A simple Python interface for AppSync resolvers and Gremlin traversals.
Project description
AppSync - Gremlin
Overview
Through the AppSync-Gremlin, developers can write powerful queries in GraphQL without having to worry about the underlying database query language in AWS Neptune. The AppSync-Gremlin provides lambda function code that converts query operation types (from GraphQL) to a gremlin traversal.
Furthermore, the library validates the queries through the user of a GraphQL schema that specifies the underlying schema of the AWS Neptune database.
Definitions
-
Property field: A field corresponding to a property of a vertex in the AWS Neptune graph database. In the below example, the
name
field is a property field.{ User { name location following { name } } }
Query 1 : (Vertex Field Example)
-
Vertex field: A field corresponding to a vertex in the AWS Neptune graph database. In the above example,
location
is a vertex field. -
Vertex list fields: A field corresponding to a list of vertices in the AWS Neptune graph database. In the above example,
following
is a vertex list field. -
Result set: An assignment of vertices in the graph to fields in the query. As the database processes the query, new result sets may be created (e.g. when traversing edges), and result sets may be discarded when they do not satisfy filters. After all parts of the query are processed by the database, all remaining result sets are used to form the query result, by taking their values at all properties marked for output (anything in an output scope).
-
Scope: The part of a query between any pair of parentheses or curly braces. We often refer to the parts between parentheses as the input scope and the parts between curly braces as the output scope or payload scope. For example, consider the query
{ User ( input: { name: { eq: "John" } } ) { name location following { name } } }
Query 2 : (Scope Example)
Filtering Operations and Pagination
Filtering
We define a filtering standard on the following scalar fields:
- ID:
For ID filtering we define the following input for filtering:
input IDFilterInput { ne: ID eq: ID in: [ID!] not_in: [ID!] }
- String: For String filtering we define the following input for filtering
input StringFilterInput { ne: String eq: String in: [String!] not_in: [String!] contains: String not_contains: String begins_with: String not_begins_with: String ends_with: String not_ends_with: String }
- Int: For Integer filtering we define the following input for filtering
input IntFilterInput { ne: Int eq: Int le: Int lt: Int ge: Int gt: Int in: [Int!] not_in: [int!] }
- Float: For Float filtering we define the following input for filtering
input FloatFilterInput { ne: Float eq: Float le: Float lt: Float ge: Float gt: Float in: [Float!] not_in: [Float!] }
- Boolean: For Boolean filtering we define the following input for filtering
input BooleanFilterInput { eq: Boolean ne: Boolean }
- DateTime: For DateTime we first have to define our own DateTime input definition. To avoid confusion and to prevent the use of different DateTime formats
in this interface, we have defined the following
DateTimeInput
to expose the individual date components (such as day, month, year, etc) as well as aformatted
field which is the ISO 8601 string representation of the DateTime value:
Using this input definition, we can then create the following input for filtering:input DateTimeInput { year: Int month: Int day: Int hour: Int minute: Int second: Int formatted: DateTime #custom datetime scalar }
input DateTimeFilterInput { eq: DateTimeInput ne: DateTimeInput in: [DateTimeInput!] not_in: [DateTimeInput!] le: DateTimeInput lt: DateTimeInput ge: DateTimeInput gt: DateTimeInput }
and a filtering standard on enum types:
enum ENUM_FIELD_TYPE {
E_1
E_2
.
.
.
E_n
}
input EnumFilterInput {
eq: ENUM_FIELD_TYPE
ne: ENUM_FIELD_TYPE
in: [ENUM_FIELD_TYPE!]
not_in: [ENUM_FIELD_TYPE!]
}
Note that these standards must be manually implemented in the original GraphQL schema. In future we may devise some method of augmenting a GraphQL schema so we don't have to manually implement them.
Pagination
Not implemented yet - TODO.
Request Mapping Template
Use the Apache VTL
{
"version" : "2017-02-28",
"operation": "Invoke",
"payload": {
"type_name": String!,
"field_name": String!,
"arguments": $util.toJson($context.args),
"identity": $util.toJson($context.identity),
"source": $util.toJson($context.source)
}
}
Usage
TODO
Project details
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