regex: Annotated[
        Optional[str],
        Doc(
            """
            RegEx pattern for strings.
            """
        ),
        deprecated(
            "Deprecated in FastAPI 0.100.0 and Pydantic v2, use `pattern` instead."
        ),
    ] = None,
    discriminator: Annotated[
        Union[str, None],
        Doc(
            """

    assertThat(inputStream.read()).isEqualTo(-1)
    val elapsedNanos = System.nanoTime() - startNanos
    val elapsedMillis = TimeUnit.NANOSECONDS.toMillis(elapsedNanos)
    assertThat(elapsedMillis).isBetween(500L, 1000L)
  }

  /**
   * Throttle the response body by sleeping 500ms after every 3 bytes. With a 6-byte response, this
   * should yield one sleep for a total delay of 500ms.
   */
  @Test

    assertUnescaped(e, '.');
    assertUnescaped(e, '*');

    assertEscaping(e, "%00", '\u0000'); // nul
    assertEscaping(e, "%7F", '\u007f'); // del
    assertEscaping(e, "%C2%80", '\u0080'); // xx-00010,x-000000
    assertEscaping(e, "%DF%BF", '\u07ff'); // xx-11111,x-111111
    assertEscaping(e, "%E0%A0%80", '\u0800'); // xxx-0000,x-100000,x-00,0000
    assertEscaping(e, "%EF%BF%BF", '\uffff'); // xxx-1111,x-111111,x-11,1111

            @Override
            public String symbol() {
                return "B";
            }
        },
        KILOBYTE {
            @Override
            public long bytes() {
                return 1000L;
            }

            @Override
            public String symbol() {
                return "kB";
            }
        },
        MEGABYTE {
            @Override
            public long bytes() {

-h | display help dialog

## Benchmarks

Obligatory benchmarks performed on files with arrays of objects, where the decoded objects are to be extracted.

Two file sizes are used -- regular (1.6mb, 1000 objects) and large (128mb, 100000 objects)

input size | lib | MB/s | Allocated
--- | --- | --- | ---
regular | standard | 97 | 3.6MB
regular | jstream | 175 | 2.1MB
large | standard | 92 | 305MB
large | jstream | 404 | 69MB

# Migra de Pydantic v1 a Pydantic v2 { #migrate-from-pydantic-v1-to-pydantic-v2 }

Si tienes una app de FastAPI antigua, podrías estar usando Pydantic versión 1.

FastAPI ha tenido compatibilidad con Pydantic v1 o v2 desde la versión 0.100.0.

Si tenías instalado Pydantic v2, lo usaba. Si en cambio tenías Pydantic v1, usaba ese.

# Migrar do Pydantic v1 para o Pydantic v2 { #migrate-from-pydantic-v1-to-pydantic-v2 }

Se você tem uma aplicação FastAPI antiga, pode estar usando o Pydantic versão 1.

O FastAPI tem suporte ao Pydantic v1 ou v2 desde a versão 0.100.0.

Se você tiver o Pydantic v2 instalado, ele será utilizado. Se, em vez disso, tiver o Pydantic v1, será ele que será utilizado.

      }
    }

    // Testing multibyte escape sequences
    assertEscaping(e, "%00", '\u0000'); // nul
    assertEscaping(e, "%7F", '\u007f'); // del
    assertEscaping(e, "%C2%80", '\u0080'); // xx-00010,x-000000
    assertEscaping(e, "%DF%BF", '\u07ff'); // xx-11111,x-111111
    assertEscaping(e, "%E0%A0%80", '\u0800'); // xxx-0000,x-100000,x-00,0000
    assertEscaping(e, "%EF%BF%BF", '\uffff'); // xxx-1111,x-111111,x-11,1111

      this.multiset = multiset;
      this.keys = keys;
    }

    @Override
    public int[] call() {
      int iterations = 100000;
      int nKeys = keys.size();
      int[] deltas = new int[nKeys];
      Operation[] operations = Operation.values();
      for (int i = 0; i < iterations; i++) {
        int keyIndex = random.nextInt(nKeys);

# Von Pydantic v1 zu Pydantic v2 migrieren { #migrate-from-pydantic-v1-to-pydantic-v2 }

Wenn Sie eine ältere FastAPI-App haben, nutzen Sie möglicherweise Pydantic Version 1.

FastAPI Version 0.100.0 unterstützte sowohl Pydantic v1 als auch v2. Es verwendete, was auch immer Sie installiert hatten.

FastAPI Version 0.119.0 führte eine teilweise Unterstützung für Pydantic v1 innerhalb von Pydantic v2 (als `pydantic.v1`) ein, um die Migration zu v2 zu erleichtern.