Usage with Python projects

After installing Raster Loader, you can import the package into your Python project. For example:

from raster_loader import rasterio_to_bigquery, bigquery_to_records

Uploading a raster file to BigQuery

Currently, Raster Loader allows you to upload a local raster file to an existing BigQuery table using the rasterio_to_bigquery() function.

Note

Accessing BigQuery with Raster Loader requires the GOOGLE_APPLICATION_CREDENTIALS environment variable to be set to the path of a JSON file containing your BigQuery credentials. See the GCP documentation for more information.

For example:

rasterio_to_bigquery(
    file_path = 'path/to/raster.tif',
    project_id = 'my-project',
    dataset_id = 'my_dataset',
    table_id = 'my_table',
)

This function returns True if the upload was successful.

Note

To upload the raster to BigQuery in a quadbin format, set the output_quadbin parameter of rasterio_to_bigquery() to True. This option requires a GoogleMapsCompatible input raster. You can make your raster compatible by converting it with GDAL:

gdalwarp your_raster.tif -of COG -co TILING_SCHEME=GoogleMapsCompatible -co COMPRESS=DEFLATE your_compatible_raster.tif

Inspecting a raster file on BigQuery

You can also access and inspect a raster file located in a BigQuery table using the bigquery_to_records() function.

For example:

records_df = bigquery_to_records(
    project_id = 'my-project',
    dataset_id = 'my_dataset',
    table_id = 'my_table',
)

This function returns a DataFrame with some samples from the raster table on BigQuery (10 rows by default).