README.md

---
license: cc0-1.0
pretty_name: Pfam (Current Release)
size_categories:
  - 100M<n<1B
task_categories:
  - other
language:
  - en
tags:
  - biology
  - proteins
  - domains
  - pfam
  - annotation
  - jsonl
---

# Pfam (Current Release)

Pfam-A clans and regions tables (current release), normalized to newline-delimited JSON with row-level provenance.

Processed and uploaded by the [MegaData](https://github.com/) post-download pipeline
(internal repo). Original source: <http://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/>.

## Statistics

| | |
|---|---|
| Table files | 2 |
| Total rows | 128,220,423 |
| Total bytes | 38.52 GiB (41,355,825,506) |

## Tables

| Table | Rows | Bytes |
|---|---:|---:|
| `annotation_pfam_current_release_Pfam-A.clans.tsv.gz.jsonl` | 27,480 | 7.00 MiB |
| `annotation_pfam_current_release_Pfam-A.regions.tsv.gz.jsonl` | 128,192,943 | 38.51 GiB |

## Layout

```
.
├── _MANIFEST.json                 # aggregate manifest (per-table counts)
└── tables/<source_slug>.jsonl    # normalized rows (one JSON object per line)
```

Each line in a `tables/*.jsonl` file is a JSON object with at least
`dataset_id`, `row` (the raw upstream row), `row_index`, and `source_file`
fields, so every row carries its upstream provenance.

## Loading

```bash
hf download LiteFold/Pfam --repo-type dataset --local-dir ./pfam
```

Programmatic streaming:

```python
import json
from pathlib import Path
from huggingface_hub import snapshot_download

local = snapshot_download(repo_id="LiteFold/Pfam", repo_type="dataset")
for jsonl in sorted(Path(local, "tables").glob("*.jsonl")):
    with jsonl.open() as f:
        for line in f:
            row = json.loads(line)
            ...  # row["row"] is the upstream record
```

## License

CC0 1.0 (EMBL-EBI Pfam).

## Citation

> Mistry J, et al. Pfam: The protein families database in 2021. Nucleic Acids Research, 49(D1):D412-D419, 2021.

## Provenance

Built from the local manifest entry `pfam` of `manifests/atlas_download_plan.json`.
Pipeline source: `megadata-post normalize --dataset pfam --tables-only`.