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Avalanche Quick Start

SubQuery Team約6分

Avalanche Quick Start

In this Quick start guide, we're going to start with a simple Avalanche starter project and then finish by indexing some actual real data. This is an excellent basis to start with when developing your own SubQuery Project.

If your are looking for guides for Substrate/Polkadot, you can read the Substrate/Polkadot specific quick start guide.

このガイドの最後には、SubQuery ノード上で動作する SubQuery プロジェクトを作成し、GraphQL エンドポイントからデータを照会できるようになります。

まだの方は、SubQuery で使われている用語に慣れることをお勧めします。

The goal of this quick start guide is to index all Pangolin token Approve logs, it should only take 10-15 minutes

準備

ローカル開発環境

SubQuery CLI をインストールする

Install SubQuery CLI globally on your terminal by using NPM:

# NPM
npm install -g @subql/cli

Please note that we DO NOT encourage the use of yarn global for installing @subql/cli due to its poor dependency management which may lead to an errors down the line.

You can then run help to see available commands and usage provide by CLI

subql help

Initialise the SubQuery Starter Project

Inside the directory in which you want to create a SubQuery project, simply run the following command to get started.

subql init

You'll be asked certain questions as the SubQuery project is initalised:

  • Project Name: A name for your SubQuery project
  • Network Family: The layer-1 blockchain network family that this SubQuery project will be developed to index, use the arrow keys on your keyboard to select from the options, for this guide we will use "Avalanche"
  • Network: The specific network that this SubQuery project will be developed to index, use the arrow keys on your keyboard to select from the options, for this guide we will use "Avalanche"
  • Template: Select a SubQuery project template that will provide a starting point to begin development, we suggest selecting the "Starter project"
  • Git repository (Optional): Provide a Git URL to a repo that this SubQuery project will be hosted in (when hosted in SubQuery Explorer)
  • RPC endpoint (Required): Provide a HTTPS URL to a running RPC endpoint that will be used by default for this project. This RPC node must be an archive node (have the full chain state). For this guide we will use the default value "avalanche.api.onfinality.io"
  • Authors (Required): Enter the owner of this SubQuery project here (e.g. your name!)
  • Description (Optional): You can provide a short paragraph about your project that describe what data it contains and what users can do with it
  • Version (Required): Enter a custom version number or use the default (1.0.0)
  • License (Required): Provide the software license for this project or accept the default (Apache-2.0)

After the initialisation process is complete, you should see a folder with your project name has been created inside the directory. The contents of this directoy should be identical to what's listed in the Directory Structure.

Last, under the project directory, run following command to install the new project's dependencies.

::: code-tabs @tab:active yarn shell cd PROJECT_NAME yarn install @tab npm shell cd PROJECT_NAME npm install :::

Making Changes to your Project

In the starter package that you just initialised, we have provided a standard configuration for your new project. You will mainly be working on the following files:

  1. The GraphQL Schema in schema.graphql
  2. The Project Manifest in project.yaml
  3. Mapping functions（ src/mappings/ ディレクトリ）

The goal of this quick start guide is to adapt the standard starter project to index all Pangolin Approve transaction logs.

Updating your GraphQL Schema File

The schema.graphql file defines the various GraphQL schemas. Due to the way that the GraphQL query language works, the schema file essentially dictates the shape of your data from SubQuery. Its a great place to start becuase it allows you to define your end goal up front.

We're going to update the schema.graphql file to remove all existing entities and read as follows

type PangolinApproval @entity {
  id: ID!
  transactionHash: String!
  blockNumber: String!
  blockHash: String!
  addressFrom: String
  addressTo: String
  amount: String
}

Important: When you make any changes to the schema file, please ensure that you regenerate your types directory. Do this now.

::: code-tabs @tab:active yarn shell yarn codegen @tab npm shell npm run-script codegen :::

You'll find the generated models in the /src/types/models directory. For more information about the schema.graphql file, check out our documentation under Build/GraphQL Schema

Updating the Project Manifest File

The Projet Manifest (project.yaml) file can be seen as an entry point of your project and it defines most of the details on how SubQuery will index and transform the chain data.

We won't do many changes to the manifest file as it already has been setup correctly, but we need to change our handlers. Remember we are planning to index all Pangolin approval logs, as a result, we need to update the datasources section to read the following.

dataSources:
  - kind: avalanche/Runtime
    startBlock: 57360 # Block when the Pangolin contract was created
    options:
      # Must be a key of assets
      abi: erc20
      ## Pangolin token https://snowtrace.io/token/0x60781c2586d68229fde47564546784ab3faca982
      address: "0x60781C2586D68229fde47564546784ab3fACA982"
    assets:
      erc20:
        file: "./node_modules/@pangolindex/exchange-contracts/artifacts/contracts/pangolin-core/interfaces/IPangolinERC20.sol/IPangolinERC20.json"
    mapping:
      file: "./dist/index.js"
      handlers:
        - handler: handleLog
          kind: avalanche/LogHandler
          filter:
            ## Follows standard log filters https://docs.ethers.io/v5/concepts/events/
            function: Approve(address spender, uint256 rawAmount)
            # address: "0x60781C2586D68229fde47564546784ab3fACA982"

This means we'll run a handleLog mapping function each and every time there is a approve log on any transaction from the Pangolin contractopen in new window.

For more information about the Project Manifest (project.yaml) file, check out our documentation under Build/Manifest File

Add a Mapping Function

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

Navigate to the default mapping function in the src/mappings directory. You'll see three exported functions, handleBlock, handleLog, and handleTransaction. You can delete both the handleBlock and handleTransaction functions, we are only dealing with the handleLog function.

The handleLog function recieved event data whenever event matches the filters that we specify previously in our project.yaml. We are going to update it to process all approval transaction logs and save them to the GraphQL entities that we created earlier.

You can update the handleLog function to the following (note the additional imports):

import { PangolinApproval } from "../types";
import { AvalancheLog } from "@subql/types-avalanche";

export async function handleLog(event: AvalancheLog): Promise<void> {
  const pangolinApprovalRecord = new PangolinApproval(
    `${event.blockHash}-${event.logIndex}`
  );

  pangolinApprovalRecord.transactionHash = event.transactionHash;
  pangolinApprovalRecord.blockHash = event.blockHash;
  pangolinApprovalRecord.blockNumber = event.blockNumber;
  # topics store data as an array
  pangolinApprovalRecord.addressFrom = event.topics[0];
  pangolinApprovalRecord.addressTo = event.topics[1];
  pangolinApprovalRecord.amount = event.topics[2];

  await pangolinApprovalRecord.save();
}

What this is doing is receiving an Avalanche Log which includes the transation log data on the payload. We extract this data and then instantiate a new PangolinApproval entity that we defined earlier in the schema.graphql file. We add additional information and then use the .save() function to save the new entity (SubQuery will automatically save this to the database).

For more information about mapping functions, check out our documentation under Build/Mappings

Build the Project

In order run your new SubQuery Project we first need to build our work. Run the build command from the project's root directory.

::: code-tabs @tab:active yarn shell yarn build @tab npm shell npm run-script build :::

Important: Whenever you make changes to your mapping functions, you'll need to rebuild your project

Running and Querying your Project

Run your Project with Docker

Whenever you create a new SubQuery Project, you should always run it locally on your computer to test it first. The easiest way to do this is by using Docker.

All configuration that controls how a SubQuery node is run is defined in this docker-compose.yml file. For a new project that has been just initalised you won't need to change anything here, but you can read more about the file and the settings in our Run a Project section

Under the project directory run following command:

::: code-tabs @tab:active yarn shell yarn start:docker @tab npm shell npm run-script start:docker :::

It may take some time to download the required packages (@subql/nodeopen in new window, @subql/queryopen in new window, and Postgres) for the first time but soon you'll see a running SubQuery node. Be patient here.

Query your Project

Open your browser and head to http://localhost:3000open in new window.

You should see a GraphQL playground is showing in the explorer and the schemas that are ready to query. プレイグラウンドの右上には、ドキュメントの描画を開く Docs ボタンがあります。 このドキュメントは自動的に生成され、クエリできるエンティティやメソッドを見つけるのに役立ちます。

For a new SubQuery starter project, you can try the following query to get a taste of how it works or learn more about the GraphQL Query language.

query {
  pangolinApprovals(first: 5) {
    nodes {
      id
      blockNumber
      blockHash
      transactionHash
      addressFrom
      addressTo
      amount
    }
  }
}

Publish your SubQuery Project

SubQuery provides a free managed service when you can deploy your new project to. You can deploy it to SubQuery Managed Serviceopen in new window and query it using our Exploreropen in new window.

Read the guide to publish your new project to SubQuery Projects, Note that you must deploy via IPFS.

Next Steps

Congratulations, you now have a locally running SubQuery project that accepts GraphQL API requests for transfers data from bLuna.

Now that you've had an insight into how to build a basic SubQuery project, the question is where to from here? If you are feeling confident, you can jump into learning more about the three key files. The manifest file, the GraphQL schema, and the mappings file under the Build section of these docs.

Otherwise, continue to our Academy section where have more in depth workshops, tutorials, and example projects. There we'll look at more advanced modifications, and we'll take a deeper dive at running SubQuery projects by running readily available and open source projects.

Finally, if you're looking for more ways to run and publish your project, our Run & Publish section provides detailed informatation about all the ways to run your SubQuery project and other advanced GraphQL aggregation and subscription features.