eth.contracts- Deployed contracts with their bytecode, function sighashes, token standard detection status, and detection confidence.
eth.tokens- Token contracts with their name, symbol, decimals, and total supply along with the status of each token standard.
eth.tokens_erc1155- Identical to
eth.tokensbut filtered to each token standard
eth.nft_contracts- Similar to
eth.tokensbut filtered only to contracts that have at least one minted NFT.
eth.nfts- NFTs and their token standard compliance status.
eth.nft_owners- NFTs and their current owner.
eth.token_transfers- Transfers of tokens including mints and burns.
token_transfersdataset filtered to the last 30 minutes. Several Spice datasets have a corresponding
recent_table that follows this pattern.
token_transfersfiltered to each token standard.
eth.nft_transfers- NFT transfers. A subset of
eth.token_transfersfiltered to all ERC-721 transfers and ERC-1155 transfers of NFTs.
nft_transfersfiltered to the last 30 minutes.
nft_transfersfiltered to transfers where no ether was exchanged.
nft_airdrop_transfersfiltered to the last 30 minutes.
eth.nftsby counting how many NFTs there are for each token standard and combining them:
eth.recent_token_transfersfiltered to ERC-721s where the
from_addressis the zero address. Counting the mints from distinct token addresses shows which contracts have recently minted tokens.
recent_datasets are the fastest to query but if you need historical mints, use
eth.recent_nft_transfers, you would be correct! You could also modify the query to add
where token_standard = 'erc721' or token_standard = 'erc1155', which would include fungible ERC-1155 token mints.
eth.nft_airdrop_transferstable is perfect for answering this question. The only potentially tricky part is filtering the data to the time period we're interested in. We've already seen above how to do an aggregation to group by contracts and display the counts.
block_timestampcolumn that tracks when the data was emitted using the number of seconds since the Unix epoch. This is commonly referred to as Unix time. There is a SQL function
UNIX_TIMESTAMP()that we can use to convert a human-readable date into a Unix timestamp.
eth.nft_ownerstable. This can be useful for performing your own data science on the data in your own systems. The HTTP API that the Spice.xyz portal uses is limited to 500 rows, so you will need to use one of the Spice SDKs (Python, Node.js) to run the query and retrieve all of the results.
OFFSET. Here is an example:
eth.erc_721. Because token standards detection is a heuristic these datasets and fields determine token standards compliance using the Spice standards compliance confidence fields: