Juno Quick Start

SubQuery TeamAbout 5 min

Juno Quick Start

Goals

The goal of this quick start guide is to adapt the standard starter project in the Juno Network and then begin indexing all votes on the Terra Developer Fundopen in new window (which also contributed to SubQuery) from Cosmos.

Important

Before we begin, make sure that you have initialised your project using the provided steps in the Start Here section. You must complete the suggested 4 stepsopen in new window for Cosmos users.

Note that we are using Juno as the example here, but SubQuery supports all the following Cosmos networks and you can quickly initialise a new project in any of them using the subql init command:

Note

SubQuery can support more Cosmos zones than listed above. It requires importing protobufs definitions for specific chain types. See Custom Cosmos Chains for more information.

Now, let's move ahead in the process 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 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 start. It allows you to define your end goal right at the start.

Update the schema.graphql file as follows. The aim is to index all votes on the Terra Developer Fundopen in new window.

type Vote @entity {
  id: ID! # id field is always required and must look like this
  blockHeight: BigInt!
  voter: String! # The address that voted
  proposalID: BigInt! # The proposal ID
  vote: Boolean! # If they voted to support or reject the proposal
}

Important

When you make any changes to the schema file, do not forget to regenerate your types directory.

You will find the generated models in the /src/types/models directory.

Check out our GraphQL Schema documentation to get more information on schema.graphql file.

Now that you have made essential changes to the GraphQL Schema file, let’s go ahead with the next configuration.

2. Update Your Manifest File

The Project Manifest (project.yaml) 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 Cosmos chains, there are four 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, run a mapping function
MessageHandlers: On each and every message that matches optional filter criteria, run a mapping function
EventHanders: On each and every event 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 change the datasource handlers. This section lists the triggers to look for on the blockchain to start indexing.

dataSources:
  - kind: cosmos/Runtime
    startBlock: 3246370 # The block when the first proposal in this fund was created
    mapping:
      file: "./dist/index.js"
      handlers:
        - handler: handleTerraDeveloperFund
          kind: cosmos/MessageHandler
          filter:
            type: "/cosmwasm.wasm.v1.MsgExecuteContract"
            # Filter to only messages with the vote function call
            contractCall: "vote" # The name of the contract function that was called
            values: # This is the specific smart contract that we are subscribing to
              contract: "juno1lgnstas4ruflg0eta394y8epq67s4rzhg5anssz3rc5zwvjmmvcql6qps2"

The above code defines that you will be running a handleTerraDeveloperFund mapping function whenever there is a message with a vote contract call from the Terra Developer Fundopen in new window smart contract.

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

Next, let’s dig further into Mapping Function’s configuration.

3. Add a Mapping Function

Mapping functions determine how chain data is transformed into the optimised GraphQL entities that you previously defined in the schema.graphql file.

Navigate to the default mapping function in the src/mappings directory. You will see four exported functions: handleBlock, handleEvent, handleMessage, handleTransaction. Delete handleBlock, handleEvent, and handleTransaction functions as you will only deal with the handleMessage function.

The handleMessage function receives event data whenever an event matches the filters that you specified previously in the project.yaml. Let’s update it to process all vote messages and save them to the GraphQL entity created earlier.

Update the handleMessage function as follows (note the additional imports):

import { Vote } from "../types";
import { CosmosMessage } from "@subql/types-cosmos";

export async function handleTerraDeveloperFund(
  message: CosmosMessage
): Promise<void> {
  // logger.info(JSON.stringify(message));
  // Example vote https://www.mintscan.io/juno/txs/EAA2CC113B3EC79AE5C280C04BE851B82414B108273F0D6464A379D7917600A4

  const voteRecord = new Vote(`${message.tx.hash}-${message.idx}`);
  voteRecord.blockHeight = BigInt(message.block.block.header.height);
  voteRecord.voter = message.msg.sender;
  voteRecord.proposalID = message.msg.msg.vote.proposal_id;
  voteRecord.vote = message.msg.msg.vote.vote === "yes";

  await voteRecord.save();
}

Let’s understand how the above code works.

Here, the function receives a CosmosMessage which includes message data on the payload. We extract this data and then instantiate a new Vote entity defined earlier in the schema.graphql file. After that, we add additional information and then use the .save() function to save the new entity (SubQuery will automatically save this to the database).

Check out our Mappings documentation and get information on the mapping functions in detail.

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:

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, never forget to run it locally on your computer and test it. And using Docker is the most hassle-free way to do this.

docker-compose.yml file defines all the configurations that control how a SubQuery node runs. For a new project, which you have just initialised, no major changes are needed.

However, visit the Running SubQuery Locally to get more information on the file and the settings.

Run the following command under the project directory:

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 {
  votes(first: 3, orderBy: BLOCK_HEIGHT_DESC) {
    nodes {
      id
      blockHeight
      voter
      vote
    }
  }
}

You will see the result similar to below:

{
  "data": {
    "votes": {
      "nodes": [
        {
          "id": "14B3EE22278C494DFE90EA440A4F049F2D39A31634F0062B0FF362DB2872A979-0",
          "blockHeight": "3246683",
          "voter": "juno1njyvry0t3j5dy4rr6ar5zfglg3cy2e8u745hl7",
          "vote": true
        },
        {
          "id": "23329451CAFF77D5A0416013045530011F4FAFEA94FEEF43784CDF0947B6CA90-0",
          "blockHeight": "3246670",
          "voter": "juno1ewq9l5ae69csh57j8sgjh8z37ypm3lt0jzamwy",
          "vote": true
        },
        {
          "id": "BEAB15E994A4E99BD0631DACF4716C5627E5D0C14E0848BF07A45609CEFB2F0D-0",
          "blockHeight": "3246665",
          "voter": "juno1az0ehz2e5emudyh8hx2qwtfely0lstzj08gg9j",
          "vote": true
        }
      ]
    }
  }
}

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 from bLuna.

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.

Juno Quick Start

# Juno Quick Start

# Goals

# 1. Update Your GraphQL Schema File

# 2. Update Your Manifest File

# 3. Add a Mapping Function

# 4. Build Your Project

# 5. Run Your Project Locally with Docker

# 6. Query your Project

# What’s Next?

Juno Quick Start

Goals

1. Update Your GraphQL Schema File

2. Update Your Manifest File

3. Add a Mapping Function

4. Build Your Project

5. Run Your Project Locally with Docker

6. Query your Project

What’s Next?