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        "author": "Brendan C. Ward",
        "author_email": "bcward@astutespruce.com",
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        "description": "# geofeather\n\nA faster file-based format for geometries with `geopandas`.\n\nThis project capitalizes on the very fast [`feather`](https://github.com/wesm/feather) file format to store geometry (points, lines, polygons) data for interoperability with `geopandas`.\n\n## Why does this exist?\n\nThis project exists because reading and writing standard spatial formats (e.g., shapefile) in `geopandas` is slow. I was working with millions of geometries in multiple processing steps, and needed a fast way to read and write intermediate files.\n\nIn our benchmarks, we see about 5-6x faster file writes than writing from geopandas to shapefile via `.to_file()` on a `GeoDataFrame`.\n\nWe see about 2x faster reads compared to geopandas `read_file()` function.\n\n## How does it work?\n\nThe `feather` format works brilliantly for standard `pandas` data frames. In order to leverage the `feather` format, we simply convert the geometry data from `shapely` objects into Well Known Binary ([WKB](https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry)) format, and then store that column as raw bytes.\n\nWe store the coordinate reference system using JSON format in a sidecar file `.crs`.\n\n## Installation\n\n`pip install geofeather`\n\n## Usage\n\n### Write\n\nGiven an existing `GeoDataFrame` `my_gdf`, pass this into `to_geofeather`:\n\n```\nto_geofeather(my_gdf, 'test.feather')\n```\n\n### Read\n\n```\nmy_gdf = from_feather('test.feather')\n\n```\n\n## Indexes\n\nRight now, indexes are not supported in `feather` files. In order to get around this, simply reset your index before calling `to_geofeather`.\n\n\n",
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        "name": "geofeather",
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        "summary": "Fast file-based format for geometries with Geopandas",
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