--- license: cc0-1.0 language: - en tags: - hyperliquid - blockchain - rev - chain-data size_categories: - 10B/ # e.g., 2026-03-01/ ├── raw/ # native node outputs, lz4-compressed where applicable │ ├── replica_cmds/ │ │ └── / │ │ └── / │ │ └── # ~2-7 GB per file, block-range chunks │ ├── asset_ctxs/ │ │ └── .csv.lz4 │ ├── misc_events_by_block/ │ │ └── hourly// # per-hour event bundle │ └── market_data/ │ └── //l2Book/ # L2 book per symbol per window └── processed/ # derived Parquet (zstd-compressed) ├── replica_cmds/part-0000.zstd.parquet ├── asset_ctxs/part-0000.zstd.parquet ├── misc_events_by_block/part-{0000..N}.zstd.parquet └── market_data/part-0000.zstd.parquet ``` Each `processed/` directory also contains a `_manifest.json` documenting the row count, schema fingerprint, and source raw files for the Parquet output. ## Loading the processed data ```python import pandas as pd # Replica commands for a given date df = pd.read_parquet( "https://huggingface.co/datasets/xylemgroup/hyperliquid-chain-captures/resolve/main/2026-03-01/processed/replica_cmds/part-0000.zstd.parquet" ) ``` Or via `datasets`: ```python from datasets import load_dataset ds = load_dataset( "xylemgroup/hyperliquid-chain-captures", data_files="2026-03-01/processed/replica_cmds/part-0000.zstd.parquet", ) ``` ## Available dates | Date | Raw size | Processed size | Block ranges covered (replica_cmds) | |------------|-----------|----------------|-------------------------------------------------------| | 2026-03-01 | ~29.1 GB | ~4.6 GB | 909,310,000–909,330,000 and 909,615,000–909,630,000 | ## Source HyperLiquid chain replica state, captured via the official replica command logs. The raw `replica_cmds` files are the unmodified node-side output for the indicated block ranges. The `processed` Parquet files are deterministic derivations of the raw inputs — schemas and source-file lineage are recorded per-dataset in the corresponding `_manifest.json`. ## License Released under **CC0 1.0** (public domain dedication). The underlying chain data is public; this dataset is the captured form of it. No attribution required.