README.md

---
license: cc-by-4.0
pretty_name: Chainticks Perp Data
tags:
- finance
- crypto
- defi
- trading
- parquet
- time-series
- pandas
- duckdb
- polars
- mlcroissant
task_categories:
- tabular-regression
configs:
- config_name: funding
  data_files:
  - split: train
    path: hyperliquid_chain/funding/date=*/part-*.parquet
- config_name: trades
  data_files:
  - split: train
    path: hyperliquid_chain/trades/date=*/part-*.parquet
- config_name: markets
  data_files:
  - split: train
    path: hyperliquid_chain/markets/date=*/part-*.parquet
- config_name: open_interest
  data_files:
  - split: train
    path: hyperliquid_chain/open_interest/date=*/part-*.parquet
- config_name: liquidations
  data_files:
  - split: train
    path: hyperliquid_chain/liquidations/date=*/part-*.parquet
---

# Chainticks Perp Data

Free, daily-updated perpetuals market data intended for quant research, backtesting, and market microstructure analysis.

```python
import pandas as pd

DATE = "YYYY-MM-DD"
URL = "https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/hyperliquid_chain/trades/date={DATE}/part-0000.parquet"

trades = pd.read_parquet(URL.format(DATE=DATE))  # first shard; see _manifest.json for all part files
print(trades.head())
```

This repository is initialized for **chain-derived perp DEX data**, starting with Hyperliquid. The public dataset must only contain records whose provenance is public chain/archive state, not venue REST API resale. The first production feed publishes Hyperliquid funding, trades, markets, open interest, and liquidations as partitioned Parquet under an explicit `hyperliquid_chain/` provider partition.

## Status

Initialized. Data publication starts after the Hetzner chain-derived `hyperliquid_chain` sink is live.

## Planned Layout

```text
hyperliquid_chain/
  funding/date=YYYY-MM-DD/part-0000.parquet
  trades/date=YYYY-MM-DD/part-0000.parquet
  trades/date=YYYY-MM-DD/part-0001.parquet
  markets/date=YYYY-MM-DD/part-0000.parquet
  open_interest/date=YYYY-MM-DD/part-0000.parquet
  liquidations/date=YYYY-MM-DD/part-0000.parquet
_schema.json
_manifest.json
LATEST_DATE.txt
```

## Quickstart

```python
import pandas as pd
from huggingface_hub import HfApi

repo = "Chainticks/perp-data"
date = "YYYY-MM-DD"
api = HfApi()
files = [
    path for path in api.list_repo_files(repo, repo_type="dataset")
    if path.startswith(f"hyperliquid_chain/trades/date={date}/") and path.endswith(".parquet")
]
urls = [f"https://huggingface.co/datasets/{repo}/resolve/main/{path}" for path in files]
trades = pd.concat([pd.read_parquet(url) for url in urls], ignore_index=True)
print(trades.head(), len(trades))
```

```python
import duckdb

date = "YYYY-MM-DD"
url = f"https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/hyperliquid_chain/liquidations/date={date}/part-0000.parquet"
rows = duckdb.sql("select symbol, count(*) as n from read_parquet(?) group by 1 order by 2 desc", [url]).df()
print(rows)
```

```python
import polars as pl

date = "YYYY-MM-DD"
url = f"https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/hyperliquid_chain/open_interest/date={date}/part-0000.parquet"
oi = pl.read_parquet(url)
print(oi.head())
```

## Provenance

Eligible public rows use one of these `source_kind` values:

- `on_chain_event`
- `chain_rpc`
- `hypercore_s3`

API-sourced internal research rows are intentionally excluded from this public dataset.

## Agent Prompt Snippet

```text
You can query Chainticks Perp Data directly from Hugging Face as partitioned Parquet. Use URLs shaped like:
https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/<provider>/<dataset>/date=YYYY-MM-DD/part-0000.parquet

Valid provider for v1: hyperliquid_chain.
Valid datasets: funding, trades, markets, open_interest, liquidations.
Large dates may have multiple part-*.parquet files. Read _schema.json before generating queries. Read _manifest.json for available files, row counts, and UTC time ranges.
Read LATEST_DATE.txt for the newest published UTC partition.
Only treat rows as public-source eligible when source_kind is one of: on_chain_event, chain_rpc, hypercore_s3.
```

## Machine Metadata

- Schema sidecar: `_schema.json`
- Manifest sidecar: `_manifest.json`
- Latest partition pointer: `LATEST_DATE.txt`
- Croissant metadata: `https://huggingface.co/api/datasets/Chainticks/perp-data/croissant`

Chainticks is independent and is not affiliated with, endorsed by, or sponsored by Hyperliquid Labs or any protocol whose data appears here. Protocol names are used descriptively.