NEAR Quick Start
NEAR Quick Start
Goals
The goal of this quick start guide is to index all price submissions from priceoracle.near on NEAR's mainnet - it's a great way to quickly learn how SubQuery works on a real world hands-on example.
Important
Before we begin, make sure that you have initialised your project using the provided steps in the Start Here section. Please initialise a NEAR Network project
Now, let's move forward and update these configurations.
Previously, in the 1. Create a New Project section, you must have noted 3 key files. Let's begin updating them one by one.
Note
The final code of this project can be found here.
1. Update Your GraphQL Schema File
The schema.graphql
file determines the shape of the data that you are using SubQuery to index, hence it's a great place to start. The shape of your data is defined in a GraphQL Schema file with various GraphQL entities.
Remove all existing entities and update the schema.graphql
file as follows, here you can see we are indexing all oracles that submit prices on the chain, as well as each individual price submission made to NEAR's price oracle:
type Oracle @entity {
id: ID! # We'll use the account_id of the oracle as the ID
creator: String!
blockHeight: BigInt!
timestamp: BigInt!
}
type Price @entity {
id: ID!
oracle: Oracle! # The oracle that reported this price
assetID: String!
price: Int!
decimals: Int!
blockHeight: BigInt!
timestamp: BigInt!
}
Since we have a one-to-many relationship, we define a foreign key using oracle: Oracle! # The oracle that reported this price
in the Price
entity.
Important
When you make any changes to the schema file, please ensure that you regenerate your types directory.
yarn codegen
npm run-script codegen
You will find the generated models in the /src/types/models
directory.
Check out the GraphQL Schema documentation to get in-depth information on schema.graphql
file.
Now that you have made essential changes to the GraphQL Schema file, let’s move forward to the next file.
2. Update Your Project Manifest File
The Project Manifest (project.yaml
) file works as an entry point to your NEAR project. It defines most of the details on how SubQuery will index and transform the chain data. For NEAR, there are three types of mapping handlers (and you can have more than one in each project):
- BlockHandler: On each and every block, run a mapping function
- TransactionHandlers: On each and every transaction that matches optional filter criteria, run a mapping function
- ActionHandlers: On each and every transaction action that matches optional filter criteria, run a mapping function
Note that the manifest file has already been set up correctly and doesn’t require significant changes, but you need to update the datasource handlers.
We are indexing all transactions sent to the priceoracle.near
address.
This section in the Project Manifest now imports all the correct definitions and lists the triggers that we look for on the blockchain when indexing.
Since you are going to index all priceoracle.near
transactions, you need to update the datasources
section as follows:
dataSources:
- kind: near/Runtime
startBlock: 50838152 # You can set any start block you want here. This block was when app.nearcrowd.near was created https://nearblocks.io/txns/6rq4BNMpr8RwxKjfGYbruHhrL1ETbNzeFwcppGwZoQBY
mapping:
file: "./dist/index.js"
handlers:
- handler: handleNewOracle
kind: near/ActionHandler
filter:
type: FunctionCall
methodName: add_oracle
receiver: priceoracle.near
- handler: handleNewPrice
kind: near/ActionHandler
filter:
type: FunctionCall
methodName: report_prices
receiver: priceoracle.near
The above code indicates that you will be running a handleNewPrice
mapping function whenever there is transaction made to the priceoracle.near
address that includes an action with the method name report_prices
. Additionally we run the handleNewOracle
mapping function whenever there is transaction made to the priceoracle.near
address that includes an action with the method name add_oracle
.
Check out our Manifest File documentation to get more information about the Project Manifest (project.yaml
) file.
Next, let’s proceed ahead with the Mapping Function’s configuration.
3. Add a Mapping Function
Mapping functions define how chain data is transformed into the optimised GraphQL entities that we previously defined in the schema.graphql
file.
Follow these steps to add a mapping function:
Navigate to the default mapping function in the src/mappings
directory. You will be able to see three exported functions: handleBlock
, handleAction
, and handleAction
. Delete both the handleBlock
and handleAction
functions as you will only deal with the handleAction
function.
The handleAction
function receives event data whenever an event matches the filters, which you specified previously in the project.yaml
. Let’s make changes to it, process the relevant transaction action, and save them to the GraphQL entities created earlier.
Update the handleAction
function as follows (note the additional imports and renaming of functions to handleNewOracle
and handleNewPrice
):
import { FunctionCall, NearAction, NearTransaction } from "@subql/types-near";
import { Oracle, Price } from "../types";
type NewOracle = {
account_id: string;
};
type NewPrices = {
prices: {
asset_id: string;
price: {
multiplier: string;
decimals: number;
};
}[];
};
export async function handleNewOracle(action: NearAction): Promise<void> {
// Data is encoded in base64 in the args, so we first decode it and parse into the correct type
const payload: NewOracle = action.action.args.toJson();
if (payload.account_id && action.transaction) {
logger.info(
`Handling new oracle ${payload.account_id} at ${action.transaction.block_height}`
);
await checkAndCreateOracle(payload.account_id, action.transaction);
}
}
export async function handleNewPrice(action: NearAction): Promise<void> {
// Data is encoded in base64 in the args, so we first decode it and parse into the correct type
const payload: NewPrices = action.action.args.toJson();
if (action.transaction) {
logger.info(
`Handling new price action at ${action.transaction.block_height}`
);
await checkAndCreateOracle(
action.transaction.signer_id,
action.transaction
);
payload.prices.map(async (p, index) => {
await Price.create({
id: `${action.transaction.result.id}-${action.id}-${index}`,
oracleId: action.transaction.signer_id.toLowerCase(),
assetID: p.asset_id,
price: parseInt(p.price.multiplier),
decimals: p.price.decimals,
blockHeight: BigInt(action.transaction.block_height),
timestamp: BigInt(action.transaction.timestamp),
}).save();
});
}
}
async function checkAndCreateOracle(
account_id: string,
transaction: NearTransaction
): Promise<void> {
const oracle = await Oracle.get(account_id.toLowerCase());
if (!oracle) {
// We need to create a new one
await Oracle.create({
id: account_id.toLowerCase(),
creator: transaction.signer_id,
blockHeight: BigInt(transaction.block_height),
timestamp: BigInt(transaction.timestamp),
}).save();
}
}
Let’s understand how the above code works.
For the handleNewOracle
mapping function, the function receives a new NearAction
payload. The data on this is a JSON payload, so we parse into the correct NewOracle
type via JSON. We then run the checkAndCreateOracle
to ensure that we create the oracle if we don't already have it (it checks if it already exists before creating a new Oracle
entity).
For the handleNewPrice
mapping function, the function receives a new NearAction
payload. The data on this is a JSON payload, so we parse into the correct NewPrices
type via JSON. We then run the checkAndCreateOracle
to ensure that the oracle we are listing this price for is already known since it's a foreign key (it checks if it already exists before creating a new Oracle
entity). Finally, for each price submission in the array, we create the price and save it to the store (Note that SubQuery will automatically save this to the database).
Check out our Mappings documentation to get more information on mapping functions.
4. Build Your Project
Next, build your work to run your new SubQuery project. Run the build command from the project's root directory as given here:
yarn build
npm run-script build
Important
Whenever you make changes to your mapping functions, you must rebuild your project.
Now, you are ready to run your first SubQuery project. Let’s check out the process of running your project in detail.
5. Run Your Project Locally with Docker
Whenever you create a new SubQuery Project, first, you must run it locally on your computer and test it and using Docker is the easiest and quickiest way to do this.
The docker-compose.yml
file defines all the configurations that control how a SubQuery node runs. For a new project, which you have just initialised, you won't need to change anything.
However, visit the Running SubQuery Locally to get more information on the file and the settings.
Run the following command under the project directory:
yarn start:docker
npm run-script start:docker
Note
It may take a few minutes to download the required images and start the various nodes and Postgres databases.
6. Query your Project
Next, let's query our project. Follow these three simple steps to query your SubQuery project:
Open your browser and head to
http://localhost:3000
.You will see a GraphQL playground in the browser and the schemas which are ready to query.
Find the Docs tab on the right side of the playground which should open a documentation drawer. This documentation is automatically generated and it helps you find what entities and methods you can query.
Try the following query to understand how it works for your new SubQuery starter project. Don’t forget to learn more about the GraphQL Query language. The query shows a list of the most recent prices, and the most active oracles(by number of prices submitted).
query {
prices(first: 50, orderBy: BLOCK_HEIGHT_DESC) {
nodes {
id
assetID
price
decimals
oracleId
oracle {
id
}
}
}
oracles(first: 50, orderBy: PRICES_COUNT_DESC) {
nodes {
id
creator
blockHeight
timestamp
}
}
}
You will see the result similar to below:
{
"data": {
"prices": {
"nodes": [
{
"id": "FkMfPrritmGbi7dboMHwscDTQFaA2w64E2BMTv2A9V6-0-2",
"assetID": "dac17f958d2ee523a2206206994597c13d831ec7.factory.bridge.near",
"price": 10006,
"decimals": 10,
"oracleId": "npo-aurora.near",
"oracle": {
"id": "npo-aurora.near"
}
},
{
"id": "FkMfPrritmGbi7dboMHwscDTQFaA2w64E2BMTv2A9V6-0-1",
"assetID": "aurora",
"price": 163242,
"decimals": 20,
"oracleId": "npo-aurora.near",
"oracle": {
"id": "npo-aurora.near"
}
},
{
"id": "FkMfPrritmGbi7dboMHwscDTQFaA2w64E2BMTv2A9V6-0-3",
"assetID": "a0b86991c6218b36c1d19d4a2e9eb0ce3606eb48.factory.bridge.near",
"price": 9999,
"decimals": 10,
"oracleId": "npo-aurora.near",
"oracle": {
"id": "npo-aurora.near"
}
}
]
},
"oracles": {
"nodes": [
{
"id": "zerkalo.near",
"creator": "zerkalo.near",
"blockHeight": "83600017",
"timestamp": "1674465246692488448"
},
{
"id": "gloriafoster.near",
"creator": "gloriafoster.near",
"blockHeight": "83600014",
"timestamp": "1674465243614499584"
},
{
"id": "pythia.near",
"creator": "pythia.near",
"blockHeight": "83600024",
"timestamp": "1674465254364237568"
},
{
"id": "npo-aurora.near",
"creator": "npo-aurora.near",
"blockHeight": "83600043",
"timestamp": "1674465275463554048"
}
]
}
}
}
Note
The final code of this project can be found here.
What's next?
Congratulations! You have now a locally running SubQuery project that accepts GraphQL API requests for transferring data.
Tip
Find out how to build a performant SubQuery project and avoid common mistakes in Project Optimisation.
Click here to learn what should be your next step in your SubQuery journey.