"name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info
    `**second_user_data` quer dizer:

    Passe as chaves e valores do dicionário `second_user_data` diretamente como argumentos chave-valor, equivalente a: `User(id=4, name="Mary", joined="2018-11-30")`

### Suporte de editores

                String phase = event.getMojoExecution().getLifecyclePhase();
                if (phase != null) {
                    Deque<String> phases = getLifecycles(project);
                    if (!Objects.equals(phase, phases.peekLast())) {
                        phases.addLast(phase);
                        if ("clean".equals(phase)) {
                            cleanProjectLocalRepository(project);
                        }

             * MNG-2277, the check below compensates for our bad plugin support where we ended up with aggregator
             * plugins that require dependency resolution although they usually run in phases of the build where project
             * artifacts haven't been assembled yet. The prime example of this is "mvn release:prepare".
             */

## Version 4.2.1

_2019-10-02_

 *  Fix: In 4.1.0 we introduced a performance regression that prevented connections from being
    pooled in certain situations. We have good test coverage for connection pooling but we missed
    this because it only occurs if you have proxy configured and you share a connection pool among
    multiple `OkHttpClient` instances.

            want to analyze the set of transitive dependencies, in particular during early lifecycle phases where
            full dependency resolution might fail due to projects which haven't been built yet.
          </description>
        </field>
        <field>
          <name>dependencyCollection</name>
          <version>2.0.0+</version>

void TFE_InferShapes(TFE_Op* tfe_op, TF_ShapeAndTypeList* input_shapes,
                     TF_Tensor** input_tensors,
                     TF_ShapeAndTypeList* input_tensors_as_shapes,
                     TF_ShapeAndTypeList** input_resource_shapes_and_types,
                     TF_ShapeAndTypeList** output_shapes,
                     TF_ShapeAndTypeList*** output_resource_shapes_and_types,
                     TF_Status* status) {

			return
		}
		sz := d.sizeRecursive(path.Key())
		leaves = append(leaves, struct {
			objects uint64
			path    dataUsageHash
		}{objects: sz.Objects, path: path})
		for ch := range e.Children {
			add(dataUsageHash(ch))
		}
	}

	// Add path recursively.
	add(path)
	sort.Slice(leaves, func(i, j int) bool {
		return leaves[i].objects < leaves[j].objects
	})
	for remove > 0 && len(leaves) > 0 {

    // Wait until all pending nodes have completed since they may have a
    // reference to default_cancellation_manager_. We ignore the status return
    // since we already have a bad status to propagate.
    TFE_ContextAsyncWait(context, await_status.get());
    // Reset the cancellation manager on a bad status. Otherwise we'll cancel
    // all future operations.

		dataDir          string
		data             []byte
		shares           int
		transitionStatus string
		restoreObjStatus string
		expireRestored   bool
		expectedDataDir  string
	}{
		{ // object versions with inlined data don't count towards shared data directory
			versionID: mustGetUUID(),
			dataDir:   d0,
			data:      data,
			shares:    0,
		},

    std::vector<PartialTensorShape> shapes;
    shapes.reserve(num_values);
    for (int i = 0; i < num_values; ++i) {
      if (num_dims[i] < 0) {
        shapes.emplace_back();
      } else {
        shapes.emplace_back(ArraySlice<int64_t>(
            reinterpret_cast<const int64_t*>(dims[i]), num_dims[i]));
      }
    }
    op_->node_builder.Attr(attr_name, shapes);
    return absl::OkStatus();
  }