```Python
with open("file.txt") as file:
    file.read()
```

Nas versões mais recentes de Python, há também um **gerenciador de contexto assíncrono**. Você o usaria com `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

## Gerenciadores de contexto

### O que são gerenciadores de contexto

"Gerenciadores de Contexto" são qualquer um dos objetos Python que podem ser utilizados com a declaração `with`.

Veja como pode parecer:

<img src="/img/tutorial/debugging/image01.png">

---

Se você usar o Pycharm, você pode:

* Abrir o menu "Executar".
* Selecionar a opção "Depurar...".
* Então um menu de contexto aparece.
* Selecionar o arquivo para depurar (neste caso, `main.py`).

Em seguida, ele iniciará o servidor com seu código **FastAPI**, parará em seus pontos de interrupção, etc.

Veja como pode parecer:

* `allow_credentials` - Indica que...

	}
	impersonateConfig := i.getImpersonateConfig()
	rawConfigContexts := maps.Keys(rawConfig.Contexts)
	for _, c := range contexts {
		if !slices.Contains(rawConfigContexts, c) {
			return nil, fmt.Errorf("context %q not found", c)
		}
	}
	var clients []kube.CLIClient
	for _, contextName := range contexts {
		if i.remoteClients[contextName] != nil {
			clients = append(clients, i.remoteClients[contextName])

package kms

import (
	"bytes"
	"sort"
	"unicode/utf8"
)

// Context is a set of key-value pairs that
// are associated with a generate data encryption
// key (DEK).
//
// A KMS implementation may bind the context to the
// generated DEK such that the same context must be
// provided when decrypting an encrypted DEK.
type Context map[string]string

// MarshalText returns a canonical text representation of

}

// extractMetadataFromReq extracts metadata from HTTP header and HTTP queryString.
func extractMetadataFromReq(ctx context.Context, r *http.Request) (metadata map[string]string, err error) {
	return extractMetadata(ctx, textproto.MIMEHeader(r.Form), textproto.MIMEHeader(r.Header))
}

func extractMetadata(ctx context.Context, mimesHeader ...textproto.MIMEHeader) (metadata map[string]string, err error) {
	metadata = make(map[string]string)

        op_outputs_ = std::vector<TensorHandlePtr>();
        Execute(context_, operation_name_, std::move(op_inputs_), attributes_,
                expected_max_outputs_, &op_outputs_, status_.get());
        execution_state_ = ExecutionState::kHasResult;
      }
    }
    finished_execute_.notify_one();
  }
}

void DeviceThread::StartExecute(TFE_Context* context,
                                const char* operation_name,

 */
package jcifs;


import java.net.URLStreamHandler;


/**
 * Encapsulation of client context
 * 
 * 
 * A context holds the client configuration, shared services as well as the active credentials.
 * 
 * Usually you will want to create one context per client configuration and then
 * multiple sub-contexts using different credentials (if necessary).
 * 

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.