README.md

metadata

title: Chainticks
emoji: 📊
colorFrom: blue
colorTo: green
sdk: static
pinned: false

Chainticks

Chainticks publishes agent-friendly crypto, perp, on-chain, and market-structure datasets for quantitative research.

The public Hugging Face datasets are designed to be easy to inspect from Python, DuckDB, Polars, pandas, and autonomous research agents. Each dataset includes:

• partitioned Parquet files
• a machine-readable _schema.json
• an append-only _manifest.json
• a LATEST_DATE.txt pointer
• source-kind provenance fields

Public Datasets

• Perp Data: Hyperliquid chain/archive-derived funding, trades, markets, open interest, and liquidations.
• Stablecoin Flows: public ERC-20 stablecoin mint, burn, and bridge-style flow rows.
• DEX Swaps: normalized public EVM swap events.
• DeFi Liquidations: normalized public liquidation events.
• MEV Tape: public relay MEV payload metadata.
• CFTC COT: normalized public-domain CFTC Commitments of Traders rows.
• Funding Divergence: derived funding-rate spread examples from publishable inputs.

Usage Pattern

import pandas as pd

date = "YYYY-MM-DD"
url = "https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/hyperliquid_chain/funding/date={date}/part-0000.parquet"
df = pd.read_parquet(url.format(date=date))
print(df.head())

Chainticks is independent and is not affiliated with the protocols, relays, venues, or agencies represented by the data.