13518219792
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。
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, FutureCallback callback) {
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_dataok, 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。
