mirror of
https://github.com/langchain-ai/datafusion.git
synced 2026-07-19 15:24:21 -04:00
Jorge Leitao
46bde0bd14
* Added Python project. * Update python/Cargo.toml Co-authored-by: Andy Grove <andygrove@users.noreply.github.com> * Update python/Cargo.toml Co-authored-by: Uwe L. Korn <xhochy@users.noreply.github.com> * Added license and black formatting. * License * Fixing build. * TesTestt * Bumped to latest DataFusion. * Bumped nightly. * Bumped pyarrow in tests. * Added some tests back. Co-authored-by: Andy Grove <andygrove@users.noreply.github.com> Co-authored-by: Uwe L. Korn <xhochy@users.noreply.github.com>
116 lines
3.7 KiB
Python
116 lines
3.7 KiB
Python
# 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.
|
|
|
|
import unittest
|
|
|
|
import pyarrow
|
|
import datafusion
|
|
f = datafusion.functions
|
|
|
|
|
|
class TestCase(unittest.TestCase):
|
|
|
|
def _prepare(self):
|
|
ctx = datafusion.ExecutionContext()
|
|
|
|
# create a RecordBatch and a new DataFrame from it
|
|
batch = pyarrow.RecordBatch.from_arrays(
|
|
[pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])],
|
|
names=["a", "b"],
|
|
)
|
|
return ctx.create_dataframe([[batch]])
|
|
|
|
def test_select(self):
|
|
df = self._prepare()
|
|
|
|
df = df.select(
|
|
f.col("a") + f.col("b"),
|
|
f.col("a") - f.col("b"),
|
|
)
|
|
|
|
# execute and collect the first (and only) batch
|
|
result = df.collect()[0]
|
|
|
|
self.assertEqual(result.column(0), pyarrow.array([5, 7, 9]))
|
|
self.assertEqual(result.column(1), pyarrow.array([-3, -3, -3]))
|
|
|
|
def test_filter(self):
|
|
df = self._prepare()
|
|
|
|
df = df \
|
|
.select(
|
|
f.col("a") + f.col("b"),
|
|
f.col("a") - f.col("b"),
|
|
) \
|
|
.filter(f.col("a") > f.lit(2))
|
|
|
|
# execute and collect the first (and only) batch
|
|
result = df.collect()[0]
|
|
|
|
self.assertEqual(result.column(0), pyarrow.array([9]))
|
|
self.assertEqual(result.column(1), pyarrow.array([-3]))
|
|
|
|
def test_limit(self):
|
|
df = self._prepare()
|
|
|
|
df = df.limit(1)
|
|
|
|
# execute and collect the first (and only) batch
|
|
result = df.collect()[0]
|
|
|
|
self.assertEqual(len(result.column(0)), 1)
|
|
self.assertEqual(len(result.column(1)), 1)
|
|
|
|
def test_udf(self):
|
|
df = self._prepare()
|
|
|
|
# is_null is a pyarrow function over arrays
|
|
udf = f.udf(lambda x: x.is_null(), [pyarrow.int64()], pyarrow.bool_())
|
|
|
|
df = df.select(udf(f.col("a")))
|
|
|
|
self.assertEqual(df.collect()[0].column(0), pyarrow.array([False, False, False]))
|
|
|
|
def test_join(self):
|
|
ctx = datafusion.ExecutionContext()
|
|
|
|
batch = pyarrow.RecordBatch.from_arrays(
|
|
[pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])],
|
|
names=["a", "b"],
|
|
)
|
|
df = ctx.create_dataframe([[batch]])
|
|
|
|
batch = pyarrow.RecordBatch.from_arrays(
|
|
[pyarrow.array([1, 2]), pyarrow.array([8, 10])],
|
|
names=["a", "c"],
|
|
)
|
|
df1 = ctx.create_dataframe([[batch]])
|
|
|
|
df = df.join(df1, on="a", how="inner")
|
|
|
|
# execute and collect the first (and only) batch
|
|
batch = df.collect()[0]
|
|
|
|
if batch.column(0) == pyarrow.array([1, 2]):
|
|
self.assertEqual(batch.column(0), pyarrow.array([1, 2]))
|
|
self.assertEqual(batch.column(1), pyarrow.array([8, 10]))
|
|
self.assertEqual(batch.column(2), pyarrow.array([4, 5]))
|
|
else:
|
|
self.assertEqual(batch.column(0), pyarrow.array([2, 1]))
|
|
self.assertEqual(batch.column(1), pyarrow.array([10, 8]))
|
|
self.assertEqual(batch.column(2), pyarrow.array([5, 4]))
|