server.py 文件源码

def post(self):
        data = tornado.escape.json_decode(self.request.body)
        is_debug = data["debug"]
        query = data["query"]
        message = {"posts": []}
        if is_debug:
            from elephant_sense.debug import search_posts_dummy
            posts = search_posts_dummy(query, count=30)
            posts = self.scoring(posts)
            message["posts"] = [self.trim(p) for p in posts]
            self.write(message)
        else:
            posts = search_posts(query, n=50)  # limit for performance. need improvements for feature extraction.
            process = 4
            batch_size = len(posts) / process
            tasks = [(int(i * batch_size), int(i * batch_size + batch_size)) for i in range(process)]
            dones = Parallel(n_jobs=process)(delayed(parallel_scoring)(self.evaluator, posts[t[0]:t[1]]) for t in tasks)
            posts = []
            for scoreds in dones:
                posts += [self.trim(s) for s in scoreds]
            posts = sorted(posts, key=lambda p: p["score"], reverse=True)
            message["posts"] = posts
            self.write(message)