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README.md
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title: Chainticks
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emoji: 📊
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# Chainticks
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Chainticks publishes agent-friendly crypto, perp, on-chain, and market-structure datasets for quantitative research.
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The public Hugging Face datasets are designed to be easy to inspect from Python, DuckDB, Polars, pandas, and autonomous research agents. Each dataset includes:
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- partitioned Parquet files
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- a machine-readable `_schema.json`
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- an append-only `_manifest.json`
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- a `LATEST_DATE.txt` pointer
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- source-kind provenance fields
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## Public Datasets
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- [Perp Data](https://huggingface.co/datasets/Chainticks/perp-data): Hyperliquid chain/archive-derived funding, trades, markets, open interest, and liquidations.
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- [Stablecoin Flows](https://huggingface.co/datasets/Chainticks/stablecoin-flows): public ERC-20 stablecoin mint, burn, and bridge-style flow rows.
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- [DEX Swaps](https://huggingface.co/datasets/Chainticks/dex-swaps): normalized public EVM swap events.
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- [DeFi Liquidations](https://huggingface.co/datasets/Chainticks/defi-liquidations): normalized public liquidation events.
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- [MEV Tape](https://huggingface.co/datasets/Chainticks/mev-tape): public relay MEV payload metadata.
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- [CFTC COT](https://huggingface.co/datasets/Chainticks/cftc-cot): normalized public-domain CFTC Commitments of Traders rows.
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- [Funding Divergence](https://huggingface.co/datasets/Chainticks/funding-divergence): derived funding-rate spread examples from publishable inputs.
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## Usage Pattern
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```python
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import pandas as pd
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date = "YYYY-MM-DD"
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url = "https://huggingface.co/datasets/Chainticks/perp-data/resolve/main/hyperliquid_chain/funding/date={date}/part-0000.parquet"
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df = pd.read_parquet(url.format(date=date))
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print(df.head())
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```
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Chainticks is independent and is not affiliated with the protocols, relays, venues, or agencies represented by the data.
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