> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tilebox.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Dataset.query

```python theme={"system"}
def Dataset.query(
    *,
    collections: list[str] | list[UUID] | list[Collection] | list[CollectionInfo] | list[CollectionClient] | dict[str, CollectionClient] | None = None,
    temporal_extent: TimeIntervalLike,
    spatial_extent: SpatialFilterLike | None = None,
    skip_data: bool = False,
    show_progress: bool | Callable[[float], None] = False,
) -> xarray.Dataset
```

Query data points across one or more collections in this dataset.

If `collections` is not provided, all collections in the dataset are queried.
If no data matches the filters, an empty `xarray.Dataset` is returned.

## Parameters

<ParamField path="collections" type="list[...] | dict[str, CollectionClient] | None">
  Optional collection scope for the query.

  Supported values include:

  * A list of collection names (`list[str]`)
  * A list of collection IDs (`list[UUID]`)
  * A list of collection objects (`list[Collection]`, `list[CollectionInfo]`, `list[CollectionClient]`)
  * The dictionary returned by `dataset.collections()`

  If omitted or set to `None`, all collections in the dataset are queried.
</ParamField>

<ParamField path="temporal_extent" type="TimeIntervalLike">
  The time or time interval to query. This can be a single time scalar, a tuple of two time scalars, or a `TimeInterval` object.
</ParamField>

<ParamField path="spatial_extent" type="SpatialFilterLike | None">
  Optional spatial filter. Use this for spatial queries in spatio-temporal datasets.
</ParamField>

<ParamField path="skip_data" type="bool">
  If `True`, only required datapoint fields are returned (`time`, `id`, `ingestion_time`). Defaults to `False`.
</ParamField>

<ParamField path="show_progress" type="bool | Callable[[float], None]">
  If `True`, display a progress bar when pagination is required. You can also pass a callback to receive progress values between `0` and `1`. Defaults to `False`.
</ParamField>

## Returns

An [`xarray.Dataset`](/sdks/python/xarray) containing matching datapoints.

## Errors

<ParamField path="ValueError" type="A temporal_extent for your query must be specified">
  Raised when `temporal_extent` is not provided.
</ParamField>

<ParamField path="ValueError" type="Collection <name> not found in dataset <dataset>">
  Raised when one or more collection names do not exist in the dataset.
</ParamField>

<ParamField path="ValueError" type="Collection <id> is not part of the dataset <dataset>">
  Raised when one or more provided collection IDs/objects are not part of the dataset.
</ParamField>

<RequestExample>
  ```python Python theme={"system"}
  # query all collections in the dataset
  data = dataset.query(
      temporal_extent=("2025-04-01", "2025-05-01"),
  )

  # query selected collections by name
  data = dataset.query(
      collections=["S2A_S2MSI2A", "S2B_S2MSI2A"],
      temporal_extent=("2025-04-01", "2025-05-01"),
      show_progress=True,
  )

  # query selected collections by object
  collections = dataset.collections()
  data = dataset.query(
      collections=[collections["S2A_S2MSI2A"], collections["S2B_S2MSI2A"]],
      temporal_extent=("2025-04-01", "2025-05-01"),
      skip_data=True,
  )
  ```
</RequestExample>