我应该在同一个类中实现这两个接口吗？

Question

我有两个接口： Normalizer和ScoringSummary如下：

1. 归一化器：

    public interface Normalizer { /** * Accepts a <code>csvPath</code> for a CSV file, perform a Z-Score normalization against * <code>colToStandardize</code>, then generate the result file with additional scored column to * <code>destPath</code>. * * @param csvPath path of CSV file to read * @param destPath path to which the scaled CSV file should be written * @param colToStandardize the name of the column to normalize * @return */ ScoringSummary zscore(Path csvPath, Path destPath, String colToStandardize); /** * Accepts a <code>csvPath</code> for a CSV file, perform a Min-Max normalization against * <code>colToNormalize</code>, then generate the result file with additional scored column to * <code>destPath</code>. * * @param csvPath path of CSV file to read * @param destPath path to which the scaled CSV file should be written * @param colToNormalize the name of the column to normalize * @return */ ScoringSummary minMaxScaling(Path csvPath, Path destPath, String colToNormalize); }

2. 评分总结：

    public interface ScoringSummary { public BigDecimal mean(); public BigDecimal standardDeviation(); public BigDecimal variance(); public BigDecimal median(); public BigDecimal min(); public BigDecimal max(); }

这是来自 TDD 的一个函数：

@Test
    public void givenMarksCSVFileToScale_whenMarkColumnIsZScored_thenNewCSVFileIsGeneratedWithAdditionalZScoreColumn() throws IOException {
        String filename = "marks.csv";
        Path induction = Files.createTempDirectory("induction");
        String columnName = "mark";
        Path csvPath = induction.resolve(filename);
        Path destPath = induction.resolve("marks_scaled.csv");
        copyFile("/marks.csv", csvPath);
        Assertions.assertTrue(Files.exists(csvPath));

        Normalizer normalizer = normalizer();
        ScoringSummary summary = normalizer.zscore(csvPath, destPath, columnName);
        Assertions.assertNotNull(summary, "the returned summary is null");

        Assertions.assertEquals(new BigDecimal("66.00"), summary.mean(), "invalid mean");
        Assertions.assertEquals(new BigDecimal("16.73"), summary.standardDeviation(), "invalid standard deviation");
        Assertions.assertEquals(new BigDecimal("280.00"), summary.variance(), "invalid variance");
        Assertions.assertEquals(new BigDecimal("65.00"), summary.median(), "invalid median");
        Assertions.assertEquals(new BigDecimal("40.00"), summary.min(), "invalid min value");
        Assertions.assertEquals(new BigDecimal("95.00"), summary.max(), "invalid maximum value");

        Assertions.assertTrue(Files.exists(destPath), "the destination file does not exists");
        Assertions.assertFalse(Files.isDirectory(destPath), "the destination is not a file");

        List<String> generatedLines = Files.readAllLines(destPath);
        Path assertionPath = copyFile("/marks_z.csv", induction.resolve("marks_z.csv"));
        List<String> expectedLines = Files.readAllLines(assertionPath);
        assertLines(generatedLines, expectedLines);
    }

如何在一个 java 类中实现这两个接口？ 我是否需要任何依赖项或其他框架来解析 CSV？

Answer 1

您不一定需要依赖项或框架来处理 CSV 数据。 但是，使用现有库比自己实现所有内容要容易得多。

有许多不同的方式来实现这两个接口。 您的实施只需要履行他们的合同。 下面是一些例子：

两个独立的类

public class NormalizerImplSplit implements Normalizer {

    @Override
    public ScoringSummary zscore(Path csvPath, Path destPath, String colToStandardize) {
        // process CSV and store summary results
        ScoringSummaryImpl summary = new ScoringSummaryImpl();
        summary.setMean(new BigDecimal("66.00"));

        // return summary object
        return summary;
    }

    // other method of Normalizer

}

public class ScoringSummaryImpl implements ScoringSummary {

    private BigDecimal mean;

    public void setMean(BigDecimal mean) {
        this.mean = mean;
    }

    @Override
    public BigDecimal mean() {
        return this.mean;
    }

    // other methods of ScoringSummary
}

具有嵌套ScoringSummary实现的Normalizer ScoringSummary实现

public class NormalizerImplNested implements Normalizer {

    @Override
    public ScoringSummary zscore(Path csvPath, Path destPath, String colToStandardize) {
        // process CSV and store summary results
        ScoringSummaryImpl summary = new ScoringSummaryImpl();
        summary.setMean(new BigDecimal("66.00"));

        // return summary object
        return summary;
    }

    // other method of Normalizer

    public static class ScoringSummaryImpl implements ScoringSummary {

        private BigDecimal mean;

        private void setMean(BigDecimal mean) {
            this.mean = mean;
        }

        @Override
        public BigDecimal mean() {
            return this.mean;
        }

        // other methods of ScoringSummary
    }
}

实现Normalizer和ScoringSummary单个类

public class NormalizerImpl implements Normalizer, ScoringSummary {

    private BigDecimal mean;

    @Override
    public ScoringSummary zscore(Path csvPath,Path destPath,String colToStandardize) {
        // process CSV and store summary results
        this.mean = new BigDecimal("66.00");

        // return this instance since ScoringSummary is also implemented
        return this;
    }

    @Override
    public BigDecimal mean() {
        return this.mean;
    }

    // other methods of the two interfaces

}