Comments (2)
All for this. Though I do think we should mark the other formats as unstable.
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Update: we will use the ciborium crate for binary serialization:
https://crates.io/crates/ciborium
The associated format will be named "binary"
. And this will become the default format.
from polars.
Related Issues (20)
- Join result cannot be used in `with_context` for LazyFrame HOT 2
- CSE not applied for large map in `.replace_strict()` HOT 1
- polars write_excel how to cancel drop-down list HOT 1
- Parquet nested slice pushdown gives incorrect results
- pl.LazyDataFrame.slice has a buggy behaviour with non scalar columns. HOT 1
- `read_ndjson()` and `read_parquet()` behave differently when the input is a list of files with different schemas HOT 1
- pl.from_numpy produces column with null dtype when input array is empty HOT 1
- equals lacks functionality that polars.testing.assert_frame_equal has HOT 4
- Polars drops pyarrow field-level metadata HOT 2
- Turn off CSE for new streaming engine
- Reading wide parquet is 25x slower with polars than pyarrow HOT 4
- In read_csv convert too long separator, quote_char, and/or eol_char to valid char HOT 2
- Optimize for simple math? HOT 3
- read_csv on gzipped csv much slower if n_rows specified
- CSV
- Some pl.Expr aggregations missing in the Aggregation section HOT 1
- Incorrect values calculated depending on the sequence of operations HOT 3
- from_jax
- Unexpected behaviour when calling list() on a slice of a series of dtype Object
- Make `new_streaming` feature available on Rust Polars
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