> For the complete documentation index, see [llms.txt](https://docs.mindkosh.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mindkosh.com/python-sdk/managing-tasks.md).

# Managing tasks

Once you've created a dataset and uploaded files to it, you can create a task to start annotating.

Here is how you can create a task.

```py
from mindkosh import Client, Label

labelsObjects = [
    mindkosh.Label(
        name="Pedestrian",
        color=hex_codes[0],
        sequence=1,
        attributes=[
            {
                'name': 'Age-group',
                'input_type': 'radio',
                'default_value': 'Adult',
                'mutable': False,
                'values': ['Adult', 'Child']
            }
        ]
    ),
    mindkosh.Label(name="Truck", color=hex_codes[1], sequence=2),
]

newTask = client.task.create(
    name="sample-task",
    labels=labelsObjects,
    dataset_id=datasetId,
    project_id=213,
    job_modes=['validation','qc'],
    batches=3,
    tags=['tag1'],
)
```

### Label properties

<table><thead><tr><th width="183">Property</th><th width="188">Type</th><th width="110">Required</th><th>Description</th></tr></thead><tbody><tr><td><code>name</code></td><td>string</td><td>Yes</td><td>Name of the task.</td></tr><tr><td><code>color</code></td><td>string</td><td>Yes</td><td>Color of the label in hex string.</td></tr><tr><td><code>sequence</code></td><td>integer</td><td>Yes</td><td>Order in which the label will appear.</td></tr><tr><td><code>track</code></td><td>boolean</td><td>No</td><td>Whether this label should be tracked across frames.</td></tr><tr><td><code>lock_dimenions</code></td><td>boolean</td><td>No</td><td>Only for tracked labels in Point cloud tasks. If set to true, the dimensions of an object stay the same across all frames. </td></tr><tr><td><code>type</code></td><td><code>non_mask</code> (default), <code>semantic_mask</code> or <code>instance_mask</code></td><td>No</td><td>Whether the label is a Segmentation label.</td></tr><tr><td><code>attributes</code></td><td>array of dictionaries</td><td>No</td><td>See the attributes section below.</td></tr></tbody></table>

#### Label attributes (properties)

Mindkosh supports the following types of attributes:

**Radio button**\
Specify a range of choices from which the labeler can choose only 1.

```py
{
    'name': 'Occlusion',
    'input_type': 'radio',
    'default_value': '0',
    'sequence': 1 ### Similar to label sequence, this specifies the order in which the property appears.
    'mutable': True, ### Only applicable to tracked labels. Can this attribute change from frame to frame?
    'values': ['0', '1', '2']
}
```

**Checkbox**\
Specify an attribute that can take on 2 values - `True` or `False`&#x20;

```py
{
    'name': 'Standing',
    'input_type': 'checkbox',
    'default_value': True,
    'sequence': 1 ### Similar to label sequence, this specifies the order in which the property appears.
    'mutable': True, ### Only applicable to tracked labels. Can this attribute change from frame to frame?
    'values' : ['true']
}
```

**Text**\
Enter freeform text. Can be used for OCR as well.

**Number**

### Task parameters

<table><thead><tr><th width="183">Property</th><th width="188">Type</th><th width="110">Required</th><th>Description</th></tr></thead><tbody><tr><td><code>name</code></td><td>string</td><td>Yes</td><td>Name of the task</td></tr><tr><td><code>labels</code></td><td>array of <code>Label</code> objects</td><td>Yes</td><td>Labels </td></tr><tr><td><code>dataset_id</code></td><td>integer</td><td>Yes</td><td>Dataset ID of the dataset from which to create the task.</td></tr><tr><td><code>tags</code></td><td>array of strings</td><td>No</td><td>Create a task from the dataset files that have the specified tags</td></tr><tr><td><code>project_id</code></td><td>integer</td><td>No</td><td>Project ID of an existing project in which this task will be placed.</td></tr><tr><td><code>job_mode</code></td><td><code>['validation']</code> or<br><code>['validation', 'qc']</code></td><td>No</td><td>What annotation modes will be present in the task. By default only the annotation is present.</td></tr><tr><td><code>batches</code></td><td>integer</td><td>No</td><td>How many batches should the task data be divided into</td></tr></tbody></table>