python/pyspark/pandas/tests/io/test_dataframe_conversion.py - spark - Git at Google

 #
 # 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 os
 import string
 import unittest
 import sys

 import numpy as np
 import pandas as pd

 from pyspark import pandas as ps
 from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
 from pyspark.testing.utils import (
     have_openpyxl,
     openpyxl_requirement_message,
     have_jinja2,
     jinja2_requirement_message,
 )


 class DataFrameConversionMixin:
     """Test cases for "small data" conversion and I/O."""

     @property
     def pdf(self):
         return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3])

     @property
     def psdf(self):
         return ps.from_pandas(self.pdf)

     @staticmethod
     def strip_all_whitespace(str):
         """A helper function to remove all whitespace from a string."""
         return str.translate({ord(c): None for c in string.whitespace})

     def test_to_html(self):
         expected = self.strip_all_whitespace("""
             <table border="1" class="dataframe">
               <thead>
                 <tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
               </thead>
               <tbody>
                 <tr><th>0</th><td>1</td><td>4</td></tr>
                 <tr><th>1</th><td>2</td><td>5</td></tr>
                 <tr><th>3</th><td>3</td><td>6</td></tr>
               </tbody>
             </table>
             """)
         got = self.strip_all_whitespace(self.psdf.to_html())
         self.assert_eq(got, expected)

         # with max_rows set
         expected = self.strip_all_whitespace("""
             <table border="1" class="dataframe">
               <thead>
                 <tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
               </thead>
               <tbody>
                 <tr><th>0</th><td>1</td><td>4</td></tr>
                 <tr><th>1</th><td>2</td><td>5</td></tr>
               </tbody>
             </table>
             """)
         got = self.strip_all_whitespace(self.psdf.to_html(max_rows=2))
         self.assert_eq(got, expected)

     @staticmethod
     def get_excel_dfs(pandas_on_spark_location, pandas_location):
         return {
             "got": pd.read_excel(pandas_on_spark_location, index_col=0),
             "expected": pd.read_excel(pandas_location, index_col=0),
         }

     @unittest.skipIf(not have_openpyxl, openpyxl_requirement_message)
     def test_to_excel(self):
         with self.temp_dir() as dirpath:
             pandas_location = dirpath + "/" + "output1.xlsx"
             pandas_on_spark_location = dirpath + "/" + "output2.xlsx"

             pdf = self.pdf
             psdf = self.psdf
             psdf.to_excel(pandas_on_spark_location)
             pdf.to_excel(pandas_location)
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

             psdf.a.to_excel(pandas_on_spark_location)
             pdf.a.to_excel(pandas_location)
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

             pdf = pd.DataFrame({"a": [1, None, 3], "b": ["one", "two", None]}, index=[0, 1, 3])

             psdf = ps.from_pandas(pdf)

             psdf.to_excel(pandas_on_spark_location, na_rep="null")
             pdf.to_excel(pandas_location, na_rep="null")
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

             pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0], "b": [4.0, 5.0, 6.0]}, index=[0, 1, 3])

             psdf = ps.from_pandas(pdf)

             psdf.to_excel(pandas_on_spark_location, float_format="%.1f")
             pdf.to_excel(pandas_location, float_format="%.1f")
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

             psdf.to_excel(pandas_on_spark_location, header=False)
             pdf.to_excel(pandas_location, header=False)
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

             psdf.to_excel(pandas_on_spark_location, index=False)
             pdf.to_excel(pandas_location, index=False)
             dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
             self.assert_eq(dataframes["got"], dataframes["expected"])

     def test_to_json(self):
         pdf = self.pdf
         psdf = ps.from_pandas(pdf)

         self.assert_eq(psdf.to_json(orient="records"), pdf.to_json(orient="records"))

     def test_to_json_negative(self):
         psdf = ps.from_pandas(self.pdf)

         with self.assertRaises(NotImplementedError):
             psdf.to_json(orient="table")

         with self.assertRaises(NotImplementedError):
             psdf.to_json(lines=False)

     def test_read_json_negative(self):
         with self.assertRaises(NotImplementedError):
             ps.read_json("invalid", lines=False)

     def test_to_json_with_path(self):
         pdf = pd.DataFrame({"a": [1], "b": ["a"]})
         psdf = ps.DataFrame(pdf)

         with self.temp_dir() as dirpath:
             psdf.to_json(dirpath, num_files=1)
             expected = pdf.to_json(orient="records")

             output_paths = [path for path in os.listdir(dirpath) if path.startswith("part-")]
             assert len(output_paths) > 0
             output_path = "%s/%s" % (dirpath, output_paths[0])
             self.assertEqual("[%s]" % open(output_path).read().strip(), expected)

     def test_to_json_with_partition_cols(self):
         pdf = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
         psdf = ps.DataFrame(pdf)

         with self.temp_dir() as dirpath:
             psdf.to_json(dirpath, partition_cols="b", num_files=1)

             partition_paths = [path for path in os.listdir(dirpath) if path.startswith("b=")]
             assert len(partition_paths) > 0
             for partition_path in partition_paths:
                 column, value = partition_path.split("=")
                 expected = pdf[pdf[column] == value].drop("b", axis=1).to_json(orient="records")

                 output_paths = [
                     path
                     for path in os.listdir("%s/%s" % (dirpath, partition_path))
                     if path.startswith("part-")
                 ]
                 assert len(output_paths) > 0
                 output_path = "%s/%s/%s" % (dirpath, partition_path, output_paths[0])
                 self.assertEqual("[%s]" % open(output_path).read().strip(), expected)

     @unittest.skipIf(
         sys.platform == "linux" or sys.platform == "linux2",
         "Pyperclip could not find a copy/paste mechanism for Linux.",
     )
     def test_to_clipboard(self):
         pdf = self.pdf
         psdf = self.psdf

         self.assert_eq(psdf.to_clipboard(), pdf.to_clipboard())
         self.assert_eq(psdf.to_clipboard(excel=False), pdf.to_clipboard(excel=False))
         self.assert_eq(
             psdf.to_clipboard(sep=";", index=False), pdf.to_clipboard(sep=";", index=False)
         )

     @unittest.skipIf(not have_jinja2, jinja2_requirement_message)
     def test_to_latex(self):
         pdf = self.pdf
         psdf = self.psdf

         self.assert_eq(psdf.to_latex(), pdf.to_latex())
         self.assert_eq(psdf.to_latex(header=True), pdf.to_latex(header=True))
         self.assert_eq(psdf.to_latex(index=False), pdf.to_latex(index=False))
         self.assert_eq(psdf.to_latex(na_rep="-"), pdf.to_latex(na_rep="-"))
         self.assert_eq(psdf.to_latex(float_format="%.1f"), pdf.to_latex(float_format="%.1f"))
         self.assert_eq(psdf.to_latex(sparsify=False), pdf.to_latex(sparsify=False))
         self.assert_eq(psdf.to_latex(index_names=False), pdf.to_latex(index_names=False))
         self.assert_eq(psdf.to_latex(bold_rows=True), pdf.to_latex(bold_rows=True))
         self.assert_eq(psdf.to_latex(decimal=","), pdf.to_latex(decimal=","))

     def test_to_records(self):
         pdf = pd.DataFrame({"A": [1, 2], "B": [0.5, 0.75]}, index=["a", "b"])

         psdf = ps.from_pandas(pdf)

         self.assert_eq(psdf.to_records(), pdf.to_records())
         self.assert_eq(psdf.to_records(index=False), pdf.to_records(index=False))
         self.assert_eq(psdf.to_records(index_dtypes="<S2"), pdf.to_records(index_dtypes="<S2"))

     def test_from_records(self):
         # Assert using a dict as input
         self.assert_eq(
             ps.DataFrame.from_records({"A": [1, 2, 3]}), pd.DataFrame.from_records({"A": [1, 2, 3]})
         )
         # Assert using a list of tuples as input
         self.assert_eq(
             ps.DataFrame.from_records([(1, 2), (3, 4)]), pd.DataFrame.from_records([(1, 2), (3, 4)])
         )
         # Assert using a NumPy array as input
         self.assert_eq(ps.DataFrame.from_records(np.eye(3)), pd.DataFrame.from_records(np.eye(3)))
         # Asserting using a custom index
         self.assert_eq(
             ps.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
             pd.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
         )
         # Assert excluding excluding column(s)
         self.assert_eq(
             ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
             pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
         )
         # Assert limiting to certain column(s)
         self.assert_eq(
             ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
             pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
         )
         # Assert limiting to a number of rows
         self.assert_eq(
             ps.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
             pd.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
         )


 class DataFrameConversionTests(
     DataFrameConversionMixin,
     PandasOnSparkTestCase,
     TestUtils,
 ):
     pass


 if __name__ == "__main__":
     from pyspark.testing import main

     main()
	#
	# 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 os
	import string
	import unittest
	import sys

	import numpy as np
	import pandas as pd

	from pyspark import pandas as ps
	from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
	from pyspark.testing.utils import (
	have_openpyxl,
	openpyxl_requirement_message,
	have_jinja2,
	jinja2_requirement_message,
	)


	class DataFrameConversionMixin:
	"""Test cases for "small data" conversion and I/O."""

	@property
	def pdf(self):
	return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3])

	@property
	def psdf(self):
	return ps.from_pandas(self.pdf)

	@staticmethod
	def strip_all_whitespace(str):
	"""A helper function to remove all whitespace from a string."""
	return str.translate({ord(c): None for c in string.whitespace})

	def test_to_html(self):
	expected = self.strip_all_whitespace("""
	<table border="1" class="dataframe">
	<thead>
	<tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
	</thead>
	<tbody>
	<tr><th>0</th><td>1</td><td>4</td></tr>
	<tr><th>1</th><td>2</td><td>5</td></tr>
	<tr><th>3</th><td>3</td><td>6</td></tr>
	</tbody>
	</table>
	""")
	got = self.strip_all_whitespace(self.psdf.to_html())
	self.assert_eq(got, expected)

	# with max_rows set
	expected = self.strip_all_whitespace("""
	<table border="1" class="dataframe">
	<thead>
	<tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
	</thead>
	<tbody>
	<tr><th>0</th><td>1</td><td>4</td></tr>
	<tr><th>1</th><td>2</td><td>5</td></tr>
	</tbody>
	</table>
	""")
	got = self.strip_all_whitespace(self.psdf.to_html(max_rows=2))
	self.assert_eq(got, expected)

	@staticmethod
	def get_excel_dfs(pandas_on_spark_location, pandas_location):
	return {
	"got": pd.read_excel(pandas_on_spark_location, index_col=0),
	"expected": pd.read_excel(pandas_location, index_col=0),
	}

	@unittest.skipIf(not have_openpyxl, openpyxl_requirement_message)
	def test_to_excel(self):
	with self.temp_dir() as dirpath:
	pandas_location = dirpath + "/" + "output1.xlsx"
	pandas_on_spark_location = dirpath + "/" + "output2.xlsx"

	pdf = self.pdf
	psdf = self.psdf
	psdf.to_excel(pandas_on_spark_location)
	pdf.to_excel(pandas_location)
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	psdf.a.to_excel(pandas_on_spark_location)
	pdf.a.to_excel(pandas_location)
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	pdf = pd.DataFrame({"a": [1, None, 3], "b": ["one", "two", None]}, index=[0, 1, 3])

	psdf = ps.from_pandas(pdf)

	psdf.to_excel(pandas_on_spark_location, na_rep="null")
	pdf.to_excel(pandas_location, na_rep="null")
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0], "b": [4.0, 5.0, 6.0]}, index=[0, 1, 3])

	psdf = ps.from_pandas(pdf)

	psdf.to_excel(pandas_on_spark_location, float_format="%.1f")
	pdf.to_excel(pandas_location, float_format="%.1f")
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	psdf.to_excel(pandas_on_spark_location, header=False)
	pdf.to_excel(pandas_location, header=False)
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	psdf.to_excel(pandas_on_spark_location, index=False)
	pdf.to_excel(pandas_location, index=False)
	dataframes = self.get_excel_dfs(pandas_on_spark_location, pandas_location)
	self.assert_eq(dataframes["got"], dataframes["expected"])

	def test_to_json(self):
	pdf = self.pdf
	psdf = ps.from_pandas(pdf)

	self.assert_eq(psdf.to_json(orient="records"), pdf.to_json(orient="records"))

	def test_to_json_negative(self):
	psdf = ps.from_pandas(self.pdf)

	with self.assertRaises(NotImplementedError):
	psdf.to_json(orient="table")

	with self.assertRaises(NotImplementedError):
	psdf.to_json(lines=False)

	def test_read_json_negative(self):
	with self.assertRaises(NotImplementedError):
	ps.read_json("invalid", lines=False)

	def test_to_json_with_path(self):
	pdf = pd.DataFrame({"a": [1], "b": ["a"]})
	psdf = ps.DataFrame(pdf)

	with self.temp_dir() as dirpath:
	psdf.to_json(dirpath, num_files=1)
	expected = pdf.to_json(orient="records")

	output_paths = [path for path in os.listdir(dirpath) if path.startswith("part-")]
	assert len(output_paths) > 0
	output_path = "%s/%s" % (dirpath, output_paths[0])
	self.assertEqual("[%s]" % open(output_path).read().strip(), expected)

	def test_to_json_with_partition_cols(self):
	pdf = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
	psdf = ps.DataFrame(pdf)

	with self.temp_dir() as dirpath:
	psdf.to_json(dirpath, partition_cols="b", num_files=1)

	partition_paths = [path for path in os.listdir(dirpath) if path.startswith("b=")]
	assert len(partition_paths) > 0
	for partition_path in partition_paths:
	column, value = partition_path.split("=")
	expected = pdf[pdf[column] == value].drop("b", axis=1).to_json(orient="records")

	output_paths = [
	path
	for path in os.listdir("%s/%s" % (dirpath, partition_path))
	if path.startswith("part-")
	]
	assert len(output_paths) > 0
	output_path = "%s/%s/%s" % (dirpath, partition_path, output_paths[0])
	self.assertEqual("[%s]" % open(output_path).read().strip(), expected)

	@unittest.skipIf(
	sys.platform == "linux" or sys.platform == "linux2",
	"Pyperclip could not find a copy/paste mechanism for Linux.",
	)
	def test_to_clipboard(self):
	pdf = self.pdf
	psdf = self.psdf

	self.assert_eq(psdf.to_clipboard(), pdf.to_clipboard())
	self.assert_eq(psdf.to_clipboard(excel=False), pdf.to_clipboard(excel=False))
	self.assert_eq(
	psdf.to_clipboard(sep=";", index=False), pdf.to_clipboard(sep=";", index=False)
	)

	@unittest.skipIf(not have_jinja2, jinja2_requirement_message)
	def test_to_latex(self):
	pdf = self.pdf
	psdf = self.psdf

	self.assert_eq(psdf.to_latex(), pdf.to_latex())
	self.assert_eq(psdf.to_latex(header=True), pdf.to_latex(header=True))
	self.assert_eq(psdf.to_latex(index=False), pdf.to_latex(index=False))
	self.assert_eq(psdf.to_latex(na_rep="-"), pdf.to_latex(na_rep="-"))
	self.assert_eq(psdf.to_latex(float_format="%.1f"), pdf.to_latex(float_format="%.1f"))
	self.assert_eq(psdf.to_latex(sparsify=False), pdf.to_latex(sparsify=False))
	self.assert_eq(psdf.to_latex(index_names=False), pdf.to_latex(index_names=False))
	self.assert_eq(psdf.to_latex(bold_rows=True), pdf.to_latex(bold_rows=True))
	self.assert_eq(psdf.to_latex(decimal=","), pdf.to_latex(decimal=","))

	def test_to_records(self):
	pdf = pd.DataFrame({"A": [1, 2], "B": [0.5, 0.75]}, index=["a", "b"])

	psdf = ps.from_pandas(pdf)

	self.assert_eq(psdf.to_records(), pdf.to_records())
	self.assert_eq(psdf.to_records(index=False), pdf.to_records(index=False))
	self.assert_eq(psdf.to_records(index_dtypes="<S2"), pdf.to_records(index_dtypes="<S2"))

	def test_from_records(self):
	# Assert using a dict as input
	self.assert_eq(
	ps.DataFrame.from_records({"A": [1, 2, 3]}), pd.DataFrame.from_records({"A": [1, 2, 3]})
	)
	# Assert using a list of tuples as input
	self.assert_eq(
	ps.DataFrame.from_records([(1, 2), (3, 4)]), pd.DataFrame.from_records([(1, 2), (3, 4)])
	)
	# Assert using a NumPy array as input
	self.assert_eq(ps.DataFrame.from_records(np.eye(3)), pd.DataFrame.from_records(np.eye(3)))
	# Asserting using a custom index
	self.assert_eq(
	ps.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
	pd.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
	)
	# Assert excluding excluding column(s)
	self.assert_eq(
	ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
	pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
	)
	# Assert limiting to certain column(s)
	self.assert_eq(
	ps.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
	pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
	)
	# Assert limiting to a number of rows
	self.assert_eq(
	ps.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
	pd.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
	)


	class DataFrameConversionTests(
	DataFrameConversionMixin,
	PandasOnSparkTestCase,
	TestUtils,
	):
	pass


	if __name__ == "__main__":
	from pyspark.testing import main

	main()