Base Goerli Quick Start

SubQuery TeamAbout 6 min

Base Goerli Quick Start

Goals

The goal of this quick start guide is to index the total faucets dripped to users from the USDC Faucet contractopen in new window on Base Goerli Testnetopen 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 an a Base project.

In every SubQuery project, there are 3 key files to update. Let's begin updating them one by one.

Note

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

We use Ethereum packages, runtimes, and handlers (e.g. @subql/node-ethereum, ethereum/Runtime, and ethereum/*Hander) for Base. Since Base is an EVM-compatible layer-2 scaling solution, we can use the core Ethereum framework to index it.

1. Your Project Manifest File

The Project Manifest (project.ts) file works as an entry point to your Base project. It defines most of the details on how SubQuery will index and transform the chain data. For Base, 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.

As we are indexing all dripped faucets from the USDC Faucet contract, the first step is to import the contract abi definition which can be obtained from hereopen in new window. Copy the entire contract ABI and save it as a file called faucet.abi.json in the /abis directory.

Update the datasources section as follows:

{
  dataSources: [
    {
      kind: EthereumDatasourceKind.Runtime,
      startBlock: 1512049,

      options: {
        // Must be a key of assets
        abi: "faucet_abi",
        // # this is the contract address for wrapped ether https://etherscan.io/address/0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2
        address: "0x298e0B0a38fF8B99bf1a3b697B0efB2195cfE47D",
      },
      assets: new Map([["faucet_abi", { file: "./abis/faucet.abi.json" }]]),
      mapping: {
        file: "./dist/index.js",
        handlers: [
          {
            kind: EthereumHandlerKind.Call,
            handler: "handleDrip",
            filter: {
              /**
               * The function can either be the function fragment or signature
               * function: '0x7ff36ab500000000000000000000000000000000000000000000000000000000'
               * function: drip(address token, uint256 amount, address receiver)
               */
              function: "0x6c81bd54",
            },
          },
          {
            kind: EthereumHandlerKind.Event,
            handler: "handleLog",
            filter: {
              /**
               * Follows standard log filters https://docs.ethers.io/v5/concepts/events/
               * address: "0x60781C2586D68229fde47564546784ab3fACA982"
               */
              topics: [
                "Transfer(address indexed from, address indexed to, uint256 amount)",
              ],
            },
          },
        ],
      },
    },
  ],
}

The above code indicates that you will be running a handleDrip mapping function whenever there is a drip method being called on any transaction from the USDC Faucet 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 block information such as the id, blockHeight and drip receiver along with an aggregation of the total value of the drip per day.

type Drip @entity {
  id: ID! # Transaction hash
  blockHeight: String
  to: String!
  value: BigInt!
  tokenAddress: String!
  date: Date!
}

#The following entity allows us to aggregate daily Drips for USDC faucet only. As of JulY 4th, this contract only drips USDC faucet anyway.
type DailyUSDCDrips @entity {
  id: ID! # this is the format YYYY-MM-DD T HH:MM:SS
  totalValue: BigInt!
}

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 one) src/types which contains generated entity classes for each type you have defined previously in schema.graphql. These classes provide type-safe entity loading, and read and write access to entity fields - see more about this process in the GraphQL Schema. All entities can be imported from the following directory:

import { Drip, DailyUSDCDrips } 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 SubQuery project, you would import these types like so.

import { DripTransaction } from "../types/abi-interfaces/FaucetAbi";

Important

When you make any changes to the schema file, please ensure that you regenerate your types directory using the SubQuery CLI prompt yarn codegen or npm run-script codegen.

Check out the GraphQL Schema documentation to get in-depth information on schema.graphql file.

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.

Navigate to the default mapping function in the src/mappings directory. You will be able to see two exported functions handleDrip and handleDailyDrips:

export async function handleDrip(tx: DripTransaction): Promise<void> {
  //We add a logger to see the output of the script in the console.
  logger.info(`New Drip transaction at block ${tx.blockNumber}`);
  assert(tx.args, "No tx.args");
  const drip = Drip.create({
    id: tx.hash,
    blockHeight: tx.blockNumber.toString(),
    to: await tx.args[2], //Third argument of the method call. Index starts at 0.
    value: BigNumber.from(await tx.args[1]).toBigInt(), //Second argument of the method call. Index starts at 0.
    tokenAddress: await tx.args[0], //First argument of the method call. Index starts at 0.
    date: new Date(Number(tx.blockTimestamp) * 1000),
  });

  await drip.save();

  //We only want to aggregate the USDC drips
  if (drip.tokenAddress == "0x7b4Adf64B0d60fF97D672E473420203D52562A84") {
    await handleDailyDrips(drip.date, drip.value);
  }
}

export async function handleDailyDrips(
  date: Date,
  dripValue: bigint
): Promise<void> {
  const id = date.toISOString().slice(0, 10);
  let aggregateDrips = await DailyUSDCDrips.get(id);

  if (!aggregateDrips) {
    aggregateDrips = DailyUSDCDrips.create({
      id,
      totalValue: dripValue,
    });
  } else {
    aggregateDrips.totalValue += dripValue;
  }

  await aggregateDrips.save();
}

The handleDrip function receives a tx parameter of type DripTransaction which includes transaction data in the payload. We extract this data 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 quickest 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.

# Write your query or mutation here
query {
  drips(first: 10, orderBy: DATE_DESC) {
    nodes {
      id
      value
      date
    }
  }
  dailyUSDCDrips(orderBy: ID_DESC) {
    nodes {
      id
      totalValue
    }
  }
}

You will see the result similar to below:

{
  "data": {
    "drips": {
      "nodes": [
        {
          "id": "0xeb49292b455670f08f971d9c5cf48b10ecaa7053ea0cc330bd3be58f18586524",
          "value": "1000000000",
          "date": "2023-07-04T22:58:20"
        },
        {
          "id": "0xa2757f9f16cc15b123cd78efd3eca977e8b33022a19d6c572cf09d6ef75b481e",
          "value": "1000000000",
          "date": "2023-07-04T22:57:58"
        },
        {
          "id": "0xf40aebe48a1bf7722ba3882c3161144f477cce7920cf717297d4e3ccbb811fa7",
          "value": "1000000000",
          "date": "2023-07-04T22:57:34"
        },
        {
          "id": "0x6286bb9fdafc68f1497bd32923e796aa310d08b65fd02af3ff4a5b8a20fb4062",
          "value": "1000000000",
          "date": "2023-07-04T22:57:10"
        },
        {
          "id": "0x166e458cd5147ecc5a35577e3408969f489a82aee1da0f95485d1f9377927dcc",
          "value": "1000000000",
          "date": "2023-07-04T22:54:54"
        },
        {
          "id": "0x69c42fddda0b8dc13bd1ddf361f1bd32c19518446b971d10d10d3aa7c725b603",
          "value": "1000000000",
          "date": "2023-07-04T22:54:18"
        },
        {
          "id": "0xc34551128b82b21beb47858ea7bff87abd58eba8e863ea0fb2a1e8220977b8c6",
          "value": "1000000000",
          "date": "2023-07-04T22:53:56"
        },
        {
          "id": "0x58e6e49cf624e809a51f732d95028ad1e4301f00356a47c4999e1df1226ebb48",
          "value": "1000000000",
          "date": "2023-07-04T22:53:22"
        },
        {
          "id": "0x7092884802e5600a844306cb95303a3ee062d4334a01f6c651d29e692cb636d7",
          "value": "1000000000",
          "date": "2023-07-04T22:52:24"
        },
        {
          "id": "0xe72aa8862d92c081275668113696903aafef80e0d40fe918bf0d289c603d906b",
          "value": "1000000000",
          "date": "2023-07-04T22:52:24"
        }
      ]
    },
    "dailyUSDCDrips": {
      "nodes": [
        {
          "id": "2023-07-04",
          "totalValue": "806000000000"
        }
      ]
    }
  }
}

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.

Base Goerli Quick Start

# Base Goerli Quick Start

# Goals

# 1. 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?

Base Goerli Quick Start

Goals

1. 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?