> ## Documentation Index
> Fetch the complete documentation index at: https://docs.keywordsai.co/llms.txt
> Use this file to discover all available pages before exploring further.

# Delete Dataset

> Permanently delete a dataset and all its associated data

## Overview

The `delete()` method allows you to permanently delete a dataset and all its associated data. This action is irreversible, so use with caution.

<Warning>
  **Irreversible Action**: Deleting a dataset permanently removes all associated logs and metadata. This action cannot be undone.
</Warning>

## Method Signature

### Synchronous

```python theme={"system"}
client.datasets.delete(
    dataset_id: str,
    **kwargs
) -> bool
```

### Asynchronous

```python theme={"system"}
await client.datasets.adelete(
    dataset_id: str,
    **kwargs
) -> bool
```

## Parameters

<ParamField path="dataset_id" type="str" required>
  The unique identifier of the dataset to delete.
</ParamField>

## Returns

Returns `True` if the dataset was successfully deleted, `False` otherwise.

## Examples

### Basic Dataset Deletion

```python theme={"system"}
from keywordsai import KeywordsAI

client = KeywordsAI(api_key="your-api-key")

# Delete a dataset
dataset_id = "dataset_123456789"
success = client.datasets.delete(dataset_id)

if success:
    print(f"Dataset {dataset_id} deleted successfully")
else:
    print(f"Failed to delete dataset {dataset_id}")
```

### Safe Deletion with Confirmation

```python theme={"system"}
def delete_dataset_safely(dataset_id, confirm_name=None):
    try:
        # Get dataset information first
        dataset = client.datasets.get(dataset_id)
        
        print(f"Dataset to delete:")
        print(f"  ID: {dataset.id}")
        print(f"  Name: {dataset.name}")
        print(f"  Log Count: {dataset.log_count}")
        print(f"  Created: {dataset.created_at}")
        
        # Require name confirmation for safety
        if confirm_name and confirm_name != dataset.name:
            print(f"Error: Confirmation name '{confirm_name}' does not match dataset name '{dataset.name}'")
            return False
        
        # Perform deletion
        success = client.datasets.delete(dataset_id)
        
        if success:
            print(f"✓ Dataset '{dataset.name}' deleted successfully")
        else:
            print(f"✗ Failed to delete dataset '{dataset.name}'")
        
        return success
        
    except Exception as e:
        print(f"Error during deletion: {e}")
        return False

# Safe deletion with name confirmation
success = delete_dataset_safely(
    "dataset_123456789",
    confirm_name="Test Dataset"
)
```

### Conditional Deletion

```python theme={"system"}
def delete_if_empty(dataset_id):
    try:
        # Get dataset information
        dataset = client.datasets.get(dataset_id)
        
        # Only delete if empty
        if dataset.log_count == 0:
            success = client.datasets.delete(dataset_id)
            if success:
                print(f"Empty dataset '{dataset.name}' deleted")
            return success
        else:
            print(f"Dataset '{dataset.name}' has {dataset.log_count} logs - not deleting")
            return False
            
    except Exception as e:
        print(f"Error checking dataset: {e}")
        return False

# Delete only if empty
success = delete_if_empty("dataset_123456789")
```

### Bulk Deletion

```python theme={"system"}
def delete_multiple_datasets(dataset_ids, confirm=False):
    if not confirm:
        print("Warning: This will delete multiple datasets permanently!")
        print("Set confirm=True to proceed")
        return []
    
    results = []
    
    for dataset_id in dataset_ids:
        try:
            # Get dataset info for logging
            dataset = client.datasets.get(dataset_id)
            
            # Attempt deletion
            success = client.datasets.delete(dataset_id)
            
            result = {
                "dataset_id": dataset_id,
                "name": dataset.name,
                "success": success
            }
            
            if success:
                print(f"✓ Deleted: {dataset.name}")
            else:
                print(f"✗ Failed: {dataset.name}")
            
            results.append(result)
            
        except Exception as e:
            print(f"✗ Error with {dataset_id}: {e}")
            results.append({
                "dataset_id": dataset_id,
                "name": "Unknown",
                "success": False,
                "error": str(e)
            })
    
    # Summary
    successful = sum(1 for r in results if r["success"])
    print(f"\nDeletion Summary:")
    print(f"  Total: {len(dataset_ids)}")
    print(f"  Successful: {successful}")
    print(f"  Failed: {len(dataset_ids) - successful}")
    
    return results

# Delete multiple datasets
dataset_ids = [
    "dataset_123456789",
    "dataset_987654321",
    "dataset_555666777"
]

results
```