HyperliquidIn development

Hyperliquid data for bots and market replay.

A planned normalized dataset for L2 order books, trades, funding, candles, and asset context—captured for systematic research and historical replay.

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DATASEThyperliquid.l2_book

PIPELINE PREVIEW

MARKET STATEBTC perpetual · L2 order bookRepresentative normalized top of book

BEST BID108,421.0size 1.842 BTC

BEST ASK108,422.0size 0.917 BTC

observed_at2026-08-30 14:32:10Zsourcehyperliquid

DATASEThyperliquid.l2_book

SOURCE INTERFACEInfo API · WebSocket · S3

UPDATE TARGET1 sec target

NETWORKHyperliquid L1

01 / BUILT FOR RESEARCH

From market question
to testable dataset.

Start with the strategy. KnownAt handles collection, normalization, timestamps, and historical storage.

Replay the book

Reconstruct market state and test execution logic against historical L2 observations.

Study liquidity

Measure spread, depth, imbalance, and the response of liquidity around market events.

Research funding

Join trades and market state with funding and asset context in one timestamp model.

02 / NORMALIZED SCHEMA

Rows you can
actually work with.

Illustrative normalized schema; final fields may change before release. Types, timestamps, and source identifiers stay explicit so the same dataset works in notebooks, bots, and backtests.

SCHEMAhyperliquid.l2_book

observed_attimestamp

When KnownAt observed this order-book state.

available_attimestamp

When the record became usable by a model.

coinstr

Hyperliquid perpetual or spot asset identifier.

sidestr

Bid or ask side of the order book.

levelint32

Normalized price-level position within the side.

pricefloat64

Price at the captured order-book level.

sizefloat64

Resting size reported at the price level.

SAMPLE ROWSUTC · Hyperliquid

observed_at timestamp	coin str	side str	price float64
14:32:10.104	BTC	bid	108421.0
14:32:10.104	BTC	ask	108422.0
14:32:10.287	BTC	bid	108420.0
14:32:10.287	BTC	ask	108423.0

03 / SOURCE COVERAGE

Raw source data in.
One query model out.

KnownAt preserves source identifiers and acquisition time while presenting a stable interface over changing upstream APIs.

L2 order booksPrice levels and sizes for perpetual and spot markets.

Trades and fillsMarket executions with source identifiers and event time.

Funding and contextFunding history, open interest, mark price, and asset context.

Candles and metadataSupported candle intervals plus perpetual and spot definitions.

Hyperliquidsource APIs

KnownAtnormalize · validate · timestamp

Your modellive · history · replay

04 / ONE ACCESS LAYER

Switch time ranges.
Not integrations.

The API shape stays familiar whether you request the latest record, bounded history, or an information set as it was known at a past moment.

Python

knownat

dataset = knownat.dataset(
  "hyperliquid.l2_book"
)

rows = dataset.history(
  from_="2026-08-01",
  to="2026-08-30",
  as_known_at="2026-08-30T00:00:00Z"
)

REST JSON Parquet

POINT-IN-TIME QUERY

The result does not borrow from the future.

Observed time, availability time, ingestion time, and later revisions remain distinct. Your backtest sees only records it could have known then.

as_known_at=2026-08-30T00:00:00Z

05 / AVAILABILITY

Hyperliquid is next in the pipeline.

The page shows the planned normalized interface. Join now to follow coverage, schema, and release progress.

Join early access See founding pricing