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The current loop is commonly used. When the default data is empty, set the default value length to take the variable length filesizeformat file size to the time that the readable slice takes from the specified location to the pointing slice datedatetime, to the specified format safe to prevent XSS attacks, and add safe to pass the tag truncatechars to display the rest.

Examples

{# format value | function #} {# if there is no value, then use the default value #}

{{bucunzai | empty default:''}}

{# take out variable length #} {{name}}-- {{name | length}} {# file size converted to readable kb automatically converted to bm, g, tb#}

File size {{file_size | filesizeformat}}

{# slice from specified position to finger location, for example: bit 3 to-2 bit #}

Slice: {{slice_str | slice:'3:-2'}}

{# the time of fetching the datetime to the specified format #}

Formatting: {{now | date:'Y-m-d Havaniriza s'}}

{# if the backend content contains tags, then add safe to escape (prevent users from cheating directly with script tags) to prevent XSS attacks #}

{{h_html | safe}}

{# the summary is displayed only one paragraph, after the specified length. Example: 120 characters #}

Long text: {{p_str | truncatechars:12}}

1. View

Class UserView (ListAPIView): "" user list "" queryset = User.objects.all () serializer_class = UserSerializer filter_backends = (DjangoFilterBackend,) filter_class = UserMonthFilter # specify the filter class

2. Filter class

Class RobotFilter (django_filters.FilterSet): # use filtering: URL?created_start_time=2020_01-20&created_end_time=2020_01-21 robot_id = django_filters.CharFilter (field_name='id') machine_id = django_filters.CharFilter (field_name='machine_id') city = django_filters.CharFilter (field_name='city') # lookup_expr (optional) is the judgment condition, field_name (required) is the model class attribute Created_time query string created_time= django_filters.CharFilter (field_name='created_at', lookup_expr='startswith') created_start_time = django_filters.DateTimeFilter (field_name='created_at', lookup_expr='gt') created_end_time = django_filters.DateTimeFilter (field_name='created_at', lookup_expr='lt') problem_isnull = django_filters.BooleanFilter (field_name='problem' Lookup_expr='isnull') name = django_filters.CharFilter (lookup_expr='iexact') # iexact for exact match, and ignore case author = django_filters.CharFilter (lookup_expr='icontains') # icontains for fuzzy query (inclusive) And ignore the case price = django_filters.NumberFilter (look_expr='exact') # exact to indicate an exact match task_res_state = django_filters.CharFilter (method= "get_task_res_state") def get_task_res_state (self, queryset, * arg): if str (arg [1]) = "0": # arg [1] = ('task_res_state',' 0') task_res = (1) 2, 3) else: task_res = (0,4,5,6) print (task_res) queryset = queryset.filter (task_res__in=task_res) return queryset class Meta: model = Robot fields = ['robot_id',' machine_id', "city", "created_start_time", "created_end_time", 'created_time' 'firmware_version',' state', "robot_type", "hardware_version", "exist_map", 'task_res_state'] are the contents of this article on "how to implement data filtering with django filters" I believe we all have a certain understanding. I hope the content shared by the editor will be helpful to you. If you want to know more about the relevant knowledge, please pay attention to the industry information channel.

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