知识点

本文是一个很另类的文章,在项目中用的比较少,但如果项目中真的出现了这种情况,我们也需要知道如何去解决,对于知识点StringContent和FormUrlEncodedContent我们应该了解的多一点,FormUrlEncodedContent是以键/值对的形式进行POST数据的提供,同时要求服务端以x-www-form-urlencoded的方式去接收数据!而StringContent是ByteArrayContent的一个子集,也是MultipartFormDataContent的一个子集,在进行大数据传输时,我们需要使用这种方法,如果传递的是字符串,可以采用StringContent,如果是二进制流,可以使用ByteArrayContent,而这两种方式都可以对外以MultipartFormDataContent的形式体现,而在服务端要以mutipart/form-data的方式来接收数据!

再深一点

multipart/form-data: 就是http请求中的multipart/form-data,它会将表单的数据处理为一条消息,以标签为单元,用分隔符分开。既可以上传键值对,也可以上传文件。当上传的字段是文件时,会有Content-Type来表名文件类型;content-disposition,用来说明字段的一些信息;由于有boundary(分隔符号)隔离,所以multipart/form-data既可以上传文件,也可以上传键值对,它采用了键值对的方式,所以可以上传多个文件。

x-www-form-urlencoded:会将表单数据转成键/值对进行传递,有大小的限制,一般是2M。

Raw:可以上传任何格式文本,你需要显示的说明content-type,如text/plain,text/html,text/json,text/xml等。

Binary:一般上传文件流,它相当于content-type为application/octet-stream的情况。

从上面的介绍不难发现,raw和binary方式都属于multipart/form-data,只不过是两种不同的体现而以。

DotNet平台为WebAPI传递大数据

对于普通方式的HttpClient(x-www-form-urlencoded)有时已经不能满足我们的需要了,所以必须上multipart/form-data,即在HttpClient构建时,采用StringContent的内容类型,下面是在客户端构建一个HttpClient的方式,以服务端(webapi restful)传递一个大大的JSON对象!

          var list = new List<TestApiModel>();

                entity.Category = new Category { Title = "北京" };
entity.OrderList = new List<OrderList>
{
new OrderList{Price=1,ProductName="tel",Address=new Address {Province="印度"}},
new OrderList{Price=100,ProductName="tv",Address=new Address {Province="日本"}},
new OrderList{Price=999,ProductName="pc",Address=new Address {Province="美国"}}
};
for (int i = 0; i <= 100; i++)
list.Add(entity); var handler = new HttpClientHandler()
{
AutomaticDecompression = System.Net.DecompressionMethods.GZip
};
using (var http = new HttpClient(handler))
{
var body = entity.ToNameValueCollection();
var content = new StringContent(list.ToJson(), Encoding.UTF8, "text/json");
var responseResult = http.PostAsync(UriAddress, content).Result;
}

如果客户端采用了这种StringContent的方式,那么在设计WebApi时只有两种选择,第一种就是使用JSON强类型(类对象)的参数,第二种就是不写参数(空),如果使用string类型的参数,那这个接口无法被找到,即出现的结果是404的状态码!下面看一下服务端的数据处理,也是很简单!

    public async Task<HttpResponseMessage> Post()//没有参数表示使用raw,form-data方式进行传输
{
try
{ var data =await Request.Content.ReadAsStringAsync();
var entity = Lind.DDD.Utils.SerializeMemoryHelper.DeserializeFromJson<IEnumerable<TestApiModel>>(data);
}
//....... }
 

上面代码从请求上下文中拿到了这个大数据的字符串,然后通过反序列化得到了下面的结果:

aaarticlea/png;base64,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" alt="" />

当然,对于非常友好的webapi来说,你完全可以在方法参数上显示的使用强类型,这种api框架会帮助我们进行序列化的操作,真的很友好!

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" alt="" />

这行list对象已经被架构进行了序列化操作

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" alt="" />

通过本篇文章,让我们更清楚的认识到了POST请求的几种方式,以及他们与服务端(api)如何去结合,对于java,.net平台,这些方法都是同样适用的!

来自:https://www.cnblogs.com/lori/p/5919306.html

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