我正在制定一项要求,我需要针对多个验证解析CSV记录字段。我正在使用supercsv,它支持现场级处理器来验证数据。
我的要求是针对多个验证验证每个记录/行字段,并将它们保存到具有成功/失败状态的数据库。对于失败记录,我必须使用一些代码显示所有失败的验证。
超级CSV是工作文件,但它只检查字段的第一次验证,如果失败,则忽略同一字段的第二次验证。请查看下面的代码并帮助我。
package com.demo.supercsv;
import java.io.FileReader;
import java.io.IOException;
import java.io.StringWriter;
import java.util.ArrayList;
import java.util.List;
import org.supercsv.cellprocessor.Optional;
import org.supercsv.cellprocessor.constraint.NotNull;
import org.supercsv.cellprocessor.constraint.StrMinMax;
import org.supercsv.cellprocessor.constraint.StrRegEx;
import org.supercsv.cellprocessor.constraint.UniqueHashCode;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.exception.SuperCsvCellProcessorException;
import org.supercsv.io.CsvBeanReader;
import org.supercsv.io.CsvBeanWriter;
import org.supercsv.io.ICsvBeanReader;
import org.supercsv.io.ICsvBeanWriter;
import org.supercsv.prefs.CsvPreference;
public class ParserDemo {
public static void main(String[] args) throws IOException {
List<Employee> emps = readCSVToBean();
System.out.println(emps);
System.out.println("******");
writeCSVData(emps);
}
private static void writeCSVData(List<Employee> emps) throws IOException {
ICsvBeanWriter beanWriter = null;
StringWriter writer = new StringWriter();
try{
beanWriter = new CsvBeanWriter(writer, CsvPreference.STANDARD_PREFERENCE);
final String[] header = new String[]{"id","name","role","salary"};
final CellProcessor[] processors = getProcessors();
// write the header
beanWriter.writeHeader(header);
//write the beans data
for(Employee emp : emps){
beanWriter.write(emp, header, processors);
}
}finally{
if( beanWriter != null ) {
beanWriter.close();
}
}
System.out.println("CSV Data\n"+writer.toString());
}
private static List<Employee> readCSVToBean() throws IOException {
ICsvBeanReader beanReader = null;
List<Employee> emps = new ArrayList<Employee>();
try {
beanReader = new CsvBeanReader(new FileReader("src/employees.csv"),
CsvPreference.STANDARD_PREFERENCE);
// the name mapping provide the basis for bean setters
final String[] nameMapping = new String[]{"id","name","role","salary"};
//just read the header, so that it don't get mapped to Employee object
final String[] header = beanReader.getHeader(true);
final CellProcessor[] processors = getProcessors();
Employee emp;
while ((emp = beanReader.read(Employee.class, nameMapping,
processors)) != null) {
emps.add(emp);
if (!CaptureExceptions.SUPPRESSED_EXCEPTIONS.isEmpty()) {
System.out.println("Suppressed exceptions for row "
+ beanReader.getRowNumber() + ":");
for (SuperCsvCellProcessorException e :
CaptureExceptions.SUPPRESSED_EXCEPTIONS) {
System.out.println(e);
}
// for processing next row clearing validation list
CaptureExceptions.SUPPRESSED_EXCEPTIONS.clear();
}
}
} finally {
if (beanReader != null) {
beanReader.close();
}
}
return emps;
}
private static CellProcessor[] getProcessors() {
final CellProcessor[] processors = new CellProcessor[] {
new CaptureExceptions(new NotNull(new StrRegEx("\\d+",new StrMinMax(0, 2)))),//id must be in digits and should not be more than two charecters
new CaptureExceptions(new Optional()),
new CaptureExceptions(new Optional()),
new CaptureExceptions(new NotNull()),
// Salary
};
return processors;
}
}
异常处理程序:
package com.demo.supercsv;
import java.util.ArrayList;
import java.util.List;
import org.supercsv.cellprocessor.CellProcessorAdaptor;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.exception.SuperCsvCellProcessorException;
import org.supercsv.util.CsvContext;
public class CaptureExceptions extends CellProcessorAdaptor {
public static List<SuperCsvCellProcessorException> SUPPRESSED_EXCEPTIONS =
new ArrayList<SuperCsvCellProcessorException>();
public CaptureExceptions(CellProcessor next) {
super(next);
}
public Object execute(Object value, CsvContext context) {
try {
return next.execute(value, context);
} catch (SuperCsvCellProcessorException e) {
// save the exception
SUPPRESSED_EXCEPTIONS.add(e);
if(value!=null)
return value.toString();
else
return "";
}
}
}
示例csv文件
ID,Name,Role,Salary
a123,kiran,CEO,"5000USD"
2,Kumar,Manager,2000USD
3,David,developer,1000USD
当我运行程序supercsv异常处理程序时,为第一行中的ID值显示此消息
Suppressed exceptions for row 2:
org.supercsv.exception.SuperCsvConstraintViolationException: 'a123' does not match the regular expression '\d+'
processor=org.supercsv.cellprocessor.constraint.StrRegEx
context={lineNo=2, rowNo=2, columnNo=1, rowSource=[a123, kiran, CEO, 5000USD]}
[com.demo.supercsv.Employee@23bf011e, com.demo.supercsv.Employee@50e26ae7, com.demo.supercsv.Employee@40d88d2d]
对于字段Id长度不应该为空且超过两个且它应该是neumeric ...我已经定义了这样的字段处理器。
new CaptureExceptions(new NotNull(new StrRegEx("\\d+",new StrMinMax(0, 2))))
但超级csv忽略第二次验证(maxlenght 2)如果给定的输入不是neumeric ...如果我的输入是100那么它的验证最大长度...但是如何得到两个错误输入的验证。请帮助我这个< / p>
答案 0 :(得分:1)
SuperCSV细胞处理器将按顺序工作。因此,如果它通过了先前的约束验证,那么它将检查下一个。
为了实现您的目标,您需要编写一个自定义CellProcessor,它将检查输入是否为数字(数字),长度介于0到2之间。 因此,这两项检查都是一步完成的。