* In practice, this largely means that references are fully qualified in the API. IP Addresses (generally) have a network associated with them, node names have a cluster associated with them, etc.

See the [XDS Evolution](https://docs.google.com/document/d/1V5wkeBHbLSLMzAMbwFlFZNHdZPyUEspG4lHbnB0UaCg/edit) document for more history and details.

# for running smoke tests in nightly/release wheel builds.
if [[ "${TFCI_MACOS_UPGRADE_PYENV_ENABLE}" == 1 ]]; then
  # The TFCI Mac VM image seems to have uncommitted local changes to the Pyenv
  # repository so we have to discard them and reset the working directory before
  # we can pull in the latest changes.
  cd /Users/kbuilder/.pyenv/ && git reset --hard HEAD && git pull && cd -
fi

            }
            if (line.startsWith("\"buildTime\"")) {
                var date = line.substring(line.indexOf("\"", 12) + 1, line.lastIndexOf("\""))
                date = date.substring(0, 4) + "-" + date.substring(4, 6) + "-" + date.substring(6, 8)
                versions[version!!] = date
            }
        }
        return versions
    }


    private

  // fails, one of the conditions will have type "Failed" and status true. When
  // a Job is suspended, one of the conditions will have type "Suspended" and
  // status true; when the Job is resumed, the status of this condition will
  // become false. When a Job is completed, one of the conditions will have
  // type "Complete" and status true.

)
async def create_item(item: Item):
    """
    Create an item with all the information:

    - **name**: each item must have a name
    - **description**: a long description
    - **price**: required
    - **tax**: if the item doesn't have tax, you can omit this
    - **tags**: a set of unique tag strings for this item
    """

                    "operationId": "read_items_items__get",
                    "parameters": [
                        {
                            "description": "Query string for the items to search in the database that have a good match",
                            "required": False,
                            "deprecated": True,
                            "schema": IsDict(
                                {

                    "operationId": "read_items_items__get",
                    "parameters": [
                        {
                            "description": "Query string for the items to search in the database that have a good match",
                            "required": False,
                            "deprecated": True,
                            "schema": IsDict(
                                {

### Edit it

It's a very simple program.

But now imagine that you were writing it from scratch.

At some point you would have started the definition of the function, you had the parameters ready...

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

## Dataclasses in Nested Data Structures

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:

        return true
      }
    }

    // If we have a routes left, use 'em.
    if (routeSelection?.hasNext() == true) return true

    // If we haven't initialized the route selector yet, assume it'll have at least one route.
    val localRouteSelector = routeSelector ?: return true

    // If we do have a route selector, use its routes.
    return localRouteSelector.hasNext()
  }

  /**