Creating a Subgraph

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This detailed guide provides instructions to successfully create a subgraph.

A subgraph extracts data from a blockchain, processes it, and stores it for efficient querying via GraphQL.

To build and deploy a subgraph, you will need the Graph CLI.

The Graph CLI is written in TypeScript, and you must have node and either npm or yarn installed to use it. Check for the most recent CLI version.

On your local machine, run one of the following commands:

npm install -g @graphprotocol/graph-cli@latest

yarn global add @graphprotocol/graph-cli

• The graph init command can be used to set up a new subgraph project, either from an existing contract or from an example subgraph.

• This graph init command can also create a subgraph in Subgraph Studio by passing in --product subgraph-studio.

• If you already have a smart contract deployed to your preferred network, you can bootstrap a new subgraph from that contract to get started.

The following command creates a subgraph that indexes all events of an existing contract:

graph init \
  --product subgraph-studio
  --from-contract <CONTRACT_ADDRESS> \
  [--network <ETHEREUM_NETWORK>] \
  [--abi <FILE>] \
  <SUBGRAPH_SLUG> [<DIRECTORY>]

• The command tries to retrieve the contract ABI from Etherscan.

  • The Graph CLI relies on a public RPC endpoint. While occasional failures are expected, retries typically resolve this issue. If failures persist, consider using a local ABI.

• If any of the optional arguments are missing, it guides you through an interactive form.

• The <SUBGRAPH_SLUG> is the ID of your subgraph in Subgraph Studio. It can be found on your subgraph details page.

The following command initializes a new project from an example subgraph:

graph init --studio <SUBGRAPH_SLUG> --from-example=example-subgraph

• The example subgraph is based on the Gravity contract by Dani Grant, which manages user avatars and emits NewGravatar or UpdateGravatar events whenever avatars are created or updated.

• The subgraph handles these events by writing Gravatar entities to the Graph Node store and ensuring these are updated according to the events.

Since v0.31.0, the Graph CLI supports adding new dataSources to an existing subgraph through the graph add command:

graph add <address> [<subgraph-manifest default: "./subgraph.yaml">]

Options:

      --abi <path>              Path to the contract ABI (default: download from Etherscan)
      --contract-name           Name of the contract (default: Contract)
      --merge-entities          Whether to merge entities with the same name (default: false)
      --network-file <path>     Networks config file path (default: "./networks.json")

The graph add command will fetch the ABI from Etherscan (unless an ABI path is specified with the --abi option) and creates a new dataSource, similar to how the graph init command creates a dataSource --from-contract, updating the schema and mappings accordingly. This allows you to index implementation contracts from their proxy contracts.

• The --merge-entities option identifies how the developer would like to handle entity and event name conflicts:

  • If true: the new dataSource should use existing eventHandlers & entities.

  • If false: a new entity & event handler should be created with ${dataSourceName}{EventName}.

• The contract address will be written to the networks.json for the relevant network.

The subgraph manifest, subgraph.yaml, defines the smart contracts & network your subgraph will index, the events from these contracts to pay attention to, and how to map event data to entities that Graph Node stores and allows to query.

The subgraph definition consists of the following files:

• subgraph.yaml: Contains the subgraph manifest

• schema.graphql: A GraphQL schema defining the data stored for your subgraph and how to query it via GraphQL

• mapping.ts: AssemblyScript Mappings code that translates event data into entities defined in your schema (e.g. mapping.ts in this guide)

A single subgraph can:

• Index data from multiple smart contracts (but not multiple networks).

• Index data from IPFS files using File Data Sources.

• Add an entry for each contract that requires indexing to the dataSources array.

The full specification for subgraph manifests can be found here.

For the example subgraph listed above, subgraph.yaml is:

specVersion: 0.0.4
description: Gravatar for Ethereum
repository: https://github.com/graphprotocol/graph-tooling
schema:
  file: ./schema.graphql
indexerHints:
  prune: auto
dataSources:
  - kind: ethereum/contract
    name: Gravity
    network: mainnet
    source:
      address: '0x2E645469f354BB4F5c8a05B3b30A929361cf77eC'
      abi: Gravity
      startBlock: 6175244
      endBlock: 7175245
    context:
      foo:
        type: Bool
        data: true
      bar:
        type: String
        data: 'bar'
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      entities:
        - Gravatar
      abis:
        - name: Gravity
          file: ./abis/Gravity.json
      eventHandlers:
        - event: NewGravatar(uint256,address,string,string)
          handler: handleNewGravatar
        - event: UpdatedGravatar(uint256,address,string,string)
          handler: handleUpdatedGravatar
      callHandlers:
        - function: createGravatar(string,string)
          handler: handleCreateGravatar
      blockHandlers:
        - handler: handleBlock
        - handler: handleBlockWithCall
          filter:
            kind: call
      file: ./src/mapping.ts

The important entries to update for the manifest are:

• specVersion: a semver version that identifies the supported manifest structure and functionality for the subgraph. The latest version is 1.2.0. See specVersion releases section to see more details on features & releases.

• description: a human-readable description of what the subgraph is. This description is displayed in Graph Explorer when the subgraph is deployed to Subgraph Studio.

• repository: the URL of the repository where the subgraph manifest can be found. This is also displayed in Graph Explorer.

• features: a list of all used feature names.

• indexerHints.prune: Defines the retention of historical block data for a subgraph. See prune in indexerHints section.

• dataSources.source: the address of the smart contract the subgraph sources, and the ABI of the smart contract to use. The address is optional; omitting it allows to index matching events from all contracts.

• dataSources.source.startBlock: the optional number of the block that the data source starts indexing from. In most cases, we suggest using the block in which the contract was created.

• dataSources.source.endBlock: The optional number of the block that the data source stops indexing at, including that block. Minimum spec version required: 0.0.9.

• dataSources.context: key-value pairs that can be used within subgraph mappings. Supports various data types like Bool, String, Int, Int8, BigDecimal, Bytes, List, and BigInt. Each variable needs to specify its type and data. These context variables are then accessible in the mapping files, offering more configurable options for subgraph development.

• dataSources.mapping.entities: the entities that the data source writes to the store. The schema for each entity is defined in the schema.graphql file.

• dataSources.mapping.abis: one or more named ABI files for the source contract as well as any other smart contracts that you interact with from within the mappings.

• dataSources.mapping.eventHandlers: lists the smart contract events this subgraph reacts to and the handlers in the mapping—./src/mapping.ts in the example—that transform these events into entities in the store.

• dataSources.mapping.callHandlers: lists the smart contract functions this subgraph reacts to and handlers in the mapping that transform the inputs and outputs to function calls into entities in the store.

• dataSources.mapping.blockHandlers: lists the blocks this subgraph reacts to and handlers in the mapping to run when a block is appended to the chain. Without a filter, the block handler will be run every block. An optional call-filter can be provided by adding a filter field with kind: call to the handler. This will only run the handler if the block contains at least one call to the data source contract.

A single subgraph can index data from multiple smart contracts. Add an entry for each contract from which data needs to be indexed to the dataSources array.

The triggers for a data source within a block are ordered using the following process:

1. Event and call triggers are first ordered by transaction index within the block.
2. Event and call triggers within the same transaction are ordered using a convention: event triggers first then call triggers, each type respecting the order they are defined in the manifest.
3. Block triggers are run after event and call triggers, in the order they are defined in the manifest.

These ordering rules are subject to change.

Topic filters, also known as indexed argument filters, are a powerful feature in subgraphs that allow users to precisely filter blockchain events based on the values of their indexed arguments.

• These filters help isolate specific events of interest from the vast stream of events on the blockchain, allowing subgraphs to operate more efficiently by focusing only on relevant data.

• This is useful for creating personal subgraphs that track specific addresses and their interactions with various smart contracts on the blockchain.

When a smart contract emits an event, any arguments that are marked as indexed can be used as filters in a subgraph's manifest. This allows the subgraph to listen selectively for events that match these indexed arguments.

• The event's first indexed argument corresponds to topic1, the second to topic2, and so on, up to topic3, since the Ethereum Virtual Machine (EVM) allows up to three indexed arguments per event.

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;

contract Token {
    // Event declaration with indexed parameters for addresses
    event Transfer(address indexed from, address indexed to, uint256 value);

    // Function to simulate transferring tokens
    function transfer(address to, uint256 value) public {
        // Emitting the Transfer event with from, to, and value
        emit Transfer(msg.sender, to, value);
    }
}

In this example:

• The Transfer event is used to log transactions of tokens between addresses.
• The from and to parameters are indexed, allowing event listeners to filter and monitor transfers involving specific addresses.
• The transfer function is a simple representation of a token transfer action, emitting the Transfer event whenever it is called.

Topic filters are defined directly within the event handler configuration in the subgraph manifest. Here is how they are configured:

eventHandlers:
  - event: SomeEvent(indexed uint256, indexed address, indexed uint256)
    handler: handleSomeEvent
    topic1: ['0xValue1', '0xValue2']
    topic2: ['0xAddress1', '0xAddress2']
    topic3: ['0xValue3']

In this setup:

• topic1 corresponds to the first indexed argument of the event, topic2 to the second, and topic3 to the third.
• Each topic can have one or more values, and an event is only processed if it matches one of the values in each specified topic.

• Within a Single Topic: The logic functions as an OR condition. The event will be processed if it matches any one of the listed values in a given topic.
• Between Different Topics: The logic functions as an AND condition. An event must satisfy all specified conditions across different topics to trigger the associated handler.

eventHandlers:
  - event: Transfer(indexed address,indexed address,uint256)
    handler: handleDirectedTransfer
    topic1: ['0xAddressA'] # Sender Address
    topic2: ['0xAddressB'] # Receiver Address

In this configuration:

• topic1 is configured to filter Transfer events where 0xAddressA is the sender.
• topic2 is configured to filter Transfer events where 0xAddressB is the receiver.
• The subgraph will only index transactions that occur directly from 0xAddressA to 0xAddressB.

eventHandlers:
  - event: Transfer(indexed address,indexed address,uint256)
    handler: handleTransferToOrFrom
    topic1: ['0xAddressA', '0xAddressB', '0xAddressC'] # Sender Address
    topic2: ['0xAddressB', '0xAddressC'] # Receiver Address

In this configuration:

• topic1 is configured to filter Transfer events where 0xAddressA, 0xAddressB, 0xAddressC is the sender.
• topic2 is configured to filter Transfer events where 0xAddressB and 0xAddressC is the receiver.
• The subgraph will index transactions that occur in either direction between multiple addresses allowing for comprehensive monitoring of interactions involving all addresses.

Declarative eth_calls are a valuable subgraph feature that allows eth_calls to be executed ahead of time, enabling graph-node to execute them in parallel.

This feature does the following:

• Significantly improves the performance of fetching data from the Ethereum blockchain by reducing the total time for multiple calls and optimizing the subgraph's overall efficiency.
• Allows faster data fetching, resulting in quicker query responses and a better user experience.
• Reduces wait times for applications that need to aggregate data from multiple Ethereum calls, making the data retrieval process more efficient.

• Declarative eth_calls: Ethereum calls that are defined to be executed in parallel rather than sequentially.
• Parallel Execution: Instead of waiting for one call to finish before starting the next, multiple calls can be initiated simultaneously.
• Time Efficiency: The total time taken for all the calls changes from the sum of the individual call times (sequential) to the time taken by the longest call (parallel).

Imagine you have a subgraph that needs to make three Ethereum calls to fetch data about a user's transactions, balance, and token holdings.

Traditionally, these calls might be made sequentially:

1. Call 1 (Transactions): Takes 3 seconds
2. Call 2 (Balance): Takes 2 seconds
3. Call 3 (Token Holdings): Takes 4 seconds

Total time taken = 3 + 2 + 4 = 9 seconds

With this feature, you can declare these calls to be executed in parallel:

1. Call 1 (Transactions): Takes 3 seconds
2. Call 2 (Balance): Takes 2 seconds
3. Call 3 (Token Holdings): Takes 4 seconds

Since these calls are executed in parallel, the total time taken is equal to the time taken by the longest call.

Total time taken = max (3, 2, 4) = 4 seconds

1. Declarative Definition: In the subgraph manifest, you declare the Ethereum calls in a way that indicates they can be executed in parallel.
2. Parallel Execution Engine: The Graph Node's execution engine recognizes these declarations and runs the calls simultaneously.
3. Result Aggregation: Once all calls are complete, the results are aggregated and used by the subgraph for further processing.

Declared eth_calls can access the event.address of the underlying event as well as all the event.params.

Subgraph.yaml using event.address:

eventHandlers:
event: Swap(indexed address,indexed address,int256,int256,uint160,uint128,int24)
handler: handleSwap
calls:
  global0X128: Pool[event.address].feeGrowthGlobal0X128()
  global1X128: Pool[event.address].feeGrowthGlobal1X128()

Details for the example above:

• global0X128 is the declared eth_call.
• The text (global0X128) is the label for this eth_call which is used when logging errors.
• The text (Pool[event.address].feeGrowthGlobal0X128()) is the actual eth_call that will be executed, which is in the form of Contract[address].function(arguments)
• The address and arguments can be replaced with variables that will be available when the handler is executed.

Subgraph.yaml using event.params

calls:
  - ERC20DecimalsToken0: ERC20[event.params.token0].decimals()

The ABI file(s) must match your contract(s). There are a few ways to obtain ABI files:

• If you are building your own project, you will likely have access to your most current ABIs.
• If you are building a subgraph for a public project, you can download that project to your computer and get the ABI by using npx hardhat compile or using solc to compile.
• You can also find the ABI on Etherscan, but this isn't always reliable, as the ABI that is uploaded there may be out of date. Make sure you have the right ABI, otherwise running your subgraph will fail.

The schema for your subgraph is in the file schema.graphql. GraphQL schemas are defined using the GraphQL interface definition language. If you've never written a GraphQL schema, it is recommended that you check out this primer on the GraphQL type system. Reference documentation for GraphQL schemas can be found in the GraphQL API section.

Before defining entities, it is important to take a step back and think about how your data is structured and linked.

• All queries will be made against the data model defined in the subgraph schema and the entities indexed by the subgraph. As a result, it is good to define the subgraph schema in a way that matches the needs of your dapp.
• It may be useful to imagine entities as "objects containing data", rather than as events or functions.
• You define entity types in schema.graphql, and Graph Node will generate top-level fields for querying single instances and collections of that entity type.
• Each type that should be an entity is required to be annotated with an @entity directive.
• By default, entities are mutable, meaning that mappings can load existing entities, modify them and store a new version of that entity.
  • Mutability comes at a price, so for entity types that will never be modified, such as those containing data extracted verbatim from the chain, it is recommended to mark them as immutable with @entity(immutable: true).
  • If changes happen in the same block in which the entity was created, then mappings can make changes to immutable entities. Immutable entities are much faster to write and to query so they should be used whenever possible.

The following Gravatar entity is structured around a Gravatar object and is a good example of how an entity could be defined.

type Gravatar @entity(immutable: true) {
  id: Bytes!
  owner: Bytes
  displayName: String
  imageUrl: String
  accepted: Boolean
}

The following example GravatarAccepted and GravatarDeclined entities are based around events. It is not recommended to map events or function calls to entities 1:1.

type GravatarAccepted @entity {
  id: Bytes!
  owner: Bytes
  displayName: String
  imageUrl: String
}

type GravatarDeclined @entity {
  id: Bytes!
  owner: Bytes
  displayName: String
  imageUrl: String
}

Entity fields can be defined as required or optional. Required fields are indicated by the ! in the schema. If a required field is not set in the mapping, you will receive this error when querying the field:

Null value resolved for non-null field 'name'

Each entity must have an id field, which must be of type Bytes! or String!. It is generally recommended to use Bytes!, unless the id contains human-readable text, since entities with Bytes! id's will be faster to write and query as those with a String! id. The id field serves as the primary key, and needs to be unique among all entities of the same type. For historical reasons, the type ID! is also accepted and is a synonym for String!.

For some entity types the id is constructed from the id's of two other entities; that is possible using concat, e.g., let id = left.id.concat(right.id) to form the id from the id's of left and right. Similarly, to construct an id from the id of an existing entity and a counter count, let id = left.id.concatI32(count) can be used. The concatenation is guaranteed to produce unique id's as long as the length of left is the same for all such entities, for example, because left.id is an Address.

The following scalars are supported in the GraphQL API:

You can also create enums within a schema. Enums have the following syntax:

enum TokenStatus {
  OriginalOwner
  SecondOwner
  ThirdOwner
}

Once the enum is defined in the schema, you can use the string representation of the enum value to set an enum field on an entity. For example, you can set the tokenStatus to SecondOwner by first defining your entity and subsequently setting the field with entity.tokenStatus = "SecondOwner". The example below demonstrates what the Token entity would look like with an enum field:

More detail on writing enums can be found in the GraphQL documentation.

An entity may have a relationship to one or more other entities in your schema. These relationships may be traversed in your queries. Relationships in The Graph are unidirectional. It is possible to simulate bidirectional relationships by defining a unidirectional relationship on either "end" of the relationship.

Relationships are defined on entities just like any other field except that the type specified is that of another entity.

Define a Transaction entity type with an optional one-to-one relationship with a TransactionReceipt entity type:

type Transaction @entity(immutable: true) {
  id: Bytes!
  transactionReceipt: TransactionReceipt
}

type TransactionReceipt @entity(immutable: true) {
  id: Bytes!
  transaction: Transaction
}

Define a TokenBalance entity type with a required one-to-many relationship with a Token entity type:

type Token @entity(immutable: true) {
  id: Bytes!
}

type TokenBalance @entity {
  id: Bytes!
  amount: Int!
  token: Token!
}

Reverse lookups can be defined on an entity through the @derivedFrom field. This creates a virtual field on the entity that may be queried but cannot be set manually through the mappings API. Rather, it is derived from the relationship defined on the other entity. For such relationships, it rarely makes sense to store both sides of the relationship, and both indexing and query performance will be better when only one side is stored and the other is derived.

For one-to-many relationships, the relationship should always be stored on the 'one' side, and the 'many' side should always be derived. Storing the relationship this way, rather than storing an array of entities on the 'many' side, will result in dramatically better performance for both indexing and querying the subgraph. In general, storing arrays of entities should be avoided as much as is practical.

We can make the balances for a token accessible from the token by deriving a tokenBalances field:

type Token @entity(immutable: true) {
  id: Bytes!
  tokenBalances: [TokenBalance!]! @derivedFrom(field: "token")
}

type TokenBalance @entity {
  id: Bytes!
  amount: Int!
  token: Token!
}

For many-to-many relationships, such as users that each may belong to any number of organizations, the most straightforward, but generally not the most performant, way to model the relationship is as an array in each of the two entities involved. If the relationship is symmetric, only one side of the relationship needs to be stored and the other side can be derived.

Define a reverse lookup from a User entity type to an Organization entity type. In the example below, this is achieved by looking up the members attribute from within the Organization entity. In queries, the organizations field on User will be resolved by finding all Organization entities that include the user's ID.

type Organization @entity {
  id: Bytes!
  name: String!
  members: [User!]!
}

type User @entity {
  id: Bytes!
  name: String!
  organizations: [Organization!]! @derivedFrom(field: "members")
}

A more performant way to store this relationship is through a mapping table that has one entry for each User / Organization pair with a schema like

type Organization @entity {
  id: Bytes!
  name: String!
  members: [UserOrganization!]! @derivedFrom(field: "organization")
}

type User @entity {
  id: Bytes!
  name: String!
  organizations: [UserOrganization!] @derivedFrom(field: "user")
}

type UserOrganization @entity {
  id: Bytes! # Set to `user.id.concat(organization.id)`
  user: User!
  organization: Organization!
}

This approach requires that queries descend into one additional level to retrieve, for example, the organizations for users:

query usersWithOrganizations {
  users {
    organizations {
      # this is a UserOrganization entity
      organization {
        name
      }
    }
  }
}

This more elaborate way of storing many-to-many relationships will result in less data stored for the subgraph, and therefore to a subgraph that is often dramatically faster to index and to query.

As per GraphQL spec, comments can be added above schema entity attributes using the hash symbol #. This is illustrated in the example below:

type MyFirstEntity @entity {
  # unique identifier and primary key of the entity
  id: Bytes!
  address: Bytes!
}

Fulltext search queries filter and rank entities based on a text search input. Fulltext queries are able to return matches for similar words by processing the query text input into stems before comparing them to the indexed text data.

A fulltext query definition includes the query name, the language dictionary used to process the text fields, the ranking algorithm used to order the results, and the fields included in the search. Each fulltext query may span multiple fields, but all included fields must be from a single entity type.

To add a fulltext query, include a _Schema_ type with a fulltext directive in the GraphQL schema.

type _Schema_
  @fulltext(
    name: "bandSearch"
    language: en
    algorithm: rank
    include: [{ entity: "Band", fields: [{ name: "name" }, { name: "description" }, { name: "bio" }] }]
  )

type Band @entity {
  id: Bytes!
  name: String!
  description: String!
  bio: String
  wallet: Address
  labels: [Label!]!
  discography: [Album!]!
  members: [Musician!]!
}

The example bandSearch field can be used in queries to filter Band entities based on the text documents in the name, description, and bio fields. Jump to GraphQL API - Queries for a description of the fulltext search API and more example usage.

query {
  bandSearch(text: "breaks & electro & detroit") {
    id
    name
    description
    wallet
  }
}

Choosing a different language will have a definitive, though sometimes subtle, effect on the fulltext search API. Fields covered by a fulltext query field are examined in the context of the chosen language, so the lexemes produced by analysis and search queries vary from language to language. For example: when using the supported Turkish dictionary "token" is stemmed to "toke" while, of course, the English dictionary will stem it to "token".

Supported language dictionaries:

Supported algorithms for ordering results:

The mappings take data from a particular source and transform it into entities that are defined within your schema. Mappings are written in a subset of TypeScript called AssemblyScript which can be compiled to WASM (WebAssembly). AssemblyScript is stricter than normal TypeScript, yet provides a familiar syntax.

For each event handler that is defined in subgraph.yaml under mapping.eventHandlers, create an exported function of the same name. Each handler must accept a single parameter called event with a type corresponding to the name of the event which is being handled.

In the example subgraph, src/mapping.ts contains handlers for the NewGravatar and UpdatedGravatar events:

import { NewGravatar, UpdatedGravatar } from '../generated/Gravity/Gravity'
import { Gravatar } from '../generated/schema'

export function handleNewGravatar(event: NewGravatar): void {
  let gravatar = new Gravatar(event.params.id)
  gravatar.owner = event.params.owner
  gravatar.displayName = event.params.displayName
  gravatar.imageUrl = event.params.imageUrl
  gravatar.save()
}

export function handleUpdatedGravatar(event: UpdatedGravatar): void {
  let id = event.params.id
  let gravatar = Gravatar.load(id)
  if (gravatar == null) {
    gravatar = new Gravatar(id)
  }
  gravatar.owner = event.params.owner
  gravatar.displayName = event.params.displayName
  gravatar.imageUrl = event.params.imageUrl
  gravatar.save()
}

The first handler takes a NewGravatar event and creates a new Gravatar entity with new Gravatar(event.params.id.toHex()), populating the entity fields using the corresponding event parameters. This entity instance is represented by the variable gravatar, with an id value of event.params.id.toHex().

The second handler tries to load the existing Gravatar from the Graph Node store. If it does not exist yet, it is created on-demand. The entity is then updated to match the new event parameters before it is saved back to the store using gravatar.save().

It is highly recommended to use Bytes as the type for id fields, and only use String for attributes that truly contain human-readable text, like the name of a token. Below are some recommended id values to consider when creating new entities.

• transfer.id = event.transaction.hash

• let id = event.transaction.hash.concatI32(event.logIndex.toI32())

• For entities that store aggregated data, for e.g, daily trade volumes, the id usually contains the day number. Here, using a Bytes as the id is beneficial. Determining the id would look like

let dayID = event.block.timestamp.toI32() / 86400
let id = Bytes.fromI32(dayID)

• Convert constant addresses to Bytes.

const id = Bytes.fromHexString('0xdead...beef')

There is a Graph Typescript Library which contains utilities for interacting with the Graph Node store and conveniences for handling smart contract data and entities. It can be imported into mapping.ts from @graphprotocol/graph-ts.

When creating and saving a new entity, if an entity with the same ID already exists, the properties of the new entity are always preferred during the merge process. This means that the existing entity will be updated with the values from the new entity.

If a null value is intentionally set for a field in the new entity with the same ID, the existing entity will be updated with the null value.

If no value is set for a field in the new entity with the same ID, the field will result in null as well.

In order to make it easy and type-safe to work with smart contracts, events and entities, the Graph CLI can generate AssemblyScript types from the subgraph's GraphQL schema and the contract ABIs included in the data sources.

This is done with

graph codegen [--output-dir <OUTPUT_DIR>] [<MANIFEST>]

but in most cases, subgraphs are already preconfigured via package.json to allow you to simply run one of the following to achieve the same:

# Yarn
yarn codegen

# NPM
npm run codegen

This will generate an AssemblyScript class for every smart contract in the ABI files mentioned in subgraph.yaml, allowing you to bind these contracts to specific addresses in the mappings and call read-only contract methods against the block being processed. It will also generate a class for every contract event to provide easy access to event parameters, as well as the block and transaction the event originated from. All of these types are written to <OUTPUT_DIR>/<DATA_SOURCE_NAME>/<ABI_NAME>.ts. In the example subgraph, this would be generated/Gravity/Gravity.ts, allowing mappings to import these types with.

import {
  // The contract class:
  Gravity,
  // The events classes:
  NewGravatar,
  UpdatedGravatar,
} from '../generated/Gravity/Gravity'

In addition to this, one class is generated for each entity type in the subgraph's GraphQL schema. These classes provide type-safe entity loading, read and write access to entity fields as well as a save() method to write entities to store. All entity classes are written to <OUTPUT_DIR>/schema.ts, allowing mappings to import them with

import { Gravatar } from '../generated/schema'

Code generation does not check your mapping code in src/mapping.ts. If you want to check that before trying to deploy your subgraph to Graph Explorer, you can run yarn build and fix any syntax errors that the TypeScript compiler might find.

A common pattern in EVM-compatible smart contracts is the use of registry or factory contracts, where one contract creates, manages, or references an arbitrary number of other contracts that each have their own state and events.

The addresses of these sub-contracts may or may not be known upfront and many of these contracts may be created and/or added over time. This is why, in such cases, defining a single data source or a fixed number of data sources is impossible and a more dynamic approach is needed: data source templates.

First, you define a regular data source for the main contract. The snippet below shows a simplified example data source for the Uniswap exchange factory contract. Note the NewExchange(address,address) event handler. This is emitted when a new exchange contract is created on-chain by the factory contract.

dataSources:
  - kind: ethereum/contract
    name: Factory
    network: mainnet
    source:
      address: '0xc0a47dFe034B400B47bDaD5FecDa2621de6c4d95'
      abi: Factory
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      file: ./src/mappings/factory.ts
      entities:
        - Directory
      abis:
        - name: Factory
          file: ./abis/factory.json
      eventHandlers:
        - event: NewExchange(address,address)
          handler: handleNewExchange

Then, you add data source templates to the manifest. These are identical to regular data sources, except that they lack a pre-defined contract address under source. Typically, you would define one template for each type of sub-contract managed or referenced by the parent contract.

dataSources:
  - kind: ethereum/contract
    name: Factory
    # ... other source fields for the main contract ...
templates:
  - name: Exchange
    kind: ethereum/contract
    network: mainnet
    source:
      abi: Exchange
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      file: ./src/mappings/exchange.ts
      entities:
        - Exchange
      abis:
        - name: Exchange
          file: ./abis/exchange.json
      eventHandlers:
        - event: TokenPurchase(address,uint256,uint256)
          handler: handleTokenPurchase
        - event: EthPurchase(address,uint256,uint256)
          handler: handleEthPurchase
        - event: AddLiquidity(address,uint256,uint256)
          handler: handleAddLiquidity
        - event: RemoveLiquidity(address,uint256,uint256)
          handler: handleRemoveLiquidity

In the final step, you update your main contract mapping to create a dynamic data source instance from one of the templates. In this example, you would change the main contract mapping to import the Exchange template and call the Exchange.create(address) method on it to start indexing the new exchange contract.

import { Exchange } from '../generated/templates'

export function handleNewExchange(event: NewExchange): void {
  // Start indexing the exchange; `event.params.exchange` is the
  // address of the new exchange contract
  Exchange.create(event.params.exchange)
}

Data source contexts allow passing extra configuration when instantiating a template. In our example, let's say exchanges are associated with a particular trading pair, which is included in the NewExchange event. That information can be passed into the instantiated data source, like so:

import { Exchange } from '../generated/templates'

export function handleNewExchange(event: NewExchange): void {
  let context = new DataSourceContext()
  context.setString('tradingPair', event.params.tradingPair)
  Exchange.createWithContext(event.params.exchange, context)
}

Inside a mapping of the Exchange template, the context can then be accessed:

import { dataSource } from '@graphprotocol/graph-ts'

let context = dataSource.context()
let tradingPair = context.getString('tradingPair')

There are setters and getters like setString and getString for all value types.

The startBlock is an optional setting that allows you to define from which block in the chain the data source will start indexing. Setting the start block allows the data source to skip potentially millions of blocks that are irrelevant. Typically, a subgraph developer will set startBlock to the block in which the smart contract of the data source was created.

dataSources:
  - kind: ethereum/contract
    name: ExampleSource
    network: mainnet
    source:
      address: '0xc0a47dFe034B400B47bDaD5FecDa2621de6c4d95'
      abi: ExampleContract
      startBlock: 6627917
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      file: ./src/mappings/factory.ts
      entities:
        - User
      abis:
        - name: ExampleContract
          file: ./abis/ExampleContract.json
      eventHandlers:
        - event: NewEvent(address,address)
          handler: handleNewEvent

The indexerHints setting in a subgraph's manifest provides directives for indexers on processing and managing a subgraph. It influences operational decisions across data handling, indexing strategies, and optimizations. Presently, it features the prune option for managing historical data retention or pruning.

indexerHints.prune: Defines the retention of historical block data for a subgraph. Options include:

1. "never": No pruning of historical data; retains the entire history.
2. "auto": Retains the minimum necessary history as set by the indexer, optimizing query performance.
3. A specific number: Sets a custom limit on the number of historical blocks to retain.

indexerHints:
  prune: auto

History as of a given block is required for:

• Time travel queries, which enable querying the past states of these entities at specific blocks throughout the subgraph's history
• Using the subgraph as a graft base in another subgraph, at that block
• Rewinding the subgraph back to that block

If historical data as of the block has been pruned, the above capabilities will not be available.

For subgraphs leveraging time travel queries, it's advisable to either set a specific number of blocks for historical data retention or use prune: never to keep all historical entity states. Below are examples of how to configure both options in your subgraph's settings:

To retain a specific amount of historical data:

indexerHints:
  prune: 1000 # Replace 1000 with the desired number of blocks to retain

To preserve the complete history of entity states:

indexerHints:
  prune: never

Event handlers in a subgraph react to specific events emitted by smart contracts on the blockchain and trigger handlers defined in the subgraph's manifest. This enables subgraphs to process and store event data according to defined logic.

An event handler is declared within a data source in the subgraph's YAML configuration. It specifies which events to listen for and the corresponding function to execute when those events are detected.

dataSources:
  - kind: ethereum/contract
    name: Gravity
    network: dev
    source:
      address: '0x731a10897d267e19b34503ad902d0a29173ba4b1'
      abi: Gravity
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      entities:
        - Gravatar
        - Transaction
      abis:
        - name: Gravity
          file: ./abis/Gravity.json
      eventHandlers:
        - event: Approval(address,address,uint256)
          handler: handleApproval
        - event: Transfer(address,address,uint256)
          handler: handleTransfer
          topic1: ['0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045', '0xc8dA6BF26964aF9D7eEd9e03E53415D37aA96325'] # Optional topic filter which filters only events with the specified topic.

While events provide an effective way to collect relevant changes to the state of a contract, many contracts avoid generating logs to optimize gas costs. In these cases, a subgraph can subscribe to calls made to the data source contract. This is achieved by defining call handlers referencing the function signature and the mapping handler that will process calls to this function. To process these calls, the mapping handler will receive an ethereum.Call as an argument with the typed inputs to and outputs from the call. Calls made at any depth in a transaction's call chain will trigger the mapping, allowing activity with the data source contract through proxy contracts to be captured.

Call handlers will only trigger in one of two cases: when the function specified is called by an account other than the contract itself or when it is marked as external in Solidity and called as part of another function in the same contract.

To define a call handler in your manifest, simply add a callHandlers array under the data source you would like to subscribe to.

dataSources:
  - kind: ethereum/contract
    name: Gravity
    network: mainnet
    source:
      address: '0x731a10897d267e19b34503ad902d0a29173ba4b1'
      abi: Gravity
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      entities:
        - Gravatar
        - Transaction
      abis:
        - name: Gravity
          file: ./abis/Gravity.json
      callHandlers:
        - function: createGravatar(string,string)
          handler: handleCreateGravatar

The function is the normalized function signature to filter calls by. The handler property is the name of the function in your mapping you would like to execute when the target function is called in the data source contract.

Each call handler takes a single parameter that has a type corresponding to the name of the called function. In the example subgraph above, the mapping contains a handler for when the createGravatar function is called and receives a CreateGravatarCall parameter as an argument:

import { CreateGravatarCall } from '../generated/Gravity/Gravity'
import { Transaction } from '../generated/schema'

export function handleCreateGravatar(call: CreateGravatarCall): void {
  let id = call.transaction.hash
  let transaction = new Transaction(id)
  transaction.displayName = call.inputs._displayName
  transaction.imageUrl = call.inputs._imageUrl
  transaction.save()
}

The handleCreateGravatar function takes a new CreateGravatarCall which is a subclass of ethereum.Call, provided by @graphprotocol/graph-ts, that includes the typed inputs and outputs of the call. The CreateGravatarCall type is generated for you when you run graph codegen.

In addition to subscribing to contract events or function calls, a subgraph may want to update its data as new blocks are appended to the chain. To achieve this a subgraph can run a function after every block or after blocks that match a pre-defined filter.

filter:
  kind: call

The defined handler will be called once for every block which contains a call to the contract (data source) the handler is defined under.

The absence of a filter for a block handler will ensure that the handler is called every block. A data source can only contain one block handler for each filter type.

dataSources:
  - kind: ethereum/contract
    name: Gravity
    network: dev
    source:
      address: '0x731a10897d267e19b34503ad902d0a29173ba4b1'
      abi: Gravity
    mapping:
      kind: ethereum/events
      apiVersion: 0.0.6
      language: wasm/assemblyscript
      entities:
        - Gravatar
        - Transaction
      abis:
        - name: Gravity
          file: ./abis/Gravity.json
      blockHandlers:
        - handler: handleBlock
        - handler: handleBlockWithCallToContract
          filter:
            kind: call

blockHandlers:
  - handler: handleBlock
    filter:
      kind: polling
      every: 10

The defined handler will be called once for every n blocks, where n is the value provided in the every field. This configuration allows the subgraph to perform specific operations at regular block intervals.

blockHandlers:
  - handler: handleOnce
    filter:
      kind: once

The defined handler with the once filter will be called only once before all other handlers run. This configuration allows the subgraph to use the handler as an initialization handler, performing specific tasks at the start of indexing.

export function handleOnce(block: ethereum.Block): void {
  let data = new InitialData(Bytes.fromUTF8('initial'))
  data.data = 'Setup data here'
  data.save()
}

The mapping function will receive an ethereum.Block as its only argument. Like mapping functions for events, this function can access existing subgraph entities in the store, call smart contracts and create or update entities.

import { ethereum } from '@graphprotocol/graph-ts'

export function handleBlock(block: ethereum.Block): void {
  let id = block.hash
  let entity = new Block(id)
  entity.save()
}

If you need to process anonymous events in Solidity, that can be achieved by providing the topic 0 of the event, as in the example:

eventHandlers:
  - event: LogNote(bytes4,address,bytes32,bytes32,uint256,bytes)
    topic0: '0x644843f351d3fba4abcd60109eaff9f54bac8fb8ccf0bab941009c21df21cf31'
    handler: handleGive

An event will only be triggered when both the signature and topic 0 match. By default, topic0 is equal to the hash of the event signature.

Starting from specVersion 0.0.5 and apiVersion 0.0.7, event handlers can have access to the receipt for the transaction which emitted them.

To do so, event handlers must be declared in the subgraph manifest with the new receipt: true key, which is optional and defaults to false.

eventHandlers:
  - event: NewGravatar(uint256,address,string,string)
    handler: handleNewGravatar
    receipt: true

Inside the handler function, the receipt can be accessed in the Event.receipt field. When the receipt key is set to false or omitted in the manifest, a null value will be returned instead.

Starting from specVersion 0.0.4, subgraph features must be explicitly declared in the features section at the top level of the manifest file, using their camelCase name, as listed in the table below:

For instance, if a subgraph uses the Full-Text Search and the Non-fatal Errors features, the features field in the manifest should be:

specVersion: 0.0.4
description: Gravatar for Ethereum
features:
  - fullTextSearch
  - nonFatalErrors
dataSources: ...

Note that using a feature without declaring it will incur a validation error during subgraph deployment, but no errors will occur if a feature is declared but not used.

Timeseries and aggregations enable your subgraph to track statistics like daily average price, hourly total transfers, etc.

This feature introduces two new types of subgraph entity. Timeseries entities record data points with timestamps. Aggregation entities perform pre-declared calculations on the Timeseries data points on an hourly or daily basis, then store the results for easy access via GraphQL.

type Data @entity(timeseries: true) {
  id: Int8!
  timestamp: Timestamp!
  price: BigDecimal!
}

type Stats @aggregation(intervals: ["hour", "day"], source: "Data") {
  id: Int8!
  timestamp: Timestamp!
  sum: BigDecimal! @aggregate(fn: "sum", arg: "price")
}

Timeseries entities are defined with @entity(timeseries: true) in schema.graphql. Every timeseries entity must have a unique ID of the int8 type, a timestamp of the Timestamp type, and include data that will be used for calculation by aggregation entities. These Timeseries entities can be saved in regular trigger handlers, and act as the “raw data” for the Aggregation entities.

Aggregation entities are defined with @aggregation in schema.graphql. Every aggregation entity defines the source from which it will gather data (which must be a Timeseries entity), sets the intervals (e.g., hour, day), and specifies the aggregation function it will use (e.g., sum, count, min, max, first, last). Aggregation entities are automatically calculated on the basis of the specified source at the end of the required interval.

• hour: sets the timeseries period every hour, on the hour.
• day: sets the timeseries period every day, starting and ending at 00:00.

• sum: Total of all values.
• count: Number of values.
• min: Minimum value.
• max: Maximum value.
• first: First value in the period.
• last: Last value in the period.

{
  stats(interval: "hour", where: { timestamp_gt: 1704085200 }) {
    id
    timestamp
    sum
  }
}

Note:

To use Timeseries and Aggregations, a subgraph must have a spec version ≥1.1.0. Note that this feature might undergo significant changes that could affect backward compatibility.

Read more about Timeseries and Aggregations.

Indexing errors on already synced subgraphs will, by default, cause the subgraph to fail and stop syncing. Subgraphs can alternatively be configured to continue syncing in the presence of errors, by ignoring the changes made by the handler which provoked the error. This gives subgraph authors time to correct their subgraphs while queries continue to be served against the latest block, though the results might be inconsistent due to the bug that caused the error. Note that some errors are still always fatal. To be non-fatal, the error must be known to be deterministic.

Enabling non-fatal errors requires setting the following feature flag on the subgraph manifest:

specVersion: 0.0.4
description: Gravatar for Ethereum
features:
    - nonFatalErrors
    ...

The query must also opt-in to querying data with potential inconsistencies through the subgraphError argument. It is also recommended to query _meta to check if the subgraph has skipped over errors, as in the example:

foos(first: 100, subgraphError: allow) {
  id
}

_meta {
  hasIndexingErrors
}

If the subgraph encounters an error, that query will return both the data and a graphql error with the message "indexing_error", as in this example response:

"data": {
    "foos": [
        {
          "id": "0xdead"
        }
    ],
    "_meta": {
        "hasIndexingErrors": true
    }
},
"errors": [
    {
        "message": "indexing_error"
    }
]

When a subgraph is first deployed, it starts indexing events at the genesis block of the corresponding chain (or at the startBlock defined with each data source) In some circumstances; it is beneficial to reuse the data from an existing subgraph and start indexing at a much later block. This mode of indexing is called Grafting. Grafting is, for example, useful during development to get past simple errors in the mappings quickly or to temporarily get an existing subgraph working again after it has failed.

A subgraph is grafted onto a base subgraph when the subgraph manifest in subgraph.yaml contains a graft block at the top-level:

description: ...
graft:
  base: Qm... # Subgraph ID of base subgraph
  block: 7345624 # Block number

When a subgraph whose manifest contains a graft block is deployed, Graph Node will copy the data of the base subgraph up to and including the given block and then continue indexing the new subgraph from that block on. The base subgraph must exist on the target Graph Node instance and must have indexed up to at least the given block. Because of this restriction, grafting should only be used during development or during an emergency to speed up producing an equivalent non-grafted subgraph.

Because grafting copies rather than indexes base data, it is much quicker to get the subgraph to the desired block than indexing from scratch, though the initial data copy can still take several hours for very large subgraphs. While the grafted subgraph is being initialized, the Graph Node will log information about the entity types that have already been copied.

The grafted subgraph can use a GraphQL schema that is not identical to the one of the base subgraph, but merely compatible with it. It has to be a valid subgraph schema in its own right, but may deviate from the base subgraph's schema in the following ways:

• It adds or removes entity types
• It removes attributes from entity types
• It adds nullable attributes to entity types
• It turns non-nullable attributes into nullable attributes
• It adds values to enums
• It adds or removes interfaces
• It changes for which entity types an interface is implemented

File data sources are a new subgraph functionality for accessing off-chain data during indexing in a robust, extendable way. File data sources support fetching files from IPFS and from Arweave.

Rather than fetching files "in line" during handler execution, this introduces templates which can be spawned as new data sources for a given file identifier. These new data sources fetch the files, retrying if they are unsuccessful, running a dedicated handler when the file is found.

This is similar to the existing data source templates, which are used to dynamically create new chain-based data sources.

File data sources requires graph-ts >=0.29.0 and graph-cli >=0.33.1

File data sources cannot access or update chain-based entities, but must update file specific entities.

This may mean splitting out fields from existing entities into separate entities, linked together.

Original combined entity:

type Token @entity {
  id: ID!
  tokenID: BigInt!
  tokenURI: String!
  externalURL: String!
  ipfsURI: String!
  image: String!
  name: String!
  description: String!
  type: String!
  updatedAtTimestamp: BigInt
  owner: User!
}