api.py 文件源码

def create_search_obj(user, search_param_dict=None, filter_on_email_optin=False):
    """
    Creates a search object and prepares it with metadata and query parameters that
    we want to apply for all ES requests

    Args:
        user (User): User object
        search_param_dict (dict): A dict representing the body of an ES query
        filter_on_email_optin (bool): If true, filter out profiles where email_optin != True

    Returns:
        Search: elasticsearch_dsl Search object
    """
    staff_program_ids = get_advance_searchable_program_ids(user)
    is_advance_search_capable = bool(staff_program_ids)
    search_obj = Search(index=get_default_alias(), doc_type=_get_search_doc_types(is_advance_search_capable))
    # Update from search params first so our server-side filtering will overwrite it if necessary
    if search_param_dict is not None:
        search_obj.update_from_dict(search_param_dict)

    if not is_advance_search_capable:
        # Learners can't search for other learners with privacy set to private
        search_obj = search_obj.filter(
            ~Q('term', **{'profile.account_privacy': Profile.PRIVATE})
        )

    # Limit results to one of the programs the user is staff on
    search_obj = search_obj.filter(create_program_limit_query(
        user,
        staff_program_ids,
        filter_on_email_optin=filter_on_email_optin
    ))
    # Filter so that only filled_out profiles are seen
    search_obj = search_obj.filter(
        Q('term', **{'profile.filled_out': True})
    )
    # Force size to be the one we set on the server
    update_dict = {'size': settings.ELASTICSEARCH_DEFAULT_PAGE_SIZE}
    if search_param_dict is not None and search_param_dict.get('from') is not None:
        update_dict['from'] = search_param_dict['from']
    search_obj.update_from_dict(update_dict)

    return search_obj