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name: datasets-and-io description: "Build and validate DGL datasets, CSV dataset folders, graph serialization caches, and GraphBolt OnDiskDataset handoffs." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

DGL Datasets and IO

Use this sub-skill when the task is about getting graph data into or out of DGL before model code runs.

Use When

• Creating a dgl.data.DGLDataset subclass with process(), save(), load(), and has_cache().
• Loading a folder of CSV node, edge, and graph files with dgl.data.CSVDataset.
• Fixing meta.yaml, feature parsing, split masks, graph-level labels, or cache reload behavior.
• Saving/loading DGLGraph objects with dgl.save_graphs() / dgl.load_graphs() and dataset metadata with save_info() / load_info().
• Preparing a data-format handoff for GraphBolt OnDiskDataset or DGL-Go CSV ingestion.

Start Here

• Read references/workflows.md for custom dataset lifecycle, caching, serialization, CSV loading, and built-in dataset caveats.
• Read references/data-formats.md for meta.yaml schemas, CSV required columns, heterograph conventions, and OnDiskDataset metadata routing.
• Read references/troubleshooting.md when CSVDataset, cache reloads, downloads, feature dtypes, or split masks fail.
• Run python scripts/csv_dataset_linter.py DATASET_DIR before calling dgl.data.CSVDataset(DATASET_DIR) on a custom CSV folder.

Route Elsewhere

• Route raw graph construction details to ../graph-apis/ after validating files and before writing a DGLGraph manually.
• Route GraphBolt datapipes, ItemSet, ItemSampler, DataLoader, sampled minibatches, and feature fetch execution to ../dataloading-graphbolt/.
• Route partition configs and distributed training output formats to ../distributed-tools/.
• Route model layers, message passing, losses, and training loops to ../message-passing-training/.
• Route DGL-Go CLI training and CSV project commands to ../dglgo-cli/; this sub-skill only covers making the CSV folder valid enough to hand off.

Core APIs

• dgl.data.DGLDataset(name, url=None, raw_dir=None, save_dir=None, hash_key=(), force_reload=False, verbose=False, transform=None).
• dgl.data.CSVDataset(data_path, force_reload=False, verbose=True, ndata_parser=None, edata_parser=None, gdata_parser=None, transform=None).
• dgl.save_graphs(filename, g_list, labels=None, formats=None) and dgl.load_graphs(filename, idx_list=None).
• dgl.data.utils.save_info(path, info) and dgl.data.utils.load_info(path).

Safety Notes

• Keep generated dataset code independent from local checkout paths; accept raw_dir, save_dir, or a dataset folder from the caller.
• Prefer tiny local fixtures for validation; avoid downloadable built-in datasets unless the user explicitly allows network access.
• Treat CSVDataset meta.yaml, GraphBolt metadata.yaml, and distributed partition JSON/configs as separate formats with different owners.