}

func bmIndexRuneUnicode(rt *unicode.RangeTable, needle rune) func(b *testing.B, n int) {
	var rs []rune
	for _, r16 := range rt.R16 {
		for r := rune(r16.Lo); r <= rune(r16.Hi); r += rune(r16.Stride) {
			if r != needle {
				rs = append(rs, r)
			}
		}
	}
	for _, r32 := range rt.R32 {
		for r := rune(r32.Lo); r <= rune(r32.Hi); r += rune(r32.Stride) {
			if r != needle {
				rs = append(rs, r)
			}
		}
	}

### Include the custom docs { #include-the-custom-docs }

Now you can create the *path operations* for the custom docs.

You can reuse FastAPI's internal functions to create the HTML pages for the docs, and pass them the needed arguments:

* `openapi_url`: the URL where the HTML page for the docs can get the OpenAPI schema for your API. You can use here the attribute `app.openapi_url`.
* `title`: the title of your API.

# Libtensorflow archives) to GCS buckets. TFCI Mac VMs need to authenticate as
# a service account that has the right permissions to be able to do so.
set +x
if [[ -n "${GOOGLE_APPLICATION_CREDENTIALS:-}" ]]; then
  # Python 3.12 removed the module `imp` which is needed by gcloud CLI so we set
  # `CLOUDSDK_PYTHON` to Python 3.11 which is the system Python on TFCI Mac
  # VMs.

          # To be able to commit it needs to fetch the head of the branch, not the
          # merge commit
          ref: ${{ github.head_ref }}
          # And it needs the full history to be able to compute diffs
          fetch-depth: 0
          # A token other than the default GITHUB_TOKEN is needed to be able to trigger CI
          token: ${{ secrets.PRE_COMMIT }}
      # pre-commit lite ci needs the default checkout configs to work

  check:  # This job does nothing and is only used for the branch protection
    if: always()
    needs:
      - coverage-combine
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - name: Decide whether the needed jobs succeeded or failed
        uses: re-actors/alls-green@release/v1
        with:

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --enable_platform_specific_config

# Enable XLA support by default.
common --define=with_xla_support=true

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --config=short_logs

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --config=v2

func (b *Buffer) Grow(n int) {
	if n < 0 {
		panic("bytes.Buffer.Grow: negative count")
	}
	m := b.grow(n)
	b.buf = b.buf[:m]
}

// Write appends the contents of p to the buffer, growing the buffer as
// needed. The return value n is the length of p; err is always nil. If the
// buffer becomes too large, Write will panic with [ErrTooLarge].
func (b *Buffer) Write(p []byte) (n int, err error) {
	b.lastRead = opInvalid

# Request Body { #request-body }

When you need to send data from a client (let's say, a browser) to your API, you send it as a **request body**.

A **request** body is data sent by the client to your API. A **response** body is the data your API sends to the client.

This is useful if you don't know the valid field/attribute names (that would be needed for a Pydantic model) beforehand.

In this case, you can use `typing.Dict` (or just `dict` in Python 3.9 and above):

{* ../../docs_src/extra_models/tutorial005_py39.py hl[6] *}

## Recap { #recap }

Use multiple Pydantic models and inherit freely for each case.

    if: always()
    needs:
      - test-redistribute
    runs-on: ubuntu-latest
    steps:
      - name: Decide whether the needed jobs succeeded or failed
        uses: re-actors/alls-green@release/v1
        with: