docs/huggingface_dataset_layout.md

# Hugging Face Dataset Layout

Prepared: 2026-07-02 UTC

## Goal

The Hugging Face dataset must support modular upload and modular download. The main use case is:

- upload new PMData dates as they are downloaded;
- preserve exact audit/catalog metadata;
- download only a requested date range, such as March 1-10 or the full month of March;
- avoid cloning the full repository on machines with limited disk space.

## Canonical Remote Layout

The upload script writes PMData ZIPs to:

```text
pmdata/
  series=btc-5m/
    date=2026-03-16/
      btc-5m_poly_l2_2026-03-16.zip
      btc-5m_polygon_trades_2026-03-16.zip
    date=2026-03-17/
      btc-5m_poly_l2_2026-03-17.zip
      btc-5m_polygon_trades_2026-03-17.zip
```

Metadata and documentation are stored separately:

```text
README.md
docs/
catalog/
reports/
tools/
```

This structure is intentionally date-partitioned. It makes `allow_patterns` downloads practical through `huggingface_hub.snapshot_download`.

## Download Only A Date Range

Use the helper:

```bash
python3 scripts/download_hf_pmdata_range.py \
  --repo-id <owner>/<dataset-name> \
  --series btc-5m \
  --start-date 2026-03-01 \
  --end-date 2026-03-10 \
  --data-type poly_l2 \
  --out-dir /tmp/pmdata_march_1_10
```

Download both L2 and polygon trades:

```bash
python3 scripts/download_hf_pmdata_range.py \
  --repo-id <owner>/<dataset-name> \
  --series btc-5m \
  --start-date 2026-03-01 \
  --end-date 2026-03-31 \
  --out-dir /tmp/pmdata_march
```

Print the exact Hugging Face `allow_patterns` without downloading:

```bash
python3 scripts/download_hf_pmdata_range.py \
  --repo-id <owner>/<dataset-name> \
  --series btc-5m \
  --start-date 2026-03-01 \
  --end-date 2026-03-10 \
  --data-type poly_l2 \
  --print-patterns
```

## Upload New Dates

After downloading and auditing new PMData dates, rebuild the catalog:

```bash
python3 scripts/build_dataset_catalog.py
```

Upload a specific range:

```bash
python3 scripts/upload_market_data_to_hf.py \
  --repo-id <owner>/<dataset-name> \
  --start-date 2026-04-01 \
  --end-date 2026-04-07 \
  --token-stdin
```

Upload only L2:

```bash
python3 scripts/upload_market_data_to_hf.py \
  --repo-id <owner>/<dataset-name> \
  --start-date 2026-04-01 \
  --end-date 2026-04-07 \
  --data-type poly_l2 \
  --token-stdin
```

The uploader creates or updates a private dataset repo by default. Use `--public` only if redistribution is allowed.

## Why Not Git Clone Everything?

Full Git or LFS clone is the wrong default for this workflow because the data will grow month by month. Use the Hugging Face Hub API with date-specific paths instead. Keep local data disposable:

1. Download only the dates needed for a backtest.
2. Run the backtest.
3. Delete the local date range.
4. Re-download later from the archive if needed.

## Catalog Files

The catalog is the source of truth for what exists:

```text
catalog/coverage_summary.md
catalog/market_data_catalog.json
catalog/pmdata_inventory.csv
catalog/pmdata_missing_windows.csv
catalog/dome_inventory.csv
```

`pmdata_inventory.csv` is the date log. It records series, date, data type, local path, Hugging Face path, ZIP size, row count, parquet count, and missing-file counts.

`pmdata_missing_windows.csv` records exact missing market files from short archives.