### Das Problem reproduzieren

In den meisten Fällen und bei den meisten Fragen ist etwas mit dem von der Person erstellten **eigenen Quellcode** los.

In vielen Fällen wird nur ein Fragment des Codes gepostet, aber das reicht nicht aus, um **das Problem zu reproduzieren**.

        assertWithMessage("Pearson's correlation coefficient of " + values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
        assertWithMessage("Pearson's correlation coefficient by addAll(PairedStats) of " + values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
      } else {
        assertWithMessage("Pearson's correlation coefficient of " + values)

        assertWithMessage("Pearson's correlation coefficient of " + values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
        assertWithMessage("Pearson's correlation coefficient by addAll(PairedStats) of " + values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
      } else {
        assertWithMessage("Pearson's correlation coefficient of " + values)

<img src="/img/python-types/image06.png">

Lưu ý rằng, điều này có nghĩa rằng "`one_person`" là một **thực thể** của lớp `Person`.

Nó không có nghĩa "`one_person`" là một **lớp** gọi là `Person`.

## Pydantic models

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> là một thư viện Python để validate dữ liệu hiệu năng cao.

    String jacksons =
        "arfo(Marlon)aorf, (Michael)orfa, afro(Jackie)orfa, " + "ofar(Jemaine), aff(Tito)";
    Iterable<String> family =
        COMMA_SPLITTER
            .trimResults(CharMatcher.anyOf("afro").or(CharMatcher.whitespace()))
            .split(jacksons);
    assertThat(family)
        .containsExactly("(Marlon)", "(Michael)", "(Jackie)", "(Jemaine)", "(Tito)")
        .inOrder();
  }

func TestMultipleMany2Many(t *testing.T) {
	type Thing struct {
		ID int
	}

	type Person struct {
		ID       int
		Likes    []Thing `gorm:"many2many:likes"`
		Dislikes []Thing `gorm:"many2many:dislikes"`
	}

	checkStructRelation(t, &Person{},
		Relation{
			Name: "Likes", Type: schema.Many2Many, Schema: "Person", FieldSchema: "Thing",
			JoinTable: JoinTable{Name: "likes", Table: "likes"},

<img src="/img/python-types/image06.png">

Beachten Sie, das bedeutet: „`one_person` ist eine **Instanz** der Klasse `Person`“.

Es bedeutet nicht: „`one_person` ist die **Klasse** genannt `Person`“.

## Pydantic Modelle

<a href="https://pydantic-docs.helpmanual.io/" class="external-link" target="_blank">Pydantic</a> ist eine Python-Bibliothek für die Validierung von Daten.

<img src="/img/python-types/image06.png">

Notice that this means "`one_person` is an **instance** of the class `Person`".

It doesn't mean "`one_person` is the **class** called `Person`".

## Pydantic models

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> is a Python library to perform data validation.

You declare the "shape" of the data as classes with attributes.

    String jacksons =
        "arfo(Marlon)aorf, (Michael)orfa, afro(Jackie)orfa, " + "ofar(Jemaine), aff(Tito)";
    Iterable<String> family =
        COMMA_SPLITTER
            .trimResults(CharMatcher.anyOf("afro").or(CharMatcher.whitespace()))
            .split(jacksons);
    assertThat(family)
        .containsExactly("(Marlon)", "(Michael)", "(Jackie)", "(Jemaine)", "(Tito)")
        .inOrder();
  }

  public double sampleCovariance() {
    checkState(count() > 1);
    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code