Maven依赖
com.opencsv
opencsv
5.2
CsvToBeanBuilder
优雅的解析文档中的字段。将CSV文件转换为Bean对象。
opencsv提供了基于"策略"的映射,将CSV绑定到bean。
接口名 | 策略 |
---|---|
MappingStrategy | 顶级的映射接口 |
headerColumnNameMappingStrategy | 基于列名的映射策略,读取csv文件的第一行作为header,比如header1,header2,header3然后调用bean的setHeader1方法,setHeader2方法,setHeader3方法分别设置值。**所以这种策略要求,列名与bean中的属性名完全一致,如果不一致,则值为空,不会出错。使用注解时,注解名字必须与csv中列名一致。 |
ColumnPositionMappingStrategy | 列位置映射策略,他没有header的概念,所以会输出取所有行。在columnMapping数组中指定bean的属性,第一个值对应csv的第一列,第二个值对应csv的第二列…… |
HeaderColumnNameTranslateMappingStrategy | 列头名字翻译映射策略,与HeaderColumnNameMappintStrategy相比,bean的属性名可以与csv列头不一样。通过指定map来映射。 |
注:bean的类型只能为基本数据类型以及String类型,若是BigDecimal类型,那么将会抛出异常。
Bean
@Data
@AllArgsConstructor
@NoArgsConstructor
public class CsvBean {
//@CsvBindByName(column = "PLEG_FLTNO")
@CsvBindByPosition(position = 0)
private String PLEG_FLTNO;
//@CsvBindByName(column = "PLEG_AP_THR_DEP")
@CsvBindByPosition(position = 1)
private String PLEG_AP_THR_DEP;
//@CsvBindByName(column = "PLEG_AP_THR_ARR")
@CsvBindByPosition(position = 2)
private String PLEG_AP_THR_ARR;
//@CsvBindByName(column = "PLEG_DATE")
@CsvBindByPosition(position = 3)
private String PLEG_DATE;
//@CsvBindByName(column = "PLEG_LON")
@CsvBindByPosition(position = 4)
private String PLEG_LON;
}
csv文件:
"PLEG_FLTNO","PLEG_AP_THR_DEP","PLEG_AP_THR_ARR","PLEG_DATE","PLEG_LON","PLEG_LAT","PLEG_ALT","PLEG_SPE","PLEG_DIR","PLEG_TM_SEN","PLEG_UPDATE_TIME"
CA1658,SHE,PEK,"2019-12-01","122.388744","41.6808833","7193.28","618.966","278.53","2019-12-01 15:52:11","2019-12-01 15:54:15"
CA1658,SHE,PEK,"2019-12-01","122.255966","41.695625","7193.28","613.44","278.44","2019-12-01 15:53:14","2019-12-01 15:55:10"
CA1658,SHE,PEK,"2019-12-01","122.128377","41.7096805","7193.28","608.292","277.65","2019-12-01 15:54:16","2019-12-01 15:55:30"
CA1658,SHE,PEK,"2019-12-01","121.994802","41.7067388","7193.28","596.826","266.89","2019-12-01 15:55:21","2019-12-01 15:57:15"
基于列索引的映射
通俗点就是列位置映射,csv文件中列位置对应到bean中的列。
需要注意的是,该策略会输出所有的行,故,我们需要跳过某些行。
@Test
public void readCsvByPosition() throws Exception
{
String fileName="C:\\Users\\lyh\\Desktop\\CA1658SHE-PEK.csv";
InputStreamReader is = new InputStreamReader(new FileInputStream(fileName), StandardCharsets.UTF_8);
ColumnPositionMappingStrategy mappingStrategy = new ColumnPositionMappingStrategy<>();
mappingStrategy.setType(CsvBean.class);
CsvToBean build = new CsvToBeanBuilder(is)
.withMappingStrategy(mappingStrategy)
.withSeparator(CSVWriter.DEFAULT_SEPARATOR)
.withSkipLines(1) //跳过第一行
.build();
List personList = build.parse();
personList.forEach(System.out::println);
}
结果
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.388744)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.255966)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.128377)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=121.994802)
基于列名的映射
@Test
public void readCsvByName() throws Exception
{
String fileName="C:\\Users\\lyh\\Desktop\\CA1658SHE-PEK.csv";
InputStreamReader is = new InputStreamReader(getInputStream(new FileInputStream(fileName)), StandardCharsets.UTF_8);
HeaderColumnNameMappingStrategy mappingStrategy = new HeaderColumnNameMappingStrategy<>();
mappingStrategy.setType(CsvBean.class);
CsvToBean build = new CsvToBeanBuilder(is)
.withMappingStrategy(mappingStrategy)
.withSeparator(CSVWriter.DEFAULT_SEPARATOR)
.build();
List personList = build.parse();
personList.forEach(System.out::println);
}
/**
* 读取流中前面的字符,看是否有bom,如果有bom,将bom头先读掉丢弃
* (opencsv 按列名获取bean对象,第一列缺失的情况)
*/
public static InputStream getInputStream(InputStream in) throws IOException {
PushbackInputStream testin = new PushbackInputStream(in);
int ch = testin.read();
if (ch != 0xEF) {
testin.unread(ch);
} else if ((ch = testin.read()) != 0xBB) {
testin.unread(ch);
testin.unread(0xef);
} else if (testin.read() != 0xBF) {
throw new IOException("错误的UTF-8格式文件");
}
return testin;
}
结果
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.388744)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.255966)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=122.128377)
CsvBean(PLEG_FLTNO=CA1658, PLEG_AP_THR_DEP=SHE, PLEG_AP_THR_ARR=PEK, PLEG_DATE=2019-12-01, PLEG_LON=121.994802)
转换器
在csv获取的都是字符串,这种情况下应该使用转换器。将csv中的字段转换为对应的bean中的字段类型。
@Data
@AllArgsConstructor
@NoArgsConstructor
public class CsvBean {
//@CsvBindByName(column = "PLEG_FLTNO")
@CsvBindByPosition(position = 0)
private String PLEG_FLTNO;
//@CsvBindByName(column = "PLEG_AP_THR_DEP")
@CsvBindByPosition(position = 1)
private String PLEG_AP_THR_DEP;
//@CsvBindByName(column = "PLEG_AP_THR_ARR")
@CsvBindByPosition(position = 2)
private String PLEG_AP_THR_ARR;
//@CsvBindByName(column = "PLEG_DATE")
//@CsvBindByPosition(position = 3)
@CsvCustomBindByPosition(position = 3,converter = ConvertToDate.class)
private LocalDate PLEG_DATE;
//@CsvBindByName(column = "PLEG_LON")
@CsvBindByPosition(position = 4)
private String PLEG_LON;
}
public class ConvertToDate extends AbstractBeanField {
@Override
protected Object convert(String s) throws CsvDataTypeMismatchException, CsvConstraintViolationException {
return LocalDate.parse(s, DateTimeFormatter.ofPattern("yyyy-MM-dd"));
}
}
注:若是列映射策略,则要使用@CsvCustomBindByPosition()注解。
注:若是名字映射策略,则要使用@CsvCustomBindByName()注解。
过滤器
opencsv提供了过滤器,可以过滤某些行,比如page header、page footer等
所有的过滤器必须实现CsvToBeanFilter 接口
public class CsvFilter implements CsvToBeanFilter {
@Override
public boolean allowLine(String[] strings) {
return strings[4].equalsIgnoreCase("122.388744");
}
}
CsvToBeanFilter 是一个函数式接口所以也可以直接简化为lambda表达式
@Test
public void readCsvByPosition() throws Exception
{
String fileName="C:\\Users\\lyh\\Desktop\\CA1658SHE-PEK.csv";
InputStreamReader is = new InputStreamReader(new FileInputStream(fileName), StandardCharsets.UTF_8);
ColumnPositionMappingStrategy mappingStrategy = new ColumnPositionMappingStrategy<>();
mappingStrategy.setType(CsvBean.class);
CsvToBean build = new CsvToBeanBuilder(is)
.withMappingStrategy(mappingStrategy)
.withSeparator(CSVWriter.DEFAULT_SEPARATOR)
.withSkipLines(1)
.withFilter(param-> param[4].equalsIgnoreCase("122.388744")) //增加过滤器
//.withFilter(new CsvFilter())
.build();
List personList = build.parse();
personList.forEach(System.out::println);
}