Example #1
0
    def get(self, request, query, sem_name, year):
        """ Return vectorized search results. """
        school = request.subdomain
        sem = Semester.objects.get_or_create(name=sem_name, year=year)[0]
        # TODO: use vectorized search after completion.
        # Use vectorized_search if and only if a valid Searcher object is created, otherwise use baseline_search
        # if apps.get_app_config('searches').searcher:
        #     course_match_objs = apps.get_app_config('searches').searcher.vectorized_search(request.subdomain, query, sem)[:4]
        # else:
        #     course_match_objs = baseline_search(request.subdomain, query, sem)[:4]

        # sorts queries by course number through a comparator
        def course_comparator(course1, course2):
            #isolate course number from XX0000
            c1=int(str(course1)[2:6])
            c2=int(str(course2)[2:6])
            if c1 < c2:
                return -1
            elif c1 > c2:
                return 1
            else:
                return 0
        course_match_objs = baseline_search(request.subdomain, query, sem).distinct()
        #only sort if results is less than 100 for efficiency sake
        if len(course_match_objs) < 100:
            course_match_objs = sorted(course_match_objs, key=cmp_to_key(course_comparator))
        #display only 12 courses to avoid displaying too many.
        course_match_objs = course_match_objs[:12]
        save_analytics_course_search(query[:200], course_match_objs[:2], sem, request.subdomain,
                                     get_student(request))
        course_matches = [CourseSerializer(course, context={'semester': sem, 'school': school}).data
                          for course in course_match_objs]
        return Response(course_matches, status=status.HTTP_200_OK)
Example #2
0
    def post(self, request, query, sem_name, year):
        """ Return advanced search results. """
        school = request.subdomain
        page = int(request.query_params.get('page', 1))
        sem, _ = Semester.objects.get_or_create(name=sem_name, year=year)
        # Filter first by the user's search query.
        # TODO : use vectorized search (change returned obj to be filterable)
        course_match_objs = baseline_search(school, query, sem)

        # Filter now by departments, areas, levels, or times if provided.
        filters = request.data.get('filters', {})
        if filters.get('areas'):
            course_match_objs = course_match_objs.filter(areas__contains=filters.get('areas'))
        if filters.get('departments'):
            course_match_objs = course_match_objs.filter(department__in=filters.get('departments'))
        if filters.get('levels'):
            course_match_objs = course_match_objs.filter(level__in=filters.get('levels'))
        if filters.get('times'):
            day_map = {"Monday": "M", "Tuesday": "T", "Wednesday": "W", "Thursday": "R",
                       "Friday": "F"}
            course_match_objs = course_match_objs.filter(
                reduce(operator.or_,
                       (Q(section__offering__time_start__gte="{0:0=2d}:00".format(min_max['min']),
                          section__offering__time_end__lte="{0:0=2d}:00".format(min_max['max']),
                          section__offering__day=day_map[min_max['day']],
                          section__semester=sem,
                          section__section_type="L") for min_max in filters.get('times'))
                       )
            )
        course_match_objs = course_match_objs.order_by('id')
        try:
            paginator = Paginator(course_match_objs.distinct(), 20)
            course_match_objs = paginator.page(page)
        except EmptyPage:
            return Response([])

        save_analytics_course_search(query[:200], course_match_objs[:2], sem, school,
                                     get_student(request),
                                     advanced=True)
        student = None
        logged = request.user.is_authenticated()
        if logged and Student.objects.filter(user=request.user).exists():
            student = Student.objects.get(user=request.user)
        serializer_context = {'semester': sem, 'student': student, 'school': request.subdomain}
        json_data = [CourseSerializer(course, context=serializer_context).data
                     for course in course_match_objs]

        return Response(json_data, status=status.HTTP_200_OK)
Example #3
0
 def get(self, request, query, sem_name, year):
     """ Return vectorized search results. """
     school = request.subdomain
     sem = Semester.objects.get_or_create(name=sem_name, year=year)[0]
     # TODO: use vectorized search after completion.
     # Use vectorized_search if and only if a valid Searcher object is created, otherwise use baseline_search
     # if apps.get_app_config('searches').searcher:
     #     course_match_objs = apps.get_app_config('searches').searcher.vectorized_search(request.subdomain, query, sem)[:4]
     # else:
     #     course_match_objs = baseline_search(request.subdomain, query, sem)[:4]
     course_match_objs = baseline_search(request.subdomain, query, sem).distinct()[:4]
     save_analytics_course_search(query[:200], course_match_objs[:2], sem, request.subdomain,
                                  get_student(request))
     course_matches = [CourseSerializer(course, context={'semester': sem, 'school': school}).data
                       for course in course_match_objs]
     return Response(course_matches, status=status.HTTP_200_OK)
Example #4
0
 def get(self, request, query, sem_name, year):
     """ Return vectorized search results. """
     school = request.subdomain
     sem = Semester.objects.get_or_create(name=sem_name, year=year)[0]
     # TODO: use vectorized search after completion.
     # Use vectorized_search if and only if a valid Searcher object is created, otherwise use baseline_search
     # if apps.get_app_config('searches').searcher:
     #     course_match_objs = apps.get_app_config('searches').searcher.vectorized_search(request.subdomain, query, sem)[:4]
     # else:
     #     course_match_objs = baseline_search(request.subdomain, query, sem)[:4]
     course_match_objs = baseline_search(request.subdomain, query, sem).distinct()[:4]
     save_analytics_course_search(query[:200], course_match_objs[:2], sem, request.subdomain,
                                  get_student(request))
     course_matches = [CourseSerializer(course, context={'semester': sem, 'school': school}).data
                       for course in course_match_objs]
     return Response(course_matches, status=status.HTTP_200_OK)
Example #5
0
    def post(self, request, query, sem_name, year):
        """ Return advanced search results. """
        school = request.subdomain
        page = int(request.query_params.get('page', 1))
        sem, _ = Semester.objects.get_or_create(name=sem_name, year=year)
        # Filter first by the user's search query.
        # TODO : use vectorized search (change returned obj to be filterable)
        course_match_objs = baseline_search(school, query, sem)

        # Filter now by departments, areas, levels, or times if provided.
        filters = request.data.get('filters', {})
        if filters.get('areas'):
            course_match_objs = course_match_objs.filter(areas__in=filters.get('areas'))
        if filters.get('departments'):
            course_match_objs = course_match_objs.filter(department__in=filters.get('departments'))
        if filters.get('levels'):
            course_match_objs = course_match_objs.filter(level__in=filters.get('levels'))
        if filters.get('times'):
            day_map = {"Monday": "M", "Tuesday": "T", "Wednesday": "W", "Thursday": "R",
                       "Friday": "F"}
            course_match_objs = course_match_objs.filter(
                reduce(operator.or_,
                       (Q(section__offering__time_start__gte="{0:0=2d}:00".format(min_max['min']),
                          section__offering__time_end__lte="{0:0=2d}:00".format(min_max['max']),
                          section__offering__day=day_map[min_max['day']],
                          section__semester=sem,
                          section__section_type="L") for min_max in filters.get('times'))
                       )
            )
        try:
            paginator = Paginator(course_match_objs.distinct(), 20)
            course_match_objs = paginator.page(page)
        except EmptyPage:
            return Response([])

        save_analytics_course_search(query[:200], course_match_objs[:2], sem, school,
                                     get_student(request),
                                     advanced=True)
        student = None
        logged = request.user.is_authenticated()
        if logged and Student.objects.filter(user=request.user).exists():
            student = Student.objects.get(user=request.user)
        serializer_context = {'semester': sem, 'student': student, 'school': request.subdomain}
        json_data = [CourseSerializer(course, context=serializer_context).data
                     for course in course_match_objs]

        return Response(json_data, status=status.HTTP_200_OK)