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147 lines (130 loc) · 4.96 KB
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""Tests for lambda expressions and higher-order array functions."""
import pickle
import pytest
from datafusion import SessionConfig, SessionContext, col, lit
from datafusion import functions as f
@pytest.fixture
def df():
ctx = SessionContext()
return ctx.from_pydict({"a": [[1, 2, 3], [4, 5]]})
def _column(df, expr, name):
return df.select(expr.alias(name)).collect_column(name).to_pylist()
@pytest.mark.parametrize(
("build_expr", "expected"),
[
pytest.param(
lambda: f.array_transform(col("a"), lambda v: v * 2),
[[2, 4, 6], [8, 10]],
id="array_transform_callable",
),
pytest.param(
lambda: f.array_transform(
col("a"), f.lambda_(["v"], f.lambda_var("v") * lit(2))
),
[[2, 4, 6], [8, 10]],
id="array_transform_explicit_lambda",
),
pytest.param(
lambda: f.array_transform(col("a"), lambda v: 0),
[[0, 0, 0], [0, 0]],
id="array_transform_literal_body_is_coerced",
),
pytest.param(
lambda: f.list_transform(col("a"), lambda v: v + 1),
[[2, 3, 4], [5, 6]],
id="list_transform_alias",
),
pytest.param(
lambda: f.array_any_match(col("a"), lambda v: v > 3),
[False, True],
id="array_any_match_callable",
),
pytest.param(
lambda: f.array_any_match(
col("a"), f.lambda_(["v"], f.lambda_var("v") > lit(2))
),
[True, True],
id="array_any_match_explicit_lambda",
),
pytest.param(
lambda: f.any_match(col("a"), lambda v: v > 4),
[False, True],
id="any_match_alias",
),
pytest.param(
lambda: f.list_any_match(col("a"), lambda v: v > 4),
[False, True],
id="list_any_match_alias",
),
pytest.param(
lambda: f.array_filter(col("a"), lambda v: v > 2),
[[3], [4, 5]],
id="array_filter_callable",
),
pytest.param(
lambda: f.array_filter(
col("a"), f.lambda_(["v"], f.lambda_var("v") > lit(2))
),
[[3], [4, 5]],
id="array_filter_explicit_lambda",
),
pytest.param(
lambda: f.list_filter(col("a"), lambda v: v > 2),
[[3], [4, 5]],
id="list_filter_alias",
),
],
)
def test_higher_order_function_results(df, build_expr, expected):
assert _column(df, build_expr(), "r") == expected
def test_lambda_param_name_appears_in_plan(df):
# The user-chosen parameter name should survive into the displayed plan
# rather than a synthetic placeholder.
expr = f.array_transform(col("a"), lambda value: value * 2)
assert "value" in expr.canonical_name()
@pytest.mark.parametrize(
("arg", "exc_type", "match"),
[
pytest.param(42, TypeError, "expected an Expr or callable", id="non_callable"),
pytest.param(
lambda: lit(1),
ValueError,
"at least one parameter",
id="zero_arg_callable",
),
],
)
def test_to_lambda_rejects_invalid_arg(arg, exc_type, match):
with pytest.raises(exc_type, match=match):
f.array_transform(col("a"), arg)
@pytest.mark.parametrize("dialect", ["DuckDB", "ClickHouse", "Snowflake", "Databricks"])
def test_sql_lambda_keyword_syntax(dialect):
# ``lambda x: x * 2`` is the forward-compatible syntax. DuckDB will drop
# the arrow form (``x -> ...``) in v2.1; the keyword form is supported by
# every dialect in sqlparser-rs that enables lambda functions.
ctx = SessionContext(SessionConfig().set("datafusion.sql_parser.dialect", dialect))
result = ctx.sql(
"select array_transform([1, 2, 3], lambda x: x * 2) as d"
).collect_column("d")
assert result.to_pylist() == [[2, 4, 6]]
def test_pickle_lambda_expr_round_trip(df):
expr = f.array_transform(col("a"), lambda v: v * 2)
decoded = pickle.loads(pickle.dumps(expr)) # noqa: S301
assert decoded.canonical_name() == expr.canonical_name()
assert _column(df, decoded, "r") == [[2, 4, 6], [8, 10]]