}
		}
	}
}

type importMetaReport struct {
	madmin.BucketMetaImportErrs
}

func (i *importMetaReport) SetStatus(bucket, fname string, err error) {
	st := i.Buckets[bucket]
	var errMsg string
	if err != nil {
		errMsg = err.Error()
	}
	switch fname {
	case bucketPolicyConfig:
		st.Policy = madmin.MetaStatus{IsSet: true, Err: errMsg}
	case bucketNotificationConfig:

          ([#21737](https://github.com/kubernetes/kubernetes/pull/21737))

        - Processes may be leaked when Docker is repeatedly terminated in a short
          time frame.
          ([#41450](https://github.com/kubernetes/kubernetes/issues/41450))
- [v1.8.0-rc.1](https://github.com/kubernetes/kubernetes/blob/master/CHANGELOG.md#v180-rc1)

## Detalhes Técnicos

Versões modernas de Python tem suporte para **"código assíncrono"** usando algo chamado **"corrotinas"**, com sintaxe **`async` e `await`**.

Vamos ver aquela frase por partes na seção abaixo:

* **Código assíncrono**
* **`async` e `await`**
* **Corrotinas**

## Código assíncrono

        writeTimeout = checkDuration("duration", duration)
      }

    /**
     * Sets the interval between HTTP/2 and web socket pings initiated by this client. Use this to
     * automatically send ping frames until either the connection fails or it is closed. This keeps
     * the connection alive and may detect connectivity failures.
     *

	ReplicatedSize int64 `json:"completedReplicationSize"`
	// Total Replica size in bytes
	ReplicaSize int64 `json:"replicaSize"`
	// Total failed operations including metadata updates for various time frames
	Failed madmin.TimedErrStats `json:"failed"`

	// Total number of completed operations
	ReplicatedCount int64 `json:"replicationCount"`
	// Total number of replica received
	ReplicaCount int64 `json:"replicaCount"`

* fix: make azure disk URI as case insensitive...

*   Improvements to the TensorFlow debugging experience:

    *   Previously, TensorFlow error stack traces involved many internal frames,
        which could be challenging to read through, while not being actionable
        for end users. As of TF 2.7, TensorFlow filters internal frames in most
        errors that it raises, to keep stack traces short, readable, and focused
        on what's actionable for end users (their own code).

  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  std::vector<StackFrame> feed_frames = {{"feed.cc", 10, "alpha"}};
  std::vector<StackFrame> neg_frames = {{"neg.cc", 15, "beta"}};
  feed->node.SetStackTrace(std::make_shared<FrozenStackTrace>(feed_frames));
  neg->node.SetStackTrace(std::make_shared<FrozenStackTrace>(neg_frames));

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};

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