> and <*.>.

Note also that we should use <=?> (not <=:>) to write an optional field personCompany. Basically TinkerPop's graph implementations don't allow writing "null" as a property value. So, if the optional field does not have a value, you should not generate ".property" step for it. The operator <=?> and writeKeyValues function take care of it.

    let p2 = Person "peter" 35 Nothing
        (script2, binding2) = runBinder $ addPerson p2
    toGremlin script2 `shouldBe`
      "g.addV(\"person\").property(\"name\",__v0).property(\"age\",__v1).identity()"
    binding2 `shouldBe`
      KM.fromList [ ("__v0", A.String "peter"),
                    ("__v1", A.Number 35)
                  ]

Read properties

The most basic way to read properties from the graph is to use ".valueMap" step. In greskell, you can use gValueMap function, which generates a PMap object as a result.

personProps :: Walk Transform VPerson (PMap Multi GValue)
personProps = gValueMap KeysNil

specRead1 :: Spec
specRead1 = specify "property readers1" $ do
  toGremlin (source "g" & sV [] &. personProps) `shouldBe` "g.V().valueMap()"

PMap is a map of property key-values. You can use the Keys to get values from it.

parsePerson :: PMap Multi GValue -> Either PMapLookupException Person
parsePerson pm =
  Person
  <$> (lookupAs keyName pm)
  <*> (lookupAs keyAge pm)
  <*> (lookupAs' keyCompany pm)

Note that you should use lookupAs' (not lookupAs) to read an optional field. lookupAs' treats lack of the key as Nothing, while lookupAs treats it as an error.

If you need more information than gValueMap can provide, you should probably use gProject. You often see such a case when you deal with data models for edges.

data Knows =
  Knows
  { knowSubject :: Name,
    -- ^ Name of a person who knows
    knowObject :: Name,
    -- ^ Name of a person who is known
    knowWeight :: Double
  }
  deriving (Show,Eq,Ord)

-- | An Edge corresponding to 'Knows'.
newtype EKnows = EKnows AEdge
        deriving (Eq,Show,FromGraphSON,ElementData,Element,Edge)

keyWeight :: Key EKnows Double
keyWeight = "weight"

knowSubject and knowObject fields are not included in the properties of a "knows" edge, but they are properties of "person" vertices the edge connects. To get all information at once, gProject is useful.

labelSubject :: AsLabel Name
labelSubject = "sub"

labelObject :: AsLabel Name
labelObject = "obj"

labelProps :: AsLabel (PMap Single GValue)
labelProps = "props"

knowsInfo :: Walk Transform EKnows (PMap Single GValue)
knowsInfo = gProject
            ( gByL labelSubject (gKnowSub >>> gValues [keyName]) )
            [ gByL labelObject  (gKnowObj >>> gValues [keyName]),
              gByL labelProps   (gValueMap KeysNil)
            ]
  where
    gKnowSub :: Walk Transform EKnows VPerson
    gKnowSub = gOutV
    gKnowObj :: Walk Transform EKnows VPerson
    gKnowObj = gInV

specRead2 :: Spec
specRead2 = specify "property readers2" $ do
  toGremlin (source "g" & sE [] &. knowsInfo)
    `shouldBe`
    ( "g.E().project(\"sub\",\"obj\",\"props\")"
      <> ".by(__.outV().values(\"name\")).by(__.inV().values(\"name\")).by(__.valueMap())"
    )

gProject takes one or more pairs of label and sub-traversal. Its result is a PMap where the key is the label and the value is the result of the sub-traversal. If you use gValueMap in a sub-traversal, its result PMap is nested.

To parse the result of gProject, you can use the labels and keys defined above.

parseKnows :: PMap Single GValue -> Either PMapLookupException Knows
parseKnows pm =
  Knows
  <$> (lookupAs labelSubject pm)
  <*> (lookupAs labelObject pm)
  <*> (lookupAs keyWeight =<< lookupAs labelProps pm)

Embed property data types

In the above examples, you cannot use property data types (Person and Knows) directly in greskell expressions. Instead, you first have to read out a PMap from the Gremlin Server, and then parse it into Person or Knows. Often it'd be more type-safe and semantic to read Person and Knows directly from the Gremlin Server.

To embed your property data types directly into greskell, you have to define FromGraphSON instance for them. That's acutally so easy, because we already define parsers for them.

instance FromGraphSON Person where
  parseGraphSON gv = (pMapToFail . parsePerson) =<< parseGraphSON gv

In the above, gv is first parsed into a PMap, which is then parsed by parsePerson. pMapToFail just converts Either into Parser.

To make it type-safe, you should define a dedicated traversal to get a Person object.

getPerson :: Walk Transform VPerson Person
getPerson = unsafeCastEnd personProps

unsafeCastEnd function converts the end type of the walk from PMap to Person. We know that Person is parsed from the PMap, so we can tolerate this unsafe cast here.

The same goes for Knows, too.

instance FromGraphSON Knows where
  parseGraphSON gv = (pMapToFail . parseKnows) =<< parseGraphSON gv

getKnows :: Walk Transform EKnows Knows
getKnows = unsafeCastEnd knowsInfo

Now, by putting them all together, we can write and read data to/from the graph database like the following.

addKnows :: Name -> Double -> Binder (Walk SideEffect VPerson EKnows)
addKnows target_name weight = do
  vtarget <- newBind target_name
  vweight <- newBind weight
  return $
    gAddE "knows" (gTo (gV [] >>> gHas2 keyName vtarget)) >>> gProperty keyWeight vweight

specIO :: Spec
specIO = specify "write and read graph properties" $ do
  -- Run this test only when we get host and port from the environment variables
  (host, port) <- needEnvHostPort Want "GRESKELL_TEST_README"
  
  bracket (connect host port) close $ \client -> do
    -- Clear graph.
    drainResults =<< submit client (gDrop $. liftWalk $ sV' [] $ source "g") Nothing

    -- Add and get a Person vertex.
    let input_p1 = Person "josh" 32 (Just "marko")
    drainResults =<< (submitPair client $ runBinder $ addPerson input_p1)
    got_p1 <- fmap toList $ slurpResults =<<
              submit client (getPerson $. sV [] $ source "g") Nothing
    got_p1 `shouldBe` [input_p1]

    -- Add another Person, add a Knows edge and get it.
    let input_p2 = Person "marko" 29 Nothing
        expected_k = Knows "marko" "josh" 1.0
    got_k <- fmap toList $ slurpResults =<<
             ( submitPair client $ runBinder $
               liftWalk getKnows <$.> addKnows "josh" 1.0 <*.> addPerson input_p2
             )
    got_k `shouldBe` [expected_k]

Todo

Complete graph traversal steps API.

Author

Toshio Ito [email protected]

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