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Merge remote-tracking branch 'origin/main' into gatekeeper/fix-2325-1
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+20
-1
@@ -191,8 +191,27 @@ pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
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}
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// datetime.datetime is a subclass of datetime.date, so it must be checked first.
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//
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// Python's datetime.timestamp() treats *naive* datetimes as local wall time.
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// PyArrow (and therefore Lance table storage) encodes naive timestamps as
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// UTC wall-clock microseconds. Using .timestamp() for naive values therefore
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// shifts the literal by the local UTC offset on non-UTC machines, so
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// `col("ts") == lit(naive_dt)` fails against a table that holds the same
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// naive value. Fix: treat naive datetimes as UTC wall clock (match Arrow);
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// keep aware datetimes on the real .timestamp() path (correct epoch).
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if let Ok(dt) = value.cast::<PyDateTime>() {
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let ts: f64 = dt.call_method0("timestamp")?.extract()?;
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let ts: f64 = if dt.getattr("tzinfo")?.is_none() {
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// Force UTC interpretation of the naive wall clock.
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let utc = pyo3::types::PyModule::import(value.py(), "datetime")?
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.getattr("timezone")?
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.getattr("utc")?;
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let kwargs = pyo3::types::PyDict::new(value.py());
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kwargs.set_item("tzinfo", utc)?;
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let aware = dt.call_method("replace", (), Some(&kwargs))?;
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aware.call_method0("timestamp")?.extract()?
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} else {
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dt.call_method0("timestamp")?.extract()?
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};
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let micros = (ts * 1_000_000.0).round() as i64;
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return Ok(PyExpr(df_lit(ScalarValue::TimestampMicrosecond(
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Some(micros),
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@@ -1668,6 +1668,17 @@ impl Table {
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})
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}
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pub fn refresh_column_async(
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self_: PyRef<'_, Self>,
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column: String,
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) -> PyResult<Bound<'_, PyAny>> {
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let inner = self_.inner_ref()?.clone();
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future_into_py(self_.py(), async move {
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let job = inner.refresh_column_async(column).await.infer_error()?;
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Ok(crate::job::Job::new(job))
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})
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}
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pub fn add_columns_with_schema(
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self_: PyRef<'_, Self>,
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schema: PyArrowType<Schema>,
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