@PostMapping(value = "/inventorySelect") public void checkInAndOutOfTheLibrary(@RequestBody BlcInOutStoreResponse BlcInOutStoreResponse) { checkInAndOutOfTheLibraryService.checkInAndOutSelect(BlcInOutStoreResponse); }完善以上代码使后端成功接收XML数据，并解决org.springframework.web.HttpMediaTypeNotSupportedException: Content type 'application/xml;charset=UTF-8' not supported问题

可以使用`consumes`属性来指定接收的请求类型为XML，同时使用`produces`属性来指定返回的响应类型为JSON，代码如下所示：

@PostMapping(value = "/inventorySelect", consumes = MediaType.APPLICATION_XML_VALUE, produces = MediaType.APPLICATION_JSON_VALUE)
public void checkInAndOutOfTheLibrary(@RequestBody BlcInOutStoreResponse BlcInOutStoreResponse) {
    checkInAndOutOfTheLibraryService.checkInAndOutSelect(BlcInOutStoreResponse);
}

这样就可以让后端成功接收XML数据，并且解决`HttpMediaTypeNotSupportedException`异常问题。注意需要导入`MediaType`类。

相关问题

将下面的java代码转python @Controller public class IndexControlle { SimpleDateFormat df = new SimpleDateFormat( pattern: "yyy-MM-dd HH:mm:ss"); private final static Logger logger = LoggerFacstory.getLogger(IndexControlle.class) @RequestMapping("/index") @ResponseBody public String index() { logger.info("hello world» » » "); return "hello world》》》"; //关键数据订阅返回响应 @PostMapping(value = "/jsoni", produces = "application/json; charset=UTF-8") @ResponseBody public void json1(@RequestBody String content) throwsUnsupportedEncodingException { logger.info("json1关键数据订阅返回响应》》》"+content); @PostMapping(value = "/json2", produces = "applicatioon/json; charset=utf-8") @ResponseBody public void hello3(@RequestBody String content) { logger.info("json2响应数据》》"+content); } @PostMapping("/map10") @ResponseBody public void hello6(@RequestBody Map<String, Oboject> params){logger.info("map10响应数据》》》"+params); } //最早版本用map接收的 @PostMapping("/map1") @ResponseBody public void hello(@RequestParam Map<String, Object> params) {logger.info("map1响应数据》》"+params); @PostMapping("/map2") @ResponseBody public void hello2(@RequestParam Map<String, Object> pparams){logger.info("map2响应数据》》"+params); }

下面是将Java代码转换成Python的结果：

from datetime import datetime
import logging

from flask import Flask, request, jsonify

app = Flask(__name__)

df = "%Y-%m-%d %H:%M:%S"
logger = logging.getLogger(__name__)

@app.route('/index')
def index():
    logger.info("hello world")
    return "hello world"

@app.route('/json1', methods=['POST'])
def json1():
    content = request.get_json()
    logger.info("json1关键数据订阅返回响应》》》" + str(content))
    return jsonify(success=True)

@app.route('/json2', methods=['POST'])
def json2():
    content = request.get_json()
    logger.info("json2响应数据》》》" + str(content))
    return jsonify(success=True)

@app.route('/map10', methods=['POST'])
def map10():
    params = request.get_json()
    logger.info("map10响应数据》》》" + str(params))
    return jsonify(success=True)

@app.route('/map1', methods=['POST'])
def map1():
    params = request.form.to_dict()
    logger.info("map1响应数据》》》" + str(params))
    return jsonify(success=True)

@app.route('/map2', methods=['POST'])
def map2():
    params = request.form.to_dict()
    logger.info("map2响应数据》》》" + str(params))
    return jsonify(success=True)

if __name__ == '__main__':
    app.run()

需要注意的是，Python中的时间格式化和Java有所不同，需要根据具体需求进行转换。此外，Python中的日志模块也有所不同，需要根据具体需求进行调整。此外，Python中使用`request.get_json()`来获取POST请求中的JSON数据，使用`request.form.to_dict()`来获取POST请求中的表单数据。

@Slf4j@RestControllerpublic class UpLoadController { @PostMapping("/upload") public Result upload(@RequestParam("upFileName") MultipartFile file) throws Exception { log.info("upFileName:{}", file); String originalFilename = file.getOriginalFilename(); file.transferTo(new File("/Users/guo/IdeaProjects/MyProject/repo/" + originalFilename)); return Result.success(); }}

### Spring Boot 文件上传 Controller 的改进建议

在Spring Boot应用程序中实现文件上传功能时，`@RestController` 和 `MultipartFile` 是常用的组件。为了提高代码的质量和可维护性，可以从多个方面进行优化。

#### 使用DTO对象封装请求体

直接操作原始的`MultipartFile`虽然简单直观，但在实际项目开发过程中推荐创建专门的数据传输对象（Data Transfer Object, DTO），这样做的好处是可以更好地管理输入验证逻辑以及保持接口定义清晰[^1]。

public class FileUploadRequest {
    private MultipartFile file;

    // getter and setter methods here...
}

#### 添加详细的异常处理机制

当遇到诸如文件大小超出限制或者不支持的文件类型等问题时，默认情况下框架只会抛出较为通用的错误信息给客户端。通过自定义全局异常处理器能够提供更友好且具体的反馈消息[^2]。

@ControllerAdvice
public class GlobalExceptionHandler {

    @ExceptionHandler(MultipartException.class)
    public ResponseEntity<String> handleFileTooLargeException(MultipartException ex){
        return new ResponseEntity<>("Failed to upload due to exceeding maximum size.", HttpStatus.BAD_REQUEST);
    }
    
    // other exception handlers...
}

#### 实现异步文件保存过程

对于大文件或多文件的同时提交场景下同步方式可能会造成主线程阻塞从而影响性能表现。借助于Java8引入的CompletableFuture特性可以让磁盘I/O密集型任务运行在一个独立的工作线程池里完成而不干扰到Web容器内部正常的业务流程调度工作[^3].

@Service
@Slf4j
public class AsyncFileService {

    ExecutorService executor = Executors.newFixedThreadPool(5);

    public CompletableFuture<Void> saveAsync(FileUploadRequest request) throws IOException{
        return CompletableFuture.runAsync(() -> {
            try {
                log.info("Saving file asynchronously...");
                request.getFile().transferTo(new java.io.File("/tmp/" + System.currentTimeMillis()));
            } catch (IOException e) {
                throw new RuntimeException(e.getMessage(),e);
            }
        },executor);
    }

}

#### 控制器层简化后的示例代码：

@RestController
@RequestMapping("/api/files")
@AllArgsConstructor(onConstructor_=@Autowired)
public class FileController {

    private final AsyncFileService asyncFileService;

    @PostMapping(consumes = MediaType.MULTIPART_FORM_DATA_VALUE)
    public ResponseEntity<?> upload(@Validated @ModelAttribute FileUploadRequest request){
        
        try {
            asyncFileService.saveAsync(request).get();
            return ResponseEntity.ok("File uploaded successfully.");
        }catch(Exception e){
            return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body(e.getMessage());
        }
    }
}