Metadata-Version: 2.1
Name: graphene-chain-mutation
Version: 1.0.1
Summary: Provide feature to reference previous mutations results in chained mutations.
Home-page: https://github.com/shinhermit/graphene-chain-mutation
Author: Josuah ARON
Author-email: josuah.aron@cogitans.fr
License: MIT
Description: # graphene-chain-mutation
        
        Provide feature to allow chaining mutations using [Graphene-python](https://docs.graphene-python.org/en/latest/quickstart/)
        
        I created this package after [a question I asked on Stackoverflow](https://stackoverflow.com/questions/61340137/graphene-graphql-how-to-chain-mutations/) and that I had to solve by myself in the end.
        
        `graphene-chain-mutation` allow to create edge-like mutations that can reference the results of previous mutations in the same query.
        
        ## Why this package ?
        
        ### The requirement
        
        Basically, when want to be able to create an object and reference it in the same query. We can use nested mutations at some extend, but it have been pointed ([here](https://www.freecodecamp.org/news/organizing-graphql-mutations-653306699f3d/) and [there](https://github.com/graphql-python/graphene/issues/944#issuecomment-492462389)) that nested mutation are not guaranteed to be sequential. So if we consider a query using nesting, like the following:
        
        ```graphql
        mutation ($parent: ParentInput, $child1: ChildInput, $child2: ChildInput) {
            n1: upsertChild(data: $child1) {
                pk
                name
                siblings { pk name }
                
                parent: createParent(data: $parent) { pk name }
                
                newSibling: createSibling(data: $child2) { pk name }
                
                # we cannot set the parent of the new sibling in this query
                # because order is not guaranted for nested mutations
            }
        }
        ```
        
        We see that we cannot set the parent of the new sibling because the latter may be created before the parent.
        
        So we want to use only root query, and maybe be able to make queries such as:
        
        ```graphql
        mutation ($parent: ParentInput, $child1: ChildInput, $child2: ChildInput) {
            n1: upsertParent(data: $parent) {
                pk
                name
            }
            
            n2: upsertChild(data: $child1) {
                pk
                name
            }
            
            n3: upsertChild(data: $child2) {
                pk
                name
            }
            
            e1: setParent(parent: "n1", child: "n2") { ok }
            
            e2: setParent(parent: "n1", child: "n3") { ok }
            
            e3: addSibling(node1: "n2", node2: "n3") { ok }
        }
        ```
        
        Where e1, e2 and e3 reference results of previous mutations.
        
        ### The problem
        
        Unfortunately, referencing results of previous mutations is not part of the GraphQL specification.
        
        In my opinion, this is an important feature for graph languages. We can compare this syntax with the Graphviz dot language, were could write for example:
        
        ```dot
        digraph D {
        
          /* Nodes */
          A 
          B
          C
        
          /* Edges */
        
          A -> B
          A -> C
          A -> D
        
        }
        ```
        
        The feature we need is simply allowing _edge-like_ operations using _nodes_ from the same mutations.
        
        ### A solution
        
        This package provide:
        
        1. A [Graphene middleware](https://docs.graphene-python.org/en/latest/execution/middleware/) that, if used, will inject a `dict` in your root resolvers so that they can _"share their results"_ if needed.
        2. A mutation class that will automatically _"share its results"_ using the `dict` injected by the middleware.
        3. 2 base edge mutation classes, to accept GraphQL alias as input argument to retrieve the results of previous mutations in the same query.
        
        ## Usage
        
        5 steps (See the [test/fake.py module](https://github.com/shinhermit/graphene-chain-mutation/blob/master/tests/fake.py) for an executable example).
        
        1. Install the package (requires [graphene](https://pypi.org/project/graphene/))
           ```bash
           pip install graphene-chain-mutation
           ```
        2. Write _node-like_ mutations by inheriting `ShareResult` _before_ `graphene.Muation`:
           ```python
            import graphene
            from graphene_chain_mutation import ShareResult
            from .types import ParentType, ParentInput, ChildType, ChildInput
           
            class CreateParent(ShareResult, graphene.Mutation, ParentType):
                class Arguments:
                    data = ParentInput()
            
                @staticmethod
                def mutate(_: None, __: graphene.ResolveInfo,
                           data: ParentInput = None) -> 'CreateParent':
                    return CreateParent(**data.__dict__)
            
            class CreateChild(ShareResult, graphene.Mutation, ChildType):
                class Arguments:
                    data = ChildInput()
            
                @staticmethod
                def mutate(_: None, __: graphene.ResolveInfo,
                           data: ChildInput = None) -> 'CreateChild':
                    return CreateChild(**data.__dict__)
           ```
        3. Create _edge-like_ mutations by inheriting either `ParentChildEdgeMutation` (for FK relationships) or `SiblingEdgeMutation` (for m2m relationships). Specify the type of their input nodes and implement the `set_link` method:
           ```python
            import graphene
            from graphene_chain_mutation import ParentChildEdgeMutation, SiblingEdgeMutation
            from .types import ParentType, ChildType
            from .fake_models import FakeChildDB
            
            class SetParent(ParentChildEdgeMutation):
        
                parent_type = ParentType
                child_type = ChildType
        
                @classmethod
                def set_link(cls, parent: ParentType, child: ChildType):
                    FakeChildDB[child.pk].parent = parent.pk
        
            class AddSibling(SiblingEdgeMutation):
        
                node1_type = ChildType
                node2_type = ChildType
        
                @classmethod
                def set_link(cls, node1: ChildType, node2: ChildType):
                    FakeChildDB[node1.pk].siblings.append(node2.pk)
                    FakeChildDB[node2.pk].siblings.append(node1.pk)
           ```
        4. Create your schema as usual
           ```python
            class Query(graphene.ObjectType):
                parent = graphene.Field(ParentType, pk=graphene.Int())
                parents = graphene.List(ParentType)
                child = graphene.Field(ChildType, pk=graphene.Int())
                children = graphene.List(ChildType)
        
            class Mutation(graphene.ObjectType):
                create_parent = CreateParent.Field()
                create_child = CreateChild.Field()
                set_parent = SetParent.Field()
                add_sibling = AddSibling.Field()
        
            schema = graphene.Schema(query=Query, mutation=Mutation)
           ```
        5. Specify the `ShareResultMiddleware` middleware while executing a query:
           ```python
            result = schema.execute(
                GRAPHQL_MUTATION
                ,variables = VARIABLES
                ,middleware=[ShareResultMiddleware()]
            )
           ```
        
        Now `GRAPHQL_MUTATION` can be a query where edge-like mutation reference the results of node-like mutations:
        
        ```python
        GRAPHQL_MUTATION = """
        mutation ($parent: ParentInput, $child1: ChildInput, $child2: ChildInput) {
            n1: upsertParent(data: $parent) {
                pk
                name
            }
            
            n2: upsertChild(data: $child1) {
                pk
                name
            }
            
            n3: upsertChild(data: $child2) {
                pk
                name
            }
            
            e1: setParent(parent: "n1", child: "n2") { ok }
            
            e2: setParent(parent: "n1", child: "n3") { ok }
            
            e3: addSibling(node1: "n2", node2: "n3") { ok }
        }
        """
        
        VARIABLES = dict(
            parent = dict(
                name = "Emilie"
            )
            ,child1 = dict(
                name = "John"
            )
            ,child2 = dict(
                name = "Julie"
            )
        )
        ```
        
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Description-Content-Type: text/markdown
