geodesic.boson.dataset.Dataset.from_tabular_data#

static Dataset.from_tabular_data(name, url=None, filepath=None, feature_limit=10000, datetime_field=None, s3_region=None, s3_endpoint=None, credential=None, crs=None, region=None, middleware={}, cache={}, tile_options={}, domain='*', category='*', type='*', **kwargs)[source]#

Create a new Dataset from a vector file in cloud storage.

This can be a Shapefile, GeoJSON Feature Collection, FlatGeobuf, and several others

Parameters:

  • name (str) – name of the Dataset to create

  • url (str | None) – the URL/URI of the data. Can be a cloud storage URI such as s3://<bucket>/key, gs://

  • filepath (str | None) – a path to a local tabular file to upload. If the file consists of multiple files (e.g. shapefiles), this be a glob pattern that matches all the files to upload

  • feature_limit (int) – the max number of features this will return per page

  • datetime_field (str | None) – if the data is time enabled, this is the name of the datetime field. The datetime field must RFC3339 formatted.

  • s3_region (str | None) – for S3 buckets, the region where the bucket is

  • s3_endpoint (str | None) – for S3 buckets, the endpoint to use (e.g. https://data.source.coop).

  • credential (str | None) – the name of the credential object needed to access this data.

  • crs (str | None) – a string coordinate reference for the data.

  • region (deprecated) – for S3 buckets, the region where the bucket is. Deprecated, use s3_region instead.

  • middleware (MiddlewareConfig | list) – configure any boson middleware to be applied to the new dataset.

  • cache (CacheConfig) – configure caching for this dataset

  • tile_options (TileOptions) – configure tile options for this dataset

  • domain (str) – domain of the resulting Dataset

  • category (str) – category of the resulting Dataset

  • type (str) – the type of the resulting Dataset

  • **kwargs – additional properties to set on the new Dataset

Returns:

a new Dataset.

Return type:

Dataset

Examples

>>> # Create a dataset from a GeoJSON file in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...    name='uscb-pop-centers',
...    url='gs://geodesic-public-data/CenPop2020_Mean_CO.geojson',
)
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
>>> ds.save()

>>> # Create a dataset from a Shapefile in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...    name='uscb-pop-centers',
...    url='gs://geodesic-public-data/CenPopShp/CenPop2020_Mean_CO.shp',
...    )
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
>>> ds.save()

>>> # Create a dataset from a GeoPackage in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...    name='uscb-pop-centers',
...    url='gs://geodesic-public-data/CenPop2020_Mean_CO.gpkg',
...    )
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
>>> ds.save()

>>> # Create a dataset from a geodatabase file in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...     name='uscb-pop-centers',
...     url='gs://geodesic-public-data/CenPop2020_Mean_CO.gdb',
...      )
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
>>> ds.save()

>>> # Create a dataset in the GML format in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...     name='uscb-pop-centers',
...     url='gs://geodesic-public-data/CenPop2020_Mean_CO.gml',
...     )
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
>>> ds.save()

>>> # Create a dataset from a FlatGeobuf file in a cloud storage bucket
>>> ds = geodesic.Dataset.from_tabular_data(
...     name='uscb-pop-centers',
...     url='gs://geodesic-public-data/CenPop2020_Mean_CO.fgb',
)
>>> ds.stage()
>>> # Staging is optional, but is a useful tool for validating configuration
...     ds.save()
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