Querying individual datapoints by ID

If you already know the ID of the datapoint you want to query, you can fetch it directly without needing to construct and execute a broader query. You can query a datapoint ID either in only specific collection of a dataset, a selected set of collections of a dataset, or from all collections of a dataset at once.

Python

datapoint_id = "0197a491-1520-102f-48f4-f087d6ef8603"

# query in all collections of a dataset
datapoint = dataset.find(datapoint_id)

# query in selected collections of a dataset
datapoint = dataset.find(
    datapoint_id,
    collections=["S2A_S2MSI2A", "S2B_S2MSI2A"],
)

# query in a single collection
datapoint = dataset.collection("S2A_S2MSI2A").find(
    datapoint_id
)

print(datapoint)

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Go

datapointID := uuid.MustParse("0197a491-1520-102f-48f4-f087d6ef8603")

// query in all collections of a dataset
var datapoint v1.Sentinel2Msi
err = client.Datapoints.GetInto(ctx,
  dataset.ID,
  datapointID,
  &datapoint,
)
if err != nil {
  log.Fatalf("Failed to query datapoint: %v", err)
}

collectionA, err := client.Collections.Get(ctx, dataset.ID, "S2A_S2MSI2A")
if err != nil {
  log.Fatalf("Failed to get collection: %v", err)
}

collectionB, err := client.Collections.Get(ctx, dataset.ID, "S2B_S2MSI2A")
if err != nil {
  log.Fatalf("Failed to get collection: %v", err)
}

// query in selected collections of a dataset
var datapointFromSelectedCollections v1.Sentinel2Msi
err = client.Datapoints.GetInto(ctx,
  dataset.ID,
  datapointID,
  &datapointFromSelectedCollections,
  datasets.WithCollectionIDs(collectionA.ID, collectionB.ID),
)
if err != nil {
  log.Fatalf("Failed to query datapoint: %v", err)
}

// query in a single collection
var datapointFromSingleCollection v1.Sentinel2Msi
err = client.Datapoints.GetInto(ctx,
  dataset.ID,
  datapointID,
  &datapointFromSingleCollection,
  datasets.WithCollectionIDs(collectionA.ID),
)
if err != nil {
  log.Fatalf("Failed to query datapoint: %v", err)
}

fmt.Println(protojson.Format(&datapoint))

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Output

Python

<xarray.Dataset> Size: 443B
Dimensions:                ()
Coordinates:
    time                   datetime64[ns] 8B 2025-06-25T00:51:01.024000
Data variables: (12/23)
    id                     <U36 144B '0197a491-1520-102f-48f4-f087d6ef8603'
    ingestion_time         datetime64[ns] 8B 2025-06-25T05:33:11.104000
    geometry               object 8B POLYGON ((156.090908 48.709728, 155.7188...
    granule_name           object 8B 'S2A_MSIL2A_20250625T005101_N0511_R045_T...
    processing_level       uint8 1B 5
    product_type           object 8B 'S2MSI2A'
    ...                     ...
    thumbnail              object 8B 'https://catalogue.dataspace.copernicus....
    cloud_cover            float64 8B 87.38
    resolution             int64 8B 0
    flight_direction       uint8 1B 2
    acquisition_mode       uint8 1B 20
    mission_take_id        object 8B 'GS2A_20250625T005101_052266_N05.11'

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Go

{
  "time": "2025-06-25T00:51:01.024Z",
  "id": {
    "uuid": "AZekkRUgEC9I9PCH1u+GAw=="
  },
  "ingestionTime": "2025-06-25T05:33:11.104Z",
  "geometry": {
    "wkb": "AQMAACDmEAAAAQAAAAoAAAA83uS36IJjQBqH+l3YWkhA+ptQiAB3Y0CmYmNeR1xIQGfROxVwdWNA58OzBBnlR0DAB69d2nZjQIQqNXug8UdABhN/FPV4Y0AwLH++LQRIQCxEh8ARe2NAhEpcx7gWSEC+UMB2MH1jQCZuFcRAKUhAxVkRNVF/Y0Cs4LchxjtIQE6AYflzgWNABAMIH0pOSEA83uS36IJjQBqH+l3YWkhA"
  },
  "granuleName": "S2A_MSIL2A_20250625T005101_N0511_R045_T56UQU_20250625T033500.SAFE",
  "processingLevel": "PROCESSING_LEVEL_L2A",
  "productType": "S2MSI2A",
  "copernicusId": {
    "uuid": "+gUdtyZrQnapFVrQjnUKUw=="
  },
  "platform": "S2A",
  "orbitNumber": "52266",
  "relativeOrbitNumber": "45",
  "processingBaseline": 5.11,
  "stopTime": "2025-06-25T00:51:01.024Z",
  "centroid": {
    "wkb": "AQEAACDmEAAAmRmrzXB6Y0ATN84DLTRIQA=="
  },
  "published": "2025-06-25T04:29:22.500212Z",
  "updated": "2025-06-25T04:29:22.500212Z",
  "location": "/eodata/Sentinel-2/MSI/L2A/2025/06/25/S2A_MSIL2A_20250625T005101_N0511_R045_T56UQU_20250625T033500.SAFE",
  "fileSize": "118828098",
  "thumbnail": "https://catalogue.dataspace.copernicus.eu/get-object?path=/Sentinel-2/MSI/L2A/2025/06/25/S2A_MSIL2A_20250625T005101_N0511_R045_T56UQU_20250625T033500.SAFE/S2A_MSIL2A_20250625T005101_N0511_R045_T56UQU_20250625T033500-ql.jpg",
  "cloudCover": 87.384349,
  "resolution": "0",
  "flightDirection": "FLIGHT_DIRECTION_DESCENDING",
  "acquisitionMode": "ACQUISITION_MODE_NOBS",
  "missionTakeId": "GS2A_20250625T005101_052266_N05.11"
}

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You can also set the skip_data parameter when calling find to query only the required fields of the data point, same as for query.

Checking if a datapoint exists

find returns an error if the specified datapoint does not exist. You can use this to check if a datapoint exists or not.

Python

from tilebox.datasets.sync.dataset import NotFoundError

datapoint_id = "0197a47f-a830-1160-6df5-61ac723dae17"  # doesn't exist

try:
    dataset.find(datapoint_id)
    exists = True
except NotFoundError:
    exists = False

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Go

datapointID := uuid.MustParse("0197a47f-a830-1160-6df5-61ac723dae17")

exists := true
var datapoint v1.Sentinel2Msi
err = client.Datapoints.GetInto(ctx,
  dataset.ID,
  datapointID,
  &datapoint,
)
if err != nil {
  if connect.CodeOf(err) == connect.CodeNotFound {
      exists = false
  } else {
    log.Fatalf("Failed to query datapoint: %v", err)
  }
}

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