### Install Specific SDK Version

Source: https://docs.up42.com/sdk/installation

Install a specific version of the SDK and import the library.

```shell
pip install up42-py==3.0.0 # The version you want to install
import up42
```

--------------------------------

### Install UP42 SDK

Source: https://docs.up42.com/sdk/installation

Use these commands to install the UP42 Python SDK package using either pip or conda.

```shell
pip install up42-py
```

```shell
conda install -c conda-forge up42-py
```

--------------------------------

### CQL2 Filter Examples

Source: https://docs.up42.com/developers/api-stac

Examples demonstrating how to construct CQL2 filters for various search criteria.

```APIDOC
## CQL2 Filter Examples

### Cloud Cover Less Than 20%
```json
{
  "filter": {
    "op": "<",
    "args": [
      {
        "property": "eo:cloud_cover"
      },
      20.0
    ]
  }
}
```

### Tags Contain Specific Values
```json
{
  "filter": {
    "op": "a_contains",
    "args": [
      {
        "property": "tags"
      },
      ["optical", "aerial"]
    ]
  }
}
```

### Tags Overlap Specific Values
```json
{
  "filter": {
    "op": "a_overlaps",
    "args": [
      {
        "property": "tags"
      },
      ["optical", "aerial"]
    ]
  }
}
```

### Asset ID Equals Specific Value
```json
{
  "filter": {
    "op": "=",
    "args": [
      {
        "property": "asset_id"
      },
      "b9fc2b75-f9de-46dd-a21b-320381bbb62d"
    ]
  }
}
```

### Data Product ID Not Equals Specific Value
```json
{
  "filter": {
    "op": "!=",
    "args": [
      {
        "property": "data_product_id"
      },
      "b0e4a80e-6a54-486c-ac0c-44497b602545"
    ]
  }
}
```

### Created Before Timestamp
```json
{
  "filter": {
    "op": "<",
    "args": [
      {
        "property": "created"
      },
      {
        "timestamp": "2023-06-27T00:00:00.000Z"
      }
    ]
  }
}
```

### Cloud Cover Greater Than 20%
```json
{
  "filter": {
    "op": ">",
    "args": [
      {
        "property": "eo:cloud_cover"
      },
      20.0
    ]
  }
}
```

### Datetime Less Than or Equal To Timestamp
```json
{
  "filter": {
    "op": "<=",
    "args": [
      {
        "property": "datetime"
      },
      {
        "timestamp": "2023-06-27T00:00:00.000Z"
      }
    ]
  }
}
```

### Ground Sample Distance Greater Than or Equal To Value
```json
{
  "filter": {
    "op": ">=",
    "args": [
      {
        "property": "gsd"
      },
      0.57
    ]
  }
}
```

### Tags Is Null
```json
{
  "filter": {
    "op": "isNull",
    "args": {
      "property": "tags"
    }
  }
}
```

### Combined Filter (AND)
```json
{
  "filter": {
    "op": "and",
    "args": [
      {
        "op": "<=",
        "args": [
          {
            "property": "gsd"
          },
          0.7
        ]
      },
      {
        "op": "<=",
        "args": [
          {
            "property": "eo:cloud_cover"
          },
          20.0
        ]
      }
    ]
  }
}
```

### Combined Filter (OR)
```json
{
  "filter": {
    "op": "or",
    "args": [
      {
        "op": "=",
        "args": [
          {
            "property": "constellation"
          },
          "PNEO"
        ]
      },
      {
        "op": "=",
        "args": [
          {
            "property": "collection_name"
          },
          "pneo-tasking"
        ]
      }
    ]
  }
}
```

### Combined Filter (NOT)
```json
{
  "filter": {
    "op": "not",
    "args": [
      {
        "op": "=",
        "args": [
          {
            "property": "constellation"
          },
          "PNEO"
        ]
      }
    ]
  }
}
```
```

--------------------------------

### Check installed UP42 SDK version

Source: https://docs.up42.com/sdk/release-notes

Use these commands to verify the currently installed version of the UP42 Python SDK.

```bash
pip show up42-py
```

```bash
conda search up42-py
```

--------------------------------

### KML Point Example

Source: https://docs.up42.com/data/formats

Example of a KML file defining a single point with coordinates.

```xml
<kml xmlns="http://www.opengis.net/kml/2.2">
  <Placemark>
    <Point>
      <coordinates>-73.98716020201383,40.73106717134863</coordinates>
    </Point>
  </Placemark>
</kml>
```

--------------------------------

### Order Status and SubStatus Example

Source: https://docs.up42.com/developers/api-tasking

This JSON snippet shows an example of an order's status and subStatus. The `status` is the primary indicator, while `subStatus` provides further clarification, such as waiting for a feasibility study.

```json
{
  "displayName": "Pléiades Neo over North America",
  // Other parameters
  "orderDetails": {
    "subStatus": "FEASIBILITY_WAITING_UPLOAD"
    // Other parameters
  },
  "status": "CREATED"
}
```

--------------------------------

### KML Multiple Points Example

Source: https://docs.up42.com/data/formats

Example of a KML file defining multiple points.

```xml
<kml xmlns="http://www.opengis.net/kml/2.2">
  <Placemark>
    <Point>
      <coordinates>-73.98716020201383,40.73106717134863</coordinates>
    </Point>
  </Placemark>
  <Placemark>
    <Point>
      <coordinates>-71.05828675347368,42.360262258503866</coordinates>
    </Point>
  </Placemark>
</kml>
```

--------------------------------

### Download and Preview Quicklooks

Source: https://docs.up42.com/sdk/quick-start

Download a preview image for a selected scene and display it within a notebook environment.

```python
1
import pathlib
2
from IPython.display import Image, display
3

4
# 1. Select a scene
5
first_scene = scenes[0]  # Get the first scene from your results
6

7
# 2. Create a directory to save the image
8
output_directory = pathlib.Path("downloaded_images")
9
output_directory.mkdir(exist_ok=True)
10

11
# 3. Download the quicklook
12
downloaded_file_path = first_scene.quicklook.download(output_directory)
13
print(f"Quicklook downloaded to: {downloaded_file_path}")
14

15
# 4. Display the downloaded image
16
print("\nQuicklook:")
17
display(Image(filename=downloaded_file_path, width=600))
```

--------------------------------

### Initialize STAC client

Source: https://docs.up42.com/sdk/sdk-data-management

Establishes a connection to the STAC client using the UP42 SDK.

```python
UP42_client = up42.stac_client()
```

--------------------------------

### Instantiate and Place a BatchOrderTemplate

Source: https://docs.up42.com/sdk/sdk-order-template

Create a batch order template with specific product parameters and submit the order.

```python
order_template = up42.BatchOrderTemplate(
    data_product_id="c3de9ed8-f6e5-4bb5-a157-f6430ba756da",
    display_name="Sentinel-2 over Berlin",
    features=features,
    params={
        "id": "S2B_T32UQD_20250520T102551_L2A"
    },
    tags=["sentinel-berlin"]
)

# Submit the order
order_template.place
```

--------------------------------

### Get Processing Jobs

Source: https://docs.up42.com/developers/api-processing

Retrieve information about processing jobs. You can get all jobs or a specific job using its ID.

```APIDOC
## GET /jobs

### Description
Retrieves a list of all processing jobs.

### Method
GET

### Endpoint
/jobs

### Query Parameters
- **status** (string) - Optional - Filters jobs by their status.

### Response
#### Success Response (200)
- **jobs** (array) - A list of job objects.
  - **job_id** (string) - The unique identifier for the job.
  - **status** (string) - The current status of the job (e.g., `created`, `running`, `successful`).

#### Response Example
{
  "jobs": [
    {
      "job_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
      "status": "successful"
    }
  ]
}

## GET /jobs/{job_id}

### Description
Retrieves information about a specific processing job using its ID.

### Method
GET

### Endpoint
/jobs/{job_id}

### Parameters
#### Path Parameters
- **job_id** (string) - Required - The ID of the job to retrieve.

### Response
#### Success Response (200)
- **job_id** (string) - The unique identifier for the job.
- **status** (string) - The current status of the job.

#### Response Example
{
  "job_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "status": "successful"
}
```

--------------------------------

### Search for Scenes using a Host Provider

Source: https://docs.up42.com/sdk/sdk-glossary

Demonstrates how to fetch archive collections, identify a host provider, define a search geometry, and perform a scene search with specific filters.

```python
import geojson
from itertools import islice

# Select the host
host = "oneatlas"

# Fetch catalog collections
archive_collections = up42.ProductGlossary.get_collections(
    collection_type = up42.CollectionType.ARCHIVE,
    sort_by = up42.CollectionSorting.name.asc,
)

# Find the provider matching the selected host name that's marked as a host
host_provider = next(
    (
        p
        for c in archive_collections
        for p in c.providers
        if p.name == host and getattr(p, "is_host", False)
    ),
    None,
)

# Define search geometry
geometry = {
    "type": "Polygon",
    "coordinates": [
        [
            [13.369713, 52.452327],
            [13.369713, 52.470760],
            [13.339159, 52.470760],
            [13.339159, 52.452327],
            [13.369713, 52.452327],
        ]
    ],
}

# Wrap the geometry into a GeoJSON FeatureCollection
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])

# Search for scenes using the host
scenes = host_provider.search(
    collections=["SPOT", "phr"],
    intersects=geometry,
    start_date="2022-06-01",
    end_date="2022-12-31",
    query={"cloudCoverage": {"LT": 20}},
)

# Define output
for scene in islice(scenes, 0, 5): # Print first 5 results
    print(f"- Scene ID: {scene.id}")
    print(f"  Bounding box: {scene.bbox}")
    print(f"  Geometry: {scene.geometry}")
    print(f"  Acquisition date and time: {scene.datetime}")
    print(f"  Acquisition start: {scene.start_datetime}")
    print(f"  Acquisition end: {scene.end_datetime}")
    print(f"  Constellation: {scene.constellation}")
    print(f"  Collection: {scene.collection}")
    print(f"  Cloud coverage: {scene.cloud_coverage}%")
    print(f"  Resolution: {scene.resolution} m")
    print(f"  Delivery time: {scene.delivery_time}")
    print(f"  Producer: {scene.producer}")
    print(f"  Quicklook: {scene.quicklook}\n")
```

--------------------------------

### Download an Image File

Source: https://docs.up42.com/sdk/sdk-utils

Instantiate an ImageFile object with a URL and filename, then download it to a specified directory. Ensure the output directory exists.

```python
import pathlib

# Select a URL
url = "https://storage.googleapis.com/user-storage-interstellar-prod/assets/a0d443a2-41e8-4995-8b54-a5cc4c448227"

# Define a directory to store the downloaded image
output_directory = pathlib.Path("downloaded_images")
output_directory.mkdir(exist_ok=True)

# Instantiate the file
image_file = up42.utils.ImageFile(
    url=url,
    file_name="my_mage_name"  # This will be used as the filename
)

# Download to the desired output directory
downloaded_file_path = image_file.download(output_directory=output_directory)
print(f"\nDownload finished.")
print(f"File was saved to: {downloaded_file_path}")
```

--------------------------------

### Retrieve EULA Metadata

Source: https://docs.up42.com/developers/api-eulas

Example response containing EULA metadata and the current document URL.

```json
1
{
2
  "id": "4136a5db-3753-42ea-87f5-61579e63cf41",
3
  "currentDocumentId": "79a45885-ec78-4158-ae7e-0460e480d44a",
4
  "currentDocumentUrl": "https://storage.googleapis.com/<...>/version/1.pdf",
5
  "currentDocumentCreatedAt": "2024-01-17T14:18:06.968272Z",
6
  "currentDocumentValidFrom": "2024-01-17T00:00:00Z",
7
  "currentDocumentFilename": "1.pdf",
8
  "title": "Pléiades Analytic",
9
  "description": "EULA for Pléiades Analytic",
10
  "isAccepted": true,
11
  "acceptedAt": "2024-01-19T15:10:16.263039Z",
12
  "acceptedById": "68567134-27ad-7bd7-4b65-d61adb11fc78"
13
}
```

--------------------------------

### GeoJSON FeatureCollection Point Example

Source: https://docs.up42.com/data/formats

Example of a GeoJSON FeatureCollection containing a Point feature. Ensure your GeoJSON is structured as a FeatureCollection object.

```json
{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {},
      "geometry": {
        "type": "Point",
        "coordinates": [...] 
      }
    }
  ]
}
```

--------------------------------

### GeoJSON FeatureCollection Polygon Example

Source: https://docs.up42.com/data/formats

Example of a GeoJSON FeatureCollection containing a Polygon feature. Ensure your GeoJSON is structured as a FeatureCollection object.

```json
{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {},
      "geometry": {
        "type": "Polygon",
        "coordinates": [...] 
      }
    }
  ]
}
```

--------------------------------

### SDK Overview

Source: https://docs.up42.com/sdk/geometry

Provides a general overview of the UP42 Python SDK.

```APIDOC
## SDK Overview

The overview of UP42's Python SDK.
```

--------------------------------

### KML Multiple Polygons Example

Source: https://docs.up42.com/data/formats

Example of a KML file defining multiple polygons. KML supports Z-values but they are ignored by the platform.

```xml
<kml xmlns="http://www.opengis.net/kml/2.2">
  <Placemark>
    <Polygon>
      <outerBoundaryIs>
        <LinearRing>
          <coordinates>
            -0.23813040507974392,51.468798304729745
            -0.04103438196207776,51.468798304729745
            -0.04103438196207776,51.54859446205262
            -0.23813040507974392,51.54859446205262
            -0.23813040507974392,51.468798304729745
          </coordinates>
        </LinearRing>
      </outerBoundaryIs>
    </Polygon>
  </Placemark>
  <Placemark>
    <Polygon>
      <outerBoundaryIs>
        <LinearRing>
          <coordinates>
            -2.007448902677595,52.535413959131574
            -2.007448902677595,52.4032156024264
            -1.7842843091614498,52.4032156024264
            -1.7842843091614498,52.535413959131574
            -2.007448902677595,52.535413959131574
          </coordinates>
        </LinearRing>
      </outerBoundaryIs>
    </Polygon>
  </Placemark>
</kml>
```

--------------------------------

### KML Polygon Example

Source: https://docs.up42.com/data/formats

Example of a KML file defining a single polygon with outer boundary coordinates. KML supports Z-values but they are ignored by the platform.

```xml
<kml xmlns="http://www.opengis.net/kml/2.2">
  <Placemark>
    <Polygon>
      <outerBoundaryIs>
        <LinearRing>
          <coordinates>
            -77.05788457660967,38.87253259892824
            -77.05465973756702,38.87291016281703
            -77.0531553685479,38.87053267794386
            -77.05552622493516,38.868757801256
            -77.05844056290393,38.86996206506943
            -77.05788457660967,38.87253259892824
          </coordinates>
        </LinearRing>
      </outerBoundaryIs>
    </Polygon>
  </Placemark>
</kml>
```

--------------------------------

### Fetch Tasking and Archive Collections Separately

Source: https://docs.up42.com/sdk/sdk-glossary

Demonstrates fetching tasking and archive collections independently using `ProductGlossary.get_collections`. This snippet focuses on the retrieval part, with subsequent code handling the output.

```python
# Fetch collections
tasking_collections = up42.ProductGlossary.get_collections(
    collection_type = up42.CollectionType.TASKING,
    sort_by = up42.CollectionSorting.name.asc,
)

archive_collections = up42.ProductGlossary.get_collections(
    collection_type = up42.CollectionType.ARCHIVE,
    sort_by = up42.CollectionSorting.name.asc,
)


# Define output
print(f"Tasking collections")
for collection in tasking_collections:
    print(f"    {collection.title}: {collection.name}")
    print(f"    {collection.description}\n")

print(f"Catalog collections")
for collection in archive_collections:
    print(f"    {collection.title}: {collection.name}")
    print(f"    {collection.description}\n")
```

```python
# Fetch collections
tasking_collections = up42.ProductGlossary.get_collections(
    collection_type = up42.CollectionType.TASKING,
    sort_by = up42.CollectionSorting.name.asc,
)

archive_collections = up42.ProductGlossary.get_collections(
    collection_type = up42.CollectionType.ARCHIVE,
    sort_by = up42.CollectionSorting.name.asc,
)



```

--------------------------------

### GET /get_collections

Source: https://docs.up42.com/sdk/sdk-data-management

Retrieves all STAC collections available in the storage.

```APIDOC
## GET /get_collections

### Description
Retrieves all STAC collections. Returns an iterator of Collection objects.

### Method
GET

### Response
#### Success Response (200)
- **collections** (Iterator[Collection]) - An iterator containing STAC collection objects.
```

--------------------------------

### Instantiate BatchOrderTemplate

Source: https://docs.up42.com/sdk/sdk-order-template

This snippet demonstrates how to instantiate a BatchOrderTemplate with a data product ID, display name, features, parameters, and tags.

```APIDOC
## Instantiate a BatchOrderTemplate with the given parameters

```python
order_template = up42.BatchOrderTemplate(
    data_product_id="c3de9ed8-f6e5-4bb5-a157-f6430ba756da",
    display_name="Sentinel-2 over Berlin",
    features=features,
    params={
        "id": "S2B_T32UQD_20250520T102551_L2A"
    },
    tags=["sentinel-berlin"]
)
```

## Submit the order

```python
order_template.place
```
```

--------------------------------

### POST /process

Source: https://docs.up42.com/processing/detection-buildings-spacept

Initiates the building detection process for a given input item.

```APIDOC
## POST /process

### Description
This endpoint triggers the building detection algorithm. It requires the title for the output and the absolute API path to the input data item.

### Method
POST

### Endpoint
/process

### Parameters
#### Request Body
- **inputs** (object) - Required - Contains input details for the processing job.
  - **inputs.title** (string) - Required - The title of the output data item.
  - **inputs.item** (string) - Required - The absolute API path to the input data item.

### Request Example
```json
{
  "inputs": {
    "title": "Processing imagery over Berlin",
    "item": "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/23e4567-e89b-12d3-a456-426614174000"
  }
}
```

### Response
#### Success Response (200)
- **id** (string) - The unique identifier for the processing job.
- **status** (string) - The current status of the processing job.

#### Response Example
```json
{
  "id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "status": "processing"
}
```
```

--------------------------------

### GET /orders

Source: https://docs.up42.com/sdk/sdk-order

Retrieves all orders with optional filtering capabilities.

```APIDOC
## GET /orders

### Description
Retrieves all orders, with optional filtering by workspace, type, status, sub-status, name, or tags.

### Parameters
#### Query Parameters
- **workspace_id** (str) - Optional - The workspace ID.
- **order_type** (OrderType) - Optional - The type of orders (TASKING or ARCHIVE).
- **status** (List[OrderStatus]) - Optional - List of order statuses.
- **sub_status** (List[OrderSubStatus]) - Optional - List of order sub-statuses.
- **display_name** (str) - Optional - Search term for order names.
- **tags** (List[str]) - Optional - List of tags to filter by.
- **sort_by** (SortingField) - Optional - Sorting method.

### Response
#### Success Response (200)
- **Iterator[Order]** - Returns an iterator of Order objects.

### Request Example
```python
orders = up42.Order.all(
    order_type="TASKING",
    status=["FULFILLED", "PLACED"],
    sort_by=up42.OrderSorting.status.asc
)
```
```

--------------------------------

### Instantiate Pansharpening Template

Source: https://docs.up42.com/sdk/sdk-processing-templates

Creates a pansharpening job template, optionally specifying grey weights for multispectral bands. Requires at least 3 bands if weights are manually defined.

```python
from up42 import processing_templates

# Select an item
stac_item_id = "68567134-27ad-7bd7-4b65-d61adb11fc78"

# Get the item from the STAC client
UP42_client = up42.stac_client()
stac_item = next(UP42_client.get_items(stac_item_id))

# Instantiate a Pansharpening template with grey weights
job_template = processing_templates.Pansharpening(
    title="Pansharpen item",
    item=stac_item,
    grey_weights=[
        processing_templates.GreyWeight(band="red", weight=0.04),
        processing_templates.GreyWeight(band="blue", weight=0.9),
        processing_templates.GreyWeight(band="green", weight=0.2),
    ],
)
```

--------------------------------

### GET /providers

Source: https://docs.up42.com/developers/api-glossary

Retrieves a list of all geospatial data providers.

```APIDOC
## GET /providers

### Description
Retrieves a list of all organizations that offer geospatial data (producers or hosts).

### Method
GET

### Endpoint
/providers
```

--------------------------------

### GET /geometries

Source: https://docs.up42.com/developers/api-geometries

Retrieves a list of all geometries saved in the library.

```APIDOC
## GET /geometries

### Description
Returns a list of all geometries available in the library.

### Method
GET

### Endpoint
/geometries
```

--------------------------------

### Generate Access Token Request

Source: https://docs.up42.com/developers/authentication

HTTP and cURL examples to request an access token from the authentication server.

```HTTP
POST /realms/public/protocol/openid-connect/token HTTP/1.1
Host: auth.up42.com
Content-Type: application/x-www-form-urlencoded


username=<your-email>&password=<your-password>&grant_type=password&client_id=up42-api
```

```Shell
curl --location --request POST 'https://auth.up42.com/realms/public/protocol/openid-connect/token' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'username=<your-email>' \
--data-urlencode 'password=<your-password>' \
--data-urlencode 'grant_type=password' \
--data-urlencode 'client_id=up42-api'
```

--------------------------------

### GET /data-products

Source: https://docs.up42.com/developers/api-glossary

Retrieves a list of all available data products.

```APIDOC
## GET /data-products

### Description
Retrieves a list of all data products, which are imagery types with specific processing levels and formats.

### Method
GET

### Endpoint
/data-products
```

--------------------------------

### Authenticate using a configuration file

Source: https://docs.up42.com/sdk/authentication

Use the authenticate method to load credentials from a JSON file. Optional region parameters can be specified.

```python
import up42
up42.authenticate(cfg_file="credentials.json")
```

```python
import up42
up42.authenticate(cfg_file="credentials.json", region="sa")
```

--------------------------------

### GET /collections

Source: https://docs.up42.com/developers/api-glossary

Retrieves a list of all available geospatial collections.

```APIDOC
## GET /collections

### Description
Retrieves a list of all geospatial collections available for ordering.

### Method
GET

### Endpoint
/collections
```

--------------------------------

### POST /process

Source: https://docs.up42.com/processing/detection-trees-spacept

Initiates the tree detection process. You need to provide the name ID `detection-trees-spacept` for this process.

```APIDOC
## POST /process

### Description
Initiates the tree detection process using the `detection-trees-spacept` algorithm.

### Method
POST

### Endpoint
/process

### Parameters
#### Request Body
- **inputs** (object) - Required - Contains input parameters for the process.
  - **title** (string) - Required - The title of the output data item.
  - **item** (string) - Required - The absolute API path to the input data item.

### Request Example
```json
{
  "inputs": {
    "title": "Processing imagery over Berlin",
    "item": "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/23e4567-e89b-12d3-a456-426614174000"
  }
}
```

### Response
#### Success Response (200)
- **id** (string) - The ID of the initiated process.
- **status** (string) - The current status of the process.

#### Response Example
```json
{
  "id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "status": "queued"
}
```
```

--------------------------------

### Instantiate a BatchOrderTemplate

Source: https://docs.up42.com/sdk/sdk-order-template

Creates a template instance for batch orders using a data product ID, display name, GeoJSON features, parameters, and tags.

```python
1
import geojson
2

3
# Define order geometry
13 collapsed lines
4
geometry = {
5
    "type": "Polygon",
6
    "coordinates": [[
7
        [13.369713, 52.452327],
8
        [13.369713, 52.470760],
9
        [13.339159, 52.470760],
10
        [13.339159, 52.452327],
11
        [13.369713, 52.452327]
12
    ]]
13
}
14

15
# Wrap the geometry into a GeoJSON FeatureCollection
16
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])
17

18
# Instantiate a BatchOrderTemplate with the given parameters
19
order_template = up42.BatchOrderTemplate(
20
    data_product_id="c3de9ed8-f6e5-4bb5-a157-f6430ba756da",
21
    display_name="Sentinel-2 over Berlin",
22
    features=features,
23
    params={
24
        "id": "S2B_T32UQD_20250520T102551_L2A"
25
    },
26
    tags=["sentinel-berlin"]
27
)
```

--------------------------------

### GET /jobs

Source: https://docs.up42.com/sdk/sdk-processing

Retrieves a list of all jobs with optional filtering parameters.

```APIDOC
## GET /jobs

### Description
Retrieves all jobs, with optional filtering. Returns an iterator of Job objects.

### Parameters
#### Query Parameters
- **process_id** (Optional[List[str]]) - Optional - Process IDs to filter by.
- **workspace_id** (Optional[str]) - Optional - The workspace ID.
- **status** (Optional[List[JobStatus]]) - Optional - Job statuses to filter by.
- **min_duration** (Optional[int]) - Optional - Minimum duration in seconds.
- **max_duration** (Optional[int]) - Optional - Maximum duration in seconds.
- **sort_by** (Optional[utils.SortingField]) - Optional - Sorting method.
- **ids** (Optional[List[str]]) - Optional - List of specific job IDs to retrieve.

### Request Example
```python
jobs = up42.Job.all(max_duration=500, sort_by=up42.JobSorting.process_id)
```
```