implementation must:
</p>

<ul>
	<li>Represent integer constants with at least 256 bits.</li>

	<li>Represent floating-point constants, including the parts of
	    a complex constant, with a mantissa of at least 256 bits
	    and a signed binary exponent of at least 16 bits.</li>

	<li>Give an error if unable to represent an integer constant
	    precisely.</li>

Ein besonderer Vorteil, der nicht unbedingt offensichtlich ist, besteht darin, dass Sie für Ihre API **Clients generieren** können (manchmal auch <abbr title="Software Development Kits">**SDKs**</abbr> genannt), für viele verschiedene **Programmiersprachen**.

## OpenAPI-Client-Generatoren

Es gibt viele Tools zum Generieren von Clients aus **OpenAPI**.

# Introduction aux Types Python

Python supporte des annotations de type (ou *type hints*) optionnelles.

Ces annotations de type constituent une syntaxe spéciale qui permet de déclarer le <abbr title="par exemple : str, int, float, bool">type</abbr> d'une variable.

En déclarant les types de vos variables, cela permet aux différents outils comme les éditeurs de texte d'offrir un meilleur support.

	for range 100 {
		for range dynamicTimeoutLogSize {
			timeout.LogSuccess(successTimeout)
		}
	}

	adjusted := timeout.Timeout()
	// Check whether eventual timeout has hit the minimum value
	if initial <= adjusted || adjusted != minimum {
		t.Errorf("Failure to decrease timeout appropriately")
	}
}

func testDynamicTimeoutAdjust(t *testing.T, timeout *dynamicTimeout, f func() float64) {

        try {
            // This will likely fail due to missing SearchEngineClient setup,
            // but we can verify the method signature and basic functionality
            SearchEngineUtil.scroll("test_index", hit -> {
                callbackCount.incrementAndGet();
                return true; // Continue processing
            });
        } catch (Exception e) {

				if bits&(1<<lo) != 0 {
					p.errorf("register R%d already in list", lo)
				}
				bits |= 1 << lo
				lo++
			}
		default:
			p.errorf("unexpected register list")
		}
		if p.peek() != ']' {
			p.get(',')
		}
	}
	a.Type = obj.TYPE_REGLIST
	switch p.arch.Family {
	case sys.ARM:
		a.Offset = int64(bits)
	case sys.ARM64:

And will also be used in the API docs inside each *path operation* that needs them:

<img src="/img/tutorial/body/image02.png">

## Editor support { #editor-support }

In your editor, inside your function you will get type hints and completion everywhere (this wouldn't happen if you received a `dict` instead of a Pydantic model):

<img src="/img/tutorial/body/image03.png">

You also get error checks for incorrect type operations:

   * interpreted as an unsigned 64-bit value. Specifically, the sign bit of {@code bits} is
   * interpreted as a normal bit, and all other bits are treated as usual.
   *
   * <p>If the argument is nonnegative, the returned result will be equal to {@code bits},
   * otherwise, the result will be equal to {@code 2^64 + bits}.
   *
   * <p>To represent decimal constants less than {@code 2^63}, consider {@link #valueOf(long)}

 * the operation and the desired access bits are compared to the SID
 * and access mask of each ACE. If the SID matches, the allow/deny flags
 * and access mask are considered. If the ACE is a "deny"
 * ACE and <i>any</i> of the desired access bits match bits in the access
 * mask of the ACE, the whole access check fails. If the ACE is an "allow"
 * ACE and <i>all</i> of the bits in the desired access bits match bits in

   * interpreted as an unsigned 32-bit value. Specifically, the sign bit of {@code bits} is
   * interpreted as a normal bit, and all other bits are treated as usual.
   *
   * <p>If the argument is nonnegative, the returned result will be equal to {@code bits},
   * otherwise, the result will be equal to {@code 2^32 + bits}.
   *
   * <p>To represent unsigned decimal constants, consider {@link #valueOf(long)} instead.
   *