https://github.com/stac-utils/stac-table

https://github.com/stac-utils/stac-table

Last synced: 4 months ago
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• Host: GitHub
• URL: https://github.com/stac-utils/stac-table
• Owner: stac-utils
• License: mit
• Created: 2021-08-09T13:29:18.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2023-10-30T13:51:35.000Z (8 months ago)
• Last Synced: 2024-01-24T19:09:31.579Z (5 months ago)
• Language: Python
• Size: 214 KB
• Stars: 5
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-earthobservation-code - stac-table

README

        
# stac-table

This library generates STAC objects for tabular dataset. It uses the [`table`][table] STAC extension.

## Installation

`stac-table` is only available through GitHub right now:

```

python -m pip install git+https://github.com/TomAugspurger/stac-table

```

## Examples

Generate a STAC item from a Parquet Dataset.

```python

>>> import datetime, geopandas, pystac, stac_table

>>> # generate the sample data

>>> gdf = geopandas.read_file(geopandas.datasets.get_path("naturalearth_lowres"))

>>> gdf.to_parquet("data.parquet")

>>> # Create the template Item

>>> item = pystac.Item(

...     "naturalearth_lowres", geometry=None, bbox=None, datetime=datetime.datetime(2021, 1, 1), properties={}

... )

>>> result = stac_table.generate("data.parquet", item)

>>> result

```

The new item is updated to include the `table` STAC extension

```python

>>> result.stac_extensions

['https://stac-extensions.github.io/table/v1.0.0/schema.json',

 'https://stac-extensions.github.io/projection/v1.0.0/schema.json']

```

The updated fields are available under `properties`.

```python

>>> result.properties

{'table:columns': [{'name': 'pop_est', 'type': 'int64'},

  {'name': 'continent', 'type': 'byte_array'},

  {'name': 'name', 'type': 'byte_array'},

  {'name': 'iso_a3', 'type': 'byte_array'},

  {'name': 'gdp_md_est', 'type': 'double'},

  {'name': 'geometry', 'type': 'byte_array'}],

 'proj:epsg': 4326}

```

Finally, an Asset is added with a link to the  the dataset,

```python

>>> result.assets["data"].to_dict()

{'href': 'data.parquet',

 'type': 'application/x-parquet',

 'title': 'Dataset root',

 'roles': ['data']}

```

`stac_table` will optionally fill in some additional values in your STAC item if you pass the appropriate keywords.

* `infer_bbox`: Sets the item's `bbox` to the bounding box of the union of the geometry column's values. Relies on spatial partitions.

* `infer_geometry`: Sets the item's `geometry` to the union of the geometry column's values.

* `infer_datetime`: Sets the item's `properties.datetime` or `properties.start_datetime` and `properties.end_daetime` based on the values in the `datetime_column` column.

[table]: https://github.com/TomAugspurger/table