我有各种CSV，其中包含一些标准列和一些完全随机的字段：
firstname, lastname, dog_name, fav_hat, fav_color
bill,smith,fido,porkpie,blue
james,smith,rover,bowler,purple
firstname, lastname, car_type, floor_number
tom, collins, ford, 14
jim, jones, toyota, 120
所以我试图将它们解析为Person.class bean，它包含firstname＆amp; lastname，然后我有一个名为PersonAttribute.class的第二个类来保存......无论如何。
两个班级的讽刺大纲：
class Person {
public String firstname;
public String lastname;
public List<PersonAttribute> attribs;
}
class PersonAttribute {
public Person p;
public String key; // header name, ex. 'car_type'
public String value; // column value, ex. 'ford'
}
我一直在opencsv中使用CsvToBean函数：
public static List<Person> parseToBeans(File csvFile, HashMap<String, String> mapStrategy, Class beanClass) throws IOException {
CSVReader reader = null;
try {
reader = new CSVReader(new BufferedReader(new FileReader(csvFile)));
HeaderColumnNameTranslateMappingStrategy<Person> strategy = new HeaderColumnNameTranslateMappingStrategy<>();
strategy.setType(beanClass);
strategy.setColumnMapping(mapStrategy);
final CsvToBean<Person> csv = new CsvToBean<Person>() {
@Override
protected Object convertValue(String value, PropertyDescriptor prop) throws InstantiationException, IllegalAccessException {
value = value.trim().replaceAll(" +", " ");
return super.convertValue(value, prop);
}
};
return csv.parse(strategy, reader);
}
...
但是，当我解析Person.class bean的csv时，我不确定如何处理创建PersonAttribute.class bean。我遇到了this post，我想知道是否需要切换到supercsv以轻松处理我正在尝试做的事情？
答案 0 :(得分：3)
您可以通过Super CSV实现这一目标。
您可以使用
CsvBeanReader - 它不支持索引映射，因此您需要在bean中创建一个帮助方法才能使用它
CsvDozerBeanReader - 支持开箱即用的索引映射，因此可以完全按照您的要求进行操作（需要最近发布的Super CSV 2.1.0）
如果您不想使用Dozer并且能够修改您的bean类，最简单的选择是在您的bean上添加一个虚拟setter，CsvBeanReader将使用它来填充属性。我假设您的Person和PersonAttribute bean有一个公共的无参数构造函数，并为每个字段定义了getter / setter（这是必需的）。
将以下虚拟设置器添加到Person bean：
public void setAddAttribute(PersonAttribute attribute){
if (attribs == null){
attribs = new ArrayList<PersonAttribute>();
}
attribs.add(attribute);
}
创建一个自定义cell processor，其中将使用CSV标头中的相应密钥和CSV列中的值填充PersonAttribute。
package org.supercsv.example;
import org.supercsv.cellprocessor.CellProcessorAdaptor;
import org.supercsv.util.CsvContext;
/**
* Creates a PersonAttribute using the corresponding header as the key.
*/
public class ParsePersonAttribute extends CellProcessorAdaptor {
private final String[] header;
public ParsePersonAttribute(final String[] header) {
this.header = header;
}
public Object execute(Object value, CsvContext context) {
if( value == null ) {
return null;
}
PersonAttribute attribute = new PersonAttribute();
// columns start at 1
attribute.setKey(header[context.getColumnNumber() - 1]);
attribute.setValue((String) value);
return attribute;
}
}
我认为以下示例主要针对自己，但这里有一些我应该指出的事情：
我必须使用自定义偏好设置，因为您的CSV空间不属于数据
我必须动态组装字段映射和单元处理器数组，因为您的数据具有未知数量的属性（此设置通常不那么复杂）
属性的所有字段映射都使用addAttribute，这对应于我们添加到您的bean的setAddAttribute()方法
我使用自定义单元格处理器为每个属性列创建PersonAttribute bean
以下是代码：
package org.supercsv.example;
import java.io.IOException;
import java.io.Reader;
import java.io.StringReader;
import org.supercsv.cellprocessor.Optional;
import org.supercsv.cellprocessor.constraint.NotNull;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.io.CsvBeanReader;
import org.supercsv.io.ICsvBeanReader;
import org.supercsv.prefs.CsvPreference;
public class ReadWithCsvBeanReader {
private static final String CSV =
"firstname, lastname, dog_name, fav_hat, fav_color\n"
+ "bill,smith,fido,porkpie,blue\n"
+ "james,smith,rover,bowler,purple";
private static final String CSV2 =
"firstname, lastname, car_type, floor_number\n"
+ "tom, collins, ford, 14\n" + "jim, jones, toyota, 120";
// attributes start at element 2 of the header array
private static final int ATT_START_INDEX = 2;
// custom preferences required because CSV contains
spaces that aren't part of the data
private static final CsvPreference PREFS =
new CsvPreference.Builder(
CsvPreference.STANDARD_PREFERENCE)
.surroundingSpacesNeedQuotes(true).build();
public static void main(String[] args) throws IOException {
System.out.println("CsvBeanReader with first CSV input:");
readWithCsvBeanReader(new StringReader(CSV));
System.out.println("CsvBeanReader with second CSV input:");
readWithCsvBeanReader(new StringReader(CSV2));
}
private static void readWithCsvBeanReader(final Reader reader)
throws IOException {
ICsvBeanReader beanReader = null;
try {
beanReader = new CsvBeanReader(reader, PREFS);
final String[] header = beanReader.getHeader(true);
// set up the field mapping and processors dynamically
final String[] fieldMapping = new String[header.length];
final CellProcessor[] processors =
new CellProcessor[header.length];
for (int i = 0; i < header.length; i++) {
if (i < ATT_START_INDEX) {
// normal mappings
fieldMapping[i] = header[i];
processors[i] = new NotNull();
} else {
// attribute mappings
fieldMapping[i] = "addAttribute";
processors[i] =
new Optional(new ParsePersonAttribute(header));
}
}
Person person;
while ((person = beanReader.read(Person.class, fieldMapping,
processors)) != null) {
System.out.println(String.format(
"lineNo=%s, rowNo=%s, person=%s",
beanReader.getLineNumber(), beanReader.getRowNumber(),
person));
}
} finally {
if (beanReader != null) {
beanReader.close();
}
}
}
}
输出（我向您的bean添加了toString()方法）：
CsvBeanReader with first CSV input:
lineNo=2, rowNo=2, person=Person [firstname=bill, lastname=smith, attribs=[PersonAttribute [key=dog_name, value=fido], PersonAttribute [key=fav_hat, value=porkpie], PersonAttribute [key=fav_color, value=blue]]]
lineNo=3, rowNo=3, person=Person [firstname=james, lastname=smith, attribs=[PersonAttribute [key=dog_name, value=rover], PersonAttribute [key=fav_hat, value=bowler], PersonAttribute [key=fav_color, value=purple]]]
CsvBeanReader with second CSV input:
lineNo=2, rowNo=2, person=Person [firstname=tom, lastname=collins, attribs=[PersonAttribute [key=car_type, value=ford], PersonAttribute [key=floor_number, value=14]]]
lineNo=3, rowNo=3, person=Person [firstname=jim, lastname=jones, attribs=[PersonAttribute [key=car_type, value=toyota], PersonAttribute [key=floor_number, value=120]]]
如果您不能或不想修改您的bean，那么我建议在Super CSV Dozer Extension项目中使用CsvDozerBeanReader，因为它支持嵌套和索引字段映射。查看一些使用它的例子here。
以下是使用CsvDozerBeanReader的示例。您会注意到它与CsvBeanReader示例几乎完全相同，但是：
它使用不同的读者（呃！）
它使用索引映射，例如attribs[0]
它通过调用configureBeanMapping()来设置映射（而不是像read()
CsvBeanReader方法上的字符串数组
它还设置了一些提示（下面有更多内容）
代码：
package org.supercsv.example;
import java.io.IOException;
import java.io.Reader;
import java.io.StringReader;
import org.supercsv.cellprocessor.Optional;
import org.supercsv.cellprocessor.constraint.NotNull;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.io.dozer.CsvDozerBeanReader;
import org.supercsv.io.dozer.ICsvDozerBeanReader;
import org.supercsv.prefs.CsvPreference;
public class ReadWithCsvDozerBeanReader {
private static final String CSV =
"firstname, lastname, dog_name, fav_hat, fav_color\n"
+ "bill,smith,fido,porkpie,blue\n"
+ "james,smith,rover,bowler,purple";
private static final String CSV2 =
"firstname, lastname, car_type, floor_number\n"
+ "tom, collins, ford, 14\n"
+ "jim, jones, toyota, 120";
// attributes start at element 2 of the header array
private static final int ATT_START_INDEX = 2;
// custom preferences required because CSV contains spaces that aren't part of the data
private static final CsvPreference PREFS = new CsvPreference.Builder(CsvPreference.STANDARD_PREFERENCE)
.surroundingSpacesNeedQuotes(true).build();
public static void main(String[] args) throws IOException {
System.out.println("CsvDozerBeanReader with first CSV input:");
readWithCsvDozerBeanReader(new StringReader(CSV));
System.out.println("CsvDozerBeanReader with second CSV input:");
readWithCsvDozerBeanReader(new StringReader(CSV2));
}
private static void readWithCsvDozerBeanReader(final Reader reader) throws IOException {
ICsvDozerBeanReader beanReader = null;
try {
beanReader = new CsvDozerBeanReader(reader, PREFS);
final String[] header = beanReader.getHeader(true);
// set up the field mapping, processors and hints dynamically
final String[] fieldMapping = new String[header.length];
final CellProcessor[] processors = new CellProcessor[header.length];
final Class<?>[] hintTypes = new Class<?>[header.length];
for( int i = 0; i < header.length; i++ ) {
if( i < ATT_START_INDEX ) {
// normal mappings
fieldMapping[i] = header[i];
processors[i] = new NotNull();
} else {
// attribute mappings
fieldMapping[i] = String.format("attribs[%d]", i - ATT_START_INDEX);
processors[i] = new Optional(new ParsePersonAttribute(header));
hintTypes[i] = PersonAttribute.class;
}
}
beanReader.configureBeanMapping(Person.class, fieldMapping, hintTypes);
Person person;
while( (person = beanReader.read(Person.class, processors)) != null ) {
System.out.println(String.format("lineNo=%s, rowNo=%s, person=%s",
beanReader.getLineNumber(),
beanReader.getRowNumber(), person));
}
}
finally {
if( beanReader != null ) {
beanReader.close();
}
}
}
}
输出：
CsvDozerBeanReader with first CSV input:
lineNo=2, rowNo=2, person=Person [firstname=bill, lastname=smith, attribs=[PersonAttribute [key=dog_name, value=fido], PersonAttribute [key=fav_hat, value=porkpie], PersonAttribute [key=fav_color, value=blue]]]
lineNo=3, rowNo=3, person=Person [firstname=james, lastname=smith, attribs=[PersonAttribute [key=dog_name, value=rover], PersonAttribute [key=fav_hat, value=bowler], PersonAttribute [key=fav_color, value=purple]]]
CsvDozerBeanReader with second CSV input:
lineNo=2, rowNo=2, person=Person [firstname=tom, lastname=collins, attribs=[PersonAttribute [key=car_type, value=ford], PersonAttribute [key=floor_number, value=14]]]
lineNo=3, rowNo=3, person=Person [firstname=jim, lastname=jones, attribs=[PersonAttribute [key=car_type, value=toyota], PersonAttribute [key=floor_number, value=120]]]
在汇总这个示例时，我在Super CSV 2.0.1中发现了CsvDozerBeanReader的错误，当您组合cell processor时（例如我在上面的示例中创建的那个解析每个人属性）键/值），索引映射如：
"firstname","lastname","attribs[0]","attribs[1]"
我刚刚发布了Super CSV 2.1.0修复此问题。事实证明，Dozer需要为索引映射配置一个提示才能正常工作。我不是百分之百确定原因，因为当你摆脱自定义单元处理器并使用以下（深层）映射时，它能够创建每个PersonAttribute并将其添加到正确的索引中：
"firstname","lastname","attribs[0].value","attribs[1].value"
我希望这会有所帮助：）