# Hyperliquid

Hyperliquid historical data is available since **2024-10-29**.

{% embed url="<https://api.tardis.dev/v1/exchanges/hyperliquid>" %}
See Hyperliquid historical data coverage: available symbols, channels, date ranges and incidents
{% endembed %}

### Downloadable **CSV** files

Historical CSV datasets for the first day of each month are **available to download without API key**. See [downloadable CSV files documentation](/downloadable-csv-files/overview.md).

| data type             | symbol | date       |                                                                                                         |
| --------------------- | ------ | ---------- | ------------------------------------------------------------------------------------------------------- |
| incremental\_book\_L2 | BTC    | 2024-12-01 | [Download sample](https://datasets.tardis.dev/v1/hyperliquid/incremental_book_L2/2024/12/01/BTC.csv.gz) |
| trades                | BTC    | 2024-12-01 | [Download sample](https://datasets.tardis.dev/v1/hyperliquid/trades/2024/12/01/BTC.csv.gz)              |
| derivative\_ticker    | BTC    | 2024-12-01 | [Download sample](https://datasets.tardis.dev/v1/hyperliquid/derivative_ticker/2024/12/01/BTC.csv.gz)   |

### API Access and data format

Historical data format is the same as provided by real-time Hyperliquid WebSocket API with addition of local timestamps. If you'd like to work with **normalized data format** instead (same format for each exchange) see [downloadable CSV files](/downloadable-csv-files/overview.md) or official [client libs](/api/quickstart.md) that can perform data normalization client-side.

{% tabs %}
{% tab title="Python" %}

```python
# pip install tardis-dev
import asyncio
from tardis_dev import Channel, replay

async def main():
    async for local_timestamp, message in replay(
        exchange="hyperliquid",
        from_date="2024-11-01",
        to_date="2024-11-02",
        filters=[Channel(name="l2Book", symbols=["BTC"])],
        api_key="YOUR_API_KEY",
    ):
        # messages as provided by Hyperliquid real-time stream
        print(message)

asyncio.run(main())
```

See [Python client docs](/python-client/quickstart.md).
{% endtab %}

{% tab title="Node.js" %}

```javascript
// npm install tardis-dev
import { replay } from 'tardis-dev';

const messages = replay({
  exchange: 'hyperliquid',
  from: '2024-11-01',
  to: '2024-11-02',
  filters: [{ channel: 'l2Book', symbols: ['BTC'] }],
  apiKey: 'YOUR_API_KEY'
});

// messages as provided by Hyperliquid real-time stream
for await (const { localTimestamp, message } of messages) {
  console.log(localTimestamp, message);
}
```

See [Node.js client docs](/node-client/quickstart.md).
{% endtab %}

{% tab title="cURL & HTTP API" %}

```bash
curl --compressed -g 'https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2024-11-01&filters=[{"channel":"l2Book","symbols":["BTC"]}]&offset=0'
```

{% embed url="<https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2024-11-01&filters=[{%22channel%22:%22l2Book%22,%22symbols%22:[%22BTC%22]}]&offset=0>" %}
Example API response for Hyperliquid historical market data request
{% endembed %}

See [HTTP API docs](/api/http-api-reference.md).
{% endtab %}

{% tab title="cURL & tardis-machine" %}

```bash
curl -g 'localhost:8000/replay?options={"exchange":"hyperliquid","filters":[{"channel":"l2Book","symbols":["BTC"]}],"from":"2024-11-01","to":"2024-11-02"}'
```

[Tardis-machine](/tardis-machine/quickstart.md) is a locally runnable server that exposes API allowing efficiently requesting historical market data for whole time periods in contrast to [HTTP API](/api/http-api-reference.md) that provides data only in minute by minute slices.

See [tardis-machine](/tardis-machine/quickstart.md) docs.
{% endtab %}
{% endtabs %}

### Captured real-time channels

{% embed url="<https://hyperliquid.gitbook.io/hyperliquid-docs/for-developers/api/websocket/subscriptions>" %}
See Hyperliquid WebSocket API docs providing documentation for each captured channel's format
{% endembed %}

{% hint style="info" %}
Click any channel below to see [HTTP API](/api/http-api-reference.md#data-feeds-exchange) response with historical data recorded for it.
{% endhint %}

* [trades](https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2025-01-01\&filters=\[{%22channel%22:%22trades%22,%22symbols%22:\[%22BTC%22]}]) Trade executions stream
* [l2Book](https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2025-01-01\&filters=\[{%22channel%22:%22l2Book%22,%22symbols%22:\[%22BTC%22]}]) Order book snapshots stream. Snapshot feed, pushed on each block that is at least 0.5s since last push.
* [bbo](https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2025-07-01\&filters=\[{%22channel%22:%22bbo%22,%22symbols%22:\[%22BTC%22]}]) — available since **2025-06-26** Best bid and offer updates stream. Sent only if the BBO changes on a block.
* [activeAssetCtx](https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2025-01-01\&filters=\[{%22channel%22:%22activeAssetCtx%22}]) Perpetual asset context updates stream with funding, open interest and mark price
* [activeSpotAssetCtx](https://api.tardis.dev/v1/data-feeds/hyperliquid?from=2025-01-01\&filters=\[{%22channel%22:%22activeSpotAssetCtx%22}]) Spot asset context updates stream. Uses the same activeAssetCtx subscription type — returns WsActiveSpotAssetCtx for spot coins.

### Market data collection details

[Market data collection infrastructure](/faq/general.md#what-is-your-infrastructure-setup) for Hyperliquid is located in GCP asia-northeast1 (Tokyo, Japan).

Real-time market data is captured via **multiple WebSocket connections** to `wss://api.hyperliquid.xyz/ws`.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.tardis.dev/historical-data-details/hyperliquid.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
