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Base Goerli Quick Start

SubQuery TeamAbout 3 min

Base Goerli Quick Start

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.

In the earlier Quickstart section , you should have taken note of three crucial files. To initiate the setup of a project from scratch, you can proceed to follow the steps outlined in the initialisation description.

As a prerequisite, you will need to generate types from the ABI files of each smart contract. Additionally, you can kickstart your project by using the EVM Scaffolding approach (detailed here). You'll find all the relevant events to be scaffolded in the documentation for each type of smart contract.

Note

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

Your Project Manifest File

The Project Manifest file is an entry point to your project. It defines most of the details on how SubQuery will index and transform the chain data.

For EVM chains, 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

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.

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.

Note

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

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!
}

Note

Importantly, these relationships can not only establish one-to-many connections but also extend to include many-to-many associations. To delve deeper into entity relationships, you can refer to this section. If you prefer a more example-based approach, our dedicated Hero Course Module can provide further insights.

SubQuery simplifies and ensures type-safety when working with GraphQL entities, smart contracts, events, transactions, and logs. The SubQuery CLI will generate types based on your project's GraphQL schema and any contract ABIs included in the data sources.

yarn
yarn codegen

This action will generate a new directory (or update the existing one) named src/types. Inside this directory, you will find automatically generated entity classes corresponding to each type defined in your schema.graphql. These classes facilitate type-safe operations for loading, reading, and writing entity fields. You can learn more about this process in the GraphQL Schema section.

It will also generate a class for every contract event, offering convenient access to event parameters, as well as information about the block and transaction from which the event originated. You can find detailed information on how this is achieved in the EVM Codegen from ABIs section. All of these types are stored in the src/types/abi-interfaces and src/types/contracts directories.

You can conveniently import all these types:

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

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.

Add a Mapping Function

Mapping functions define how blockchain 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).

Note

For more information on mapping functions, please refer to our Mappings documentation.

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

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.

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.

Run Your Project Locally with Docker

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

Note

It may take a few minutes to download the required images and start the various nodes and Postgres databases.

Query your Project

Next, let's query our project. Follow these three simple steps to query your SubQuery project:

  1. Open your browser and head to http://localhost:3000.

  2. You will see a GraphQL playground in the browser and the schemas which are ready to query.

  3. 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 queries 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.