},
               "unit": "bytes"
            },
            "overrides": [
               {
                  "matcher": {
                     "id": "byRegexp",
                     "options": "/(virtual|resident)/i"
                  },
                  "properties": [
                     {
                        "id": "custom.fillOpacity",
                        "value": 0
                     },

	ss := re.FindStringSubmatch(path)
	if ss == nil {
		return "", "", fmt.Errorf("not a VS path: %s", path)
	}
	return ss[3], ss[2], nil
}

// getIstioVirtualServicePathForSvcFromRoute returns something like "/apis/networking/v1alpha3/namespaces/default/virtual-service/reviews"

type headerRewriter struct{}

// Clean up IP in case if it is ipv6 address and it has {zone} information in it, like
// "[fe80::d806:a55d:eb1b:49cc%vEthernet (vmxnet3 Ethernet Adapter - Virtual Switch)]:64692"
func ipv6fix(clientIP string) string {
	return strings.Split(clientIP, "%")[0]
}

func (rw *headerRewriter) Rewrite(req *http.Request) {

tensorflow::ServerDef GetServerDef(int num_tasks);

// Create a multi-client ServerDef with the given `job_name`, add `num_tasks`
// tasks and `num_virtual_gpus` virtual GPUs in it.
tensorflow::ServerDef GetMultiClientServerDef(const std::string& job_name,
                                              int num_tasks,
                                              int num_virtual_gpus = 0);

### Em um servidor remoto

Ao configurar um servidor remoto (um servidor em nuvem, uma máquina virtual, etc.), a coisa mais simples que você pode fazer é usar `fastapi run` (que usa Uvicorn) ou algo semelhante, manualmente, da mesma forma que você faz ao desenvolver localmente.

E funcionará e será útil **durante o desenvolvimento**.

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests

## Instalar o `SQLModel`

Primeiro, certifique-se de criar seu [ambiente virtual](../virtual-environments.md){.internal-link target=_blank}, ativá-lo e, em seguida, instalar o `sqlmodel`:

<div class="termy">

```console
$ pip install sqlmodel
---> 100%
```

</div>

Example:

```sh

labels.max_access_count=Max Access Count
labels.number_of_thread=The number of Thread
labels.interval_time=Interval time
labels.millisec=ms
labels.permissions=Permissions
labels.virtual_hosts=Virtual Hosts
labels.virtual_host=Virtual Host
labels.label_type=Label
labels.file_crawling_button_create=Create
labels.file_crawling_button_create_job=Create new job
labels.web_crawling_configuration=Web Crawling

### Install `pydantic-settings`

First, make sure you create your [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install the `pydantic-settings` package:

<div class="termy">

```console
$ pip install pydantic-settings
---> 100%
```

</div>