Fiona and Pyogrio are both libraries used for reading and writing spatial vector data formats. While they share some similarities, there are key differences in their approaches and capabilities:
1. Approach
- Fiona: Fiona is a full-featured Python library for working with OGR vector data sources. It uses a stateful approach, where data is read or written in a series of passes, allowing for more flexibility and control over the data processing. This makes it suitable for a wide range of tasks, including complex data transformations and incremental writes or appends[1].- Pyogrio: Pyogrio is an experimental approach that uses a vectorized (array-oriented) approach for reading and writing spatial vector file formats. It internally uses a numpy-oriented approach in Cython to read information about data sources and records from spatial data layers. This approach enables faster I/O operations but may be less flexible than Fiona due to its stateless nature, where all data are read or written in a single pass[1].
2. File Format Support
- Fiona: Fiona supports a wide range of file formats, including ESRI Shapefile, GeoPackage, GeoJSON, and many others. It is a general-purpose spatial format I/O library used within many projects in the Python ecosystem[1].- Pyogrio: Pyogrio specifically targets GeoPandas as an attempt to reduce the number of data transformations required to read/write data between GeoPandas GeoDataFrames and spatial file formats using Fiona. It supports GeoJSON, GeoPackage, and Shapefile formats, but its primary focus is on GeoPandas-oriented I/O operations[1][5].
3. Performance
- Fiona: Fiona is known for its flexibility and robustness but may not be optimized for performance. It is designed to handle complex data transformations and supports incremental writes or appends.- Pyogrio: Pyogrio is designed for faster I/O operations, leveraging a vectorized approach. This can result in significant performance improvements compared to Fiona, especially for large datasets[1].
4. Installation and Compatibility
- Fiona: Fiona is widely available and supports a broader range of platforms, including Windows. It is included in GeoPandas by default and can be used as the engine for reading and writing files.- Pyogrio: Pyogrio is available on Conda-forge for Linux and MacOS but not yet on PyPi due to the complexity of packaging binary dependencies for Windows. It requires compatible versions of GDAL and numpy from Conda-forge for raw I/O support and geopandas, pygeos, and their dependencies for GeoDataFrame I/O support[1].
5. Default Engine in GeoPandas
- Fiona: Fiona is currently the default engine used by GeoPandas for reading and writing files. However, GeoPandas 1.0 will switch to use Pyogrio as the default engine due to its potential for significant speedups[4].In summary, Fiona offers more flexibility and control over data processing, while Pyogrio is optimized for faster I/O operations. Fiona supports a broader range of file formats and is more widely available, but Pyogrio is designed specifically for GeoPandas-oriented I/O operations and can provide performance improvements.
Citations:[1] https://pypi.org/project/pyogrio/0.2.0/
[2] https://github.com/geopandas/geopandas/issues/2908
[3] https://discourse.pangeo.io/t/geopandas-bbox-and-mask-params-return-empty-dataframe-fiona-pyogrio-for-file-geodatabase/3011
[4] https://geopandas.org/en/stable/docs/reference/api/geopandas.read_file.html
[5] https://github.com/geopandas/pyogrio