raster-loader 0.6.1

Python library for loading GIS raster data to standard cloud-based data warehouses that don't natively support raster data.

raster-loader

Python library for loading GIS raster data to standard cloud-based data warehouses that don't natively support raster data.

Raster Loader is currently tested on Python 3.8, 3.9, 3.10, and 3.11.

Documentation

The Raster Loader documentation is available at raster-loader.readthedocs.io.

Install

pip install -U raster-loader

pip install -U raster-loader"[bigquery]"
pip install -U raster-loader"[snowflake]"

Installing from source

git clone https://github.com/cartodb/raster-loader
cd raster-loader
pip install .

Usage

There are two ways you can use Raster Loader:

• Using the CLI by running carto in your terminal
• Using Raster Loader as a Python library (import raster_loader)

CLI

After installing Raster Loader, you can run the CLI by typing carto in your terminal.

Currently, Raster Loader supports uploading raster data to BigQuery. 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.

Two commands are available:

Uploading to BigQuery

carto bigquery upload loads raster data from a local file to a BigQuery table. At a minimum, the carto bigquery upload command requires a file_path to a local raster file that can be read by GDAL and processed with rasterio. It also requires the project (the GCP project name) and dataset (the BigQuery dataset name) parameters. There are also additional parameters, such as table (BigQuery table name) and overwrite (to overwrite existing data).

For example:

carto bigquery upload \
    --file_path /path/to/my/raster/file.tif \
    --project my-gcp-project \
    --dataset my-bigquery-dataset \
    --table my-bigquery-table \
    --overwrite

This command uploads the TIFF file from /path/to/my/raster/file.tif to a BigQuery project named my-gcp-project, a dataset named my-bigquery-dataset, and a table named my-bigquery-table. If the table already contains data, this data will be overwritten because the --overwrite flag is set.

Inspecting a raster file on BigQuery

Use the carto bigquery describe command to retrieve information about a raster file stored in a BigQuery table.

At a minimum, this command requires a GCP project name, a BigQuery dataset name, and a BigQuery table name.

For example:

carto bigquery describe \
    --project my-gcp-project \
    --dataset my-bigquery-dataset \
    --table my-bigquery-table

Using Raster Loader as a Python library

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

Currently, Raster Loader supports uploading raster data to BigQuery. 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.

You can use Raster Loader to upload a local raster file to an existing BigQuery table using the rasterio_to_bigquery() function:

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.

You can also access and inspect a raster file from a BigQuery table using the bigquery_to_records() function:

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).

Development

See CONTRIBUTING.md for information on how to contribute to this project.

ROADMAP.md contains a list of features and improvements planned for future versions of Raster Loader.