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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.
#
import pandas as pd
from pyspark.sql.types import LongType, StructType, StructField
from pyspark.pandas.internal import (
InternalFrame,
SPARK_DEFAULT_INDEX_NAME,
SPARK_INDEX_NAME_FORMAT,
)
from pyspark.pandas.utils import spark_column_equals
from pyspark.testing.pandasutils import PandasOnSparkTestCase
from pyspark.testing.sqlutils import SQLTestUtils
class InternalFrameTestsMixin:
def test_from_pandas(self):
pdf = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
internal = InternalFrame.from_pandas(pdf)
sdf = internal.spark_frame
self.assert_eq(internal.index_spark_column_names, [SPARK_DEFAULT_INDEX_NAME])
self.assert_eq(internal.index_names, [None])
self.assert_eq(internal.column_labels, [("a",), ("b",)])
self.assert_eq(internal.data_spark_column_names, ["a", "b"])
self.assertTrue(spark_column_equals(internal.spark_column_for(("a",)), sdf["a"]))
self.assertTrue(spark_column_equals(internal.spark_column_for(("b",)), sdf["b"]))
self.assert_eq(internal.to_pandas_frame, pdf)
# non-string column name
pdf1 = pd.DataFrame({0: [1, 2, 3], 1: [4, 5, 6]})
internal = InternalFrame.from_pandas(pdf1)
sdf = internal.spark_frame
self.assert_eq(internal.index_spark_column_names, [SPARK_DEFAULT_INDEX_NAME])
self.assert_eq(internal.index_names, [None])
self.assert_eq(internal.column_labels, [(0,), (1,)])
self.assert_eq(internal.data_spark_column_names, ["0", "1"])
self.assertTrue(spark_column_equals(internal.spark_column_for((0,)), sdf["0"]))
self.assertTrue(spark_column_equals(internal.spark_column_for((1,)), sdf["1"]))
self.assert_eq(internal.to_pandas_frame, pdf1)
# categorical column
pdf2 = pd.DataFrame({0: [1, 2, 3], 1: pd.Categorical([4, 5, 6])})
internal = InternalFrame.from_pandas(pdf2)
sdf = internal.spark_frame
self.assert_eq(internal.index_spark_column_names, [SPARK_DEFAULT_INDEX_NAME])
self.assert_eq(internal.index_names, [None])
self.assert_eq(internal.column_labels, [(0,), (1,)])
self.assert_eq(internal.data_spark_column_names, ["0", "1"])
self.assertTrue(spark_column_equals(internal.spark_column_for((0,)), sdf["0"]))
self.assertTrue(spark_column_equals(internal.spark_column_for((1,)), sdf["1"]))
self.assert_eq(internal.to_pandas_frame, pdf2)
# multi-index
pdf.set_index("a", append=True, inplace=True)
internal = InternalFrame.from_pandas(pdf)
sdf = internal.spark_frame
self.assert_eq(
internal.index_spark_column_names,
[SPARK_INDEX_NAME_FORMAT(0), SPARK_INDEX_NAME_FORMAT(1)],
)
self.assert_eq(internal.index_names, [None, ("a",)])
self.assert_eq(internal.column_labels, [("b",)])
self.assert_eq(internal.data_spark_column_names, ["b"])
self.assertTrue(spark_column_equals(internal.spark_column_for(("b",)), sdf["b"]))
self.assert_eq(internal.to_pandas_frame, pdf)
# multi-index columns
pdf.columns = pd.MultiIndex.from_tuples([("x", "b")])
internal = InternalFrame.from_pandas(pdf)
sdf = internal.spark_frame
self.assert_eq(
internal.index_spark_column_names,
[SPARK_INDEX_NAME_FORMAT(0), SPARK_INDEX_NAME_FORMAT(1)],
)
self.assert_eq(internal.index_names, [None, ("a",)])
self.assert_eq(internal.column_labels, [("x", "b")])
self.assert_eq(internal.data_spark_column_names, ["(x, b)"])
self.assertTrue(spark_column_equals(internal.spark_column_for(("x", "b")), sdf["(x, b)"]))
self.assert_eq(internal.to_pandas_frame, pdf)
def test_attach_distributed_column(self):
sdf1 = self.spark.range(10)
self.assert_eq(
InternalFrame.attach_distributed_sequence_column(sdf1, "index").schema,
StructType(
[
StructField("index", LongType(), False),
StructField("id", LongType(), False),
]
),
)
# zero columns
sdf2 = self.spark.range(10).select()
self.assert_eq(
InternalFrame.attach_distributed_sequence_column(sdf2, "index").schema,
StructType([StructField("index", LongType(), False)]),
)
# empty dataframe, zero columns
sdf3 = self.spark.range(10).where("id < 0").select()
self.assert_eq(
InternalFrame.attach_distributed_sequence_column(sdf3, "index").schema,
StructType([StructField("index", LongType(), False)]),
)
class InternalFrameTests(InternalFrameTestsMixin, PandasOnSparkTestCase, SQLTestUtils):
pass
if __name__ == "__main__":
import unittest
from pyspark.pandas.tests.test_internal import * # noqa: F401
try:
import xmlrunner
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)