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Latest version: v1.0.0.1
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greskell - Haskell binding for Gremlin graph query language

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



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

```haskell common {-# 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.HashMap.Strict as HM import qualified Data.Aeson as A 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](https://github.com/debug-ito/greskell/tree/master/test-readme) 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`.

```haskell Greskell
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.

``haskell Greskell main = hspec $ specify "Greskell" $ do toGremlin literalTextshouldBe` "\"foo\""

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

```haskell 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.

```haskell Binder 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.

```haskell Binder
main = hspec $ specify "Binder" $ do
  let (script, binding) = runBinder $ plusTen 50
  toGremlin script `shouldBe` "(__v0)+(10)"
  binding `shouldBe` HM.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.

```haskell submit 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](http://tinkerpop.apache.org/docs/current/reference/#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](http://tinkerpop.apache.org/javadocs/current/full/org/apache/tinkerpop/gremlin/process/traversal/dsl/graph/GraphTraversal.html) 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](http://tinkerpop.apache.org/docs/current/reference/#graph-traversal-steps)." greskell defines those traversal steps as functions returning a `Walk` object.

For example,

```haskell GTraversal
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)

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.

``haskell GTraversal (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

``haskell GTraversal 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.

```haskell WalkType
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.

```haskell WalkType 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.

```haskell WalkType
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".

```haskell monomorphic 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](http://hackage.haskell.org/package/aeson/docs/Data-Aeson.html) module. With Aeson, greskell implements parsers for GraphSON.

[GraphSON](http://tinkerpop.apache.org/docs/current/dev/io/#graphson) is a format to encode graph structure types into JSON. [greskell-websocket](http://hackage.haskell.org/package/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.

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

Since greskell-, 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.

```haskell own_types2 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 @[email protected] vertex. newtype VPerson = VPerson AVertex deriving (Eq,Show,FromGraphSON,ElementData,Element,Vertex)

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

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

-- | A @[email protected] 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.

```haskell own_types2
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.

``haskell own_types2 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.

```haskell graph_io
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,
    (<*.>), (&.), ($.), (<$.>),
    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

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.

```haskell graph_io 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 `Key`s for properties of `Person`.

```haskell graph_io
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.

```haskell graph_io -- | 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 HM.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.

```haskell graph_io
    let p2 = Person "peter" 35 Nothing
        (script2, binding2) = runBinder $ addPerson p2
    toGremlin script2 `shouldBe`
    binding2 `shouldBe`
      HM.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.

```haskell graph_io 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 `Key`s to get values from it.

```haskell graph_io
parsePerson :: PMap Multi GValue -> Either PMapLookupException Person
parsePerson pm =
  <$> (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.

```haskell graph_io 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.

```haskell graph_io
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)
    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)
    ( "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.

```haskell graph_io 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.

```haskell graph_io
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.

```haskell graph_io 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.

```haskell graph_io
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.

```haskell graph_io 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]>