arklight

class CourseViewSet(viewsets.ModelViewSet):
    queryset = Course.objects.filter(is_deleted=False)
    serializer_class = CourseSerializer
    swagger_tags = ["Course"]

    def create(self, request, *args, **kwargs):
        data = request.data
        course = Course.objects.create(
            name=data["name"],
            description=data["description"],
            information=data["information"],
            author_id=data["author"]
        )
        course.save()
        tags = set(data["tags"])
        for tag in tags:
            created_tag = Tags.objects.get_or_create(name=tag)[0]
            course.tags.add(created_tag.id)
        return Response(status=status.HTTP_201_CREATED)

    def partial_update(self, request, *args, **kwargs):
        course = Course.objects.get(id=int(kwargs["pk"]))
        if request.user.id == course.author.id:
            return super().partial_update(request, *args, **kwargs)
        return Response(status=status.HTTP_403_FORBIDDEN)

class CourseViewSet(viewsets.ModelViewSet):
    queryset = Course.objects.filter(is_deleted=False)
    serializer_class = CourseSerializer
    authentication_classes = [JWTAuthentication]
    swagger_tags = ["Course"]
    ...

%include "io.inc"

section .data
    arr db "genius" ; основная строка
    len equ $-arr ; длина этой строки

section .bss
    str2 resb 64 ; резирвирую память для развёрнутой строки

section .text
    global CMAIN
CMAIN:
    mov ebp, esp; for correct debugging
    mov ebx, len
    dec ebx
    mov esi, 0
cycle:
    cmp ebx, 0
    jl end
    mov al, byte[arr+ebx]
    mov [str2+esi], al
    inc esi
    dec ebx
    jmp cycle
end:
    PRINT_STRING str2
    xor eax, eax
    ret

For Spring MVC 5, the Spring MVC DispatcherServlet has a dependency on the javax.servlet.* package namespace. This is using the Java EE 8 javax package naming. Since Tomcat 10 is based on Jakarta EE 9, the packages for javax naming are not supported. This explains why Spring MVC 5 does not work on Tomcat 10.

#!/usr/bin/bash

name=$1
nest generate module "$name"
nest generate controller "$name"
nest generate service "$name"

echo "import {Entity, PrimaryGeneratedColumn, Column} from \"typeorm\";

@Entity()
export class ${name^} {

    @PrimaryGeneratedColumn()
    id: number;
}" > "src/$name/$name.entity.ts"

<a href="{% url "check_resume" resume.client_id %}">Посмотреть</a>

<a href="{% url "check_resume" resume.pk %}">Посмотреть</a>

path('resumes/<slug:pk>', views.ResumesDetail.as_view(), name="check_resume"),

def get_form_kwargs(self):
        kwargs = super().get_form_kwargs()
        if self.request.method == "POST" and hasattr(self, 'object'):
            data = kwargs["data"].dict()
            data.update({"client_id": self.request.user.id})
            kwargs["data"] = data
        return kwargs

$("#root").on("click", (e) => {
        console.log(e.target.tagName)
        if (e.target.tagName === "DIV") {
            let rng = document.createRange()
            let sel = window.getSelection()
            rng.selectNodeContents($(e.target)[0])
            sel.removeAllRanges()
            sel.addRange(rng)
        }
    })

function selectData() {
    tName = $("#selectTabName").val()
    $.getJSON(
        "/select_data",
        {"tableName": tName},
        function(data) {
            console.log(data)
        }
    )
}

@staticmethod
    def paint_normal_distribution(mexp, otkl):
        """
        Строит график кривой нормального распределения
        """
        head = 0.4 / otkl
        left = mexp - 3 * otkl
        right = mexp + 3 * otkl
        arr = np.arange(left, right, 0.001)
        plt.plot(arr, norm.pdf(arr, mexp, otkl))
        print("Левая граница = {}, правая граница = {}, высота = {}".format(left, right, head))
        plt.show()

def read_csv(data):
    with open("data.csv", "r") as csvfile:
        file = csv.reader(csvfile, delimiter=";")
        for row in file:
            data.append(row)
    print_data(data)

def write_csv(data):
    with open("data.csv", "w") as csvfile:
        wrt = csv.writer(csvfile, delimiter=";", quotechar="|", lineterminator="\r")
        wrt.writerows(data)

item = np.array([], int)
data = np.column_stack((data, item))

struct s
{
  string name;
  int balli;
};

bool cmp(s a, s b) {
  if (a.balli > b.balli)
    return true;
  else 
    if (a.balli == b.balli && a.name < b.name)
      return true;
    else
      return false;
}