Tpt commented on code in PR #9439:
URL: https://github.com/apache/arrow-rs/pull/9439#discussion_r2955818325
##########
arrow-pyarrow/src/lib.rs:
##########
@@ -606,21 +595,52 @@ impl FromPyArrow for Table {
/// Convert a [`Table`] into `pyarrow.Table`.
impl IntoPyArrow for Table {
fn into_pyarrow(self, py: Python) -> PyResult<Bound<PyAny>> {
- let module = py.import(intern!(py, "pyarrow"))?;
- let class = module.getattr(intern!(py, "Table"))?;
-
let py_batches = PyList::new(py,
self.record_batches.into_iter().map(PyArrowType))?;
let py_schema = PyArrowType(Arc::unwrap_or_clone(self.schema));
let kwargs = PyDict::new(py);
kwargs.set_item("schema", py_schema)?;
- let reader = class.call_method("from_batches", (py_batches,),
Some(&kwargs))?;
+ let reader = table_class(py)?.call_method("from_batches",
(py_batches,), Some(&kwargs))?;
Ok(reader)
}
}
+fn array_class(py: Python<'_>) -> PyResult<&Bound<'_, PyType>> {
+ static TYPE: PyOnceLock<Py<PyType>> = PyOnceLock::new();
+ TYPE.import(py, "pyarrow", "Array")
Review Comment:
Thank you! I just ran a benchmark by curiosity. Here is the result:
```
import_direct time: [272.33 ns 274.23 ns 276.52 ns]
Found 4 outliers among 100 measurements (4.00%)
1 (1.00%) high mild
3 (3.00%) high severe
import_intern time: [206.61 ns 207.60 ns 208.84 ns]
Found 8 outliers among 100 measurements (8.00%)
6 (6.00%) high mild
2 (2.00%) high severe
import_static time: [1.3524 ns 1.3578 ns 1.3648 ns]
Found 17 outliers among 100 measurements (17.00%)
4 (4.00%) high mild
13 (13.00%) high severe
```
the three benchmarks import `uuid.UUID`.
- `import_direct` uses `Python::import()?.getattr()`
- `import_intern` uses `Python::import(intern!())?.getattr(intern!())` to
avoid always allocating the strings `"uuid"` and `"UUID"`
- `import_static` uses `PyOnceLock::import`
-
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