The Mobile Buy SDK makes it easy to create custom storefronts in your mobile app. The SDK connects to the Shopify platform using GraphQL, and supports a wide range of native storefront experiences.
Installation ⤴
Mobile Buy SDK for Android is represented by runtime module that provides support to build and execute GraphQL queries.
implementation 'com.shopify.mobilebuysdk:buy3:3.2.3'<dependency>
<groupId>com.shopify.mobilebuysdk</groupId>
<artifactId>buy3</artifactId>
<version>3.2.3</version>
</dependency>
Getting started ⤴
The Buy SDK is built on GraphQL. The SDK handles all the query generation and response parsing, exposing only typed models and compile-time checked query structures. It doesn't require you to write stringed queries, or parse JSON responses.
You don't need to be an expert in GraphQL to start using it with the Buy SDK (but it helps if you've used it before). The sections below provide a brief introduction to this system, and some examples of how you can use it to build secure custom storefronts.
Migration from SDK v2.0 ⤴
The previous version of the Mobile SDK (version 2.0) is based on a REST API. With version 3.0, Shopify is migrating from REST to GraphQL.
Unfortunately, the specifics of generation GraphQL models make it almost impossible to create a migration path from v2.0 to v3.0 (domains models are not backward compatible). However, the main concepts are the same across the two versions, such as collections, products, checkouts, and orders.
Code Generation ⤴
The Buy SDK is built on a hierarchy of generated classes that construct and parse GraphQL queries and response. These classes are generated manually by running a custom Ruby script that relies on the GraphQL Java Generation library. Most of the generation functionality and supporting classes live inside the library. It works by downloading the GraphQL schema, generating Java class hierarchy, and saving the generated files to the specified folder path. In addition, it provides overrides for custom GraphQL scalar types like DateTime.
Request Models ⤴
All generated request models are represented by interfaces with one method define that takes single argument, generated query builder. Every query starts with generated Storefront.QueryRootQueryDefinition interface that defines the root of your query.
Let's take a look at an example query for a shop's name:
QueryRootQuery query = Storefront.query(new Storefront.QueryRootQueryDefinition() {
@Override public void define(final Storefront.QueryRootQuery rootQueryBuilder) {
rootQueryBuilder.shop(new Storefront.ShopQueryDefinition() {
@Override public void define(final Storefront.ShopQuery shopQueryBuilder) {
shopQueryBuilder.name();
}
});
}
})In this example:
Storefront.queryis the entry point for building GraphQL queries.Storefront.QueryRootQueryDefinitionrepresents the root of the query where we ask for the shop'srootQueryBuilder.shop.Storefront.ShopQueryDefinitionrepresents the subquery definition for shop field, where we request the shop'sshopQueryBuilder.name.
Request models are generated in such way where lambda expressions can come in handy. We can use lambda expressions to make the initial query more concise:
QueryRootQuery query = Storefront.query(rootQueryBuilder ->
rootQueryBuilder
.shop(shopQueryBuilder ->
shopQueryBuilder
.name()
)
)The code example above produces the following GraphQL query (you can call query.toString() to see a built GraphQL query):
query {
shop {
name
}
}Response models ⤴
All generated response models are derived from the AbstractResponse type. This abstract class provides a similar key-value type interface to a Map for accessing field values in GraphQL responses. You should never use these accessors directly, and instead rely on typed, derived properties in generated subclasses.
Let's continue the example of accessing the result of a shop name query:
// The right way
Storefront.QueryRoot response = ...;
String name = response.getShop().getName();Never use the abstract class directly:
// The wrong way (never do this)
AbstractResponse response = ...;
AbstractResponse shop = (AbstractResponse) response.get("shop");
String name = (String) shop.get("name");Again, both of the approaches produce the same result, but the former case is safe and requires no casting since it already knows about the expected type.
The Node protocol ⤴
GraphQL schema defines a Node interface that declares an id field on any conforming type. This makes it convenient to query for any object in the schema given only its id. The concept is carried across to the Buy SDK as well, but requires a cast to the correct type. You need to make sure that the Node type is of the correct type, otherwise casting to an incorrect type will return a runtime exception.
Given this query:
ID id = new ID("NkZmFzZGZhc");
Storefront.query(rootQueryBuilder ->
rootQueryBuilder
.node(id, nodeQuery ->
nodeQuery
.onProduct(productQuery ->
productQuery
.title()
...
)
)
);The Storefront.Order requires a cast:
Storefront.QueryRoot response = ...;
String title = ((Storefront.Product)response.getNode()).getTitle();Aliases ⤴
Aliases are useful when a single query requests multiple fields with the same names at the same nesting level, since GraphQL allows only unique field names. Multiple nodes can be queried by using a unique alias for each one:
Storefront.query(rootQueryBuilder ->
rootQueryBuilder
.node(new ID("NkZmFzZGZhc"), nodeQuery ->
nodeQuery
.onCollection(collectionQuery ->
collectionQuery
.withAlias("collection")
.title()
.description()
...
)
)
.node(new ID("GZhc2Rm"), nodeQuery ->
nodeQuery
.onProduct(productQuery ->
productQuery
.withAlias("product")
.title()
.description()
...
)
)
);Accessing the aliased nodes is similar to a plain node:
Storefront.QueryRoot response = ...;
Storefront.Collection collection = (Storefront.Collection) response.withAlias("collection").getNode();
Storefront.Product product = (Storefront.Product) response.withAlias("product").getNode();Learn more about GraphQL aliases.
GraphClient ⤴
The GraphClient is a network layer built on top of Square's OkHttp client that prepares GraphCall to execute query and mutation requests. It also simplifies polling and retrying requests. To get started with GraphClient, you need the following:
- Your shop's
.myshopify.comdomain - Your API key, which you can find in your shop's admin
OkHttpClient(optional), if you want to customize the configuration used for network requests or share your existingOkHttpClientwith theGraphClient- Settings for HTTP cache (optional), like the path to the cache folder and maximum allowed size in bytes
- HTTP cache policy (optional), to be used as default for all GraphQL query operations (it be ignored for mutation operations, which aren't supported). By default, the HTTP cache policy is set to
NETWORK_ONLY.
GraphClient.builder(this)
.shopDomain(BuildConfig.SHOP_DOMAIN)
.accessToken(BuildConfig.API_KEY)
.httpClient(httpClient) // optional
.httpCache(new File(getApplicationContext().getCacheDir(), "/http"), 10 * 1024 * 1024) // 10mb for http cache
.defaultHttpCachePolicy(HttpCachePolicy.CACHE_FIRST.expireAfter(5, TimeUnit.MINUTES)) // cached response valid by default for 5 minutes
.build()GraphQL specifies two types of operations: queries and mutations. The GraphClient exposes these as two type-safe operations, while also offering some conveniences for retrying and polling in each.
Queries ⤴
Semantically, a GraphQL query operation is equivalent to a GET RESTful call. It guarantees that no resources will be mutated on the server. With GraphClient, you can perform a query operation using:
GraphClient graphClient = ...;
Storefront.QueryRootQuery query = ...;
QueryGraphCall call = graphClient.queryGraph(query);For example, let's take a look at how we can query for a shop's name:
GraphClient graphClient = ...;
Storefront.QueryRootQuery query = Storefront.query(rootQuery ->
rootQuery
.shop(shopQuery ->
shopQuery
.name()
)
);
QueryGraphCall call = graphClient.queryGraph(query);
call.enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(@NonNull GraphResponse<Storefront.QueryRoot> response) {
String name = response.data().getShop().getName();
}
@Override public void onFailure(@NonNull GraphError error) {
Log.e(TAG, "Failed to execute query", error);
}
});Learn more about GraphQL queries.
Mutations ⤴
Semantically a GraphQL mutation operation is equivalent to a PUT, POST or DELETE RESTful call. A mutation is almost always accompanied by an input that represents values to be updated and a query to fetch fields of the updated resource. You can think of a mutation as a two-step operation where the resource is first modified, and then queried using the provided query. The second half of the operation is identical to a regular query request.
With GraphClient, you can perform a mutation operation using:
GraphClient graphClient = ...;
Storefront.MutationQuery query = ...;
MutationGraphCall call = graphClient.mutateGraph(query);For example, let's take a look at how we can reset a customer's password using a recovery token:
GraphClient graphClient = ...;
Storefront.CustomerResetInput input = new Storefront.CustomerResetInput("c29tZSB0b2tlbiB2YWx1ZQ", "abc123");
Storefront.MutationQuery query = Storefront.mutation(rootQuery ->
rootQuery
.customerReset(new ID("YSBjdXN0b21lciBpZA"), input, payloadQuery ->
payloadQuery
.customer(customerQuery ->
customerQuery
.firstName()
.lastName()
)
.userErrors(userErrorQuery ->
userErrorQuery
.field()
.message()
)
)
);
MutationGraphCall call = graphClient.mutateGraph(query);
call.enqueue(new GraphCall.Callback<Storefront.Mutation>() {
@Override public void onResponse(@NonNull final GraphResponse<Storefront.Mutation> response) {
if (response.data().getCustomerReset().getUserErrors().isEmpty()) {
String firstName = response.data().getCustomerReset().getCustomer().getFirstName();
String lastName = response.data().getCustomerReset().getCustomer().getLastName();
} else {
Log.e(TAG, "Failed to reset customer");
}
}
@Override public void onFailure(@NonNull final GraphError error) {
Log.e(TAG, "Failed to execute query", error);
}
});A mutation will often rely on some kind of user input. Although you should always validate user input before posting a mutation, there are never guarantees when it comes to dynamic data. For this reason, you should always request the userErrors field on mutations (where available) to provide useful feedback in your UI regarding any issues that were encountered in the mutation query. These errors can include anything from Invalid email address to Password is too short.
Learn more about GraphQL mutations.
Retry ⤴
Both QueryGraphCall and MutationGraphCall have an enqueue function that accepts RetryHandler. This object encapsulates the retry state and customization parameters for how the GraphCall will retry subsequent requests (such as after a delay, or a number of retries).
To enable retry or polling:
- Create a handler with a condition from one of two factory methods:
RetryHandler.delay(long delay, TimeUnit timeUnit)orRetryHandler.exponentialBackoff(long delay, TimeUnit timeUnit, float multiplier). - Provide an optional retry condition for response
whenResponse(Condition<GraphResponse<T>> retryCondition)or for errorwhenError(Condition<GraphError> retryCondition).
If the retryCondition evaluates to true, then the GraphCall will continue to execute the request:
GraphClient graphClient = ...;
Storefront.QueryRootQuery shopNameQuery = ...;
QueryGraphCall call = graphClient.queryGraph(shopNameQuery);
call.enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(GraphResponse<Storefront.QueryRoot> response) {
...
}
@Override public void onFailure(GraphError error) {
...
}
}, null, RetryHandler.delay(1, TimeUnit.SECONDS)
.maxCount(5)
.<Storefront.QueryRoot>whenResponse(response -> response.data().getShop().getName().equals("Empty"))
.build());
}The retry handler is generic, and can handle both QueryGraphCall and MutationGraphCall requests equally well.
Caching ⤴
Network queries and mutations can be both slow and expensive. For resources that change infrequently, you might want to use caching to help reduce both bandwidth and latency. Since GraphQL relies on POST requests, we can't easily take advantage of the HTTP caching that's available in OkHttp. For this reason, the GraphClient is equipped with an opt-in caching layer that can be enabled client-wide or on a per-request basis.
IMPORTANT: Caching is provided only for query operations. It isn't available for mutation operations.
There are four available cache policies HttpCachePolicy:
CACHE_ONLY- Fetch a response from the cache only, ignoring the network. If the cached response doesn't exist or is expired, then return an error.NETWORK_ONLY- Fetch a response from the network only, ignoring any cached responses.CACHE_FIRST- Fetch a response from the cache first. If the response doesn't exist or is expired, then fetch a response from the network.NETWORK_FIRST- Fetch a response from the network first. If the network fails and the cached response isn't expired, then return cached data instead.
For CACHE_ONLY, CACHE_FIRST and NETWORK_FIRST policies you can define the timeout after what cached response is treated as expired and will be evicted from the http cache, expireAfter(expireTimeout, timeUnit).
You can enable client-wide caching by providing a default defaultHttpCachePolicy for any instance of GraphClient. This sets all query operations to use your default cache policy, unless you specify an alternate policy for an individual request.
In this example, we set the client's defaultHttpCachePolicy property to CACHE_FIRST :
GraphClient.Builder builder = ...;
builder.defaultHttpCachePolicy(HttpCachePolicy.CACHE_FIRST)Now, all calls to queryGraph will yield a QueryGraphCall with a CACHE_FIRST cache policy.
If you want to override a client-wide cache policy for an individual request, then specify an alternate cache policy as a parameter of QueryGraphCall:
GraphClient client = ...;
QueryGraphCall queryCall = client.queryGraph(query)
.cachePolicy(HttpCachePolicy.NETWORK_FIRST.expireAfter(5, TimeUnit.MINUTES))In this example, the queryCall cache policy changes to NETWORK_FIRST, which means that the cached response will be valid for 5 minutes from the time the response is received.
Errors ⤴
There are two types of errors that you need to handle in the response callback:
Errorreturns a list of errors insideGraphResponse, which represent errors related to GraphQL query itself. These should be used for debugging purposes only.GraphErrorrepresents more critical errors related to the GraphQL query execution and processing response.
GraphQL Error ⤴
The GraphResponse class represents a GraphQL response for either a QueryGraphCall or MutationGraphCall request. It can also contain a value for Error, which represents the current error state of the GraphQL query.
It's important to note that errors and data are NOT mutually exclusive. That is to say that it's perfectly valid to have a non-null error and data. Error will provide more in-depth information about the query error. Keep in mind that these errors are not meant to be displayed to the end-user. They are for debug purposes only.
GraphClient graphClient = ...;
QueryRootQuery query = Storefront.query(rootQueryBuilder ->
rootQueryBuilder
.shop(shopQueryBuilder ->
shopQueryBuilder
.name()
)
);
QueryGraphCall call = graphClient.queryGraph(query);
call.enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(GraphResponse<Storefront.QueryRoot> response) {
if (response.hasErrors()) {
String errorMessage = response.formatErrorMessage();
}
}
@Override public void onFailure(GraphError error) {
}
});The following example shows a GraphQL error response:
{
"errors": [
{
"message": "Field 'Shop' doesn't exist on type 'QueryRoot'",
"locations": [
{
"line": 2,
"column": 90
}
],
"fields": ["Shop"]
}
]
}Learn more about GraphQL errors
GraphError ⤴
Errors for either a QueryGraphCall or MutationGraphCall request are defined by the hierarchy of the GraphError abstraction, which represents critical errors for query execution. These errors appear in the GraphCall.Callback#onFailure callback call. The error codes include:
GraphError:GraphCallcan't be executed due to an unknown reasonGraphCallCanceledError:GraphCallhas been canceledGraphHttpError:GraphCallexecuted but the HTTP response status code is not from the 200 seriesGraphNetworkError:GraphCallcan't be executed due to network issues, such as a timeout or the network being offlineGraphParseError:GraphCallexecuted but parsing JSON response has failed
To handle this type of error:
GraphClient graphClient = ...;
QueryRootQuery query = ...;
QueryGraphCall call = graphClient.queryGraph(query);
call.enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(GraphResponse<Storefront.QueryRoot> response) {
...
}
@Override public void onFailure(GraphError error) {
if (error instanceof GraphCallCanceledError) {
Log.e(TAG, "Call has been canceled", error);
} else if (error instanceof GraphHttpError) {
Log.e(TAG, "Http request failed: " + ((GraphHttpError) error).formatMessage(), error);
} else if (error instanceof GraphNetworkError) {
Log.e(TAG, "Network is not available", error);
} else if (error instanceof GraphParseError) {
// in most cases should never happen
Log.e(TAG, "Failed to parse GraphQL response", error);
} else {
Log.e(TAG, "Failed to execute GraphQL request", error);
}
}
});Search ⤴
Some Storefront models accept search terms via the query parameter. For example, you can provide a query to search for collections that contain a specific search term in any of their fields.
The following example shows how you can find collections that contain the word "shoes":
Storefront.query(root -> root
.shop(shop -> shop
.collections(
arg -> arg
.first(10)
.query("shoes"),
connection -> connection
.edges(edges -> edges
.node(node -> node
.title()
.description()
)
)
)
)
)Fuzzy matching ⤴
In the example above, the query is shoes. This will match collections that contain "shoes" in the description, title, and other fields. This is the simplest form of query. It provides fuzzy matching of search terms on all fields of a collection.
Field matching ⤴
As an alternative to object-wide fuzzy matches, you can also specify individual fields to include in your search. For example, if you want to match collections of particular type, you can do so by specifying a field directly:
.collections(arg -> arg.query("collection_type:runners"), ...The format for specifying fields and search parameters is the following: field:search_term. Note that it's critical that there be no space between the : and the search_term. Fields that support search are documented in the generated interfaces of the Buy SDK.
IMPORTANT: If you specify a field in a search (as in the example above), then the search_term will be an exact match instead of a fuzzy match. For example, based on the query above, a collection with the type blue_runners will not match the query for runners.
Negating field matching ⤴
Each search field can also be negated. Building on the example above, if you want to match all collections that were not of the type runners, then you can append a - to the relevant field:
.collections(arg -> arg.query("-collection_type:runners"), ...Boolean operators ⤴
In addition to single field searches, you can build more complex searches using boolean operators. They very much like ordinary SQL operators.
The following example shows how you can search for products that are tagged with blue and that are of type sneaker:
.products(arg -> arg.query("tag:blue AND product_type:sneaker"), ...You can also group search terms:
.products(arg -> arg.query("(tag:blue AND product_type:sneaker) OR tag:red"), ...Comparison operators ⤴
The search syntax also allows for comparing values that aren't exact matches. For example, you might want to get products that were updated only after a certain a date. You can do that as well:
.products(arg -> arg.query("updated_at:>\"2017-05-29T00:00:00Z\""), ...The query above will return products that have been updated after midnight on May 29, 2017. Note how the date is enclosed by another pair of escaped quotations. You can also use this technique for multiple words or sentences.
The SDK supports the following comparison operators:
:equal to:<less than:>greater than:<=less than or equal to:>=greater than or equal to
IMPORTANT: := is not a valid operator.
Exists operator ⤴
There is one special operator that can be used for checking null or empty values.
The following example shows how you can find products that don't have any tags. You can do so using the * operator and negating the field:
.products(arg -> arg.query("-tag:*"), ...Case studies ⤴
Getting started with any SDK can be confusing. The purpose of this section is to explore all areas of the Buy SDK that may be necessary to build a custom storefront on Android and provide a solid starting point for your own implementation.
In this section we're going to assume that you've setup a client somewhere in your source code. While it's possible to have multiple instances of GraphClient, reusing a single instance offers many behind-the-scenes performance improvements.
Fetch shop ⤴
Before you display products to the user, you typically need to obtain various metadata about your shop. This can be anything from a currency code to your shop's name:
GraphClient client = ...;
...
Storefront.QueryRootQuery query = Storefront.query(rootQuery -> rootQuery
.shop(shopQuery -> shopQuery
.name()
.currencyCode()
.refundPolicy(refundPolicyQuery -> refundPolicyQuery
.title()
.url()
)
)
);
client.queryGraph(query).enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(@NonNull GraphResponse<Storefront.QueryRoot> response) {
String name = response.data().getShop().getName();
String currencyCode = response.data().getShop().getCurrencyCode().toString();
String refundPolicyUrl = response.data().getShop().getRefundPolicy().getUrl();
}
...
});The corresponding GraphQL query would look like this:
query {
shop {
name
currencyCode
refundPolicy {
title
url
}
}
}Fetch collections and products ⤴
In our custom storefront, we want to display collection with a preview of several products. With a conventional RESTful service, this would require one network call for collections and another network call for each collection in that array. This is often referred to as the n + 1 problem.
The Buy SDK is built on GraphQL, which solves the n + 1 request problem. In the following example, a single query retrieves 10 collection and 10 products for each collection with just one network request:
GraphClient client = ...;
...
Storefront.QueryRootQuery query = Storefront.query(rootQuery -> rootQuery
.shop(shopQuery -> shopQuery
.collections(arg -> arg.first(10), collectionConnectionQuery -> collectionConnectionQuery
.edges(collectionEdgeQuery -> collectionEdgeQuery
.node(collectionQuery -> collectionQuery
.title()
.products(arg -> arg.first(10), productConnectionQuery -> productConnectionQuery
.edges(productEdgeQuery -> productEdgeQuery
.node(productQuery -> productQuery
.title()
.productType()
.description()
)
)
)
)
)
)
)
);
client.queryGraph(query).enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(@NonNull GraphResponse<Storefront.QueryRoot> response) {
List<Storefront.Collection> collections = new ArrayList<>();
for (Storefront.CollectionEdge collectionEdge : response.data().getShop().getCollections().getEdges()) {
collections.add(collectionEdge.getNode());
List<Storefront.Product> products = new ArrayList<>();
for (Storefront.ProductEdge productEdge : collectionEdge.getNode().getProducts().getEdges()) {
products.add(productEdge.getNode());
}
}
}
...
});The corresponding GraphQL query looks like this:
{
shop {
collections(first: 10) {
edges {
node {
id
title
products(first: 10) {
edges {
node {
id
title
productType
description
}
}
}
}
}
}
}
}Since it retrieves only a small subset of properties for each resource, this GraphQL request is also much more bandwidth-efficient than it would be to fetch 100 complete resources via conventional REST.
But what if you need to get more than 10 products in each collection?
Pagination ⤴
Although it might be convenient to assume that a single network request will suffice for loading all collections and products, in many cases a single request . The best practice is to paginate results. Since the Buy SDK is built on top of GraphQL, it inherits the concept of edges and nodes.
Learn more about pagination in GraphQL.
Let's take a look at how we can paginate through products in a collection:
GraphClient client = ...;
...
Storefront.QueryRootQuery query = Storefront.query(rootQuery -> rootQuery
.node(new ID("IjoxNDg4MTc3MzEsImxhc3R"), nodeQuery -> nodeQuery
.onCollection(collectionQuery -> collectionQuery
.products(
args -> args
.first(10)
.after(productPageCursor),
productConnectionQuery -> productConnectionQuery
.pageInfo(pageInfoQuery -> pageInfoQuery
.hasNextPage()
)
.edges(productEdgeQuery -> productEdgeQuery
.cursor()
.node(productQuery -> productQuery
.title()
.productType()
.description()
)
)
)
)
)
);
client.queryGraph(query).enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(@NonNull GraphResponse<Storefront.QueryRoot> response) {
Storefront.Collection collection = (Storefront.Collection) response.data().getNode();
boolean hasNextProductPage = collection.getProducts().getPageInfo().getHasNextPage();
List<Storefront.Product> products = new ArrayList<>();
for (Storefront.ProductEdge productEdge : collection.getProducts().getEdges()) {
String productPageCursor = productEdge.getCursor();
products.add(productEdge.getNode());
}
}
...
});The corresponding GraphQL query looks like this:
query {
node(id: "IjoxNDg4MTc3MzEsImxhc3R") {
... on Collection {
products(first: 10, after: "sdWUiOiIxNDg4MTc3M") {
pageInfo {
hasNextPage
}
edges {
cursor
node {
id
title
productType
description
}
}
}
}
}
}Since we know exactly what collection we want to fetch products for, we'll use the node interface to query the collection by id. You might notice that we're fetching a couple of additional fields and objects: pageInfo and cursor. We can then use a cursor of any product edge to fetch more products before it or after it. Likewise, the pageInfo object provides additional metadata about whether the next page (and potentially previous page) is available or not.
Fetch product details ⤴
In our sample app we likely want to have a detailed product page with images, variants, and descriptions. Conventionally, we'd need multiple REST calls to fetch all the required information. But with Buy SDK, we can do it with a single query:
GraphClient client = ...;
Storefront.QueryRootQuery query = Storefront.query(rootQuery -> rootQuery
.node(new ID("9Qcm9kdWN0LzMzMj"), nodeQuery -> nodeQuery
.onProduct(productQuery -> productQuery
.title()
.description()
.images(arg -> arg.first(10), imageConnectionQuery -> imageConnectionQuery
.edges(imageEdgeQuery -> imageEdgeQuery
.node(imageQuery -> imageQuery
.src()
)
)
)
.variants(arg -> arg.first(10), variantConnectionQuery -> variantConnectionQuery
.edges(variantEdgeQuery -> variantEdgeQuery
.node(productVariantQuery -> productVariantQuery
.price()
.title()
.available()
)
)
)
)
)
);
client.queryGraph(query).enqueue(new GraphCall.Callback<Storefront.QueryRoot>() {
@Override public void onResponse(@NonNull GraphResponse<Storefront.QueryRoot> response) {
Storefront.Product product = (Storefront.Product) response.data().getNode();
List<Storefront.Image> productImages = new ArrayList<>();
for (final Storefront.ImageEdge imageEdge : product.getImages().getEdges()) {
productImages.add(imageEdge.getNode());
}
List<Storefront.ProductVariant> productVariants = new ArrayList<>();
for (final Storefront.ProductVariantEdge productVariantEdge : product.getVariants().getEdges()) {
productVariants.add(productVariantEdge.getNode());
}
}
...
});The corresponding GraphQL query looks like this:
{
node(id: "9Qcm9kdWN0LzMzMj") {
... on Product {
id
title
description
images(first: 10) {
edges {
node {
id
src
}
}
}
variants(first: 10) {
edges {
node {
id
price
title
available
}
}
}
}
}
}Customer Accounts ⤴
Using the Buy SDK, you can build custom storefronts that let your customers create accounts, browse previously completed orders, and manage their information. Since most customer-related actions modify states on the server, they are performed using various mutation requests. Let's take a look at a few examples.
Creating a customer ⤴
Before a customer can log in, they must first create an account. In your application, you can provide a sign-up form that runs the following mutation request. In this example, the input for the mutation is some basic customer information that will create an account on your shop.
Storefront.CustomerCreateInput input = new Storefront.CustomerCreateInput("john.smith@gmail.com", "123456")
.setFirstName(Input.value("John"))
.setLastName(Input.value("Smith"))
.setAcceptsMarketing(Input.value(true))
.setPhone(Input.value("1-123-456-7890"));
Storefront.MutationQuery mutationQuery = Storefront.mutation(mutation -> mutation
.customerCreate(input, query -> query
.customer(customer -> customer
.id()
.email()
.firstName()
.lastName()
)
.userErrors(userError -> userError
.field()
.message()
)
)
);Keep in mind that this mutation returns a Storefront.Customer object, not an access token. After a successful mutation, the customer will still be required to log in using their credentials.
Customer login ⤴
Any customer who has an account can log in to your shop. All log-in operations are mutation requests that exchange customer credentials for an access token. You can log in your customers using the customerAccessTokenCreate mutation. Keep in mind that the return access token will eventually expire. The expiry Date is provided by the expiresAt property of the returned payload.
Storefront.CustomerAccessTokenCreateInput input = new Storefront.CustomerAccessTokenCreateInput("john.smith@gmail.com", "123456");
Storefront.MutationQuery mutationQuery = Storefront.mutation(mutation -> mutation
.customerAccessTokenCreate(input, query -> query
.customerAccessToken(customerAccessToken -> customerAccessToken
.accessToken()
.expiresAt()
)
.userErrors(userError -> userError
.field()
.message()
)
)
);Optionally, you can refresh the custom access token periodically using the customerAccessTokenRenew mutation.
IMPORTANT: It is your responsibility to securely store the customer access token.
Password reset ⤴
Occasionally, a customer might forget their account password. The SDK provides a way for your application to reset a customer's password. A minimalistic implementation can simply call the recover mutation, at which point the customer will receive an email with instructions on how to reset their password in a web browser.
The following mutation takes a customer's email as an argument and returns userErrors in the payload if there are issues with the input:
Storefront.MutationQuery mutationQuery = Storefront.mutation(mutation -> mutation
.customerRecover("john.smith@gmail.com", query -> query
.userErrors(userError -> userError
.field()
.message()
)
)
);Create, update, and delete address ⤴
You can create, update, and delete addresses on the customer's behalf using the appropriate mutation. Keep in mind that these mutations require customer authentication. Each query requires a customer access token as a parameter to perform the mutation.
The following example shows a mutation for creating an address:
String accessToken = ...;
Storefront.MailingAddressInput input = new Storefront.MailingAddressInput()
.setAddress1(Input.value("80 Spadina Ave."))
.setAddress2(Input.value("Suite 400"))
.setCity(Input.value("Toronto"))
.setCountry(Input.value("Canada"))
.setFirstName(Input.value("John"))
.setLastName(Input.value("Smith"))
.setPhone(Input.value("1-123-456-7890"))
.setProvince(Input.value("ON"))
.setZip(Input.value("M5V 2J4"));
Storefront.MutationQuery mutationQuery = Storefront.mutation(mutation -> mutation
.customerAddressCreate(accessToken, input, query -> query
.customerAddress(customerAddress -> customerAddress
.address1()
.address2()
)
.userErrors(userError -> userError
.field()
.message()
)
)
);Customer information ⤴
Up to this point, our interaction with customer information has been through mutation requests. At some point, we'll also need to show the customer their information. We can do this using customer query operations.
Just like the address mutations, customer query operations are authenticated and require a valid access token to execute. The following example shows how to obtain some basic customer info:
String accessToken = ...;
Storefront.QueryRootQuery query = Storefront.query(root -> root
.customer(accessToken, customer -> customer
.firstName()
.lastName()
.email()
)
);Customer Addresses ⤴
You can obtain the addresses associated with the customer's account:
String accessToken = ...;
Storefront.QueryRootQuery query = Storefront.query(root -> root
.customer(accessToken, customer -> customer
.addresses(arg -> arg.first(10), connection -> connection
.edges(edge -> edge
.node(node -> node
.address1()
.address2()
.city()
.province()
.country()
)
)
)
)
);Customer Orders ⤴
You can also obtain a customer's order history:
String accessToken = ...;
Storefront.QueryRootQuery query = Storefront.query(root -> root
.customer(accessToken, customer -> customer
.orders(arg -> arg.first(10), connection -> connection
.edges(edge -> edge
.node(node -> node
.orderNumber()
.totalPrice()
)
)
)
)
);Customer Update ⤴
Input objects, like Storefront.CustomerUpdateInput, use Input<T> (where T is the type of value) to represent optional fields and distinguish null values from undefined values (eg. phone: Input<String>).
The following example uses Storefront.CustomerUpdateInput to show how to update a customer's phone number:
Storefront.CustomerUpdateInput input = new Storefront.CustomerUpdateInput()
.setPhone(Input.value("1-123-456-7890"));In this example, you create an input object by setting the phone field to the new phone number that you want to update the field with. Notice that you need to pass in an Input.value() instead of a simple string containing the phone number.
The Storefront.CustomerUpdateInput object also includes other fields besides the phone field. These fields all default to a value of Input.undefined() if you don't specify them otherwise. This means that the fields aren't serialized in the mutation, and will be omitted entirely. The result GraphQL query looks like this:
mutation {
customerUpdate(
customer: { phone: "+16471234567" }
customerAccessToken: "..."
) {
customer {
phone
}
}
}This approach works well for setting a new phone number or updating an existing phone number to a new value. But what if the customer wants to remove the phone number completely? Leaving the phone number blank or sending an empty string are semantically different and won't achieve the intended result. The former approach indicates that we didn't define a value, and the latter returns an invalid phone number error. This is where the Input<T> is especially useful. You can use it to signal the intention to remove a phone number by specifying a null value:
Storefront.CustomerUpdateInput input = new Storefront.CustomerUpdateInput()
.setPhone(Input.value(null));The result is a mutation that updates a customer's phone number to null:
mutation {
customerUpdate(customer: { phone: null }, customerAccessToken: "...") {
customer {
phone
}
}
}Sample application ⤴
To help get started, have a look at the Storefront Sample android app. It covers the most common use cases of the SDK and how to integrate with it. You can also use the Storefront sample android app as a template, a starting point, or a place to cherrypick components as needed. Check out the sample app's readme for more details.
Contributions ⤴
We welcome contributions. Please follow the steps in our contributing guidelines.
Help ⤴
For help, see the Android Buy SDK documentation or post questions on our forum, in Shopify APIs & SDKs section.
License ⤴
The Mobile Buy SDK is provided under an MIT License.