// ETag.
//
// In general, a caller has to distinguish the following cases:
//   - The object is a multipart object. In this case,
//     Format returns the ETag unmodified.
//   - The object is a SSE-KMS or SSE-C encrypted single-
//     part object. In this case, Format returns the last
//     16 bytes of the encrypted ETag which will be a random
//     value.

   * opening the data stream.
   *
   * <p>The default implementation returns {@link Optional#absent}. Some sources, such as a {@code
   * CharSequence}, may return a non-absent value. Note that in such cases, it is <i>possible</i>
   * that this method will return a different number of chars than would be returned by reading all
   * of the chars.
   *

   * opening the data stream.
   *
   * <p>The default implementation returns {@link Optional#absent}. Some sources, such as a {@code
   * CharSequence}, may return a non-absent value. Note that in such cases, it is <i>possible</i>
   * that this method will return a different number of chars than would be returned by reading all
   * of the chars.
   *

func Index(s, sep []byte) int {
	n := len(sep)
	switch {
	case n == 0:
		return 0
	case n == 1:
		return IndexByte(s, sep[0])
	case n == len(s):
		if Equal(sep, s) {
			return 0
		}
		return -1
	case n > len(s):
		return -1
	case n <= bytealg.MaxLen:
		// Use brute force when s and sep both are small
		if len(s) <= bytealg.MaxBruteForce {

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

    switch (mode) {
      case UNNECESSARY:
        checkRoundingUnnecessary(x == floorPow);
      // fall through
      case FLOOR:
      case DOWN:
        return logFloor;
      case CEILING:
      case UP:
        return logFloor + lessThanBranchFree(floorPow, x);
      case HALF_DOWN:
      case HALF_UP:
      case HALF_EVEN:

                problemsList.add(modelProblem);
            }
        }

        return success(model, problemsList);
    }

    /**
     * Error with problems describing the cause
     *
     * @param problems
     */
    public static <T> Result<T> error(Iterable<? extends ModelProblem> problems) {
        return error(null, problems);
    }

    public static <T> Result<T> error(T model) {

///

## Duplicate headers { #duplicate-headers }

It is possible to receive duplicate headers. That means, the same header with multiple values.

You can define those cases using a list in the type declaration.

You will receive all the values from the duplicate header as a Python `list`.

For example, to declare a header of `X-Token` that can appear more than once, you can write:

		}
	}

	// Test cases for signature-V4.
	testCasesV4 := []struct {
		objectName         string
		data               []byte
		expectedHeaders    map[string]string
		expectedRespStatus int
		accessKey          string
		secretKey          string
		malformedBody      bool
	}{
		// Success case.
		{
			objectName:         "test",

This way, you can do the upgrade and make sure everything is still working as expected.

## `bump-pydantic` { #bump-pydantic }

In many cases, when you use regular Pydantic models without customizations, you will be able to automate most of the process of migrating from Pydantic v1 to Pydantic v2.