Avalanche Quick Start - Pangolin Rewards

SubQuery TeamAbout 6 min

Avalanche Quick Start - Pangolin Rewards

Goals

The goal of this quick start guide is to index all token deposits and transfers from the Avalanche's Pangolin tokenopen in new window.

Note

Before we begin, make sure that you have initialised your project using the provided steps in the Start Here section. Please initialise a Avalanche 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 hereopen in new window.

1. Update Your Project Manifest File

Important

We use Ethereum packages, runtimes, and handlers (e.g. @subql/node-ethereum, ethereum/Runtime, and ethereum/*Handler) for Avalanche. Since Avalanche's C-chain is built on Ethereum's EVM, we can use the core Ethereum framework to index it.

The Project Manifest (project.ts) file works as an entry point to your Avalanche project. It defines most of the details on how SubQuery will index and transform the chain data. For Avalanche, there are three types of mapping handlers (and you can have more than one in each project):

BlockHanders: On each and every block, run a mapping function
TransactionHandlers: On each and every transaction that matches optional filter criteria, run a mapping function
LogHanders: On each and every log 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 import the correct contract definitions and update the datasource handlers.

We are indexing actions from the Pangolin Rewards contract, first you will need to import the contract abi defintion from hereopen in new window. You can copy the entire JSON and save as a file ./abis/PangolinRewards.json in the root directory.

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 Pangolin Rewards, you need to update the datasources section as follows:

{
  dataSources: [
    {
      kind: EthereumDatasourceKind.Runtime,
      // # Block when the first reward is made
      startBlock: 7906490,
      options: {
        // Must be a key of assets
        abi: "erc20",
        // Pangolin reward contract https://snowtrace.io/token/0x88afdae1a9f58da3e68584421937e5f564a0135b
        address: "0x88afdae1a9f58da3e68584421937e5f564a0135b",
      },
      assets: new Map([["erc20", { file: "./abis/PangolinRewards.json" }]]),
      mapping: {
        file: "./dist/index.js",
        handlers: [
          {
            kind: EthereumHandlerKind.Event,
            handler: "handleLog",
            filter: {
              topics: ["RewardPaid(address user, uint256 reward)"],
            },
          },
        ],
      },
    },
  ],
}

The above code indicates that you will be running a handleLog mapping function whenever there is an RewardPaid log on any transaction from the Pangolin Rewards contractopen in new window.

Check out our Manifest File documentation to get more information about the Project Manifest (project.ts) file.

2. Update Your GraphQL Schema File

The schema.graphql file determines the shape of your data from SubQuery due to the mechanism of the GraphQL query language. Hence, updating the GraphQL Schema file is the perfect place to start. It allows you to define your end goal right at the start.

Remove all existing entities and update the schema.graphql file as follows. Here you can see we are indexing two entities, PangolineRewards and Users where receiver is of type User and rewards contains a reverse look up to the receiver field.

type PangolinRewards @entity {
  id: ID! # Id is required and made up of block has and log index
  transactionHash: String!
  blockNumber: BigInt!
  blockHash: String!
  receiver: User!
  amount: BigInt!
}

type User @entity {
  id: ID! # Wallet address
  totalRewards: BigInt!
  rewards: [PangolinRewards]! @derivedFrom(field: "receiver") #This is virtual field
}

Important

When you make any changes to the schema file, please ensure that you regenerate your types directory.

SubQuery makes it easy and type-safe to work with your GraphQL entities, as well as smart contracts, events, transactions, and logs. SubQuery CLI will generate types from your project's GraphQL schema and any contract ABIs included in the data sources.

yarn

yarn codegen

npm

npm run-script codegen

This will create a new directory (or update the existing) src/types which contain generated entity classes for each type you have defined previously in schema.graphql. These classes provide type-safe entity loading, read and write access to entity fields - see more about this process in the GraphQL Schema. All entites can be imported from the following directory:

import { PangolinRewards, User } from "../types";

As you're creating a new EVM based project, this command will also generate ABI types and save them into src/types using the npx typechain --target=ethers-v5 command, allowing you to bind these contracts to specific addresses in the mappings and call read-only contract methods against the block being processed.

It will also generate a class for every contract event to provide easy access to event parameters, as well as the block and transaction the event originated from. Read about how this is done in EVM Codegen from ABIs.

In this example Avalanche SubQuery project, you would import these types like so.

import { RewardPaidLog } from "../types/abi-interfaces/PangolinRewards";

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 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, handleLog, and handleTransaction. Replace these functions with the following code (note the additional imports):

import { PangolinRewards, User } from "../types";
import { RewardPaidLog } from "../types/abi-interfaces/PangolinRewards";

async function checkGetUser(id: string): Promise<User> {
  let user = await User.get(id.toLowerCase());
  if (!user) {
    // does not exist, create a new user
    user = User.create({
      id: id.toLowerCase(),
      totalRewards: BigInt(0),
    });
  }
  return user;
}

export async function handleLog(event: RewardPaidLog): Promise<void> {
  logger.info(`New Reward Paid at block ${event.blockNumber}`);
  const { args } = event;
  if (args) {
    const user = await checkGetUser(args.user);

    const pangolinRewardRecord = new PangolinRewards(
      `${event.blockHash}-${event.logIndex}`
    );

    pangolinRewardRecord.transactionHash = event.transactionHash;
    pangolinRewardRecord.blockHash = event.blockHash;
    pangolinRewardRecord.blockNumber = BigInt(event.blockNumber);
    pangolinRewardRecord.receiverId = user.id;
    pangolinRewardRecord.amount = BigInt(args.reward.toString());

    user.totalRewards += pangolinRewardRecord.amount;
    await user.save();
    await pangolinRewardRecord.save();
  }
}

Let’s understand how the above code works.

The mapping function here receives an RewardPaidLog which includes transaction log data in the payload. We extract this data and first read and confirm that we have a User record via checkGetUser. We then create a new PangolinRewards entity that we defined in our schema.graphql and then save this to the store using the .save() function (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

yarn build

npm

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

yarn start:docker

npm

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.

query {
  pangolinRewards(first: 5) {
    nodes {
      id
      amount
    }
  }
  users(first: 5, orderBy: TOTAL_REWARDS_DESC) {
    nodes {
      id
      totalRewards
      rewards(first: 5) {
        totalCount
      }
    }
  }
}

You will see the result similar to below:

{
  "data": {
    "pangolinRewards": {
      "nodes": [
        {
          "id": "0xa0759b9929d68bc88ad01832484ecc24fd0abbcaf19a92a69a1a8fc1f2f23a71-20",
          "amount": "750406183852"
        },
        {
          "id": "0xf4b8a0948afc4264b876b4431da01a7a96a11f1ce24d73a2a0a71f9a8228b3c9-121",
          "amount": "31106152923645074116"
        },
        {
          "id": "0x8f348fcc2eb78e91e6d212a045356983f4f46ba1843e5e0f763e1e75a1ae8582-33",
          "amount": "612972344478229813"
        },
        {
          "id": "0xbb588aa14c97bad75d34ccbae332af03eab1390678516df01badf4b4f1886d4e-56",
          "amount": "3588963063129"
        },
        {
          "id": "0x477c12a0a4a5642378e58569743b24af200d36f7952d2e6bc4cfd9fa8e96592f-74",
          "amount": "30987822664812021072"
        }
      ]
    },
    "users": {
      "nodes": [
        {
          "id": "0x5da33bcd38fbc3e9632f9f6a198f4f0ef13746b6",
          "totalRewards": "4883581127128396302822",
          "rewards": {
            "totalCount": 2
          }
        },
        {
          "id": "0x79dcf1ef9786255c0f00f506c785bbd878ec184a",
          "totalRewards": "2282547055289881964699",
          "rewards": {
            "totalCount": 1
          }
        },
        {
          "id": "0x695b71dbd30a9f30c1958644086900ac9cd33c85",
          "totalRewards": "1620206587081566430579",
          "rewards": {
            "totalCount": 1
          }
        },
        {
          "id": "0xfd94d62683d8962055b661c4e64e762ed41e5489",
          "totalRewards": "1149590592806652626951",
          "rewards": {
            "totalCount": 1
          }
        },
        {
          "id": "0xab7901b09b67ee05b016456289cf74d362bd6d8c",
          "totalRewards": "882873704607946614381",
          "rewards": {
            "totalCount": 1
          }
        }
      ]
    }
  }
}

Note

The final code of this project can be found hereopen in new window.

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.

Avalanche Quick Start - Pangolin Rewards

# Avalanche Quick Start - Pangolin Rewards

# Goals

# 1. Update Your Project Manifest File

# 2. Update Your GraphQL Schema File

# 3. Add a Mapping Function

# 4. Build Your Project

# 5. Run Your Project Locally with Docker

# 6. Query your Project

# What's next?

Avalanche Quick Start - Pangolin Rewards

Goals

1. Update Your Project Manifest File

2. Update Your GraphQL Schema File

3. Add a Mapping Function

4. Build Your Project

5. Run Your Project Locally with Docker

6. Query your Project

What's next?