使用Django怎么对gzip数据流进行处理-创新互联
这期内容当中小编将会给大家带来有关使用Django怎么对gzip数据流进行处理,文章内容丰富且以专业的角度为大家分析和叙述,阅读完这篇文章希望大家可以有所收获。
让客户满意是我们工作的目标,不断超越客户的期望值来自于我们对这个行业的热爱。我们立志把好的技术通过有效、简单的方式提供给客户,将通过不懈努力成为客户在信息化领域值得信任、有价值的长期合作伙伴,公司提供的服务项目有:域名申请、网络空间、营销软件、网站建设、正定网站维护、网站推广。class XXDataPushView(APIView): """ 接收xx数据推送 """ # ... @white_list_required def post(self, request, **kwargs): req_data = request.data or {} # ...
但随后,发现每日数据并没有任何变化,质问供应商是否没有做推送,在忽悠我们。然后对方给的答复是,他们推送的是gzip
压缩的数据流,接收端需要主动进行解压。此前从没有处理过这种压缩的数据,对方具体如何做的推送对我来说也是一个黑盒。
因此,我要求对方给一个推送的简单示例,没想到对方不讲武德,仍过来一段没法单独运行的java代码:
private byte[] compress(JSONObject body) { try { ByteArrayOutputStream out = new ByteArrayOutputStream(); GZIPOutputStream gzip = new GZIPOutputStream(out); gzip.write(body.toString().getBytes()); gzip.close(); return out.toByteArray(); } catch (Exception e) { logger.error("Compress data failed with error: " + e.getMessage()).commit(); } return JSON.toJSONString(body).getBytes(); } public void post(JSONObject body, String url, FutureCallbackcallback) { RequestBuilder requestBuilder = RequestBuilder.post(url); requestBuilder.addHeader("Content-Type", "application/json; charset=UTF-8"); requestBuilder.addHeader("Content-Encoding", "gzip"); byte[] compressData = compress(body); int timeout = (int) Math.max(((float)compressData.length) / 5000000, 5000); RequestConfig.Builder requestConfigBuilder = RequestConfig.custom(); requestConfigBuilder.setSocketTimeout(timeout).setConnectTimeout(timeout); requestBuilder.setEntity(new ByteArrayEntity(compressData)); requestBuilder.setConfig(requestConfigBuilder.build()); excuteRequest(requestBuilder, callback); } private void excuteRequest(RequestBuilder requestBuilder, FutureCallback callback) { HttpUriRequest request = requestBuilder.build(); httpClient.execute(request, new FutureCallback () { @Override public void completed(HttpResponse httpResponse) { try { int responseCode = httpResponse.getStatusLine().getStatusCode(); if (callback != null) { if (responseCode == 200) { callback.completed(httpResponse); } else { callback.failed(new Exception("Status code is not 200")); } } } catch (Exception e) { logger.error("Get error on " + requestBuilder.getMethod() + " " + requestBuilder.getUri() + ": " + e.getMessage()).commit(); if (callback != null) { callback.failed(e); } } EntityUtils.consumeQuietly(httpResponse.getEntity()); } @Override public void failed(Exception e) { logger.error("Get error on " + requestBuilder.getMethod() + " " + requestBuilder.getUri() + ": " + e.getMessage()).commit(); if (callback != null) { callback.failed(e); } } @Override public void cancelled() { logger.error("Request cancelled on " + requestBuilder.getMethod() + " " + requestBuilder.getUri()).commit(); if (callback != null) { callback.cancelled(); } } }); }
从上述代码可以看出,对方将json
数据压缩为了gzip
数据流stream
。于是搜索django
的文档,只有这段关于gzip
处理的装饰器描述:
django.views.decorators.gzip
里的装饰器控制基于每个视图的内容压缩。
gzip_page()
如果浏览器允许 gzip 压缩,那么这个装饰器将压缩内容。它相应的设置了 Vary 头部,这样缓存将基于 Accept-Encoding 头进行存储。
但是,这个装饰器只是压缩请求响应至浏览器的内容,我们目前的需求是解压缩接收的数据。这不是我们想要的。
幸运的是,在flask
中有一个扩展叫flask-inflate
,安装了此扩展会自动对请求来的数据做解压操作。查看该扩展的具体代码处理:
# flask_inflate.py import gzip from flask import request GZIP_CONTENT_ENCODING = 'gzip' class Inflate(object): def __init__(self, app=None): if app is not None: self.init_app(app) @staticmethod def init_app(app): app.before_request(_inflate_gzipped_content) def inflate(func): """ A decorator to inflate content of a single view function """ def wrapper(*args, **kwargs): _inflate_gzipped_content() return func(*args, **kwargs) return wrapper def _inflate_gzipped_content(): content_encoding = getattr(request, 'content_encoding', None) if content_encoding != GZIP_CONTENT_ENCODING: return # We don't want to read the whole stream at this point. # Setting request.environ['wsgi.input'] to the gzipped stream is also not an option because # when the request is not chunked, flask's get_data will return a limited stream containing the gzip stream # and will limit the gzip stream to the compressed length. This is not good, as we want to read the # uncompressed stream, which is obviously longer. request.stream = gzip.GzipFile(fileobj=request.stream)
上述代码的核心是:
request.stream = gzip.GzipFile(fileobj=request.stream)
于是,在django
中可以如下处理:
class XXDataPushView(APIView): """ 接收xx数据推送 """ # ... @white_list_required def post(self, request, **kwargs): content_encoding = request.META.get("HTTP_CONTENT_ENCODING", "") if content_encoding != "gzip": req_data = request.data or {} else: gzip_f = gzip.GzipFile(fileobj=request.stream) data = gzip_f.read().decode(encoding="utf-8") req_data = json.loads(data) # ... handle req_data
ok, 问题完美解决。还可以用如下方式测试请求:
import gzip import requests import json data = {} data = json.dumps(data).encode("utf-8") data = gzip.compress(data) resp = requests.post("http://localhost:8760/push_data/",data=data,headers={"Content-Encoding": "gzip", "Content-Type":"application/json;charset=utf-8"}) print(resp.json())
上述就是小编为大家分享的使用Django怎么对gzip数据流进行处理了,如果刚好有类似的疑惑,不妨参照上述分析进行理解。如果想知道更多相关知识,欢迎关注创新互联行业资讯频道。
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