# TypeError: Streaming dataset does not have a known length. Use `len(dataset)` only on non-streaming datasets.

- **ID:** `huggingface/datasets-streaming-iterable-dataset-length-error`
- **Domain:** huggingface
- **Category:** type_error
- **Verification:** ai_generated
- **Fix Rate:** 90%

## Root Cause

Calling len() on a streaming (Iterable) dataset which does not support length computation because it is lazily loaded.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| datasets>=2.5.0 | active | — | — |

## Workarounds

1. **Check if the dataset is streaming with `isinstance(dataset, IterableDataset)` before calling len(). Example: `if not isinstance(dataset, IterableDataset): print(len(dataset)) else: print('Length unknown')`** (95% success)
   ```
   Check if the dataset is streaming with `isinstance(dataset, IterableDataset)` before calling len(). Example: `if not isinstance(dataset, IterableDataset): print(len(dataset)) else: print('Length unknown')`
   ```
2. **If you need the length, load the dataset non-streaming only once to get the size, then reload with streaming=True: `length = len(load_dataset('dataset_name', split='train', streaming=False)); dataset = load_dataset('dataset_name', split='train', streaming=True)`** (85% success)
   ```
   If you need the length, load the dataset non-streaming only once to get the size, then reload with streaming=True: `length = len(load_dataset('dataset_name', split='train', streaming=False)); dataset = load_dataset('dataset_name', split='train', streaming=True)`
   ```
3. **Use dataset.n_shards if available (for sharded datasets) to estimate length, or rely on the dataset's metadata if provided by the source.** (70% success)
   ```
   Use dataset.n_shards if available (for sharded datasets) to estimate length, or rely on the dataset's metadata if provided by the source.
   ```

## Dead Ends

- **** — This defeats the purpose of streaming (memory efficiency) and may cause OOM for large datasets. Also, the dataset might be too large to fit in memory. (70% fail)
- **** — These methods also rely on known length and will raise similar errors or return None. (80% fail)
- **** — This iterates through the entire dataset, which is slow and defeats streaming benefits; also, for very large datasets it may take hours or cause memory issues. (50% fail)