Update README.md

README.md

@@ -27,9 +27,9 @@ represents a playlist and includes high-level metadata (name, owner, follower
 count), cover image URLs, JSON payloads with the full Spotify response, and
 various bookkeeping columns (status, popularity histograms, history, etc.).
 
-The dataset ships as a ready-to-use CSV (`playlists.csv`, ~9 GB) along with the
-raw dump (`playlists_full.sql`, 27 GB) and a Python extractor script
-(`export_playlists_to_csv.py`) so anyone can regenerate the CSV from source.
+The public release ships as a ready-to-use CSV (`playlists.csv`, ~9 GB) plus
+supporting documentation. The original PostgreSQL dump and extractor script are
+kept private but can be shared on request for verification purposes.
 
 > ⚠️ **Attribution + ToS**: This dataset aggregates Spotify metadata originally
 > provided via their APIs. Redistribution is offered under CC BY 4.0, but you are
@@ -40,10 +40,11 @@ raw dump (`playlists_full.sql`, 27 GB) and a Python extractor script
 
 | Path | Description |
 | --- | --- |
-| `playlists_full.sql` | Original PostgreSQL dump (27 GB) containing `INSERT` statements for every table. |
-| `export_playlists_to_csv.py` | Streaming parser that extracts only `public.playlists` rows into CSV with progress reporting and batching. |
 | `playlists.csv` | Final 91,906-row CSV (17 columns, ~9 GB) with one playlist per row. |
-| `LICENSE` | CC BY 4.0 license text covering this dataset and helper scripts. |
+| `LICENSE` | CC BY 4.0 license text covering this dataset. |
+
+> The original SQL dump and exporter script remain private. Contact the
+> maintainer if you require the raw source data for verification.
 
 ## Schema
 
@@ -69,21 +70,9 @@ raw dump (`playlists_full.sql`, 27 GB) and a Python extractor script
 
 ## Regenerating the CSV
 
-```bash
-python3 export_playlists_to_csv.py \
-  --batch-size 2000 \
-  --progress-interval 0.5
-```
-
-Arguments:
-
-- `--batch-size` (default 2000): number of rows buffered before writing to CSV.
-- `--progress-interval` (default 0.25 seconds): how often to refresh the
-  progress line.
-
-The script streams the SQL file, stops after the playlists table, and prints
-live progress (`rows`, `% of dump read`, and GiB consumed). It sets
-`csv.field_size_limit` to accommodate multi-megabyte JSON blobs.
+The private repository includes an extraction script that streams the SQL dump,
+filters the `public.playlists` table, and writes the CSV with progress
+reporting and batching. Reach out if you need access to reproduce the export.
 
 ## Loading the Dataset
 
@@ -108,7 +97,7 @@ chunked `pandas.read_csv(..., chunksize=10_000)`.
 
 1. **Create dataset repo**: `huggingface-cli repo create <namespace>/spotify-playlists-2025 --type dataset`.
 2. **Clone with Git LFS**: `GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/<namespace>/spotify-playlists-2025` then `cd` into it and run `git lfs install`.
-3. **Copy assets**: Bring over `playlists.csv`, `export_playlists_to_csv.py`, `README.md`, and `LICENSE`.
+3. **Copy assets**: Bring over `playlists.csv`, `README.md`, and `LICENSE`.
 4. **Track large files**: `git lfs track "*.csv" "*.sql"`. Commit the updated `.gitattributes`.
 5. **Push**: `git add . && git commit -m "Add Spotify playlists dataset" && git push`.
 6. **Add metadata**: The `README.md` you are reading doubles as the Hugging Face dataset card, so it will render on the hub automatically.
@@ -119,7 +108,7 @@ you want to allow full reproducibility for others.
 ## License
 
 Creative Commons Attribution 4.0 International (CC BY 4.0). See `LICENSE` for
-the full text. When using the dataset, credit “Spotify Public Playlists (Oct 2025)”
+the full text. When using the dataset, credit “Spotify Public Playlists (Nov 2025)”
 and include a link back to the Hugging Face dataset page or this repository.
 
 ## Citation
@@ -137,4 +126,4 @@ and include a link back to the Hugging Face dataset page or this repository.
 ## Contact
 
 Questions or takedown requests? Open an issue or reach out via the contact info
-on my Hugging Face profile.
+on your Hugging Face profile.