Java 生成 csv文件

java导出CSV文件,EXCEL文件(不用指定下载路劲) 亲测OK,可直接导出excel文件,csv文件;不用指定下载路劲,直接下载到本地,服务器不用生成临时文件。 立即下载

转载:https://blog.youkuaiyun.com/xuxu198899223/article/details/38079885


package csvdemo002;

import java.util.LinkedHashMap;

public class CouponCountBean {
	
	private String account_id;
	private String coupon_count;
	private String coupon_money;
	private String phone;
	
	public String getAccount_id() {
		return account_id;
	}
	public void setAccount_id(String account_id) {
		this.account_id = account_id;
	}
	public String getCoupon_count() {
		return coupon_count;
	}
	public void setCoupon_count(String coupon_count) {
		this.coupon_count = coupon_count;
	}
	public String getCoupon_money() {
		return coupon_money;
	}
	public void setCoupon_money(String coupon_money) {
		this.coupon_money = coupon_money;
	}
	public String getPhone() {
		return phone;
	}
	public void setPhone(String phone) {
		this.phone = phone;
	}
	
	LinkedHashMap<String ,String> getMap(){
		LinkedHashMap<String ,String>  map  = new LinkedHashMap<String ,String>();
		map.put("1", phone);
		map.put("2", coupon_count);
		map.put("3", coupon_money);
		return map;
	}
	
	static LinkedHashMap<String ,String>  getTitleMap(){
		LinkedHashMap<String ,String>  map  = new LinkedHashMap<String ,String>();
		map.put("1", "phone");
		map.put("2", "coupon_count");
		map.put("3", "coupon_money");
		return map;
	}
	
	

}


package csvdemo002;

import java.io.BufferedWriter;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.io.OutputStreamWriter;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

import javax.servlet.http.HttpServletResponse;

/**
 * 文件操作
 * 
 * @author lizhiyong
 * @version $Id: CSVUtils.java, v 0.1 2014年7月22日 下午2:19:59 Exp $
 */
public class CSVUtils2 {

	/**
	 * 生成为CVS文件
	 * 
	 * @param exportData
	 *            源数据List
	 * @param map
	 *            csv文件的列表头map
	 * @param outPutPath
	 *            文件路径
	 * @param fileName
	 *            文件名称
	 * @return
	 */
	public static File createCSVFile(List<CouponCountBean> exportData, LinkedHashMap<String, String> titleMap,
			String outPutPath, String fileName) {
		File csvFile = null;
		BufferedWriter csvFileOutputStream = null;
		try {
			File file = new File(outPutPath);
			if (!file.exists()) {
				file.mkdir();
			}
			// 定义文件名格式并创建
			csvFile = File.createTempFile(fileName, ".csv", new File(outPutPath));
			System.out.println("csvFile:" + csvFile);
			// UTF-8使正确读取分隔符","
			csvFileOutputStream = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(csvFile), "GBK"),
					1024);
			System.out.println("csvFileOutputStream:" + csvFileOutputStream);

			// 写入title行数据
			for (Iterator propertyIterator = titleMap.entrySet().iterator(); propertyIterator.hasNext();) {
				java.util.Map.Entry propertyEntry = (java.util.Map.Entry) propertyIterator.next();
				csvFileOutputStream.write((String) propertyEntry.getValue() != null
						? new String(((String) propertyEntry.getValue()).getBytes("GBK"), "GBK") : "");
				if (propertyIterator.hasNext()) {
					csvFileOutputStream.write(",");
				}
				System.out.println(new String(((String) propertyEntry.getValue()).getBytes("GBK"), "GBK"));
			}

			// 头和体中间的换行
			csvFileOutputStream.write("\r\n");
 

			long i = 0;
			for (CouponCountBean couponCountBean : exportData) {
				csvFileOutputStream.write(couponCountBean.getPhone());
				csvFileOutputStream.write(",");
				csvFileOutputStream.write(couponCountBean.getCoupon_count());
				csvFileOutputStream.write(",");
				csvFileOutputStream.write(couponCountBean.getCoupon_money());
				csvFileOutputStream.write("\r\n");
				// 每1000行提交一次
				if(++i%1000==0){
					csvFileOutputStream.flush();
					System.out.println("this i = "+i);
				}
			}

			csvFileOutputStream.flush();
		} catch (Exception e) {
			e.printStackTrace();
		} finally {
			try {
				csvFileOutputStream.close();
			} catch (IOException e) {
				e.printStackTrace();
			}
		}
		return csvFile;
	}

	/**
	 * 下载文件
	 * 
	 * @param response
	 * @param csvFilePath
	 *            文件路径
	 * @param fileName
	 *            文件名称
	 * @throws IOException
	 */
	public static void exportFile(HttpServletResponse response, String csvFilePath, String fileName)
			throws IOException {
		response.setContentType("application/csv;charset=GBK");
		response.setHeader("Content-Disposition",
				"attachment;  filename=" + new String(fileName.getBytes("GBK"), "ISO8859-1"));
		// URLEncoder.encode(fileName, "GBK")

		InputStream in = null;
		try {
			in = new FileInputStream(csvFilePath);
			int len = 0;
			byte[] buffer = new byte[1024];
			response.setCharacterEncoding("GBK");
			OutputStream out = response.getOutputStream();
			while ((len = in.read(buffer)) > 0) {
				// out.write(new byte[] { (byte) 0xEF, (byte) 0xBB, (byte) 0xBF
				// });
				out.write(buffer, 0, len);
			}
		} catch (FileNotFoundException e) {
			System.out.println(e);
		} finally {
			if (in != null) {
				try {
					in.close();
				} catch (Exception e) {
					throw new RuntimeException(e);
				}
			}
		}
	}

	/**
	 * 删除该目录filePath下的所有文件
	 * 
	 * @param filePath
	 *            文件目录路径
	 */
	public static void deleteFiles(String filePath) {
		File file = new File(filePath);
		if (file.exists()) {
			File[] files = file.listFiles();
			for (int i = 0; i < files.length; i++) {
				if (files[i].isFile()) {
					files[i].delete();
				}
			}
		}
	}

	/**
	 * 删除单个文件
	 * 
	 * @param filePath
	 *            文件目录路径
	 * @param fileName
	 *            文件名称
	 */
	public static void deleteFile(String filePath, String fileName) {
		File file = new File(filePath);
		if (file.exists()) {
			File[] files = file.listFiles();
			for (int i = 0; i < files.length; i++) {
				if (files[i].isFile()) {
					if (files[i].getName().equals(fileName)) {
						files[i].delete();
						return;
					}
				}
			}
		}
	}

	/**
	 * 测试数据
	 * 
	 * @param args
	 */
	@SuppressWarnings({ "rawtypes", "unchecked" })
	public static void main(String[] args) {

		// 标题
		LinkedHashMap<String, String> titleMap = new LinkedHashMap<String, String>();
		titleMap.put("1", "phone");
		titleMap.put("2", "coupon_count");
		titleMap.put("3", "coupon_amount");

		List<CouponCountBean> exportData = new ArrayList<CouponCountBean>();

		for (int i = 0; i < 10; i++) {
			CouponCountBean bean = new CouponCountBean();
			bean.setAccount_id(i + "");
			bean.setCoupon_count(i + 10 + "");
			bean.setCoupon_money(i + 100 + "");
			bean.setPhone(i + 1000 + "");
			exportData.add(bean);
		}

		 
		String path = "c:/export/";
		String fileName = "文件导出";
		File file = CSVUtils2.createCSVFile(exportData, titleMap, path, fileName);
		String fileName2 = file.getName();
		System.out.println("文件名称:" + fileName2);
	}
}


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% Dropout fraction opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex4 neural net with sigmoid activation functionrand('state',0)nn = nnsetup([784 100 10]);nn.activation_function = 'sigm'; % Sigmoid activation functionnn.learningRate = 1; % Sigm require a lower learning rateopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex5 plotting functionalityrand('state',0)nn = nnsetup([784 20 10]);opts.numepochs = 5; % Number of full sweeps through datann.output = 'softmax'; % use softmax outputopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex6 neural net with sigmoid activation and plotting of validation and training error% split training data into training and validation datavx = train_x(1:10000,:);tx = train_x(10001:end,:);vy = train_y(1:10000,:);ty = train_y(10001:end,:);rand('state',0)nn = nnsetup([784 20 10]); 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