This page will guide you through the steps to get your first selective indexer up and running in a few minutes without getting too deep into the details.

Let's create an indexer for the USDt token contract. Our goal is to save all token transfers to the database and then calculate some statistics of its holders' activity.

Install DipDup

A modern Linux/macOS distribution with Python 3.12 installed is required to run DipDup.

The easiest way to install DipDup as a CLI application pipx. We have a convenient wrapper script that installs DipDup for the current user. Run the following command in your terminal:

curl -Lsf https://dev.dipdup.io/install.py | python3.12 - --pre

See the Installation page for all options.

Create a project

DipDup CLI has a built-in project generator. Run the following command in your terminal:

dipdup new

Choose Starknet network and demo_starknet_events template.

Want to skip a tutorial and start from scratch? Choose [none] and demo_blank instead and proceed to the Config section.

Follow the instructions; the project will be created in the new directory.

Write a configuration file

In the project root, you'll find a file named dipdup.yaml. It's the main configuration file of your indexer. We will discuss it in detail in the Config section; now it has the following content:

spec_version: 3.0
package: demo_starknet_events

    kind: starknet.subsquid
    url: ${SUBSQUID_URL:-https://v2.archive.subsquid.io/network/starknet-mainnet}
    kind: starknet.node
    url: ${NODE_URL:-https://starknet-mainnet.g.alchemy.com/v2}/${NODE_API_KEY:-''}

    kind: starknet
    address: '0x68f5c6a61780768455de69077e07e89787839bf8166decfbf92b645209c0fb8'
    typename: stark_usdt

    kind: starknet.events
      - subsquid
      - node
      - callback: on_transfer
        contract: stark_usdt
        name: Transfer

Generate types and stubs

Now it's time to generate typeclasses and callback stubs based on definitions from config. Examples below use demo_starknet_events as a package name; yours may differ.

Run the following command:

dipdup init

DipDup will create a Python package demo_starknet_events with everything you need to start writing your indexer. Use package tree command to see the generated structure:

$ dipdup package tree
demo_starknet_events [.]
├── abi
   └── stark_usdt/cairo_abi.json
├── configs
   ├── dipdup.compose.yaml
   ├── dipdup.sqlite.yaml
   ├── dipdup.swarm.yaml
   └── replay.yaml
├── deploy
   ├── .env.default
   ├── Dockerfile
   ├── compose.sqlite.yaml
   ├── compose.swarm.yaml
   ├── compose.yaml
   ├── sqlite.env.default
   └── swarm.env.default
├── graphql
├── handlers
   └── on_transfer.py
├── hasura
├── hooks
   ├── on_index_rollback.py
   ├── on_reindex.py
   ├── on_restart.py
   └── on_synchronized.py
├── models
   └── __init__.py
├── sql
├── types
   └── stark_usdt/starknet_events/transfer.py
└── py.typed

That's a lot of files and directories! But don't worry, we will need only models and handlers sections in this guide.

Define data models

DipDup supports storing data in SQLite, PostgreSQL and TimescaleDB databases. We use custom ORM based on Tortoise ORM as an abstraction layer.

First, you need to define a model class. Our schema will consist of a single model Holder with the following fields:

addressaccount address
balancetoken amount held by the account
turnovertotal amount of transfer/mint calls
tx_countnumber of transfers/mints
last_seentime of the last transfer/mint

Here's how to define this model in DipDup:

from dipdup import fields
from dipdup.models import CachedModel

class Holder(CachedModel):
    address = fields.TextField(primary_key=True)
    balance = fields.DecimalField(decimal_places=6, max_digits=20, default=0)
    turnover = fields.DecimalField(decimal_places=6, max_digits=20, default=0)
    tx_count = fields.BigIntField(default=0)
    last_seen = fields.BigIntField(null=True)

    class Meta:
        maxsize = 2 ** 18

Implement handlers

Everything's ready to implement an actual indexer logic.

Our task is to index all the balance updates. Put some code to the on_transfer handler callback to process matched logs:

from decimal import Decimal

from demo_starknet_events import models as models
from demo_starknet_events.types.stark_usdt.starknet_events.transfer import TransferPayload
from dipdup.context import HandlerContext
from dipdup.models.evm import EvmEvent
from tortoise.exceptions import DoesNotExist

async def on_transfer(
    ctx: HandlerContext,
    event: EvmEvent[TransferPayload],
) -> None:
    amount = Decimal(event.payload.value) / (10**6)
    if not amount:

    address_from = f'0x{event.payload.from_:x}'
    await on_balance_update(
    address_to = f'0x{event.payload.to:x}'
    await on_balance_update(

async def on_balance_update(
    address: str,
    balance_update: Decimal,
    level: int,
) -> None:
        holder = await models.Holder.cached_get(pk=address)
    except DoesNotExist:
        holder = models.Holder(
    holder.balance += balance_update
    holder.turnover += abs(balance_update)
    holder.tx_count += 1
    holder.last_seen = level
    await holder.save()

And that's all! We can run the indexer now.

Next steps

Run the indexer in memory:

dipdup run

Store data in SQLite database:

dipdup -c . -c configs/dipdup.sqlite.yaml run

Or spawn a Compose stack with PostgreSQL and Hasura:

cd deploy
cp .env.default .env
# Edit .env file before running
docker-compose up

DipDup will fetch all the historical data and then switch to realtime updates. You can check the progress in the logs.

If you use SQLite, run this query to check the data:

sqlite3 demo_starknet_events.sqlite 'SELECT * FROM holder LIMIT 10'

If you run a Compose stack, check open in your browser to see the Hasura console (an exposed port may differ). You can use it to explore the database and build GraphQL queries.

Congratulations! You've just created your first DipDup indexer. Proceed to the Getting Started section to learn more about DipDup configuration and features.

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