Flare Quick Start
Flare Quick Start
Goals
The goal of this quick start guide is to index all rewards from the Flare FTSO Reward Manager from Flare's Songbird network.
Important
Before we begin, make sure that you have initialised your project using the provided steps in the Start Here section. Please initialise a Flare Songbird Network, not Flare Network
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 here.
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 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 all rewards and also addresses that those rewards go to/are claimed from:
type Reward @entity {
id: ID! # Transaction has
recipient: Address!
dataProvider: String! @index
whoClaimed: Address!
rewardEpoch: BigInt! @index
amount: BigInt!
}
type Address @entity {
id: ID! # accountIDs
receivedRewards: [Reward] @derivedFrom(field: "recipient")
claimedRewards: [Reward] @derivedFrom(field: "whoClaimed")
}
Since we have a many-to-many relationship, we add the @derivedFrom
annotation to ensure that we are mapping to the right foreign key.
Important
When you make any changes to the schema file, please ensure that you regenerate your types directory.
yarn codegen
npm run-script codegen
You will find the generated models in the /src/types/models
directory.
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 move forward to the next file.
2. Update Your Project Manifest File
The Project Manifest (project.yaml
) file works as an entry point to your Flare project. It defines most of the details on how SubQuery will index and transform the chain data. For Flare, 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 all RewardClaimed logs from the FTSORewardManager contract, first you will need to import the contract abi defintion from here. You can copy the entire JSON and save as a file ftsoRewardManager.abi.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 RewardClaimed logs, you need to update the datasources
section as follows:
dataSources:
- kind: flare/Runtime
startBlock: 36036 # Block that this contract was deployed
options:
# Must be a key of assets
abi: ftsoRewardManager
address: "0xc5738334b972745067ffa666040fdeadc66cb925" # https://songbird-explorer.flare.network/address/0xc5738334b972745067fFa666040fdeADc66Cb925
assets:
ftsoRewardManager:
file: "ftsoRewardManager.abi.json" # Import the correct contract file
mapping:
file: "./dist/index.js"
handlers:
- handler: handleLog
kind: flare/LogHandler
filter:
topics:
## Follows standard log filters https://docs.ethers.io/v5/concepts/events/
- RewardClaimed(address indexed dataProvider, address indexed whoClaimed, address indexed sentTo, uint256 rewardEpoch, uint256 amount)
The above code indicates that you will be running a handleLog
mapping function whenever there is an RewardClaimed
log on any transaction from the FTSO Reward Manager contract.
Check out our Manifest File documentation to get more information about the Project Manifest (project.yaml
) file.
Next, 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
. Delete both the handleBlock
and handleTransaction
functions as you will only deal with the handleLog
function.
The handleLog
function receives event data whenever an event matches the filters, which you specified previously in the project.yaml
. Let’s make changes to it, process all RewardClaimed
transaction logs, and save them to the GraphQL entities created earlier.
Update the handleLog
function as follows (note the additional imports):
import { FlareLog } from "@subql/types-flare";
import { BigNumber } from "@ethersproject/bignumber";
import { Address, Reward } from "../types";
type RewardClaimedLogArgs = [string, string, string, BigNumber, BigNumber] & {
dataProvider: string;
whoClaimed: string;
sentTo: string;
rewardEpoch: BigNumber;
amount: BigNumber;
};
export async function handleLog(
event: FlareLog<RewardClaimedLogArgs>
): Promise<void> {
// See example log in this transaction https://songbird-explorer.flare.network/tx/0xd832d0283f56acbda902066dd47147f510a68fd923296a2162cffcf10c15d8f8/logs
// logger.info("flare Event");
// Ensure that our account entities exist
const whoClaimed = await Address.get(event.args.whoClaimed.toLowerCase());
if (!whoClaimed) {
// Does not exist, create new
await Address.create({
id: event.args.whoClaimed.toLowerCase(),
}).save();
}
const whoRecieved = await Address.get(event.args.sentTo.toLowerCase());
if (!whoRecieved) {
// Does not exist, create new
await Address.create({
id: event.args.sentTo.toLowerCase(),
}).save();
}
// Create the new Reward entity
const reward = Reward.create({
id: event.transactionHash,
recipientId: event.args.sentTo.toLowerCase(),
dataProvider: event.args.dataProvider,
whoClaimedId: event.args.whoClaimed.toLowerCase(),
rewardEpoch: event.args.rewardEpoch.toBigInt(),
amount: event.args.amount.toBigInt(),
});
await reward.save();
}
Let’s understand how the above code works.
The function here receives an FlareLog
which includes transaction log data in the payload. We extract this data and then first ensure that our account entities (foreign keys) exist. We then instantiate a new Reward
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 (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 build
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 start:docker
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 {
rewards(first: 5, orderBy: AMOUNT_DESC) {
nodes {
id
amount
recipientId
dataProvider
whoClaimedId
amount
}
}
addresses(first: 5, orderBy: RECEIVED_REWARDS_SUM_AMOUNT_DESC) {
nodes {
id
}
}
}
You will see the result similar to below:
{
"data": {
"rewards": {
"nodes": [
{
"id": "0xd832d0283f56acbda902066dd47147f510a68fd923296a2162cffcf10c15d8f8",
"amount": "62306014311508310008",
"recipientId": "0xc2e6628b5b0277e97c68a47328f8effde9629184",
"dataProvider": "0x69141E890F3a79cd2CFf552c0B71508bE23712dC",
"whoClaimedId": "0xc2e6628b5b0277e97c68a47328f8effde9629184"
},
{
"id": "0xd6e84fc6b13f5832e04c8a851a2d3e634e82b029f253000d980ec68dc59e697f",
"amount": "248122819100600283",
"recipientId": "0x665574495eb0a4a03291f2fb3f150914dc4009f3",
"dataProvider": "0x939789ed3D07A80da886A3E3017d665cBb5591dC",
"whoClaimedId": "0x665574495eb0a4a03291f2fb3f150914dc4009f3"
}
]
},
"addresses": {
"nodes": [
{
"id": "0xc2e6628b5b0277e97c68a47328f8effde9629184"
},
{
"id": "0x665574495eb0a4a03291f2fb3f150914dc4009f3"
}
]
}
}
}
Note
The final code of this project can be found here.
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.