## Update

`gpu_droplets.autoscale.update(strautoscale_pool_id, AutoscaleUpdateParams**kwargs)  -> AutoscaleUpdateResponse`

**put** `/v2/droplets/autoscale/{autoscale_pool_id}`

To update the configuration of an existing autoscale pool, send a PUT request to
`/v2/droplets/autoscale/$AUTOSCALE_POOL_ID`. The request must contain a full representation
of the autoscale pool including existing attributes.

### Parameters

- **autoscale\_pool\_id:** `str`

- **config:** `Config`

  The scaling configuration for an autoscale pool, which is how the pool scales up and down (either by resource utilization or static configuration).

  - `AutoscalePoolStaticConfigParam`

  - `AutoscalePoolDynamicConfigParam`

- **droplet\_template:** `AutoscalePoolDropletTemplateParam`

- **name:** `str`

  The human-readable name of the autoscale pool. This field cannot be updated

### Returns

- `class AutoscaleUpdateResponse`

  - **autoscale\_pool:** `Optional[AutoscalePool]`

### Example

```python
from do_gradientai import GradientAI

client = GradientAI()
autoscale = client.gpu_droplets.autoscale.update(
    autoscale_pool_id="0d3db13e-a604-4944-9827-7ec2642d32ac",
    config={
        "target_number_instances": 2
    },
    droplet_template={
        "name": "example.com",
        "region": "nyc3",
        "size": "c-2",
        "image": "ubuntu-20-04-x64",
        "ssh_keys": ["3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"],
        "backups": True,
        "ipv6": True,
        "monitoring": True,
        "tags": ["env:prod", "web"],
        "user_data": "#cloud-config\nruncmd:\n  - touch /test.txt\n",
        "vpc_uuid": "760e09ef-dc84-11e8-981e-3cfdfeaae000",
    },
    name="my-autoscale-pool",
)
print(autoscale.autoscale_pool)
```