# Labeling Jobs

## Introduction

In this tutorial you will learn how to manage `Labeling Jobs` using Supervisely SDK and API.

📗 Everything you need to reproduce [this tutorial is on GitHub](https://github.com/supervisely-ecosystem/automation-with-python-sdk-and-api/tree/master/examples/labeling-jobs-automation): source code and demo data.

## How to debug this tutorial

**Step 1.** Prepare `~/supervisely.env` file with credentials. [Learn more here.](https://developer.supervisely.com/getting-started/basics-of-authentication#how-to-use-in-python)

**Step 2.** Clone [repository](https://github.com/supervisely-ecosystem/automation-with-python-sdk-and-api) with source code and demo data and create [Virtual Environment](https://docs.python.org/3/library/venv.html).

```bash
git clone https://github.com/supervisely-ecosystem/automation-with-python-sdk-and-api
cd automation-with-python-sdk-and-api
./create_venv.sh
```

**Step 3.** Open repository directory in Visual Studio Code.

```bash
code -r .
```

**Step 4.** change ✅ IDs ✅ in `local.env` file by copying the IDs from Supervisely instance.

* Change Team ID in `local.env` file by copying the ID from the context menu of the team.

  ```python
  TEAM_ID=8                 # ⬅️ change it
  ```

  <figure><img src="https://user-images.githubusercontent.com/48913536/194878720-c7754e91-1475-493c-9cdd-19a9e4cc8713.png" alt=""><figcaption></figcaption></figure>
* Get [**Lemons (Test)**](https://ecosystem.supervise.ly/projects/lemons-test) project from ecosystem. Lemons (Test) is an example project with 6 images of lemons and kiwi fruits.

<figure><img src="https://user-images.githubusercontent.com/48913536/194888410-0e505e58-8221-43c0-9d1c-2b86a9eeb922.png" alt=""><figcaption></figcaption></figure>

Change project id in `local.env` file by copying the ID from the context menu of the project.

```python
PROJECT_ID=5555                 # ⬅️ change it
```

<figure><img src="https://user-images.githubusercontent.com/48913536/194878729-9fff5bac-f470-4eee-8149-6f2e077aa48c.png" alt=""><figcaption></figcaption></figure>

* Change User ID and user login in `local.env` to your own from Team members page.

  ```python
  USER_ID=7                 # ⬅️ change it
  USER_LOGIN="my_username"  # ⬅️ change it
  ```

  <figure><img src="https://user-images.githubusercontent.com/48913536/194878737-5d1f6650-99f2-4e87-b731-58f8027ae1b7.png" alt=""><figcaption></figcaption></figure>

**Step 5.** Start debugging `examples/labeling-jobs-automation/main.py`

## Labeling Jobs automation

### Import libraries

```python
import os
from dotenv import load_dotenv
import supervisely as sly
```

### Init API client

​Init API for communicating with Supervisely Instance. First, we load environment variables with credentials:

```python
if sly.is_development():
    load_dotenv("local.env")
    load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api.from_env()
```

### Get your IDs and username from environment

```python
TEAM_ID = sly.env.team_id()
PROJECT_ID = sly.env.project_id()
USER_ID = sly.env.user_id()
USER_LOGIN = sly.env.user_login()
```

### Prepare project for Labeling Job

Function will populate project meta with classes: "kiwi", "lemon", and tags: "size", "origin".

```python
prepare_project(api=api, id=PROJECT_ID)
```

| [![](https://user-images.githubusercontent.com/48913536/194885404-5215aef1-dccc-45ec-8226-f4fbf40b1eba.png)](https://user-images.githubusercontent.com/48913536/194885404-5215aef1-dccc-45ec-8226-f4fbf40b1eba.png) | [![](https://user-images.githubusercontent.com/48913536/194885409-f60e7135-cce3-4413-b636-17689deb76ab.png)](https://user-images.githubusercontent.com/48913536/194885409-f60e7135-cce3-4413-b636-17689deb76ab.png) |
| :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |

## Labeling jobs automation

### Step 1. Create and add annotators to the team, before creating Labeling Job

<figure><img src="https://user-images.githubusercontent.com/48913536/194878748-c0710394-d821-407a-9379-42999135c5f5.png" alt=""><figcaption></figcaption></figure>

Create accounts for annotators with restrictions.

**Note:** Creating users requires admin permission.

```python
labeler_1 = api.user.get_info_by_login(login='labeler_1')
if labeler_1 is None:
    labeler_1 = api.user.create(login='labeler_1', password='11111abc', is_restricted=True)

labeler_2 = api.user.get_info_by_login(login='labeler_2')
if labeler_2 is None:
    labeler_2 = api.user.create(login='labeler_2', password='22222abc', is_restricted=True)
```

Labelers will be able to login only after being added to at least one team

**Note:** Adding users to the Team requires admin permission.

```python
if api.user.get_team_role(labeler_1.id, TEAM_ID) is None:
    api.user.add_to_team(labeler_1.id, TEAM_ID, api.role.DefaultRole.ANNOTATOR)
if api.user.get_team_role(labeler_2.id, TEAM_ID) is None:
    api.user.add_to_team(labeler_2.id, TEAM_ID, api.role.DefaultRole.ANNOTATOR)
```

<figure><img src="https://user-images.githubusercontent.com/48913536/194878766-f96f3ae0-cfc5-41b0-b973-e23e40338399.png" alt=""><figcaption></figcaption></figure>

### Step 2. Define project and datasets for labeling job

```python
project_meta_json = api.project.get_meta(PROJECT_ID)
project_meta = sly.ProjectMeta.from_json(project_meta_json)
print(project_meta)
```

Output:

```
ProjectMeta:
Object Classes
+-------+--------+----------------+--------+
|  Name | Shape  |     Color      | Hotkey |
+-------+--------+----------------+--------+
|  kiwi | Bitmap |  [208, 2, 27]  |        |
| lemon | Bitmap | [80, 227, 194] |        |
+-------+--------+----------------+--------+
Tags
+--------+--------------+------------------------------+--------+---------------+--------------------+
|  Name  |  Value type  |       Possible values        | Hotkey | Applicable to | Applicable classes |
+--------+--------------+------------------------------+--------+---------------+--------------------+
| origin |  any_string  |             None             |        |  objectsOnly  | ['kiwi', 'lemon']  |
|  size  | oneof_string | ['small', 'medium', 'large'] |        |  objectsOnly  | ['kiwi', 'lemon']  |
+--------+--------------+------------------------------+--------+---------------+--------------------+
```

```python
datasets = api.dataset.get_list(project.id)
print(datasets)
```

Output:

```
[
  DatasetInfo(
    id=10555, 
    name='ds1',
    description='', 
    size='1277440',
    project_id=5555,
    images_count=6, 
    created_at='2022-10-18T15:39:57.377Z',
    updated_at='2022-10-18T15:39:57.377Z'
  )
]
```

### Step 3. Create Labeling Jobs

<figure><img src="https://user-images.githubusercontent.com/48913536/194878773-a898f358-d224-4fda-82af-a52dab4a3ad0.png" alt=""><figcaption></figcaption></figure>

Create labeling job for labeler 1, and assign class lemon to label.

```python
created_jobs = api.labeling_job.create(name='labeler1_lemons_task',
                                       dataset_id=datasets[0].id,
                                       user_ids=[labeler_1.id],
                                       readme='annotation manual for fruits in markdown format here (optional)',
                                       description='short description is here (optional)',
                                       classes_to_label=["lemon"])
print(created_jobs)
```

Output:

```
[
  LabelingJobInfo(
      id=1, 
      name='labeler1_lemons_task', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=7,
      created_by_login='my_username', 
      assigned_to_id=101, 
      assigned_to_login='labeler_1',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=[],
      tags_to_label=[], 
      images_range=(None, None), 
      objects_limit_per_image=None, 
      tags_limit_per_image=None,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
        {
          'reviewStatus': 'none', 
          'id': 3882702, 
          'name': 'IMG_8144.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882697, 
          'name': 'IMG_4451.jpeg'
        },
        {
          'reviewStatus': 'none',
          'id': 3882698,
          'name': 'IMG_3861.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882700, 
          'name': 'IMG_2084.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882701, 
          'name': 'IMG_1836.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882699,
          'name': 'IMG_0748.jpeg'
        }
      ]
  )
]
```

You can stop Labeling Job if you need. Job will become unavailable for labeler.

```python
api.labeling_job.stop(created_jobs[0].id)
```

Create labeling job for labeler 2, and assign class kiwi to label, and also tags "size" and "origin", with objects and tags limit. You can also specify which images to label by providing images ids.

List all images in dataset and get their IDs. As an example we will select only half of images in the dataset.

```python
dataset_images_infos = api.image.get_list(dataset_id=datasets[0].id)
dataset_images_ids = [image_info.id for image_info in dataset_images_infos]
selected_images_ids = dataset_images_ids[:len(dataset_images_ids) // 2]
```

```python
created_jobs = api.labeling_job.create(
                                name='labeler2_kiwi_task_with_complex_settings',
                                dataset_id=datasets[0].id,
                                user_ids=[labeler_2.id],
                                readme='annotation manual for fruits in markdown format here (optional)',
                                description='short description is here (optional)',
                                classes_to_label=["kiwi"],
                                objects_limit_per_image=10,
                                tags_to_label=["size", "origin"],
                                tags_limit_per_image=20,
                                images_ids=selected_images_ids
                                )
print(created_jobs)
```

Output:

```
[
  LabelingJobInfo(
      id=2, 
      name='labeler2_kiwi_task_with_complex_settings', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=100,
      created_by_login='my_username', 
      assigned_to_id=102, 
      assigned_to_login='labeler_2',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=["kiwi"],
      tags_to_label=["size", "origin"], 
      images_range=(None, None), 
      objects_limit_per_image=10, 
      tags_limit_per_image=20,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
          {
            'reviewStatus': 'none', 
            'id': 3882697, 
            'name': 'IMG_4451.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882698, 
            'name': 'IMG_3861.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882699, 
            'name': 'IMG_0748.jpeg'
          }
      ]
  )
]
```

<figure><img src="https://1972929262-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2ZRtnNbqSpWk5uCfyE1A%2Fuploads%2Fgit-blob-d3a324ee5edfd9c631ce9a4db1e3fa540445e48e%2Flj_created.png?alt=media" alt=""><figcaption><p>Created Labeling Jobs</p></figcaption></figure>

Get all labeling jobs in a team

```python
jobs = api.labeling_job.get_list(TEAM_ID)
print(jobs)
```

Output:

```
[
  LabelingJobInfo(
      id=1, 
      name='labeler1_lemons_task', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=7,
      created_by_login='my_username', 
      assigned_to_id=101, 
      assigned_to_login='labeler_1',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=[],
      tags_to_label=[], 
      images_range=(None, None), 
      objects_limit_per_image=None, 
      tags_limit_per_image=None,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
        {
          'reviewStatus': 'none', 
          'id': 3882702, 
          'name': 'IMG_8144.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882697, 
          'name': 'IMG_4451.jpeg'
        },
        {
          'reviewStatus': 'none',
          'id': 3882698,
          'name': 'IMG_3861.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882700, 
          'name': 'IMG_2084.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882701, 
          'name': 'IMG_1836.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882699,
          'name': 'IMG_0748.jpeg'
        }
      ]
  ),
  LabelingJobInfo(
      id=2, 
      name='labeler2_kiwi_task_with_complex_settings', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=100,
      created_by_login='my_username', 
      assigned_to_id=102, 
      assigned_to_login='labeler_2',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=["kiwi"],
      tags_to_label=["size", "origin"], 
      images_range=(None, None), 
      objects_limit_per_image=10, 
      tags_limit_per_image=20,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
          {
            'reviewStatus': 'none', 
            'id': 3882697, 
            'name': 'IMG_4451.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882698, 
            'name': 'IMG_3861.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882699, 
            'name': 'IMG_0748.jpeg'
          }
      ]
  )
]
```

### Labeling Jobs filtering

List of available filters:

* created\_by\_id
* assigned\_to\_id
* project\_id
* dataset\_id

**Note:** filters can be used in various combinations

Get all labeling jobs that were created by user 'my\_username'

**Note:** Getting UserInfo by login requires admin permission.

```python
user = api.user.get_info_by_login(USER_LOGIN)
jobs = api.labeling_job.get_list(TEAM_ID, created_by_id=user.id)
print(jobs)
```

Output

```
[
  LabelingJobInfo(
      id=1, 
      name='labeler1_lemons_task', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=7,
      created_by_login='my_username', 
      assigned_to_id=101, 
      assigned_to_login='labeler_1',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=[],
      tags_to_label=[], 
      images_range=(None, None), 
      objects_limit_per_image=None, 
      tags_limit_per_image=None,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
        {
          'reviewStatus': 'none', 
          'id': 3882702, 
          'name': 'IMG_8144.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882697, 
          'name': 'IMG_4451.jpeg'
        },
        {
          'reviewStatus': 'none',
          'id': 3882698,
          'name': 'IMG_3861.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882700, 
          'name': 'IMG_2084.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882701, 
          'name': 'IMG_1836.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882699,
          'name': 'IMG_0748.jpeg'
        }
      ]
  ),
  LabelingJobInfo(
      id=2, 
      name='labeler2_kiwi_task_with_complex_settings', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=100,
      created_by_login='my_username', 
      assigned_to_id=102, 
      assigned_to_login='labeler_2',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=["kiwi"],
      tags_to_label=["size", "origin"], 
      images_range=(None, None), 
      objects_limit_per_image=10, 
      tags_limit_per_image=20,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
          {
            'reviewStatus': 'none', 
            'id': 3882697, 
            'name': 'IMG_4451.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882698, 
            'name': 'IMG_3861.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882699, 
            'name': 'IMG_0748.jpeg'
          }
      ]
  )
]
```

Get all labeling jobs that were created by user "my\_username" and were assigned to labeler 2

```python
jobs = api.labeling_job.get_list(TEAM_ID, created_by_id=user.id, assigned_to_id=labeler_2.id)
print(jobs)
```

Output:

```
[
  LabelingJobInfo(
      id=2, 
      name='labeler2_kiwi_task_with_complex_settings', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=100,
      created_by_login='my_username', 
      assigned_to_id=102, 
      assigned_to_login='labeler_2',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=["kiwi"],
      tags_to_label=["size", "origin"], 
      images_range=(None, None), 
      objects_limit_per_image=10, 
      tags_limit_per_image=20,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
          {
            'reviewStatus': 'none', 
            'id': 3882697, 
            'name': 'IMG_4451.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882698, 
            'name': 'IMG_3861.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882699, 
            'name': 'IMG_0748.jpeg'
          }
      ]
  )
]
```

Get all active labeling jobs in a team

```python
jobs = api.labeling_job.get_list(TEAM_ID)
print(jobs)
```

Output:

```
[
  LabelingJobInfo(
      id=1, 
      name='labeler1_lemons_task', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=7,
      created_by_login='my_username', 
      assigned_to_id=101, 
      assigned_to_login='labeler_1',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=[],
      tags_to_label=[], 
      images_range=(None, None), 
      objects_limit_per_image=None, 
      tags_limit_per_image=None,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
        {
          'reviewStatus': 'none', 
          'id': 3882702, 
          'name': 'IMG_8144.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882697, 
          'name': 'IMG_4451.jpeg'
        },
        {
          'reviewStatus': 'none',
          'id': 3882698,
          'name': 'IMG_3861.jpeg'
        }, 
        {
          'reviewStatus': 'none', 
          'id': 3882700, 
          'name': 'IMG_2084.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882701, 
          'name': 'IMG_1836.jpeg'
        }, 
        {
          'reviewStatus': 'none',
          'id': 3882699,
          'name': 'IMG_0748.jpeg'
        }
      ]
  ),
  LabelingJobInfo(
      id=2, 
      name='labeler2_kiwi_task_with_complex_settings', 
      readme='annotation manual for fruits in markdown format here (optional)',
      description='short description is here (optional)', 
      team_id=8,
      workspace_id=349,
      workspace_name='Testing Workspace', 
      project_id=5555,
      project_name='Lemons (Test)', 
      dataset_id=10555,
      dataset_name='ds1', 
      created_by_id=100,
      created_by_login='my_username', 
      assigned_to_id=102, 
      assigned_to_login='labeler_2',
      created_at='2022-10-05T08:42:30.588Z', 
      started_at=None, 
      finished_at=None,
      status='pending',
      disabled=False, 
      images_count=6, 
      finished_images_count=0, 
      rejected_images_count=0,
      accepted_images_count=0,
      classes_to_label=["kiwi"],
      tags_to_label=["size", "origin"], 
      images_range=(None, None), 
      objects_limit_per_image=10, 
      tags_limit_per_image=20,
      filter_images_by_tags=[], 
      include_images_with_tags=[],
      exclude_images_with_tags=[],
      entities=[
          {
            'reviewStatus': 'none', 
            'id': 3882697, 
            'name': 'IMG_4451.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882698, 
            'name': 'IMG_3861.jpeg'
          }, 
          {
            'reviewStatus': 'none', 
            'id': 3882699, 
            'name': 'IMG_0748.jpeg'
          }
      ]
  )
]
```

### Labeling Jobs Statuses

`api.labeling_job.Status.PENDING` - labeling job is created, labeler still has not started `api.labeling_job.Status.IN_PROGRESS` - labeler started, but not finished `api.labeling_job.Status.ON_REVIEW` - labeler finished his job, reviewer is in progress `api.labeling_job.Status.COMPLETED` - reviewer completed job `api.labeling_job.Status.STOPPED` - job was stopped at some stage

```python
job_id = jobs[-2].id
api.labeling_job.get_status(job_id)
```

Output

```
<Status.STOPPED: 'stopped'>
```

```python
job_id = jobs[-1].id
api.labeling_job.get_status(job_id)
```

Output:

```
<Status.PENDING: 'pending'>
```

If you want to change Labeling Job status you can use `api.labeling_job.set_status()` method

<pre class="language-python"><code class="lang-python">job_id = jobs[-1].id
<strong>api.labeling_job.set_status(id=job_id, status="completed")
</strong></code></pre>

Output:

```
<Status.COMPLETED: 'completed'>
```

The following methods will wait until labeling job will change status to the given expected status:

* Labeler has finished annotating

  ```python
  api.labeling_job.wait(job_id, target_status=api.labeling_job.Status.ON_REVIEW)
  ```
* Reviewer has finished his annotation review

  ```python
  api.labeling_job.wait(job_id, target_status=api.labeling_job.Status.COMPLETED) 
  ```

### Archive Labeling Job

Archive Labeling job by ID. Data can be retrieved after archiving.

```python
api.labeling_job.archive(jobs[0].id)
```

<figure><img src="https://1972929262-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F2ZRtnNbqSpWk5uCfyE1A%2Fuploads%2Fgit-blob-49c6393b29a709c9444c07a45ea20b000396aa3a%2Flj_archived.png?alt=media" alt=""><figcaption><p>Archived Labelling Job</p></figcaption></figure>

### Remove Labeling Jobs

Labeling job will be removed permanently.

#### Remove single Labeling Job

Remove Labeling job by ID.

```python
job_id = 278
api.labeling_job.remove(job_id)
```

#### Remove list of Labeling Jobs

Remove Labeling jobs by IDs.

```python
job_ids = [279, 280, 281]
api.labeling_job.remove_batch(job_ids)
```