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Quickstart

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 3.11 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:

Terminal
curl -Lsf https://dipdup.io/install.py | python3

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:

Terminal
dipdup new

For educational purposes, we'll create a project from scratch, so choose [none] network and demo_blank template.

Note
Want to skip a tutorial? Choose EVM-compatible and demo_evm_events instead!

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; for now just replace its content with the following:

dipdup.yaml
spec_version: 2.0
package: demo_evm_events

datasources:
  subsquid:
    kind: evm.subsquid
    url: ${SUBSQUID_URL:-https://v2.archive.subsquid.io/network/ethereum-mainnet}
    node: evm_node
  etherscan:
    kind: abi.etherscan
    url: ${ETHERSCAN_URL:-https://api.etherscan.io/api}
    api_key: ${ETHERSCAN_API_KEY:-''}
  evm_node:
    kind: evm.node
    url: ${NODE_URL:-https://eth-mainnet.g.alchemy.com/v2}/${NODE_API_KEY:-''}
    ws_url: ${NODE_WS_URL:-wss://eth-mainnet.g.alchemy.com/v2}/${NODE_API_KEY:-''}

contracts:
  eth_usdt:
    kind: evm
    address: 0xdac17f958d2ee523a2206206994597c13d831ec7
    typename: eth_usdt

indexes:
  eth_usdt_events:
    kind: evm.subsquid.events
    datasource: subsquid
    handlers:
      - callback: on_transfer
        contract: eth_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_evm_events as a package name; yours may differ.

Run the following command:

Terminal
dipdup init

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

Terminal
$ dipdup package tree
demo_evm_events [.]
├── abi
   └── eth_usdt/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
   └── eth_usdt/evm_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 implement this model in DipDup:

models/__init__.py
from dipdup import fields
from dipdup.models import CachedModel


class Holder(CachedModel):
    address = fields.TextField(pk=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:
        # NOTE: Decrease if you're low on RAM
        maxsize = 2 ** 20

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:

handlers/on_transfer.py
from decimal import Decimal

from demo_evm_events import models as models
from demo_evm_events.types.eth_usdt.evm_events.transfer import Transfer
from dipdup.context import HandlerContext
from dipdup.models.evm_subsquid import SubsquidEvent
from tortoise.exceptions import DoesNotExist


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

    await on_balance_update(
        address=event.payload.from_,
        balance_update=-amount,
        level=event.data.level,
    )
    await on_balance_update(
        address=event.payload.to,
        balance_update=amount,
        level=event.data.level,
    )
    

async def on_balance_update(
    address: str,
    balance_update: Decimal,
    level: int,
) -> None:
    try:
        holder = await models.Holder.cached_get(pk=address)
    except DoesNotExist:
        holder = models.Holder(
            address=address,
            balance=0,
            turnover=0,
            tx_count=0,
            last_seen=None,
        )
        holder.cache()
    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_evm_events.sqlite 'SELECT * FROM holder LIMIT 10'

If you run a Compose stack, check open http://127.0.0.1:8080 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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