@dcos/data-service
v2.0.0
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The goal of this project is to make access to the data as simple as writing a GraphQL query
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@dcos/data-service
The goal of this project is to make access to the data as simple as writing a GraphQL query
API
Mediator Pattern
The mediator pattern is used here to decouple data handling from the view components by encapsulating the way they communicate.
With this pattern, a component will receive down all the pieces of data (data down)
it needs via props,
and send events up
so the mediator can react to events. The key concept here is that both the
data provider and the view component have no idea how each other work.
The caller of componentFromStream
bellow is the mediator responsible for the exchange between
the part of the application which handles data, and the UI components.
/*
* Receives a stream of React.Component and outputs a single component that
* renders the most recent component emitted by the observer.
*/
componentFromStream(component$: Observable<React.Component>): React.Component;
Note that the way we achieve the Mediator pattern is not in an OO fashion, but by abstracting all the communication between the data sources and the view components by using a stream.
Query Example
This example uses a stream of repository of packages
that are fetched via one or more
APIs (abstracted here by a single stream). We use graphql to describe the query and streams
to achieve the concrete implementation. We also use streams to pass event from the components
in order to implement a search filter.
This example is an extract from DC/OS UI.
import React from "react";
import { Observable } from "rxjs";
import {
// Recompose helps handle data down and event up as streams
createEventHandler,
componentFromStream,
// Our in-house solution to resolve graphql queries using streams
graphqlObservable
} from "@dcos/data-service";
// tools to make easier to create schemas and queries
import { makeExecutableSchema } from "graphql-tools";
import gql from "graphql-tag";
// Streams we get our data from
// That could be already a more complex stream that actually merge
// different api's endpoints, sockets with REST and etc.
import { fetchRepositories } from "#PLUGINS/catalog/src/js/repositories/repositoriesStream";
// The graphql schema and resolvers for those streams;
// Normally you would import it from another file, but we inlined them here
// for a more complete example.
// import { typeDefs, resolvers } from "#SRC/js/model/repositoryModel";
export const typeDefs = `
type PackageRepository {
id: ID!
name: String!
uri: String!
}
type Query {
packageRepository(filter: String): [PackageRepository!]!
}
type Mutation {
addPackageRepository(uri: String!, name: String!): PackageRepository
}
`;
export const resolvers = {
Query: {
packageRepository: (parent, args, context) => {
const { filter } = args;
// Filter Logic Backwards compatible with the previous struct/RepositoryList
return context.query.combineLatest(filter, (result, filter) =>
Object.values(
new RepositoryList({ items: result.repositories })
.filterItemsByText(filter)
.getItems()
)
);
}
}
};
// UI components
import RepositoriesTabUI from "#SRC/js/components/RepositoriesTabUI";
import RepositoryList from "#SRC/js/structs/RepositoryList";
// Using the data layer
// 1. We first make a schema out of the resolvers and typeDefinitions
const schema = makeExecutableSchema({
typeDefs,
resolvers
});
// 2. We declare which data our component needs in graphql (data down)
const packageRepositoryQuery = gql`
query {
packageRepository(filter: $filter) {
name
uri
}
}
`;
// 3. We create an event handler as a stream to deal with search (events up)
const { handler: onSearch, stream: searchEvent$ } = createEventHandler();
// Almost always you need to provide an initial value for two reasons:
// First. it should be defined what is the first value of search,
// even when it is null, you should startWith(null)
// Second. if you don't emit a first value, the graphqlStream that depend
// on this, to filter will actually emit no result until they have the first
// value for searchTerm.
const searchTerm$ = searchEvent$.startWith("");
// 4. We compose the result with the query and massage it down the pipe until
// we get the props for our component.
// The idea is from an Observable of data and events, compose a stream of React.Components
const components$ = graphqlObservable(packageRepositoryQuery, schema, {
query: fetchRepositories(),
filter: searchTerm$
})
.combineLatest(searchTerm$, (result, searchTerm) => {
// Backwards compatible with the previous struct/RepositoryList for packages
return {
packageRepository: new RepositoryList({
items: result.packageRepository
}),
searchTerm
};
})
// We map over the data and return a component to render
.map(data => {
return (
<RepositoriesTabUI
repositories={data.packageRepository}
searchTerm={data.searchTerm}
onSearch={onSearch}
/>
);
})
// The first component is the loading
.startWith(<RepositoriesTabUI.Loading />)
// If anything goes wrong on the stream, we render an error component
// Note. that does not catch errors from within RepositoriesTabUI
.catch(err => Observable.of(<RepositoriesTabUI.Error err={err} />));
// componentFromStream create a single component who render the latest emitted
// component from the stream
const RepositoriesTab = componentFromStream(() => components$);
// the reason we don`t `export componentFromStream()` is so you can add those
// router specific things
RepositoriesTab.routeConfig = {
label: "Package Repositories",
matches: /^\/settings\/repositories/
};
// We end by exporting a single React component that will change according to the stream
module.exports = RepositoriesTab;
Notice how easy is to provide error handling whenever an exception happens and how we could start the stream of components providing a loading component.
To pass information from the components to the graphql, we use another capability
from recompose
, the createEventHandler()
.
/*
* Creates a stream that will emit a the value evetytime you call handler(value)
*/
const { handler: onSearch, stream: searchEvent$ } = createEventHandler();