4d2b559d92
### What changes were proposed in this pull request? Consolidate PySpark testing utils by removing `python/pyspark/pandas/testing`, and then creating a file `pandasutils` under `python/pyspark/testing` for test utilities used in `pyspark/pandas`. ### Why are the changes needed? `python/pyspark/pandas/testing` hold test utilites for pandas-on-spark, and `python/pyspark/testing` contain test utilities for pyspark. Consolidating them makes code cleaner and easier to maintain. Updated import statements are as shown below: - from pyspark.testing.sqlutils import SQLTestUtils - from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils (PandasOnSparkTestCase is the original ReusedSQLTestCase in `python/pyspark/pandas/testing/utils.py`) Minor improvements include: - Usage of missing library's requirement_message - `except ImportError` rather than `except` - import pyspark.pandas alias as `ps` rather than `pp` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Unit tests under python/pyspark/pandas/tests. Closes #32177 from xinrong-databricks/port.merge_utils. Authored-by: Xinrong Meng <xinrong.meng@databricks.com> Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
276 lines
11 KiB
Python
276 lines
11 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import os
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import shutil
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import string
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import tempfile
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import unittest
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import numpy as np
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import pandas as pd
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from distutils.version import LooseVersion
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from pyspark import pandas as ps
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from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
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from pyspark.testing.sqlutils import SQLTestUtils
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class DataFrameConversionTest(PandasOnSparkTestCase, SQLTestUtils, TestUtils):
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"""Test cases for "small data" conversion and I/O."""
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def setUp(self):
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self.tmp_dir = tempfile.mkdtemp(prefix=DataFrameConversionTest.__name__)
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def tearDown(self):
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shutil.rmtree(self.tmp_dir, ignore_errors=True)
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@property
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def pdf(self):
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return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3])
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@property
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def kdf(self):
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return ps.from_pandas(self.pdf)
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@staticmethod
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def strip_all_whitespace(str):
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"""A helper function to remove all whitespace from a string."""
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return str.translate({ord(c): None for c in string.whitespace})
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def test_to_html(self):
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expected = self.strip_all_whitespace(
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"""
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<table border="1" class="dataframe">
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<thead>
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<tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
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</thead>
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<tbody>
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<tr><th>0</th><td>1</td><td>4</td></tr>
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<tr><th>1</th><td>2</td><td>5</td></tr>
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<tr><th>3</th><td>3</td><td>6</td></tr>
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</tbody>
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</table>
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"""
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)
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got = self.strip_all_whitespace(self.kdf.to_html())
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self.assert_eq(got, expected)
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# with max_rows set
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expected = self.strip_all_whitespace(
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"""
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<table border="1" class="dataframe">
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<thead>
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<tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
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</thead>
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<tbody>
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<tr><th>0</th><td>1</td><td>4</td></tr>
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<tr><th>1</th><td>2</td><td>5</td></tr>
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</tbody>
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</table>
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"""
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)
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got = self.strip_all_whitespace(self.kdf.to_html(max_rows=2))
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self.assert_eq(got, expected)
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@staticmethod
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def get_excel_dfs(koalas_location, pandas_location):
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return {
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"got": pd.read_excel(koalas_location, index_col=0),
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"expected": pd.read_excel(pandas_location, index_col=0),
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}
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@unittest.skip("openpyxl")
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def test_to_excel(self):
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with self.temp_dir() as dirpath:
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pandas_location = dirpath + "/" + "output1.xlsx"
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koalas_location = dirpath + "/" + "output2.xlsx"
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pdf = self.pdf
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kdf = self.kdf
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kdf.to_excel(koalas_location)
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pdf.to_excel(pandas_location)
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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kdf.a.to_excel(koalas_location)
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pdf.a.to_excel(pandas_location)
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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pdf = pd.DataFrame({"a": [1, None, 3], "b": ["one", "two", None]}, index=[0, 1, 3])
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kdf = ps.from_pandas(pdf)
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kdf.to_excel(koalas_location, na_rep="null")
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pdf.to_excel(pandas_location, na_rep="null")
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0], "b": [4.0, 5.0, 6.0]}, index=[0, 1, 3])
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kdf = ps.from_pandas(pdf)
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kdf.to_excel(koalas_location, float_format="%.1f")
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pdf.to_excel(pandas_location, float_format="%.1f")
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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kdf.to_excel(koalas_location, header=False)
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pdf.to_excel(pandas_location, header=False)
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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kdf.to_excel(koalas_location, index=False)
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pdf.to_excel(pandas_location, index=False)
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dataframes = self.get_excel_dfs(koalas_location, pandas_location)
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self.assert_eq(dataframes["got"], dataframes["expected"])
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def test_to_json(self):
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pdf = self.pdf
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kdf = ps.from_pandas(pdf)
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self.assert_eq(kdf.to_json(orient="records"), pdf.to_json(orient="records"))
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def test_to_json_negative(self):
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kdf = ps.from_pandas(self.pdf)
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with self.assertRaises(NotImplementedError):
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kdf.to_json(orient="table")
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with self.assertRaises(NotImplementedError):
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kdf.to_json(lines=False)
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def test_read_json_negative(self):
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with self.assertRaises(NotImplementedError):
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ps.read_json("invalid", lines=False)
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def test_to_json_with_path(self):
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pdf = pd.DataFrame({"a": [1], "b": ["a"]})
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kdf = ps.DataFrame(pdf)
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kdf.to_json(self.tmp_dir, num_files=1)
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expected = pdf.to_json(orient="records")
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output_paths = [path for path in os.listdir(self.tmp_dir) if path.startswith("part-")]
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assert len(output_paths) > 0
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output_path = "%s/%s" % (self.tmp_dir, output_paths[0])
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self.assertEqual("[%s]" % open(output_path).read().strip(), expected)
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def test_to_json_with_partition_cols(self):
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pdf = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
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kdf = ps.DataFrame(pdf)
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kdf.to_json(self.tmp_dir, partition_cols="b", num_files=1)
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partition_paths = [path for path in os.listdir(self.tmp_dir) if path.startswith("b=")]
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assert len(partition_paths) > 0
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for partition_path in partition_paths:
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column, value = partition_path.split("=")
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expected = pdf[pdf[column] == value].drop("b", axis=1).to_json(orient="records")
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output_paths = [
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path
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for path in os.listdir("%s/%s" % (self.tmp_dir, partition_path))
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if path.startswith("part-")
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]
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assert len(output_paths) > 0
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output_path = "%s/%s/%s" % (self.tmp_dir, partition_path, output_paths[0])
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with open(output_path) as f:
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self.assertEqual("[%s]" % open(output_path).read().strip(), expected)
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@unittest.skip("Pyperclip could not find a copy/paste mechanism for Linux.")
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def test_to_clipboard(self):
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pdf = self.pdf
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kdf = self.kdf
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self.assert_eq(kdf.to_clipboard(), pdf.to_clipboard())
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self.assert_eq(kdf.to_clipboard(excel=False), pdf.to_clipboard(excel=False))
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self.assert_eq(
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kdf.to_clipboard(sep=";", index=False), pdf.to_clipboard(sep=";", index=False)
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)
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def test_to_latex(self):
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pdf = self.pdf
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kdf = self.kdf
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self.assert_eq(kdf.to_latex(), pdf.to_latex())
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self.assert_eq(kdf.to_latex(col_space=2), pdf.to_latex(col_space=2))
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self.assert_eq(kdf.to_latex(header=True), pdf.to_latex(header=True))
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self.assert_eq(kdf.to_latex(index=False), pdf.to_latex(index=False))
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self.assert_eq(kdf.to_latex(na_rep="-"), pdf.to_latex(na_rep="-"))
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self.assert_eq(kdf.to_latex(float_format="%.1f"), pdf.to_latex(float_format="%.1f"))
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self.assert_eq(kdf.to_latex(sparsify=False), pdf.to_latex(sparsify=False))
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self.assert_eq(kdf.to_latex(index_names=False), pdf.to_latex(index_names=False))
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self.assert_eq(kdf.to_latex(bold_rows=True), pdf.to_latex(bold_rows=True))
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self.assert_eq(kdf.to_latex(decimal=","), pdf.to_latex(decimal=","))
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if LooseVersion(pd.__version__) < LooseVersion("1.0.0"):
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self.assert_eq(kdf.to_latex(encoding="ascii"), pdf.to_latex(encoding="ascii"))
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def test_to_records(self):
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if LooseVersion(pd.__version__) >= LooseVersion("0.24.0"):
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pdf = pd.DataFrame({"A": [1, 2], "B": [0.5, 0.75]}, index=["a", "b"])
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kdf = ps.from_pandas(pdf)
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self.assert_eq(kdf.to_records(), pdf.to_records())
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self.assert_eq(kdf.to_records(index=False), pdf.to_records(index=False))
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self.assert_eq(kdf.to_records(index_dtypes="<S2"), pdf.to_records(index_dtypes="<S2"))
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def test_from_records(self):
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# Assert using a dict as input
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self.assert_eq(
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ps.DataFrame.from_records({"A": [1, 2, 3]}), pd.DataFrame.from_records({"A": [1, 2, 3]})
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)
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# Assert using a list of tuples as input
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self.assert_eq(
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ps.DataFrame.from_records([(1, 2), (3, 4)]), pd.DataFrame.from_records([(1, 2), (3, 4)])
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)
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# Assert using a NumPy array as input
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self.assert_eq(ps.DataFrame.from_records(np.eye(3)), pd.DataFrame.from_records(np.eye(3)))
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# Asserting using a custom index
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self.assert_eq(
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ps.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
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pd.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
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)
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# Assert excluding excluding column(s)
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self.assert_eq(
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ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
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pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
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)
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# Assert limiting to certain column(s)
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self.assert_eq(
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ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
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pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
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)
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# Assert limiting to a number of rows
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self.assert_eq(
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ps.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
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pd.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
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)
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if __name__ == "__main__":
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from pyspark.pandas.tests.test_dataframe_conversion import * # noqa: F401
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try:
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import xmlrunner # type: ignore[import]
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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