],
    extra_copts = if_pywrap(["-DTENSORFLOW_NO_SHARED_OBJECTS"]),
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],
        "//conditions:default": [],
    }),
    tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],
    # We must ensure that the dependencies can be dynamically linked since

	}
}

// proxyTaggingToRepTarget proxies tagging requests to remote targets for
// active-active replicated setups
func proxyTaggingToRepTarget(ctx context.Context, bucket, object string, tags *tags.Tags, opts ObjectOptions, proxyTargets *madmin.BucketTargets) (proxy proxyResult) {
	// this option is set when active-active replication is in place between site A -> B,
	// and request hits site B that does not have the object yet.

```Python hl_lines="3  5-6"
{
    "name": "Baz",
    "description": None,
    "price": 50.2,
    "tax": 10.5,
    "tags": []
}
```

FastAPI достатньо розумний (насправді, Pydantic достатньо розумний), щоб зрозуміти, що, хоча `description`, `tax` і `tags` мають ті самі значення, що й типові, вони були встановлені явно (а не взяті як значення за замовчуванням).

Отже, вони будуть включені у JSON-відповідь.

```Python hl_lines="3  5-6"
{
    "name": "Baz",
    "description": None,
    "price": 50.2,
    "tax": 10.5,
    "tags": []
}
```

FastAPI достаточно умен (на самом деле, это заслуга Pydantic), чтобы понять, что, хотя `description`, `tax` и `tags` хранят такие же данные, какие должны быть по умолчанию - для них эти значения были установлены явно (а не получены из значений по умолчанию).

.nav-item`\nconst SELECTOR_TAB_NAVBAR_NAV_LINK = `${SELECTOR_TAB_NAVBAR_NAV} .nav-link`\nconst SELECTOR_TAB_CONTENT = `${SELECTOR_CONTENT_WRAPPER}.iframe-mode .tab-content`\nconst SELECTOR_TAB_EMPTY = `${SELECTOR_TAB_CONTENT} .tab-empty`\nconst SELECTOR_TAB_LOADING = `${SELECTOR_TAB_CONTENT} .tab-loading`\nconst SELECTOR_TAB_PANE = `${SELECTOR_TAB_CONTENT} .tab-pane`\nconst SELECTOR_SIDEBAR_MENU_ITEM = '.main-sidebar .nav-item > a.nav-link'\nconst SELECTOR_SIDEBAR_SEARCH_ITEM = '.sidebar-search-results .lis...

pushd "${TFCI_OUTPUT_DIR}"

# Unpack the wheel to get all the file contents. The pure python wheel we built
# above is tagged with "py3-none-any". We cannot change the tags by simply
# renaming the wheels as uploading to PyPI would fail with "File already exists"
# error. In order to upload to PyPI, we unpack the wheel and change the tag

/// note | 📡 ℹ

👆 💪 ⚙️ `from starlette import status`.

**FastAPI** 🚚 🎏 `starlette.status` `fastapi.status` 🏪 👆, 👩‍💻. ✋️ ⚫️ 👟 🔗 ⚪️➡️ 💃.

///

## 🔖

👆 💪 🚮 🔖 👆 *➡ 🛠️*, 🚶‍♀️ 🔢 `tags` ⏮️ `list` `str` (🛎 1️⃣ `str`):

{* ../../docs_src/path_operation_configuration/tutorial002.py hl[17,22,27] *}

👫 🔜 🚮 🗄 🔗 & ⚙️ 🏧 🧾 🔢:

<img src="/img/tutorial/path-operation-configuration/image01.png">

  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")
  bazel cquery --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps
  # Find all one-step dependencies of those tests which are from //tensorflow

    while (!utf8.exhausted()) {
      require(utf8.readByte() == '.'.code.toByte())
      val vN = utf8.readDecimalLong()
      writeVariableLengthLong(vN)
    }
  }

  /** Used for tags and subidentifiers. */
  private fun writeVariableLengthLong(v: Long) {
    val sink = sink()
    val bitCount = 64 - java.lang.Long.numberOfLeadingZeros(v)
    val byteCount = (bitCount + 6) / 7

          results_format: sarif
          publish_results: true

      # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
      # format to the repository Actions tab.
      - name: "Upload artifact"
        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
        with:
          name: SARIF file
          path: results.sarif
          retention-days: 5