Python VideoLog.sign方法代码示例

# 需要导入模块: from main.models import VideoLog [as 别名]
# 或者: from main.models.VideoLog import sign [as 别名]

#.........这里部分代码省略.........
        #   and watching videos without finishing.
        # Get (or create) user type
        try:
            user_settings = json.loads(facility_user.notes)
        except:
            user_settings = sample_user_settings()
            facility_user.notes = json.dumps(user_settings)
            facility_user.save()

        date_diff_started = datetime.timedelta(seconds=datediff(date_diff, units="seconds") * user_settings["time_in_program"])  # when this user started in the program, relative to NOW

        for topic in topics:
            videos = get_topic_videos(topic_id=topic)

            exercises = get_topic_exercises(topic_id=topic)
            exercise_ids = [ex["id"] if "id" in ex else ex['name'] for ex in exercises]
            exercise_logs = ExerciseLog.objects.filter(user=facility_user, id__in=exercise_ids)

            # Probability of watching a video, irrespective of the context
            p_video_outer = probability_of("video", user_settings=user_settings)
            logging.debug("# videos: %d; p(videos)=%4.3f, user settings: %s\n" % (len(videos), p_video_outer, json.dumps(user_settings)))

            for video in videos:
                p_completed = probability_of("completed", user_settings=user_settings)

                # If we're just doing random videos, fine.
                # If these videos relate to exercises, then suppress non-exercise-related videos
                #   for this user.
                p_video = p_video_outer  # start with the context-free value
                did_exercise = False
                if exercise_logs.count() > 0:
                    # 5x less likely to watch a video if you haven't done the exercise,
                    if "related_exercise" not in video:
                        p_video /= 5  # suppress

                    # 5x more likely to watch a video if they've done the exercise
                    # 2x more likely to have finished it.
                    else:
                        exercise_log = ExerciseLog.objects.filter(user=facility_user, id=video["related_exercise"]["id"])
                        did_exercise = exercise_log.count() != 0
                        if did_exercise:
                            p_video *= 5
                            p_completed *= 2

                # Do the sampling
                if p_video < random.random():
                    continue
                    # didn't watch it
                elif p_completed > random.random():
                    pct_completed = 100.
                else:      # Slower students will use videos more.  Effort also important.
                    pct_completed = 100. * min(1., sqrt(random.random() * sqrt(user_settings["effort_level"] * user_settings["time_in_program"] / sqrt(user_settings["speed_of_learning"]))))
                # Compute quantities based on sample
                total_seconds_watched = int(video["duration"] * pct_completed / 100.)
                points = int(750 * pct_completed / 100.)

                # Choose a rate of videos, based on their effort level.
                #   Compute the latest possible start time.
                #   Then sample a start time between their start time
                #   and the latest possible start_time
                if did_exercise:
                    # More jitter if you learn fast, less jitter if you try harder (more diligent)
                    date_jitter = datetime.timedelta(days=max(0, random.gauss(1, user_settings["speed_of_learning"] / user_settings["effort_level"])))
                    date_completed = exercise_log[0].completion_timestamp - date_jitter
                else:
                    rate_of_videos = 0.66 * user_settings["effort_level"] + 0.33 * user_settings["speed_of_learning"]  # exercises per day
                    time_for_watching = total_seconds_watched
                    time_delta_completed = datetime.timedelta(seconds=random.randint(int(time_for_watching), int(datediff(date_diff_started, units="seconds"))))
                    date_completed = datetime.datetime.now() - time_delta_completed

                try:
                    vlog = VideoLog.objects.get(user=facility_user, youtube_id=video["youtube_id"])
                except VideoLog.DoesNotExist:

                    logging.info("Creating video log: %-12s: %-45s (%4.1f%% watched, %d points)%s" % (
                        facility_user.first_name,
                        video["title"],
                        pct_completed,
                        points,
                        " COMPLETE on %s!" % date_completed if pct_completed == 100 else "",
                    ))
                    vlog = VideoLog(
                        user=facility_user,
                        youtube_id=video["youtube_id"],
                        total_seconds_watched=total_seconds_watched,
                        points=points,
                        complete=(pct_completed == 100.),
                        completion_timestamp=date_completed,
                        completion_counter=datediff(date_completed, start_date, units="seconds"),
                    )
                    vlog.full_clean()
                    # TODO(bcipolli): bulk saving of logs
                    vlog.counter = own_device.increment_and_get_counter()
                    vlog.sign(own_device)  # have to sign after setting the counter
                    vlog.save(imported=True)  # avoid userlog issues


                video_logs.append(vlog)

    return video_logs