python/pyspark/pandas/tests/io/test_dataframe_conversion.py - master - githubmirror/spark

python/pyspark/pandas/tests/io/test_dataframe_conversion.py
272 строки11 KB
Ruifeng Zheng
[SPARK-56863][PYTHON][PS][TESTS] Drop redundant `SQLTestUtils`
19 май 2026, 03:55
19 май 2026, 03:55369d502
#
# 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()