Sei Quick Start
Sei Quick Start
The goal of this quick start guide is to index all ETH-USD exchange rates provided to Levana’s Sei DEX protocol by the Pyth price oracle.
Info
This network is based on the Cosmos SDK, which means you can index chain data via the standard Cosmos RPC interface.
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 steps for Cosmos users.
Tips
The final code of this project can be found here.
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 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 that the manifest file looks for on the blockchain to start indexing.
{
dataSources: [
{
kind: CosmosDatasourceKind.Runtime,
startBlock: 24596905,
mapping: {
file: "./dist/index.js",
handlers: [
{
handler: "handleFundingRateChangeEvent",
kind: CosmosHandlerKind.Event,
filter: {
// https://sei.explorers.guru/transaction/9A5D1FB99CDFB03282459355E4C7221D93D9971160AE79E201FA2B2895952878
type: "wasm-funding-rate-change",
messageFilter: {
type: "/cosmwasm.wasm.v1.MsgExecuteContract",
},
},
},
{
handler: "handleSpotPriceEvent",
kind: CosmosHandlerKind.Event,
filter: {
type: "wasm-spot-price",
messageFilter: {
type: "/cosmwasm.wasm.v1.MsgExecuteContract",
},
},
},
],
},
},
],
}
The above code defines that you will be running two handlers. A handleFundingRateChangeEvent handler which will be triggered when a wasm-funding-rate-change type is encountered on a MsgExecuteContract type and a handleSpotPriceEvent handler which will be triggered when a wasm-spot-price type is encountered on a MsgExecuteContract type.
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.
Update the schema.graphql file as follows. In this project, since we are indexing all ETH-USD exchange rates provided to Levana’s Sei DEX protocol by the Pyth price oracle, we have a ExchangeRate entity that includes a number of properties, including exchange rate data such as the notional and USD price, the long and short rate and also contract details.
Daily aggregated price data such as open, close, low and high prices are also captured in a seperate DailyAggregation entity.
type ExchangeRate @entity {
id: ID! # Blockheight-contractaddress
blockHeight: BigInt!
timestamp: Date!
txHash: String!
contractAddress: String!
priceNotional: Float
priceUSD: Float
longRate: Float
shortRate: Float
contractName: String
contractVersion: String
}
type DailyAggregation @entity {
id: ID! # 2023-03-05
openPriceUSD: Float!
closePriceUSD: Float!
highPriceUSD: Float!
lowPriceUSD: Float!
}
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, actions, and transactions.
yarn codegen
npm run-script 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.
If you've expressed a preference to employ the Cosmos message based on the provided proto files, this command will also generate types for your listed protobufs and save them into src/types directory, providing you with more typesafety. For example, you can find Osmosis' protobuf definitions in the official documentation. Read about how this is done in Cosmos Codegen from CosmWasm Protobufs and Cosmos Manifest File Configuration.
Now that you have made essential changes to the GraphQL Schema file, let’s go ahead with the next configuration.
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 and update your mapping files to match the following (note the additional imports):
import { CosmosEvent } from "@subql/types-cosmos";
import { ExchangeRate, DailyAggregation } from "../types";
async function updateDailyAggregation(date: Date,priceUSD: number): <void> {
const id = date.toISOString().slice(0, 10);
let aggregation = await DailyAggregation.get(id);
if (!aggregation) {
aggregation = DailyAggregation.create({
id,
openPriceUSD: priceUSD,
highPriceUSD: priceUSD,
lowPriceUSD: priceUSD,
closePriceUSD: priceUSD,
});
}
if (priceUSD > aggregation.highPriceUSD) aggregation.highPriceUSD = priceUSD;
if (priceUSD < aggregation.lowPriceUSD) aggregation.lowPriceUSD = priceUSD;
aggregation.closePriceUSD = priceUSD;
await aggregation.save();
}
export async function handleFundingRateChangeEvent(event: CosmosEvent): <void> {
// We create a new entity using the transaction hash and message index as a unique ID
logger.info(`New funding rate change at block ${event.block.block.header.height}`);
const contractAddress: string | undefined = event.event.attributes.find((a) => a.key === "_contract_address")?.value;
if (contractAddress) {
const id = `${event.block.header.height}-${contractAddress}`;
let exchangeRate = await ExchangeRate.get(id);
if (!exchangeRate) {
exchangeRate = ExchangeRate.create({
id,
blockHeight: BigInt(event.block.header.height),
timestamp: new Date(event.block.header.time.toISOString()),
txHash: event.tx.hash,
contractAddress,
});
}
// Cosmos events code attributes as an array of key value pairs, we're looking for to extract a few things
// Example https://sei.explorers.guru/transaction/9A5D1FB99CDFB03282459355E4C7221D93D9971160AE79E201FA2B2895952878
for (const attr of event.event.attributes) {
if (attr.key === "time") {
// encoded as seconds
exchangeRate.timestamp = new Date(parseFloat(attr.value) * 1000);
} else if (attr.key === "long-rate") {
exchangeRate.longRate = parseFloat(attr.value);
} else if (attr.key === "short-rate") {
exchangeRate.shortRate = parseFloat(attr.value);
} else if (attr.key === "contract_version") {
exchangeRate.contractVersion = attr.value;
} else if (attr.key === "contract_name") {
exchangeRate.contractName = attr.value;
}
}
await exchangeRate.save();
if (exchangeRate.priceUSD) {
await updateDailyAggregation(
exchangeRate.timestamp,
exchangeRate.priceUSD
);
}
}
}
export async function handleSpotPriceEvent(event: CosmosEvent): Promise<void> {
// We create a new entity using the transaction hash and message index as a unique ID
logger.info(`New spot price change at block ${event.block.block.header.height}`);
const contractAddress: string | undefined = event.event.attributes.find((a) => a.key === "_contract_address")?.value;
if (contractAddress) {
const id = `${event.block.header.height}-${contractAddress}`;
let exchangeRate = await ExchangeRate.get(id);
if (!exchangeRate) {
exchangeRate = ExchangeRate.create({
id,
blockHeight: BigInt(event.block.header.height),
timestamp: new Date(event.block.header.time.toISOString()),
txHash: event.tx.hash,
contractAddress,
});
}
// Cosmos events code attributes as an array of key value pairs, we're looking for to extract a few things
// Example https://sei.explorers.guru/transaction/9A5D1FB99CDFB03282459355E4C7221D93D9971160AE79E201FA2B2895952878
for (const attr of event.event.attributes) {
if (attr.key === "time") {
// encoded as seconds
exchangeRate.timestamp = new Date(parseFloat(attr.value) * 1000);
} else if (attr.key === "price-notional") {
exchangeRate.priceNotional = parseFloat(attr.value);
} else if (attr.key === "price-base") {
exchangeRate.priceUSD = parseFloat(attr.value);
} else if (attr.key === "contract_version") {
exchangeRate.contractVersion = attr.value;
} else if (attr.key === "contract_name") {
exchangeRate.contractName = attr.value;
}
}
await exchangeRate.save();
if (exchangeRate.priceUSD) {
await updateDailyAggregation(
exchangeRate.timestamp,
exchangeRate.priceUSD
);
}
}
}
Here we have three functions. Our handleFundingRateChangeEvent and handleSpotPriceEvent handler functions which were defined in the manifest file along with an extra function called updateDailyAggregation.
handleFundingRateChangeEvent receives an event of type CosmosEvent, logs a message to the console for debugging purposes and then attempts to obtain the contract address from the event.event.attributes (Cosmos events code attributes as an array of key value pairs). This contract address, along with the block height is used as a unique id.
An exchange rate object is then created, provided that it hasn't been created already, and then we look for certain event attributes to index by searching through the attribute keys.
The handleSpotPriceEvent handler function works in the same way.
The updateDailyAggregation function is called by the previous two functions to determine the highest and lowest price of the day along with the opening and closing price of the day. It is called when each new exhanged rate object is created or update.
Check out our Mappings documentation and get information on the mapping functions in detail.
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.
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 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.
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 queries to understand how it works for your new SubQuery starter project. Don’t forget to learn more about the GraphQL Query language.
query {
exchangeRates(first: 5, orderBy: BLOCK_HEIGHT_DESC) {
totalCount
nodes {
id
blockHeight
timestamp
txHash
contractName
contractAddress
contractVersion
longRate
shortRate
priceNotional
priceUSD
}
}
dailyAggregations(first: 5, orderBy: ID_DESC) {
nodes {
id
openPriceUSD
lowPriceUSD
highPriceUSD
closePriceUSD
}
}
}
You will see the result similar to below:
{
"data": {
"exchangeRates": {
"totalCount": 23,
"nodes": [
{
"id": "15613515-sei1xg9nz66lw2u6esc036tcjug35s06wljenjfn9qntzv6pcee3782q8hyx28",
"blockHeight": "15613515",
"timestamp": "2023-06-16T06:59:29.321",
"txHash": "3BCCD70CCA957630D33E059EA9F74882A53B74603FCFAED0EFB5A4F8DB761153",
"contractName": "levana.finance:market",
"contractAddress": "sei1xg9nz66lw2u6esc036tcjug35s06wljenjfn9qntzv6pcee3782q8hyx28",
"contractVersion": "0.1.0-beta.15",
"longRate": -0.11993339988124402,
"shortRate": 0.11803523598915301,
"priceNotional": 0.000598617598372426,
"priceUSD": 1670.515539000002
},
{
"id": "15613506-sei1xg9nz66lw2u6esc036tcjug35s06wljenjfn9qntzv6pcee3782q8hyx28",
"blockHeight": "15613506",
"timestamp": "2023-06-16T06:59:25.818",
"txHash": "EB1839610D908D1D3DF71E89EB0CE7C10582FC85EE4A8070298E859AADC03B51",
"contractName": "levana.finance:market",
"contractAddress": "sei1xg9nz66lw2u6esc036tcjug35s06wljenjfn9qntzv6pcee3782q8hyx28",
"contractVersion": "0.1.0-beta.15",
"longRate": -0.11993339988124402,
"shortRate": 0.11803523598915301,
"priceNotional": 0.000598619969003707,
"priceUSD": 1670.5089234900004
}
]
},
"dailyAggregations": {
"nodes": [
{
"id": "2023-06-16",
"openPriceUSD": 1670.76,
"lowPriceUSD": 1670.508887540001,
"highPriceUSD": 1670.8,
"closePriceUSD": 1670.515539000002
}
]
}
}
}
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.