Files
lancedb/python/python/tests/test_expr.py
T
Igor Ganapolsky a075aa62f8 fix(python): treat naive lit(datetime) as UTC wall clock (#3262) (#3775)
## Summary

Fixes naive `lit(datetime)` equality filters against table timestamp
columns on non-UTC hosts, and adds the integration matrix from #3262.

## Failure (before)

On a machine in US Eastern (UTC−4 / EDT), with PyPI `lancedb==0.36.0`:

```python
from datetime import datetime
import lancedb
from lancedb.expr import col, lit

db = lancedb.connect("memory://")
ts = datetime(2024, 7, 1, 10, 0, 0)  # naive
table = db.create_table("t", [{"id": 1, "ts": ts}])
rows = table.search().where(col("ts") == lit(ts)).to_list()
# actual: []  (0 rows)
# expected: 1 row
```

### Root cause

In `python/src/expr.rs`, `expr_lit` converted every `datetime` via
Python's `.timestamp()`:

- **naive** `.timestamp()` = local wall → UTC epoch (shifted by host
offset)
- **PyArrow naive** storage = UTC wall-clock microseconds (no local
shift)

So `lit(naive)` became `CAST('2024-07-01 14:00:00' AS TIMESTAMP)` on EDT
while the table held `10:00:00`.

## After

Naive datetimes are interpreted as UTC wall clock
(`replace(tzinfo=timezone.utc).timestamp()`), matching Arrow storage.
Aware datetimes still use `.timestamp()` (correct epoch).

Same repro on this branch: **1 matching row**.

## Tests

Added `TestExprDatetimeTimezoneIntegration` covering:

| Case | Result |
|------|--------|
| both naive | match |
| both same TZ (UTC) | match |
| different TZs, same instant | match |
| table TZ + naive lit | match (wall clock) |
| table naive + aware lit | match |
| naive lit SQL is wall clock, not local-shifted | asserts `10:00:00` in
SQL |

### Verification

```bash
cd python
maturin develop
pytest python/tests/test_expr.py -v
```

**102 passed** (full `test_expr.py`, including the 6 new cases).

Closes #3262

---------

Co-authored-by: Will Jones <willjones127@gmail.com>
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-17 10:48:02 -07:00

733 lines
24 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
"""Tests for the type-safe expression builder API."""
from datetime import date, datetime, timedelta, timezone
from decimal import Decimal
import pyarrow as pa
import pytest
import lancedb
from lancedb.expr import Expr, col, func, lit
# ── unit tests for Expr construction ─────────────────────────────────────────
class TestExprConstruction:
def test_col_returns_expr(self):
e = col("age")
assert isinstance(e, Expr)
def test_lit_int(self):
e = lit(42)
assert isinstance(e, Expr)
def test_lit_float(self):
e = lit(3.14)
assert isinstance(e, Expr)
def test_lit_str(self):
e = lit("hello")
assert isinstance(e, Expr)
def test_lit_bool(self):
e = lit(True)
assert isinstance(e, Expr)
def test_lit_bytes(self):
e = lit(b"\xde\xad\xbe\xef")
assert isinstance(e, Expr)
def test_lit_bytes_empty(self):
e = lit(b"")
assert isinstance(e, Expr)
def test_lit_unsupported_type_raises(self):
with pytest.raises(Exception):
lit([1, 2, 3])
def test_func(self):
e = func("lower", col("name"))
assert isinstance(e, Expr)
assert e.to_sql() == "lower(name)"
def test_func_unknown_raises(self):
with pytest.raises(Exception):
func("not_a_real_function", col("x"))
def test_lit_date(self):
e = lit(date(2024, 1, 1))
assert isinstance(e, Expr)
def test_lit_datetime(self):
# Naive datetime
e = lit(datetime(2024, 1, 1, 10, 0))
assert isinstance(e, Expr)
def test_lit_datetime_tz(self):
# Timezone-aware datetime
tz = timezone(timedelta(hours=5))
dt = datetime(2024, 1, 1, 10, 0, tzinfo=tz)
e = lit(dt)
assert isinstance(e, Expr)
def test_lit_decimal_precision(self):
# High precision Decimal that would be rounded if converted to float
d = Decimal("1.234567890123456789")
e = lit(d)
assert isinstance(e, Expr)
class TestExprOperators:
def test_eq_operator(self):
e = col("x") == lit(1)
assert isinstance(e, Expr)
assert e.to_sql() == "(x = 1)"
def test_ne_operator(self):
e = col("x") != lit(1)
assert isinstance(e, Expr)
assert e.to_sql() == "(x <> 1)"
def test_lt_operator(self):
e = col("age") < lit(18)
assert isinstance(e, Expr)
assert e.to_sql() == "(age < 18)"
def test_le_operator(self):
e = col("age") <= lit(18)
assert isinstance(e, Expr)
assert e.to_sql() == "(age <= 18)"
def test_gt_operator(self):
e = col("age") > lit(18)
assert isinstance(e, Expr)
assert e.to_sql() == "(age > 18)"
def test_ge_operator(self):
e = col("age") >= lit(18)
assert isinstance(e, Expr)
assert e.to_sql() == "(age >= 18)"
def test_and_operator(self):
e = (col("age") > lit(18)) & (col("status") == lit("active"))
assert isinstance(e, Expr)
assert e.to_sql() == "((age > 18) AND (status = 'active'))"
def test_or_operator(self):
e = (col("a") == lit(1)) | (col("b") == lit(2))
assert isinstance(e, Expr)
assert e.to_sql() == "((a = 1) OR (b = 2))"
def test_invert_operator(self):
e = ~(col("active") == lit(True))
assert isinstance(e, Expr)
assert e.to_sql() == "NOT (active = true)"
def test_add_operator(self):
e = col("x") + lit(1)
assert isinstance(e, Expr)
assert e.to_sql() == "(x + 1)"
def test_sub_operator(self):
e = col("x") - lit(1)
assert isinstance(e, Expr)
assert e.to_sql() == "(x - 1)"
def test_mul_operator(self):
e = col("price") * lit(1.1)
assert isinstance(e, Expr)
assert e.to_sql() == "(price * 1.1)"
def test_div_operator(self):
e = col("total") / lit(2)
assert isinstance(e, Expr)
assert e.to_sql() == "(total / 2)"
def test_radd(self):
e = lit(1) + col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(1 + x)"
def test_rmul(self):
e = lit(2) * col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(2 * x)"
def test_coerce_plain_int(self):
# Operators should auto-wrap plain Python values via lit()
e = col("age") > 18
assert isinstance(e, Expr)
assert e.to_sql() == "(age > 18)"
def test_coerce_plain_str(self):
e = col("name") == "alice"
assert isinstance(e, Expr)
assert e.to_sql() == "(name = 'alice')"
def test_reflexive_comparisons(self):
# 10 < col("age") swaps to col("age") > 10
assert (10 < col("age")).to_sql() == "(age > 10)"
assert (10 <= col("age")).to_sql() == "(age >= 10)"
assert (10 > col("age")).to_sql() == "(age < 10)"
assert (10 >= col("age")).to_sql() == "(age <= 10)"
assert (10 == col("age")).to_sql() == "(age = 10)"
assert (10 != col("age")).to_sql() == "(age <> 10)"
def test_reflexive_logical(self):
# True & Expr calls Expr.__rand__(True)
assert (True & (col("age") > 18)).to_sql() == "(true AND (age > 18))"
assert (False | (col("age") > 18)).to_sql() == "(false OR (age > 18))"
class TestExprBytesLiteral:
def test_bytes_to_sql(self):
e = lit(b"\xde\xad\xbe\xef")
assert e.to_sql() == "X'DEADBEEF'"
def test_empty_bytes_to_sql(self):
e = lit(b"")
assert e.to_sql() == "X''"
def test_bytes_repr(self):
e = lit(b"\x01\x02")
assert repr(e) == "Expr(X'0102')"
def test_bytes_equality_expr_sql(self):
e = col("data") == lit(b"\xca\xfe")
assert e.to_sql() == "(data = X'CAFE')"
def test_bytes_ne_expr_sql(self):
e = col("data") != lit(b"\xff")
assert e.to_sql() == "(data <> X'FF')"
def test_bytes_compound_expr_sql(self):
e = (col("data") == lit(b"\x01")) & (col("id") > lit(5))
assert e.to_sql() == "((data = X'01') AND (id > 5))"
def test_bytes_in_function_call(self):
# Regression test: binary literals inside scalar function calls
# used to fail because DataFusion's unparser does not support Binary
# scalars. Now handled via a placeholder-substitution rewrite.
e = func("contains", col("data"), lit(b"\xff"))
assert e.to_sql() == "contains(data, X'FF')"
def test_bytes_in_not(self):
e = ~(col("data") == lit(b"\xff"))
assert e.to_sql() == "NOT (data = X'FF')"
class TestExprStringMethods:
def test_lower(self):
e = col("name").lower()
assert isinstance(e, Expr)
assert e.to_sql() == "lower(name)"
def test_upper(self):
e = col("name").upper()
assert isinstance(e, Expr)
assert e.to_sql() == "upper(name)"
def test_contains(self):
e = col("text").contains(lit("hello"))
assert isinstance(e, Expr)
assert e.to_sql() == "contains(text, 'hello')"
def test_contains_with_str_coerce(self):
e = col("text").contains("hello")
assert isinstance(e, Expr)
assert e.to_sql() == "contains(text, 'hello')"
def test_chained_lower_eq(self):
e = col("name").lower() == lit("alice")
assert isinstance(e, Expr)
assert e.to_sql() == "(lower(name) = 'alice')"
class TestExprCast:
def test_cast_string(self):
e = col("id").cast("string")
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(id AS VARCHAR)"
def test_cast_int32(self):
e = col("score").cast("int32")
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(score AS INTEGER)"
def test_cast_float64(self):
e = col("val").cast("float64")
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(val AS DOUBLE)"
def test_cast_pyarrow_type(self):
e = col("score").cast(pa.int32())
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(score AS INTEGER)"
def test_cast_pyarrow_float64(self):
e = col("val").cast(pa.float64())
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(val AS DOUBLE)"
def test_cast_pyarrow_string(self):
e = col("id").cast(pa.string())
assert isinstance(e, Expr)
assert e.to_sql() == "CAST(id AS VARCHAR)"
def test_cast_pyarrow_and_string_equivalent(self):
# pa.int32() and "int32" should produce equivalent SQL
sql_str = col("x").cast("int32").to_sql()
sql_pa = col("x").cast(pa.int32()).to_sql()
assert sql_str == sql_pa
class TestExprNamedMethods:
def test_eq_method(self):
e = col("x").eq(lit(1))
assert isinstance(e, Expr)
assert e.to_sql() == "(x = 1)"
def test_gt_method(self):
e = col("x").gt(lit(0))
assert isinstance(e, Expr)
assert e.to_sql() == "(x > 0)"
def test_and_method(self):
e = col("x").gt(lit(0)).and_(col("y").lt(lit(10)))
assert isinstance(e, Expr)
assert e.to_sql() == "((x > 0) AND (y < 10))"
def test_or_method(self):
e = col("x").eq(lit(1)).or_(col("x").eq(lit(2)))
assert isinstance(e, Expr)
assert e.to_sql() == "((x = 1) OR (x = 2))"
class TestExprRepr:
def test_repr(self):
e = col("age") > lit(18)
assert repr(e) == "Expr((age > 18))"
def test_to_sql(self):
e = col("age") > 18
assert e.to_sql() == "(age > 18)"
def test_unhashable(self):
e = col("x")
with pytest.raises(TypeError):
{e: 1}
class TestExprReflexive:
def test_reflexive_eq(self):
e = 1 == col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(x = 1)"
def test_reflexive_ne(self):
e = 1 != col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(x <> 1)"
def test_reflexive_lt(self):
# 1 < x => (x > 1)
e = 1 < col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(x > 1)"
def test_reflexive_gt(self):
# 1 > x => (x < 1)
e = 1 > col("x")
assert isinstance(e, Expr)
assert e.to_sql() == "(x < 1)"
def test_reflexive_and(self):
e = True & col("active")
assert isinstance(e, Expr)
assert e.to_sql() == "(true AND active)"
def test_reflexive_or(self):
e = False | col("inactive")
assert isinstance(e, Expr)
assert e.to_sql() == "(false OR inactive)"
# ── integration tests: end-to-end query against a real table ─────────────────
@pytest.fixture
def simple_table(tmp_path):
db = lancedb.connect(str(tmp_path))
data = pa.table(
{
"id": [1, 2, 3, 4, 5],
"name": ["Alice", "Bob", "Charlie", "alice", "BOB"],
"age": [25, 17, 30, 22, 15],
"score": [1.5, 2.0, 3.5, 4.0, 0.5],
}
)
return db.create_table("test", data)
class TestExprFilter:
def test_simple_gt_filter(self, simple_table):
result = simple_table.search().where(col("age") > lit(20)).to_arrow()
assert result.num_rows == 3 # ages 25, 30, 22
def test_compound_and_filter(self, simple_table):
result = (
simple_table.search()
.where((col("age") > lit(18)) & (col("score") > lit(2.0)))
.to_arrow()
)
assert result.num_rows == 2 # (30, 3.5) and (22, 4.0)
def test_string_equality_filter(self, simple_table):
result = simple_table.search().where(col("name") == lit("Bob")).to_arrow()
assert result.num_rows == 1
def test_or_filter(self, simple_table):
result = (
simple_table.search()
.where((col("age") < lit(18)) | (col("age") > lit(28)))
.to_arrow()
)
assert result.num_rows == 3 # ages 17, 30, 15
def test_coercion_no_lit(self, simple_table):
# Python values should be auto-coerced
result = simple_table.search().where(col("age") > 20).to_arrow()
assert result.num_rows == 3
def test_string_sql_still_works(self, simple_table):
# Backwards compatibility: plain strings still accepted
result = simple_table.search().where("age > 20").to_arrow()
assert result.num_rows == 3
class TestExprProjection:
def test_select_with_expr(self, simple_table):
result = (
simple_table.search()
.select({"double_score": col("score") * lit(2)})
.to_arrow()
)
assert "double_score" in result.schema.names
def test_select_mixed_str_and_expr(self, simple_table):
result = (
simple_table.search()
.select({"id": "id", "double_score": col("score") * lit(2)})
.to_arrow()
)
assert "id" in result.schema.names
assert "double_score" in result.schema.names
def test_select_list_of_columns(self, simple_table):
# Plain list of str still works
result = simple_table.search().select(["id", "name"]).to_arrow()
assert result.schema.names == ["id", "name"]
# ── column name edge cases ────────────────────────────────────────────────────
class TestColNaming:
"""Unit tests verifying that col() preserves identifiers exactly.
Identifiers that need quoting (camelCase, spaces, leading digits, unicode)
are wrapped in backticks to match the lance SQL parser's dialect.
"""
def test_camel_case_preserved_in_sql(self):
# camelCase is quoted with backticks so the case round-trips correctly.
assert col("firstName").to_sql() == "`firstName`"
def test_camel_case_in_expression(self):
assert (col("firstName") > lit(18)).to_sql() == "(`firstName` > 18)"
def test_space_in_name_quoted(self):
assert col("first name").to_sql() == "`first name`"
def test_space_in_expression(self):
assert (col("first name") == lit("A")).to_sql() == "(`first name` = 'A')"
def test_leading_digit_quoted(self):
assert col("2fast").to_sql() == "`2fast`"
def test_unicode_quoted(self):
assert col("名前").to_sql() == "`名前`"
def test_snake_case_unquoted(self):
# Plain snake_case needs no quoting.
assert col("first_name").to_sql() == "first_name"
@pytest.fixture
def special_col_table(tmp_path):
db = lancedb.connect(str(tmp_path))
data = pa.table(
{
"firstName": ["Alice", "Bob", "Charlie"],
"first name": ["A", "B", "C"],
"score": [10, 20, 30],
}
)
return db.create_table("special", data)
class TestColNamingIntegration:
def test_camel_case_filter(self, special_col_table):
result = (
special_col_table.search()
.where(col("firstName") == lit("Alice"))
.to_arrow()
)
assert result.num_rows == 1
assert result["firstName"][0].as_py() == "Alice"
def test_space_in_col_filter(self, special_col_table):
result = (
special_col_table.search().where(col("first name") == lit("B")).to_arrow()
)
assert result.num_rows == 1
def test_camel_case_projection(self, special_col_table):
result = (
special_col_table.search()
.select({"upper_name": col("firstName").upper()})
.to_arrow()
)
assert "upper_name" in result.schema.names
assert sorted(result["upper_name"].to_pylist()) == ["ALICE", "BOB", "CHARLIE"]
@pytest.fixture
def type_check_table(tmp_path):
"""Fixture that creates a table with Date32 and Decimal128 columns."""
db = lancedb.connect(str(tmp_path))
schema = pa.schema(
[
("date", pa.date32()),
("decimal", pa.decimal128(10, 2)),
("binary", pa.binary()),
]
)
data = pa.table(
{
"date": [date(2024, 1, 1), date(2024, 1, 2)],
"decimal": [Decimal("10.50"), Decimal("20.75")],
"binary": [b"\x01", b"\x02"],
},
schema=schema,
)
return db.create_table("extended_types", data)
class TestExtendedTypeIntegration:
"""Integration tests verifying that typed literals work correctly in filters."""
def test_date_integration(self, type_check_table):
"""Verify that Date32 literals are correctly parsed and filtered."""
result = (
type_check_table.search()
.where(col("date") == lit(date(2024, 1, 1)))
.to_arrow()
)
assert result.num_rows == 1
assert result["date"][0].as_py() == date(2024, 1, 1)
def test_decimal_integration(self, tmp_path):
"""A Decimal literal must retain full 128-bit precision in a filter.
1.234567890123456789 and 1.234567890123456790 differ only in the last
digit and are indistinguishable once truncated to f64. The filter
therefore returns the single expected row only if ``lit(Decimal)``
produces a true ``Decimal128`` scalar rather than being coerced to f64.
"""
low = Decimal("1.234567890123456789")
high = Decimal("1.234567890123456790")
db = lancedb.connect(str(tmp_path / "decimal_precision"))
schema = pa.schema([("val", pa.decimal128(19, 18))])
table = db.create_table(
"decimal_precision",
pa.table({"val": [low, high]}, schema=schema),
)
result = table.search().where(col("val") < lit(high)).to_arrow()
assert result.num_rows == 1
assert result["val"][0].as_py() == low
def test_binary_integration(self, type_check_table):
"""Verify that Binary literals are correctly filtered."""
result = (
type_check_table.search().where(col("binary") == lit(b"\x01")).to_arrow()
)
assert result.num_rows == 1
assert result["binary"][0].as_py() == b"\x01"
# ── bytes / binary column integration tests ───────────────────────────────────
@pytest.fixture
def binary_table(tmp_path):
db = lancedb.connect(str(tmp_path))
data = pa.table(
{
"id": [1, 2, 3],
"payload": pa.array(
[b"\x01\x02", b"\xca\xfe", b"\xff\x00"],
type=pa.binary(),
),
}
)
return db.create_table("binary_test", data)
class TestExprIsin:
def test_isin_ints(self):
assert col("id").isin([1, 2, 3]).to_sql() == "id IN (1, 2, 3)"
def test_isin_strs(self):
assert (
col("status").isin(["active", "pending"]).to_sql()
== "status IN ('active', 'pending')"
)
def test_isin_coerces_and_mixes(self):
assert col("id").isin([lit(1), 2]).to_sql() == "id IN (1, 2)"
def test_isin_empty(self):
assert col("id").isin([]).to_sql() == "id IN ()"
def test_isin_filter(self, simple_table):
result = simple_table.search().where(col("id").isin([1, 3, 5])).to_arrow()
assert result.num_rows == 3
class TestExprBytesIntegration:
def test_binary_equality_filter(self, binary_table):
result = (
binary_table.search().where(col("payload") == lit(b"\xca\xfe")).to_arrow()
)
assert result.num_rows == 1
assert result["id"][0].as_py() == 2
def test_binary_ne_filter(self, binary_table):
result = (
binary_table.search().where(col("payload") != lit(b"\x01\x02")).to_arrow()
)
assert result.num_rows == 2
def test_binary_compound_filter(self, binary_table):
result = (
binary_table.search()
.where((col("payload") == lit(b"\x01\x02")) | (col("id") == lit(3)))
.to_arrow()
)
assert result.num_rows == 2
# ── datetime / timezone integration for lit() (issue #3262) ──────────────────
class TestExprDatetimeTimezoneIntegration:
"""Integration coverage for lit(datetime) against table timestamp columns.
PyArrow stores naive timestamps as UTC wall-clock microseconds. Python's
datetime.timestamp() treats naive values as *local* time, which used to
shift lit(naive) by the host UTC offset and break equality filters on
non-UTC machines. These cases lock the expected semantics.
"""
def test_both_naive_match(self, tmp_path):
"""Table naive + lit naive with the same wall clock must match."""
db = lancedb.connect(str(tmp_path / "naive"))
ts = datetime(2024, 7, 1, 10, 0, 0)
table = db.create_table(
"t", [{"id": 1, "ts": ts}, {"id": 2, "ts": datetime(2024, 7, 2, 10, 0, 0)}]
)
result = table.search().where(col("ts") == lit(ts)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_both_same_timezone_match(self, tmp_path):
"""Table UTC + lit UTC for the same instant must match."""
db = lancedb.connect(str(tmp_path / "utc"))
ts = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
table = db.create_table(
"t",
pa.table(
{
"id": [1, 2],
"ts": pa.array(
[ts, datetime(2024, 7, 2, 10, 0, 0, tzinfo=timezone.utc)],
type=pa.timestamp("us", tz="UTC"),
),
}
),
)
result = table.search().where(col("ts") == lit(ts)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_different_timezones_same_instant(self, tmp_path):
"""UTC table row equals lit of the same instant in a different zone."""
db = lancedb.connect(str(tmp_path / "diff_tz"))
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
# Same instant as 06:00 in UTC-4
ts_est = datetime(2024, 7, 1, 6, 0, 0, tzinfo=timezone(timedelta(hours=-4)))
table = db.create_table(
"t",
pa.table(
{
"id": [1],
"ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
}
),
)
result = table.search().where(col("ts") == lit(ts_est)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_table_tz_literal_naive(self, tmp_path):
"""UTC table + naive lit uses wall-clock equality (10:00 == 10:00 UTC)."""
db = lancedb.connect(str(tmp_path / "tz_naive"))
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
ts_naive = datetime(2024, 7, 1, 10, 0, 0)
table = db.create_table(
"t",
pa.table(
{
"id": [1],
"ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
}
),
)
result = table.search().where(col("ts") == lit(ts_naive)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_table_naive_literal_aware(self, tmp_path):
"""Naive table + UTC lit with the same wall clock must match."""
db = lancedb.connect(str(tmp_path / "naive_aware"))
ts_naive = datetime(2024, 7, 1, 10, 0, 0)
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
table = db.create_table("t", [{"id": 1, "ts": ts_naive}])
result = table.search().where(col("ts") == lit(ts_utc)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_naive_lit_sql_is_wall_clock_not_local_shifted(self):
"""Regression: naive lit must not apply the host local UTC offset."""
ts = datetime(2024, 7, 1, 10, 0, 0)
sql = lit(ts).to_sql()
# Must encode 10:00 wall clock, not 10:00+local_offset.
assert "2024-07-01 10:00:00" in sql