GeoPandas: implement read_feather
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A pull request for this has already been merged.
- #3483 by @Mayukh-D — merged
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 62/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- pandas, python
- Domain
- data, documentation
Research direction
Start with the sedona.spark.geopandas package, where read_file and read_parquet are exported, and add read_feather beside them with the geopandas signature (path, columns, to_pandas_kwargs, **kwargs). Read on the driver with GeoPandas and convert to a Sedona GeoDataFrame, keeping CRS and index. Done means a to_feather then read_feather round trip passes in tests, columns selection works, and docs/api/geopandas-coverage.md is updated. The approach is not yet confirmed by maintainers, so check with them first.
Written by the indexing model from the issue text.
Description
Part of #2230.
Implement geopandas.read_feather in sedona.spark.geopandas. The coverage reference lists it as having no implementation or public export.
Keep the geopandas signature (path, columns, to_pandas_kwargs, **kwargs) and export it next to read_file and read_parquet.
This is the reading half of GeoDataFrame.to_feather (#3364, #3455). Feather has no Spark reader, so the proposed approach is the same as the writer: read on the driver with GeoPandas and convert the result to a Sedona GeoDataFrame, preserving the CRS and index. That keeps a round trip through to_feather and read_feather working, and suits files small enough to read on one machine, which is the case Feather is used for.
Tests would cover a round trip with to_feather, the columns selection, and the index and CRS surviving the read. I would update the coverage reference as part of the change.
I'm a student contributing as part of a university software engineering course, and I'd like to take this one if the approach is acceptable.
- Dominant language
- Java
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- Merged PRs (30d)
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Getting set up
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
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- Open a pull request that references the issue number.
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