> ## Documentation Index > Fetch the complete documentation index at: https://docs.goldsky.com/llms.txt > Use this file to discover all available pages before exploring further. # ERC-721 transfers > Create a table containing ERC-721 Transfers for several or all token contracts This guide streams every ERC-721 Transfer event into your own database, with token IDs intact, so you can track ownership, mints, and burns per token. This guide is part of a series of tutorials on how you can stream transfer data into your data warehouse using Turbo pipelines. Here we will be focusing on ERC-721 Transfers, visit the following guides for other types of transfers: * [Native Transfers](/turbo-pipelines/guides/token-transfers/native-transfers) * [ERC-20 Transfers](/turbo-pipelines/guides/token-transfers/ERC-20-transfers) * [ERC-1155 Transfers](/turbo-pipelines/guides/token-transfers/ERC-1155-transfers) ## What you'll need 1. A Goldsky account and the CLI installed 1. Install the Goldsky CLI: **For macOS/Linux:** ```shell theme={"dark"} curl https://goldsky.com | sh ``` **For Windows:** ```shell theme={"dark"} npm install -g @goldskycom/cli ``` Windows users need to have Node.js and npm installed first. Download from [nodejs.org](https://nodejs.org) if not already installed. 2. Log into your Project by running: ```shell theme={"dark"} goldsky login ``` This opens your browser to sign in (Google, GitHub, SSO, or email). Once you authenticate, the CLI is logged in automatically — there's no API key to copy or paste. On a headless or remote machine (or in CI), create an API key on your [Project Settings](https://app.goldsky.com/dashboard/settings) page and pass it directly with `goldsky login --token `. Use `goldsky login --no-browser` to print the login URL instead of opening a browser. 3. Now that you are logged in, run `goldsky` to get started: ```shell theme={"dark"} goldsky ``` 2. A basic understanding of the [Turbo product](/turbo-pipelines/introduction) 3. A destination sink to write your data to. In this example, we will use [the PostgreSQL sink](/turbo-pipelines/sinks/postgres) ## Introduction In order to stream all the ERC-721 Transfers of a chain there are two potential methods available: 1. Use the readily available ERC-721 dataset for the chain you are interested in: this is the easiest and quickest method to get you streaming token transfers into your sink of choice with minimum code. 2. Build the ERC-721 Transfers pipeline from scratch using raw or decoded logs: this method takes more code and time to implement but it's a great way to learn about how you can use decoding functions in case you want to build more customized pipelines. Let's explore both methods below with more detail: ## Using the ERC-721 transfers source dataset Every EVM chain has its own ERC-721 dataset available for you to use as source in your pipelines. You can check this by running the `goldsky dataset list` command and finding the EVM chain of your choice. For this example, let's use `apex` chain and create a simple pipeline definition using its ERC-721 dataset that writes the data into a PostgreSQL instance: ```yaml apex-erc721-transfers.yaml expandable theme={"dark"} name: apex-erc721-pipeline resource_size: s sources: apex_erc721_transfers: type: dataset dataset_name: apex.erc721_transfers version: 1.0.0 start_at: earliest transforms: {} sinks: # Postgres sink for the apex.erc721_transfers dataset postgres_erc721_transfers: type: postgres from: apex_erc721_transfers schema: public table: apex_erc721_transfers secret_name: primary_key: id ``` If you copy and use this configuration file, make sure to update: 1. Your `secret_name`. If you already [created a secret](/platform/secrets), you can find it via the CLI command `goldsky secret list`. 2. The schema and table you want the data written to, by default it writes to `public.apex_erc721_transfers`. You can start the pipeline by running: ```bash theme={"dark"} goldsky turbo apply apex-erc721-transfers.yaml ``` That's it! You should soon start seeing ERC-721 token transfers in your database. ## Building ERC-721 transfers from scratch using logs The ERC-721 datasets used as the source above encapsulate all the decoding logic explained in this section. Read on if you want to see how it's implemented, or to extend or modify this logic yourself. To build the token transfers pipeline from scratch, use the `raw_logs` dataset for that chain in combination with [decoding functions](/turbo-pipelines/reference/sql-functions#evm--ethereum-functions) using the ABI of a specific ERC-721 contract. ### Building ERC-721 transfers using decoding functions In this example, we will stream all the `Transfer` events of all the ERC-721 tokens for the [Scroll chain](https://scroll.io/). To that end, we will dynamically fetch the ABI of the [Cosmic Surprise](https://scrollscan.com/token/0xcf7f37b4916ac5c530c863f8c8bb26ec1e8d2ccb) token from the Scrollscan API (available [here](https://api.scrollscan.com/api?module=contract\&action=getabi\&address=0xcf7f37b4916ac5c530c863f8c8bb26ec1e8d2ccb)) and use it to identify all the same events for the tokens in the chain. We have decided to use the ABI of this NFT contract for this example but any other ERC-721 compliant token would also work. We need to differentiate ERC-20 token transfers from ERC-721 (NFT) transfers since they have the same event signature in decoded data: `Transfer(address,address,uint256)`. However, if we look closely at their event definitions we can appreciate that the number of topics differ: * [ERC-20](https://ethereum.org/en/developers/docs/standards/tokens/erc-20/): `event Transfer(address indexed _from, address indexed _to, uint256 _value)` * [ERC-721](https://ethereum.org/en/developers/docs/standards/tokens/erc-721/): `event Transfer(address indexed _from, address indexed _to, uint256 indexed _tokenId)` ERC-20 Transfer events have three topics (one topic for event signature + 2 topics for the indexed params). NFTs on the other hand have four topics as they have one more indexed param in the event signature. We will use this as a filter in our pipeline transform to only index ERC-721 Transfer events. Let's now see all these concepts applied in an example pipeline definition: #### Pipeline definition ```yaml scroll-erc721-transfers.yaml expandable theme={"dark"} name: scroll-erc721-transfers resource_size: s sources: my_scroll_mainnet_raw_logs: type: dataset dataset_name: scroll_mainnet.raw_logs version: 1.0.0 start_at: earliest transforms: # Fetch the ABI from Scrollscan for the Cosmic Surprise token and decode matching logs scroll_decoded: type: sql primary_key: id sql: | SELECT *, _gs_log_decode( _gs_fetch_abi('https://api.scrollscan.com/api?module=contract&action=getabi&address=0xcf7f37b4916ac5c530c863f8c8bb26ec1e8d2ccb&apikey=YOUR_KEY', 'etherscan'), topics, data ) AS decoded FROM my_scroll_mainnet_raw_logs WHERE topics LIKE '0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef%' AND SPLIT_INDEX(topics, ',', 3) IS NOT NULL # Clean up the previous transform, unnest the values from the decoded struct scroll_clean: type: sql primary_key: id sql: | SELECT *, decoded.event_params AS event_params, decoded.event_signature AS event_name FROM scroll_decoded WHERE decoded IS NOT NULL AND decoded.event_signature = 'Transfer' # Select the transfer columns we want in the database scroll_721_transfers: type: sql primary_key: id sql: | SELECT id, lower(address) AS contract_address, lower(event_params[1]) AS sender, lower(event_params[2]) AS recipient, COALESCE(TRY_CAST(event_params[3] AS DECIMAL(38, 0)), -999) AS token_id, event_name, block_number, block_hash, log_index, transaction_hash, transaction_index FROM scroll_clean sinks: # Postgres sink for ERC-721 transfers scroll_721_sink: type: postgres from: scroll_721_transfers schema: public table: erc721_transfers secret_name: primary_key: id ``` If you copy and use this configuration file, make sure to update: 1. Your `secret_name`. If you already [created a secret](/platform/secrets), you can find it via the CLI command `goldsky secret list`. 2. The schema and table you want the data written to, by default it writes to `public.erc721_transfers`. There are 3 transforms in this pipeline definition which we'll explain how they work: ```sql Transform: scroll_decoded theme={"dark"} SELECT *, _gs_log_decode( _gs_fetch_abi('https://api.scrollscan.com/api?module=contract&action=getabi&address=0xcf7f37b4916ac5c530c863f8c8bb26ec1e8d2ccb&apikey=YOUR_KEY', 'etherscan'), topics, data ) AS decoded FROM my_scroll_mainnet_raw_logs WHERE topics LIKE '0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef%' AND SPLIT_INDEX(topics, ',', 3) IS NOT NULL ``` As explained in the [decode custom contract events guide](/turbo-pipelines/sources/evm#guide-decode-custom-contract-events) we first make use of the `_gs_fetch_abi` function to get the ABI from Scrollscan and pass it as first argument to the function `_gs_log_decode` to decode its topics and data. We store the result in a `decoded` struct which we unnest on the next transform. We include the topic and `SPLIT_INDEX` filters here to limit decoding only to the relevant events. * `topics LIKE '0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef%'`: `topics` is a comma separated string. Each value in the string is a hash. The first is the hash of the full event\_signature (including arguments), in our case `Transfer(address,address,uint256)` for ERC-721, which is hashed to `0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef`. We use `LIKE` to only consider the first signature, with a `%` at the end, which acts as a wildcard. * `SPLIT_INDEX(topics, ',', 3) IS NOT NULL`: as mentioned in the introduction, ERC-20 transfers share the same `event_signature` as ERC-721 transfers. The difference between them is the number of topics associated with the event. ERC-721 transfers have four topics, and ERC-20 transfers have three. To make the `SPLIT_INDEX` check more concrete, here's an example topics string for an ERC-721 transfer: ``` 0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef,0x000000000000000000000000441e1e47a6fa2dbfd3cd9b54291e9ab3a58d7975,0x00000000000000000000000097d2e8eeb59e521f10c2e7716eac3dd805ea9a46,0x0000000000000000000000000000000000000000000000000000000000043321 ``` `SPLIT_INDEX` splits the string by commas and extracts the element at the given 0-based index, in this case `3`, which is the fourth element (here the token ID). An ERC-20 transfer would only have three elements when the topics are split, so `SPLIT_INDEX` would return `NULL`. If you want to get into the nitty gritty you may enjoy the Solidity developer documentation for [events](https://docs.soliditylang.org/en/latest/abi-spec.html#abi-events). ```sql Transform: scroll_clean theme={"dark"} SELECT *, decoded.event_params AS event_params, decoded.event_signature AS event_name FROM scroll_decoded WHERE decoded IS NOT NULL AND decoded.event_signature = 'Transfer' ``` In this second transform, we take the `event_params` and `event_signature` from the result of the decoding. We then filter the query on: * `decoded IS NOT NULL`: to leave out potential null results from the decoder * `decoded.event_signature = 'Transfer'`: the decoder will output the event name as event\_signature, excluding its arguments. We use it to filter only for Transfer events. ```sql Transform: scroll_721_transfers theme={"dark"} SELECT id, lower(address) AS contract_address, lower(event_params[1]) AS sender, lower(event_params[2]) AS recipient, COALESCE(TRY_CAST(event_params[3] AS DECIMAL(38, 0)), -999) AS token_id, event_name, block_number, block_hash, log_index, transaction_hash, transaction_index FROM scroll_clean ``` In this last transform we are essentially selecting all the Transfer information we are interested in having in our database. We've included a number of columns that you may or may not need, the main columns needed for most purposes are: `id`, `contract_address` (if you are syncing multiple contract addresses), `sender`, `recipient` and `token_id`. * `id`: This is the Goldsky provided `id`, it is a string composed of the dataset name, block hash, and log index, which is unique per event, here's an example: `log_0x60eaf5a2ab37c73cf1f3bbd32fc17f2709953192b530d75aadc521111f476d6c_18` * `lower(address) AS contract_address`: We use the `lower` function here to lower-case the address to make using this data simpler downstream, we also rename the column to `contract_address` to make it more explicit. * `lower(event_params[1]) AS sender`: Here we continue to lower-case values for consistency. In this case we're using the first element of the `event_params` array (using a 1-based index), and renaming it to `sender`. Each event parameter maps to an argument to the `event_signature`. * `lower(event_params[2]) AS recipient`: Like the previous column, we're pulling the second element in the `event_params` array and renaming it to `recipient`. You can save some space when storing the ID by using `md5(id) AS id` in your transform. One reason you may want to keep the existing `id` format is that it makes it easier to order events in the same block without also syncing block hash and log index. For the token\_id we introduce a few SQL functions `COALESCE(TRY_CAST(event_params[3] AS DECIMAL(38, 0)), -999) AS token_id`. We'll start from the inside and work our way out. 1. `event_params[3]` is the third element of the `event_params` array, and for ERC-721 this is the token ID. Although not covered in this example, since ERC-20 shares the same signature, this element represents a token balance rather than token ID if you're decoding ERC-20 transfers. 2. `TRY_CAST(event_params[3] AS DECIMAL(38, 0))` is casting the string element `event_params[3]` to a fixed-precision decimal. Token IDs can be as large as an unsigned 256 bit integer (up to 78 digits), which exceeds `DECIMAL(38, 0)` precision; some contracts derive token IDs from hashes, for example. We use `TRY_CAST` because it will prevent the pipeline from failing in case the cast fails, returning a `NULL` value instead. If you need the full 256-bit range, keep `event_params[3]` as a string instead, or use the [U256 functions](/turbo-pipelines/reference/sql-functions#large-numbers-u256--i256). 3. `COALESCE(TRY_CAST(event_params[3] AS DECIMAL(38, 0)), -999)`: `COALESCE` can take an arbitrary number of arguments and returns the first non-NULL value. Since `TRY_CAST` can return a `NULL` we're returning `-999` in case it does. This isn't strictly necessary but is useful to do in case you want to find offending values that were unable to be cast. Lastly, we are also adding more block metadata to the query to add context to each transaction: ``` event_name, block_number, block_hash, log_index, transaction_hash, transaction_index ``` These columns are often useful for looking up the transfers in another tool, such as a block explorer like [Etherscan](https://etherscan.io/). It's worth mentioning that in this example we are interested in all the ERC-721 Transfer events but if you would like to filter for specific contract addresses you could simply add a `WHERE` filter to this query with the addresses you are interested in, like: `WHERE address IN ('0xBC4CA0EdA7647A8aB7C2061c2E118A18a936f13D', '0x22c1f6050e56d2876009903609a2cc3fef83b415')` If you plan to combine ERC-721 transfers with [ERC-1155 transfers](/turbo-pipelines/guides/token-transfers/ERC-1155-transfers) in a single table, add a constant `1 AS amount` column to this transform. NFTs don't have a quantity associated with them when transferred, so normalizing each ERC-721 transfer as a transfer of a single token with an amount of `1` keeps the schemas aligned. #### Deploying the pipeline Our last step is to deploy this pipeline and start sinking ERC-721 transfer data into our database. Assuming we are using the same file name for the pipeline configuration as in this example, we can use the [CLI apply command](/turbo-pipelines/cli-reference#apply-a-pipeline) like this: ```bash theme={"dark"} goldsky turbo apply scroll-erc721-transfers.yaml ``` After some time, you should see the pipeline start streaming Transfer data into your sink. Remember that you can always speed up the streaming process by increasing the `resource_size` in your pipeline YAML and re-applying it with `goldsky turbo apply`. Here's an example transfer record from our sink: | id | contract\_address | sender | recipient | token\_id | event\_name | block\_number | block\_hash | log\_index | transaction\_hash | transaction\_index | | --------------------------------------------------------------------------- | ------------------------------------------ | ------------------------------------------ | ------------------------------------------ | --------- | ----------- | ------------- | ------------------------------------------------------------------ | ---------- | ------------------------------------------------------------------ | ------------------ | | log\_0x5e3225c40254dd5b1b709152feafaa8437e505ae54c028b6d433362150f99986\_34 | 0x6e55472109e6abe4054a8e8b8d9edffcb31032c5 | 0xd2cda3fa01d34878bbe6496c7327b3781d4422bc | 0x6e55472109e6abe4054a8e8b8d9edffcb31032c5 | 38087399 | Transfer | 4057598 | 0x5e3225c40254dd5b1b709152feafaa8437e505ae54c028b6d433362150f99986 | 34 | 0xf06c42ffd407bb9abba8f00d4a42cb7f1acc1725c604b8895cdb5f785f827967 | 11 | We can find this [transaction in Scrollscan](https://scrollscan.com/tx/0xf06c42ffd407bb9abba8f00d4a42cb7f1acc1725c604b8895cdb5f785f827967). We see that it corresponds to the transfer of MERK token: This concludes our successful deployment of a Turbo pipeline streaming ERC-721 tokens from Scroll chain into our database using inline decoders. Congrats! ## Using the data With this table in place, you can create views in your database that show you a number of useful pieces of information: 1. All mints. For ERC-721 (and ERC-1155) a mint is identified by having the zero address `0x0000000000000000000000000000000000000000` as the sender. 2. All current holders of a token. For example, here's a query you can run against the `erc721_transfers` table in your database to compute current holders. Each transfer credits the recipient with one token and debits the sender with one: ```sql theme={"dark"} WITH ledger AS ( SELECT contract_address, recipient AS owner_address, token_id, 1 AS quantity, block_number FROM erc721_transfers UNION ALL SELECT contract_address, sender AS owner_address, token_id, -1 AS quantity, block_number FROM erc721_transfers ) SELECT contract_address, owner_address, token_id, SUM(quantity) AS balance, MIN(block_number) AS first_updated, MAX(block_number) AS last_updated FROM ledger WHERE owner_address <> '0x0000000000000000000000000000000000000000' GROUP BY contract_address, owner_address, token_id HAVING SUM(quantity) > 0; ``` ## Conclusion In this guide, we have learnt how Turbo pipelines simplify streaming NFT Transfer events into your database. We have first looked into the easy way of achieving this, simply by making use of the readily available ERC-721 dataset of the EVM chain and using it as the source to our pipeline. We have also deep dived into the standard decoding method using decoding functions, implementing an example on Scroll chain. With Turbo pipelines, developers gain flexibility and efficiency in integrating blockchain data, opening up new possibilities for applications and insights. Can't find what you're looking for? Reach out to us at [support@goldsky.com](mailto:support@goldsky.com) for help. ## Related topics - [ERC-20 transfers](/turbo-pipelines/guides/token-transfers/ERC-20-transfers.md) - [ERC-1155 transfers](/turbo-pipelines/guides/token-transfers/ERC-1155-transfers.md) - [Native transfers](/turbo-pipelines/guides/token-transfers/native-transfers.md) - [Curated dataset schemas: ERC-20, ERC-721, ERC-1155](/turbo-pipelines/reference/schema/curated-schemas.md) - [Supported networks](/chains/supported-networks.md)